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ii
5th CONSTRUCTION MANAGEMENT
CONFERENCE
Edited by
Prof Fidelis Emuze
ISBN: 978-1-920508-70-8
Published by:
Department of Construction Management
Nelson Mandela Metropolitan University
PO Box 77000
Port Elizabeth
6031, South Africa
© Authors of papers in this publication have the copyright for the articles.
Correspondence:
All correspondence about the 5th CM conference should be sent to:
Prof Fidelis Emuze
Department of Built Environment
Central University of Technology, Free State
Private Bag X20539
Bloemfontein
9300, South Africa
Email: femuze@cut.ac.za
28-29 November 2016
Protea Marine Hotel, Port Elizabeth, South Africa
iii
FOREWORD
The organizing team of the 5th Construction Management Conference (CMC) is happy
to welcome you to Port Elizabeth, South Africa.
The meeting provides an international forum for researchers and practitioners to address
important problems that affect the Architecture, Engineering, and Construction (AEC)
sector. The forum is a platform where recognized best practices are shared between
researchers and practitioners. The conference seeks responses to critical questions, which
include:
What changes would lead to an improvement in performance?
What are the barriers to change in practice?
How can business and project aspects of construction management be promoted?
How can education, training, and professional development be improved?
How can skills better be developed and transferred?
How can management difficulties be addressed?
How can efficiency and sustainability become engendered in the AEC sector?
The peer-reviewed papers, and edited proceedings is aimed at contributing to the built
environment body of knowledge to improve the management of business and project
aspects of construction processes and products through teaching, learning, research and
practice in South Africa, and beyond.
Prof Fidelis Emuze
Chair: Academic Programme
Bloemfontein, South Africa
November, 2016
iv
ACKNOWLEDGEMENTS
The planning and execution of the 5th Construction Management conference is based on
the goodwill of the Nelson Mandela Metropolitan University (NMMU), the Central
University of Technology, Free State (CUT), and other supportive entities.
The effort of the International Scientific Committee, who diligently compiled refereed
and edited papers, which led to published proceedings that satisfy the subsidy criteria of
the Department of Higher Education and Training (DHET) in South Africa, is highly
appreciated. The support of Prof Winston Shakantu (NMMU) and Prof Alfred Ngowi
(CUT) is notable and the efforts of Mrs Mariana Botes, Dr Brink Botha, Mr Chris Allen,
and Ms Katharina Herich in Port Elizabeth; and Prof Yali Woyessa, Dr Dillip Das, Dr
Bankole Awuzie, Ms Zanelle Matsane, Mr Arno Ferreira, Mr Thabiso Monyane, Mr
George Mollo, Mr Rasheed Isa, Mr Adefemi Aka, and Mr Chikerizim Okorafor in
Bloemfontein are much-appreciated.
v
ORGANISING COMMITTEE
Prof John Smallwood (Technical Programme Chair)
Prof Fidelis Emuze (Academic Programme Chair)
Mrs Mariana Botes (Administration – NMMU)
Ms Portia Atoro (Administration – CUT)
Mr Lesiba Mollo
DECLARATION
The papers in this CMC volume were double-blind reviewed at abstract and full paper
stages by members of the International Scientific Committee. This process entailed
detailed reading of the abstracts and papers, reporting of comments to authors,
modification of articles by authors whose papers were not rejected by the reviewers, and
re-evaluation of revised papers to ensure quality of content. The conference proceedings
are therefore made up of papers that have been reviewed by experts in specific fields of
construction research.
vi
THE PEER REVIEW PROCESS
To uphold and guarantee the quality of the conference proceedings and comply with the
criteria for the Department of Higher Education and Training (DHET) subsidy in South
Africa, a rigorous two-stage peer review process by no less than two recognized experts
was followed. The process was executed by ensuring that each abstract was twice blind
reviewed with particular reference to relevance to conference themes and objectives,
scientific rigor, originality of research output and extent of contributions to knowledge.
Authors, whose abstracts were accepted, after the stage one review process was
completed, were provided with anonymous reviewers’ reports and requested to submit
their full papers that complied with the recommendations of the reviewers. The review of
the full papers followed the two-tier blind review process again. Authors whose papers
were accepted after this second review were provided with additional anonymous
reviewers’ comments and requested to submit their revised full papers.
These final papers were only included in the conference presentation programme and the
conference proceedings after evidence was provided that all comments were
appropriately responded to, having been double peer-reviewed for publication. Authors’
feedback box on the online submission system was used to capture the extent of revision
in each paper. The CMT online system was fully utilized for the peer review of all
submissions for the conference. The submissions were made to:
https://cmt.research.microsoft.com/CM2016
The members of the Scientific Committee were not involved in the review related to their
own authored or co-authored papers. The role of the editor was to ensure that the final
papers incorporated the reviewers’ comments and arrange the papers into the final order
as captured on the Table of Contents. Of the 69 submissions initially received, only 29
papers were accepted for inclusion in the proceedings. This statistic results in an
acceptance rate of 42% / rejection rate of 58%. To be eligible for inclusion these papers
were required to receive a minimum score of 3 out of 5 allocated by the peer reviewers
during the final review process.
vii
INTERNATIONAL SCIENTIFIC COMMITTEE
The paper peer review exercise for this international conference was expedited through
the voluntary contributions of experts from various countries. The academic programme
chair is sincerely grateful to:
Abimbola Windapo University of Cape Town
Adebayo Oladapo University of Central Lancashire
Adefemi Aka Central University of Technology, Free State
Alex Opoku University College London
Alfred Ngowi Central University of Technology, Free State
Alistair Gibb Loughborough University
Andreas Hartmann University of Twente
Apollo Tutesigensi University of Leeds
Ayman Othman The British University in Egypt
Ayodeji Aiyetan Durban University of Technology
Bankole Awuzie Central University of Technology, Free State
Bing Li Xiamen University
Bon-Gang Hwang National University of Singapore
Chien-Ho Ko National Pingtung University of Science & Technology
Chikezerim Okorafor Central University of Technology, Free State
Clinton Aigbavboa, University of Johannesburg
Dave Root University of the Witwatersrand
David Edwards Birmingham City University
David Thorpe University of Southern Queensland
Dillip Das Central University of Technology, Free State
Dominic Ahiaga-Dagbui Robert Gordon University
Emmanuel Achuenu University of Jos
Emmanuel Aboagye-Nimo University of Brighton
Erastus Mwanaumo University of Zambia
Evelyn Ai-Lin Teo National University of Singapore
Ezekiel Chinyio University of Wolverhampton
George Ofori National University of Singapore
Geraldine Kikwasi Ardhi University
Hamimah Adnan University Teknologi MARA
Ifte Choudhury Texas A&M University
Jack Goulding University of Central Lancashire
Jan Wium Stellenbosch University
James Rotimi Auckland University of Technology
Jasper Mbachu Massey University
John Ebohon De Montfort University
John Kamara Newcastle University
John Ameh University of Lagos
Johnson Adafin University of Auckland
viii
Julius Fapohunda Cape Penisula University of Technology
Justus Agumba University of Johannesburg
K.A.K. Devapriya University of Moratuwa
Kathy Michell University of Cape Town
Lance Wentzel Cape Penisula University of Technology
Low Pheng National University of Singapore
Manya Mooya University of Cape Town
Mike Kagioglou University of Huddersfield
Mohammed Berawi University of Indonesia, Indonesia
Nicholas Chileshe University of South Australia
Nien-Tsu Tuan University of Cape Town
Pantaleo Rwelamila University of South Africa
Patrick Manu University of the West of England
Paul Ho City University of Hong Kong
Rasheed Isa Central University of Technology, Free State
Richard Jimoh Federal University of Technology, Minna
Rick Best Bond University
Rodney Milford Construction Industry Development Board
Salma Azhar Auburn University
Samuel Chikafalimani Industrial Development Corporation of South Africa
Sherif Mohamed Griffiths University
Taibat Lawanson University of Lagos
Theuns Knoetze Council for Scientific and Industrial Research
Will Hughes University of Reading
Willy Sher University of Newcastle
Yali Woyessa Central University of Technology
ix
TECHNICAL COMMITTEE
Prof John Smallwood, Nelson Mandela Metropolitan University, South Africa
Prof Alfred Ngowi, Central University of Technology, Free State, South Africa
Prof George Ofori, National University of Singapore, Singapore
Prof PD Rwelamila, University of South Africa, South Africa
Prof Alfred Talukhaba, Tshwane University of Technology, South Africa
Prof WD Thwala, University of Johannesburg, South Africa
Prof David Edwards, Birmingham City University, United Kingdom
Prof Chris Gorse, Leeds Beckett University, United Kingdom
Dr Nicholas Chileshe, University of South Australia, Australia
Dr Geraldine Kikwasi, Ardhi University, Tanzania
x
HOSTS
Department of Construction Management
Department of Built Environment
ENDORSEMENT
South African Council for the Project and Construction Management Professions
(SACPCMP)
xi
November 2016
Dear Author,
RE: PEER REVIEW PROCEDURE FOR THE 5th CM CONFERENCE
The academic programme chair of the 5th CM conference confirms that the following peer
review process was strictly undertaken in this conference. A rigorous two-stage peer
review process by no less than two recognized experts was followed. The process was
executed by ensuring that each abstract was twice blind reviewed with particular
reference to relevance to conference themes and objectives, apart from scientific rigor,
originality of research output and extent of contributions to knowledge. Authors, whose
abstracts were accepted, after the stage one review process was completed, were provided
with anonymous reviewers’ reports and requested to submit their full papers that
complied with the recommendations of the reviewers. The review of the full papers
followed the two-tier blind review process again. Authors whose papers were accepted
after this second review were provided with additional anonymous reviewers’ comments
and requested to submit their revised full papers.
These final papers were only included in the conference presentation programme and the
conference proceedings after evidence was provided that all comments were
appropriately responded to, having been double peer-reviewed for publication. Authors’
feedback box on the online submission system was used to capture the extent of revision
in each paper. The CMT online system was fully utilized for the peer review of all
submissions for the conference. The submissions were made to:
https://cmt.research.microsoft.com/CM2016
The members of the Scientific Committee were not involved in the review related to their
own authored or co-authored papers. The role of the editor was to ensure that the final
papers incorporated the reviewers’ comments and arrange the papers into the final order
as captured on the Table of Contents. Of the 69 submissions initially received, only 29
papers were accepted for inclusion in the proceedings. This statistic results in an
acceptance rate of 42% / rejection rate of 58%. To be eligible for inclusion these papers
were required to receive a minimum score of 3 out of 5 allocated by the peer reviewers
during the final review process.
Best wishes,
Prof Fidelis Emuze
Chair: Academic Programme
Bloemfontein, South Africa
xii
TABLE OF CONTENTS
Foreword ......................................................................................................................... iii
Acknowledgements ............................................................................................................ iv
Organising Committee ....................................................................................................... v
Declaration ........................................................................................................................ v
The Peer Review Process ................................................................................................. vi
International Scientific Committee ................................................................................. vii
Technical Committee ........................................................................................................ ix
Hosts .................................................................................................................................. x
Endorsement ...................................................................................................................... x
Unethical Practices in the South African Construction Industry ................................... 15
C Aigbavboa, A Oke and S Tyali ........................................................................................
An Appraisal of Imminent Unethical Practices in the Nigerian Construction Industry: A
Case of Abuja.................................................................................................................. 23
A Hafeez and EM Ugbor ....................................................................................................
Confirmatory Factor Analysis of Contractors’ Safety Policy ........................................ 33
Z Mustapha, C Aigbavboa and WD Thwala ......................................................................
Influence of Health and Safety Practices on Performance of Construction Projects in
Abuja ............................................................................................................................... 45
R Jimoh, L Oyewobi, K Ibrahim and K Abibu ..................................................................
Exploring the Impact of Team Members’ Behaviours on Accident Causation Within
Construction Projects ..................................................................................................... 54
V Okorie, F Emuze and J Smallwood ................................................................................
Making Project Team Decisions Using Choosing by Advantages on a Concrete Task
Project ............................................................................................................................ 63
LG Mollo, F Emuze and F Geminiani ................................................................................
Assessment of Construction Risks and Mitigation Strategies in Public Private
Partnership (PPP) Projects in Abuja, Nigeria ............................................................... 73
I Yahaya, W Shakantu, R Jimoh, I Saidu ...........................................................................
Decision to Engage Nominated Subcontractors on Construction Projects in Nigeria .. 83
A Adamu and W Shakantu ................................................................................................
Conceptual Evaluation Ideas for the Infrastructure Delivery Improvement Programme
in South Africa ................................................................................................................ 91
T Monyane, F Emuze and G Crafford ................................................................................
xiii
Risk Management Framework for Property Development Projects: Real Estate
Demand ......................................................................................................................... 101
Z Shrosbree, B Botha and R Cumberlege ...........................................................................
Clients’ Knowledge of Procurement Systems and Its Influence on Construction Project
Performance ................................................................................................................. 110
AO Windapo, AA Adediran and JOB Rotimi ....................................................................
Determinants of Building Construction Costs in South Africa..................................... 120
A Windapo, S Odediran, A Moghayedhi, A Adediran and D Oliphant .............................
Influences of Cultural Differences on Construction Project Delivery: A Case Of
Gauteng Province ......................................................................................................... 129
K Matobole, O Ogunsanya and C Aigbavboa ....................................................................
Effects of Material Waste Causes on Cost Overruns in Abuja, Nigeria: A Project
Planning Stage Perspective .......................................................................................... 139
I Saidu and W Shakantu .....................................................................................................
An Assessment of Electronic Payment System among SME’s in the Nigerian Building
Industry ......................................................................................................................... 150
I Abdulhafeez, K Ibrahim and T Mustapha ........................................................................
Community Engagement on Public Projects – Case Study of Hammanskraal Pedestrian
Bridge, Gauteng, South Africa ..................................................................................... 159
BDC Rathenam, I Musonda, A Talukhaba and NL Dabup ................................................
A Review of Factors Affecting Construction Labour Productivity in Developed and
Developing Countries ................................................................................................... 168
O Adebowale and J Smallwood ..........................................................................................
Traffic Demand Determinants: A Review of Long-Term Scenario Effects ................. 177
C Okoro, I Musonda and J Agumba ...................................................................................
Influence of Administrative and Political Authorities’ Decisions on the Construction of
Community Development Projects in India .................................................................. 186
DK Das ...............................................................................................................................
Valuation of Sugarcane Farmland for Construction Projects in Durban, South Africa
...................................................................................................................................... 194
SHP Chikafalimani and K Ramphal ...................................................................................
xiv
Predicting Academic Success of Undergraduate Architecture Students: Using K Nearest
Neighbour Algorithm .................................................................................................... 202
R Aluko, C Aigbavboa and OS Oshodi ..............................................................................
Critical Review of Ethical Considerations in the Teaching Approach of Construction
Professionals ................................................................................................................ 211
M Els...................................................................................................................................
Evaluation of Barriers to University - Industry Collaboration (UIC) in the Nigerian
Construction Industry ................................................................................................... 218
G Odawn, S Muhammad and MZ Muhammad ..................................................................
Contribution of Value Management to Construction Projects in South Africa ............ 226
C Aigbavboa, A Oke and S Mojele ....................................................................................
Perceptions of Skilled Labour Attributes on Delay on Construction Projects in India 235
DK Das ...............................................................................................................................
Determinants of Small and Medium Contractor Business Failure .............................. 243
C Collins and G Crafford....................................................................................................
Critical Success Factors of Labour-Intensive Subcontractors in South Africa: An
Eastern Cape Study ...................................................................................................... 257
D Massyn and G Crafford ..................................................................................................
Factors for Selecting Joint Venture Partners for Construction Projects in South Africa
...................................................................................................................................... 267
B Mba and J Agumba .........................................................................................................
Factors Affecting Cost and Time Control in Construction Projects ............................ 276
O Faremi and O Ogunsanmi ...............................................................................................
15
Unethical Practices in the South African Construction
Industry Clinton Aigbavboa, Ayodeji Oke and Sibiwe Tyali
Department of Quantity Surveying and Construction Management,
University of Johannesburg, South Africa
Email: caigbavboa@uj.ac.za, emayok@gmail.com, tyalisib@gmail.com
Abstract:
Development of infrastructure to meet the needs of South Africans is a major concern for the
construction industry, however the failure of the industry to keep up with the expectation has
drawn some criticism from the citizens. Lack of adherence to ethical practices that help ensure
transparency and accountability within the industry is a major impediment towards being a
consistent and an effective contributor to the growth of the South African economy. This study
therefore examines unethical practices in South African Construction Industry and measures to
address the menace for better project performance. Well-structured questionnaires were
administered on registered and experienced construction professionals within the industry and
Mean Item Score (MIS) was used to analyse the returned data. Non-adherence to ethical
practices in the industry are as a result of greed, favouritism, political influence, monopoly of
bigger companies over smaller and emerging companies and pressure to meet unrealistic
company objective and deadlines. The unethical practices prevalent in the industry include
bribery and fraud, falsification of experience, illegal award of tenders and collusive tendering.
These unethical practices result to dissatisfied clients, poor workmanship, poor quality of
infrastructural development and loss of public trust. Professionals, especially construction and
project managers should shoulder the responsibility of stamping out unethical practices in the
industry by developing viable measures to achieve the goal. More so, whistle-blower protection
mechanisms need to be revised and improved to encourage effective monitoring and
sanctioning of individuals involved in unethical practices in the industry.
Keywords:
Construction, Corruption, Ethics, Stakeholders
1 Introduction
Ethics are moral principles that direct or influence a person’s behaviour, activities and conduct,
it is concerned with differentiating between what is right and wrong. Ethics basically seeks to
resolve the questions dealing with human morality, concepts such as good and bad, acceptable
and unacceptable, self-interests and selfishness. In order for one to achieve an ethical outcome
to a course of action it is important to understand the influencers of such concepts. Schoeman
(2014) noted that these concepts are mostly determined by values, relevant laws, rules or
regulations. Ethics is the ability to do right and in construction, it can be defined as
trustworthiness and integrity at construction businesses are conducted (Mason, 2009).
The construction industry plays a vital role in the economy of any country, regardless of the
level of development of such country. South Africa is no exception, the country’s construction
industry has been one of the main engine in the country’s economy, contributing to about 6%
of the nation’s Gross Domestic Product (GDP) and creating several job opportunities. Ehsan,
16
et al., (2009) regarded ethics as a very important aspect in the engineering and general
construction profession as they have a huge role in obtaining tremendous benefits from the
construction projects, ethics also have huge influence on the function of the industry.
Ethical conduct is paramount in the running of a business because it provides personnel with
conceptual guidelines on how to conduct themselves in their endeavour. However, holistic
understanding and general application of ethical code of conduct remains an issue for concern
in the construction industry while enhancing ethical standards among stakeholders is also a
challenge. It is of paramount importance that ethical standards are adhered to in order to
maintain a good image of the industry. Bowen et al. (2007) revealed that stakeholders in the
construction industry have a tendency of possessing a reputation of unethical conduct. This
study therefore examines causes and consequences of unethical practices prevalent in South
African construction industry with a view to formulating recommendations to address the
menace and enhance ethical standards in the industry.
2 Literature Review
2.1 Code of Conduct/Ethics
The major objective of code of conduct is to uphold a higher standard of conduct by concerned
individuals beyond what is required by law. It is a catalyst for enhancing the company’s
reputation. Davis (1991) describes the code of professional ethics as acting as a central to advise
individual engineers on how to conduct themselves, to judging their conduct and ultimately to
understand engineering as a profession. In the context of this research codes of conduct refers
to code of ethics which are distinct and formal document written to guide individual
professionals within the organisation/profession on how to conduct themselves in carrying their
professional duties and services, it is concerned with moral standards. Codes of conduct are
available in professional bodies association and their regulatory bodies to govern the behaviour
and practice of their members (Wolverton and Wolverton, 1999).
Nadeem, et al., (2009) admitted that construction and engineering professionals have a great
influence on the society, these professionals owe a special responsibility. However, claims have
been made that the professionals in general have a tendency of believing that their obligations
to their client far outweigh their responsibility to others, such as the society. This means
because of the standard of knowledge that they possess and their importance to the public, they
should have considerable standard of conduct to answer ethical questions. In addition, there
are some expectations that the building and design professionals should be aware of, this
includes the incalculable value of human life that demands nothing less than the highest moral
consideration from them. In addition, Davis (1991) pointed out the purpose of code of
professional ethics is to guide and protect individuals, including professionals from pressures
which tempts to act unethical.
2.2 Ethics and the Construction Industry
The construction industry is a very complex sector which requires professionals to be
professionally fit in order to execute projects according to the required scope and time. The
professionalism does not only end with professionals possessing knowledgeable ability and
skill to deliver project but it requires one to be psychological fit in order to conduct business
according to guiding principles and regulations of the professions. In addition, construction
professionals must be able to demonstrate competency and integrity by passing certain tests,
adhering to existing code of conducts and keeping a good reputation with the public by offering
17
their services in an acceptable manner. Mason (2009) identifies the early stages of construction
projects as the most crucial where several levels of values and ethical terms should be taken
into consideration.
Dabson et al. (2007) pointed out that an act of one professional in a particular profession has
an ability to tarnish the name of the entire profession. This proves that each and every
individual who is part of a profession carries the reputation, not only of himself but of the
profession as a whole. However, it was emphasised that ethics understood by an individual can
be classified as being subjective, where right and wrong might differ from certain individual’s
view. This conflict in perception of ethic is a good indication that an establishment of a standard
level of behaviour for all professionals is of paramount importance (Greenhalyn, 1997).
2.3 Unethical Practices in Construction Industry
Unethical behaviour in the construction industry has been developed by the fierce competition
amongst and between professionals and contractors. This competitive behaviour among
participants in construction development has an ability to trigger ethical misconduct in the
relationships between professionals, their clients and supply chain (Bowen, et al., 2007). The
major notable unethical misconducts in construction industry according to Zarkada-Fraser and
Skitmore (2001), Zou (2006), Othman (2012), and Nawaz and Ikram (2013), are administrative
interference, the illegal award of contracts or subcontracts, the exposure of confidential
information to certain tenderers and the extortion of kickbacks by client and government
officials. While on the other hand contractors are found guilty of soliciting bribes to clients or
tender committees in order for them to closeout tenders, collusive tendering and bid rigging,
invoice fraud, the use of cheap material that do not conform with acceptable standards and
collusion between contractors and other supervisory authorities.
The Chartered Institution of Building (CIOB 2006) noted that improvement of ethical
behaviour would improve construction projects performance and satisfaction of stakeholders.
Moreover, adherence to ethical standard and principles by individuals involved in construction
process and activities would also improve the industry’s performance through establishing
mutual understanding of the rights of each party in the industry and recognising the
responsibilities and obligations of each.
3 Research Methodology
Using survey design, structured questionnaire was adopted as the approach of collecting data
from respondents. The target population are construction professionals that are registered with
their respective professional bodies to engage and provide services based on their training and
qualification. These are architects, quantity surveyors, construction managers, construction
project managers and engineers that are directly involved with construction activities in the
industry. The choice of the design and data collection instrument is due to their convenience,
time saving and cost efficiency. It also allows for anonymity in that respondents decided to
partake and can answer the questions at their convenient time. A cover letter was provided to
provide basic information for respondents and the first section of the main of the questionnaire
was used to solicit demographic information from the respondents. The other parts were
divided into sections based on the objectives of the study and the purpose of each section and
the kind of results expected were well explained. Prior to actual administration of the
instrument, a pilot study was carried out to determine discrepancies and error and evaluate
average duration of completing a questionnaire. The discrepancies, comments and suggestions
were corrected and effected in the final instruments. Duration of completing the questionnaire
18
was found to be approximately 15 minutes. 50 instruments were finally administered out of
which 45 were returned and certified fit for further analysis.
In order to achieve the objectives of the study, 5-point Likert scale was used to inquire
information from respondents where 1= Strongly disagree, 2= Disagree, 3= Neutral, 4= Agree,
5= Strongly agree. The Likert scale was transformed to Mean Item Score (MIS) and Standard
Deviation (SD) for each of the identified variables relating to causes of ethical misconducts,
effects and the mitigation measures. The MIS was used to rank each item while SD was used
for cases where 2 factors have the same MIS value.
4 Findings and Discussion
4.1 General Characteristics of Respondents
Information regarding the respondents revealed that 8% are African, 27% are Whites, 9% are
Coloured and 6% are Asians/Indians. Quantity surveyors represents 20% of the respondents,
18% are construction managers, 11% are architects, 11% are construction project manager
while 40% are engineers. Of these, 26 are male while the remaining are female with an
average of about 8 years working experience in the construction industry.
4.2 Common Ethical Misconduct and their Causes
The common ethical misconducts in the South African construction industry as revealed in
table 1 are bribery, illegal award of tender and Collusive tendering. The least important ones
are complexity of the industry and deny compensation of tendering cost.
Table 1. Common Unethical Practices in the Industry
Common ethical misconducts MIS SD RANK
Bribery 4.578 13.115 1
Fraud 4.267 9.179 2
Falsification of experience 4.222 8.461 3
Nepotism 4.200 8.832 4
Illegal award of tender 4.133 10.563 5
collusive tendering 4.000 10.563 6
Negligence 3.978 10.563 7
Overstatement of qualification/training to secure jobs 3.933 6.652 8
Bid shopping 3.933 8.221 9
Conflict of interest 3.911 8.860 10
Cover pricing 3.822 6.397 11
Bid cutting 3.756 7.676 12
Bid rigging 3.756 7.890 13
Complexity of the industry 3.533 6.782 14
Deny compensation of tendering cost 3.511 7.106 15
Source: Researcher
In examining drivers for ethical misconducts in the industry in table 2, it could be observed
that greed, favouritism and political influence, that is related to politics in the award for tender
and doing general construction activities are the most important ones. Other factors are lack of
transparency and lack of high executive control, the least important variables weak level of
supervision, personal culture and poverty.
Table 2. Causes of Ethical Misconduct
Factors MIS SD RANK
Greed 4.089 7.969 1
Favouritism 4.000 6.449 2
19
Political influence (e.g., Politics in the award for tender) 3.911 7.714 3
Monopoly of bigger firms to smaller emerging construction firms 3.889 6.442 4
Pressure to meet unrealistic business objectives and deadlines 3.822 7.182 5
Personal behaviour 3.822 8.093 6
Lack of transparency 3.800 9.899 7
Lack of high executive control 3.778 9.028 8
Lack of ethical awareness amongst industry players 3.733 8.456 9
False communication 3.689 5.339 10
Inadequate administrative structure 3.667 6.782 11
Stringent operational regulations in the Industry 3.644 7.842 12
Barriers to enter into the market 3.600 6.124 13
Weak levels of supervision 3.600 10.607 14
Personal culture 3.511 6.042 15
Poverty 3.200 4.637 16
Source: Researcher
4.3 Effects of Ethical Misconduct on the Construction Industry
Ethical standards were introduced to guide an individual and guide against practices that can
undermine the activities of an individual. Where there are ethical misconducts, the notable
results are dissatisfaction of clients, poor workmanship, deterioration in professionalism and
poor quality of infrastructure development as indicated in table 3. It also leads to loss of public
trust, low productivity/efficiency of project team, poor project coordination and high project
maintenance cost. The least impacts are related to disputes and conflicts among project
stakeholders, cost and time overrun of projects as well as collapse of buildings.
Table 3. Effects of Ethical Misconducts
Effects MIS SD RANK
Dissatisfaction of clients 4.178 6.557 1
Poor workmanship 4.089 9.811 2
Deterioration in professionalism 4.067 7.937 3
Poor quality infrastructure development 4.044 11.533 4
Loss of public trust 3.978 7.676 5
Low productivity/efficiency of project team 3.978 8.180 6
Poor project coordination 3.956 5.737 7
High maintenance cost 3.933 6.702 8
Growth of the industry 3.889 6.595 9
Late compensation due to delays 3.889 7.314 10
Conflicts between client and construction team 3.867 8.093 11
Cost overruns 3.822 6.964 12
Schedule overruns 3.778 6.519 13
Collapse of buildings 3.333 2.739 14
Source: Researcher
4.4 Measures to Enhance Ethical Conducts
It has been established that unethical practices still abound in the construction industry and it
has affected not only the performance of projects but image of the industry as a whole. In order
to stem this measures, the major measure as indicated in table 4 is for concerned stakeholders
to take action on any form of ethical violation and ensure effective communication and
awareness on ethical standards and punishments for their violation. More so, current law and
regulation concerned with ethical standards should be reviewed and adequately monitored.
There should be benchmark for effective ways of improving adherence to ethics in the
20
construction industry and organisation should hire the right personnel using acceptable
standard of knowledge, experience and qualification.
Table 4. Enhancing Adherence to Ethical Standard
Source: Researcher
4.5 Discussion of Findings
Bowen et al. (2012) and Uneke (2010) noted that most individual are found of unethical
practices for personal gain, this is concerned with greed and sometimes favouritism which are
the important causes of unethical practices in the construction industry as revealed in this study.
Political influence and monopoly of bigger firms to smaller emerging companies are equally
important factors. Stanbury (2006) noted that construction contractors are influenced by
politicians to engage in unethica practice.
Due to unethical practices, Shakantu (2006) noted that quality of projects is reduced which
affect users’ safety and satisfaction. As revealed in the finding, dissatisfaction of clients is the
most notable effect of unethical practice in the construction industry. Oyewobi, et al. (2011);
Nawaz and Ikram (2013); and Inuwa, Usman and Dantong (2015) stated that unethical
practices lead to poor quality and defective structure development which results in high
maintenance cost. Legal action through legislative laws that spell out punishment for any
unethical practise is a critical measure for the practice in the industry. Rothwell and Baldwin
(2007) suggested that the construction industry requires a high level of supervision to regulate
employee behaviour, enforce standards and report ethical misconducts. However, Bowen et al
(2007) recognises South Africa as one of the countries with an abundance of legislative laws
but largely lacks the capacity to enforce. Whistle-blowing mechanism is found to be less
effective measure, this is substantiated by Chiu (2003) as well as Lewis and Uys (2007) that
the whistle –blowing mechanism is poorly protected hence its ineffectiveness over the years.
5 Conclusion and Recommendation
Despite various laws and code of ethics guiding stakeholders' practices in the construction
industry, some ethical misconduct is still prevalent. Notable among them are bribery and fraud,
falsification of experience, nepotism, illegal award of tender, collusive tendering and
overstatement of qualification/training to secure jobs. These are largely caused by greed,
Measures MIS SD RANK
Take action on ethical violation 4.600 6.364 1
Effective communication 4.378 10.468 2
Legislative laws that spell out punishment for any unethical practice 4.267 9.674 3
Review, monitor and report ethics behaviour 4.267 13.528 4
Development of honest and ethical construction culture 4.244 9.106 5
Establishment of annual business ethics training for employees and
employers
4.178 12.339 6
Punish offenders 4.133 8.544 7
Implementation of ethical guidelines and policy 4.133 9.925 8
Initiation of regular and random ethics checks 4.111 9.849 9
Constant supervision of ethics 4.044 8.139 10
Transparency and accountability in contract administration 4.022 7.810 11
Verbally promote ethical environment and relentlessly 3.911 7.274 12
Good whistle-blowing mechanism 3.889 7.969 13
Benchmark of effective ways of improving adherence to ethics in the CI 3.844 6.602 14
Hiring right personnel 3.844 7.455 15
21
political influence, pressure to meet unrealistic business objectives and deadlines as well as
lack of transparency. As a result of these practices, clients are becoming more dissatisfied due
to poor workmanship, deterioration in professionalism, poor quality infrastructure
development, low productivity/efficiency of project team, poor project coordination and high
maintenance cost.
There are exiting laws, regulations and guidelines guiding the practice of individuals and
stakeholders in the construction industry. More so, ethical misconduct is directly traceable to
construction professionals due to their direct influence on construction projects. In addressing
unethical practice, it is necessary for professionals’ bodies and their regulatory agencies to
improve on their existing code of conducts and seek better means to enforce and sanction
members found culpable of breaching them. Organisations should hire the right personnel, be
concerned about their welfare and ensure proper and timely training. Annual business ethics
training should also be established for employees and employers for proper awareness and
adequate knowledge of the nest way to conduct themselves in offering their services. More so,
whistle-blower protection mechanisms need to be revised and improved to enhance its
effectiveness.
6 References
Bowen, P. A., Edwards, P. J., & Cattell, K. (2012). 'Corruption in the South African
construction industry: A thematic analysis of verbatim comments from survey participants',
Construction Management and Economics, 30(10), pp. 885-901.
Bowen, P., Pearl, R., & Akintoye, A. (2007). 'Professional ethics in the South African
construction industry', Building Research and Information, 35(2), pp. 189-205.
Chartered Institute of Building (2006). 'Corruption in the UK Construction Industry', available
at http://www.ciob.org.uk/document/corruption-uk-construction-industry (accessed 5 July
2015).
Chiu, R. K. (2003). 'Ethical judgment and whistle blowing intention: Examining the
moderating role of locus of control', Journal of Business Ethics, 43(1-2), pp. 65-74.
Dabson, A., Plimmer, F., Waters, M. and Kenney, S. (2007). 'Ethics for Surveyors: What are
the problems?', Paper presented at the FIG Working Week, Hong Kong, China. 13–17 May
2007. Available from: www.fig.net/pub (accessed 9 September 2015).
Davis, M. (1991). 'Thinking like an engineer: The place of a code of ethics in the practice of a
profession', Philosophy & Public Affairs, pp. 150-167.
Ehsan, N., Anwar, S., & Talha, M. (2009). 'Professional ethics in construction industry of
Pakistan', In Ao, S. I., Douglas, C., Grundfest W. & Burgstone, J., Proceedings of the World
Congress on Engineering, 20 - 29 October, San Francisco, USA, pp. 1-5.
Greenhalgh, B. (1997) Practice management for Land, Construction and Property
Professionals; London, E & F N Spon.
Inuwa, I.I., Usman, N.D. & Dantong, J.S. (2015) 'The Effects of Unethical Professional
Practice on Construction Projects Performance in Nigeria', African Journal of Applied
Research, 1(1), pp. 72-88.
Lewis, D., & Uys, T. (2007). 'Protecting whistleblowers at work: A comparison of the impact
of British and South African legislation', Managerial Law, 49(3), pp. 76-92.
Mason, J. (2009). 'Ethics in the construction industry: The prospects for a single professional
code', International Journal of Law in the Built Environment, 1(3), pp. 194-204.
Nadeem, E., Sohail, A., & Muhammad, T. (2009). 'Professional ethics in construction industry
of Pakistan', In Ao, S. I., Douglas, C., Grundfest W. & Burgstone, J., Proceedings of the
World Congress on Engineering, 20 - 29 October, San Francisco, USA, pp. 729-733.
22
Nawaz, T., & Ikram, A. A. (2013). 'Unethical practices in Pakistani construction industry',
European Journal of Business and Management, 5(4), pp. 188-204.
Oyewobi, L., Ganiyu, B., Oke, A., Ola-Awo, A., & Shittu, A. (2011). 'Determinants of
unethical performance in Nigerian construction industry', Journal of Sustainable
Development, 4(4), pp. 175-182.
Rothwell, G. R., & Baldwin, J. N. (2007). 'Ethical climate theory, whistle-blowing, and the
code of silence in police agencies in the state of Georgia', Journal of Business Ethics, 70(4),
pp. 341-361.
Schoeman, C. (2014). Ethics and remuneration: Ethics-in the light, South Africa, HR Future.
Shakantu, W. (2006). 'Corruption in the construction industry: Forms, susceptibility and
possible solutions: Industry issues', Civil Engineering, 14(7), pp. 43-47.
Stansbury, N. (2006). 'Business not as usual', a paper published by the chartered Institute of
Builders, 3rd Quarter, pp. 3-8.
Uneke, O. (2010). 'Corruption in Africa South of the Sahara: Bureaucratic facilitator or
handicap to development?', The Journal of Pan African Studies, 3(6), 111-119.
Wolverton, M. L., & Wolverton, M. (1999). Toward a common perception of ethical behavior
in real estate, In Roulac, S. E. Ethics in Real Estate, USA, Springer Science, pp. 89-106.
Zarkada-Fraser, A., & Skitmore, M. (2000). 'Decisions with moral content: Collusion',
Construction Management & Economics, 18(1), pp. 101-111.
Zou, P. X. (2006). 'Strategies for minimizing corruption in the construction industry in China',
Journal of Construction in Developing Countries, 11(2), pp. 15-29.
23
An Appraisal of Imminent Unethical Practices in the
Nigerian Construction Industry: A Case of Abuja Abdul Hafeez and EM Ugbor
Department of Building
Ahmadu Bello University, Zaria – Nigeria
E-mail: mscenv10656@gmail.com
Abstract The Construction industry is composed of various professionals’ governed by a structured body with
ethical code of conducts but these codes are not always complied to. This research developed a frame
work for professional ethics compliance with a view to improving professional practice and ethics in
Nigerian Construction Industry. The study identified the areas of unethical practices, as well as the
causes of unethical practices among professionals in the built environment. Data were obtained using
questionnaires administered to Architects, Builders, Civil Engineers, Quantity surveyors and Town
planners involved in building project delivery. A total of two hundred and fifty-three (253)
questionnaires were distributed with two hundred and eighteen (218) returned and found worthy to be
included in the study. Data obtained were analysed using Relative Importance Index (RII) and
percentage. Findings show that 96% of respondents have experienced unethical conduct while
performing their duties. The study concludes that bribery (RII= 0.93), nepotism (RII= 0.89); fraudulent
activities (RII=0.87) and unethical tendering practices (RII=0.84) are the most common unethical
practice. The developed framework will improve professionalism and ethical behaviour in the
construction industry.
Keywords:
Construction, Ethics, Professionalism, Unethical Practices, Nigeria
1 Introduction Nigeria is one of the most developed countries in Africa. According to data from National Bureau of
Statistics (2015) the construction industry which comprises of civil and building works is one of the top
contributors to Nigeria’s Gross Domestic Product (GDP). One of the hindrances to meaningful growth
and development in Nigerian is the menace of corruption and corrupt practices (Oyewobi, et al., 2011).
Concerns about corruption have mounted in recent years, in tandem with growing evidence of its
harmful impact on development. Unethical practices are endemic in all industry world-wide, and the
construction industry is not an exception. Ameh and Odusami (2010) submitted that the international
community viewed corruption and other unethical practices as common occurrences at all stages of the
Nigerian workforce. Funds for infrastructure are being lost because of the unethical practices in the
industry. It is believed that the easiest way to siphon or divert public funds in through the construction
industry. Large construction projects like road conceal thousands of opportunities for bribery and
kickbacks. There is little opportunity to detect when costs have been artificially inflated to facilitate
money being diverted.
Transparency International (2005) describes construction as an industry possessing characteristics that
render it particularly susceptible to corruption. Unethical practices can take place at any stage of a
construction project at planning and design, pre-qualification and tender, construction and completion
(Oyewobi, et al., 2011).
24
The Nigerian construction industry is extremely susceptible to ethical erosion due to heterogeneous
nature of the industry which makes it imperative for construction professionals to exhibit high level of
professional ethics. To address the challenges arising from ethical malpractices, Transparency
International (2006) advocated for among other things a code of ethics. The purpose of a code of ethics
or set of ethical principles is to define a standard of conduct that reflects the values of the organization
or profession. They are designed to guide one's personal reaction to ethical dilemmas. But when it comes
to ethical dilemmas, not construction all stakeholders have the skills or competencies to deal with it.
The outcome of this research will be cornerstone for encouraging professionalism and professional
compliance to ethics, so that construction works meets clients' expectations. Ethical behaviour is a
significant aspect for the success of an organization, as a result of its influences in relations with various
stakeholders (employees, investors, clients, suppliers, etc.). Ethical malpractices have also lead to the
collapse of companies (Muya and Mukumbuwa, 2013). It is important for professionals to practice the
knowledge of ethics using applicable codes or standards. The more the professionals practice their
responses to ethical dilemmas, the more likely it is to make the right decision when the pressure is on.
Today, efforts are being made around the world to increase ethical and integrity among professionals.
The aim of the study is to appraise unethical practices in the Nigerian construction industry with a view
to improving professional practice and ethics. The objectives are to identify the areas and causes of
unethical practices in the construction industry. A framework was also developed for professional ethics
compliance in the construction industry in Nigeria
2 Literature Review Muya and Mukumbwa (2013) assert that the construction industry in develop and developing countries
are not immune to unethical practices. According to Nawaz and Ali Ikram (2013) the industry is
seriously infected with unethical behaviours which lay major obstacles towards growth and productivity
of the industry. The industry is a fertile breeding ground for unethical behaviours like fraud, bid-rigging,
bribery, collusion, coercion, misrepresentation of facts and extortion (Shakantu and Chiocha (2009);
Mukumbwa and Muya, 2013). According to Nawaz and Ali Ikram (2013) Corruption and bribery, bid
shopping, and fraud and unfair conduct are among the top three unethical practices prevalent in
Pakistani construction industry. Olatunji (2007) stated that professional misconduct in the construction
industry has not just affected public confidence but also respect for the professionals practising in the
industry.
The trend of unethical performance in Nigerian construction industry is a calamitous cancer eroding
millions in lost resources that could have been utilized for the development of nation’s infrastructure.
Thus, the pervasiveness of corrupt practices in the Nigerian construction industry if unabated, could
retard the growth of the industry, and consequently reduce the contribution of the sector to the Gross
Domestic Product (GDP). Unethical practices lay devastating effects on quality management, quality
of works and performance of projects in quality dimension. Unethical practice increases the cost of
construction, and lead to both time and cost overrun (Oyewobi et al., 2011).
Transparent International (2005) stated that fierce competition, numerous levels of bureaucracy for
obtaining statutory approvals and permits, the uniqueness of construction projects rendering it difficult
to compare pricing, the opportunities for delays and overruns and the fact that the quality of much of
the work is rapidly concealed by concrete, plaster, cladding or underground are factors that make the
construction sector prone to unethical behaviour. Construction professionals are expected to behave
with professional integrity and reasonable of care. Ideally professionals strive to achieve good quality
of work as they owe it to themselves and the general public. Only when professorial ethics are well
25
practiced, professionalism will be enhanced. Bowen et al., (2007) stated that construction professionals
are expected to conduct themselves with integrity, honesty and fairness.
Professionals (Engineers, Architects, Builders, Surveyors) directing and executing work at different
stages of the construction process in the Nigerian construction industry, have their own codes of ethics.
But the existences of professional ethical codes have not translated into ethical behaviour. Oladinrin
and Ho (2016) assert that the existence of codes of ethics in most organizations does not seem to have
reduced unethical behaviour especially in the construction organizations due to lack of effective ethics
management such as embeddedness of ethical codes
Ethics are dynamic and cannot be learnt once. It is a way of reviewing behaviour against constantly
changing standards. What may be ethical today, or in a particular society may be viewed differently by
others or at another time. Bayles (1989) defined professional ethics as a system of norms so that both
the morality and behaviour of professionals could be dealt with in their day-to-day practice by this
system. Professional ethics also ascribes moral responsibility not to an individual, but to all
professionals practicing in a particular profession. A code of ethics prescribes how employees are
expected to conduct themselves when faced with an ethical dilemma (Liu et al., 2004). Codes of ethics
guide an organisation, individual or even profession to help them conduct their business in accordance
with acceptable values of the society and integrity. Even with the presence of ethical principle and codes
unethical practices still flourish in the construction industry.
Various researchers have suggested ways to enhance compliance. Oyewobi et al. (2011) recommends
enactment of legislation to deal with small levels of corruption. They also suggested for strengthening
of professional institutions in the industry to punish members found wanting. This could include
withdrawal of practicing licenses of offenders. Training and educating professional on codes of ethics
should be one of the solutions to combating unethical practices in construction. Implementing codes of
ethics, ethics training programs and leaders as role model, are the major options which can streamline
the unprofessional behaviour within the construction industry according to Nawaz and Ali-Ikram
(2013). The role of the government is also very vital. Transparency International (2006) suggested
contracting opportunities being widely publicized; awards are made to those who meet the contractual
requirement and make best offers; the rule is clear and fair; the process is transparent with predictable
results and public officials are accountable.
Professional institutions have a crucial role to play in minimizing ethical lapses in the construction
industry. Ameh and Odusami (2010) posit that professional institutions should give more priority
consideration to ethical discourse such as professional negligence, liabilities, responsibility to the
profession and the society, whistle blowing and other contemporary ethical issues at technical sessions,
public lectures, and seminars. Many countries have legislated against corruption and other unethical
practices, not only in construction, but other industries as well. Enforcement of these laws and
prosecuting offenders is also very important.
3 Research Methodology This research was pursued through field survey. The field work entails the use of the questionnaire to
respondents to establish their perception on professional ethics and compliance in construction project
delivery. The research adopted a quantitative research method. According to Tero (2006) quantitative
research method is based on the premise that social phenomena can be quantified, measured and
expressed numerically. In other words, the information about a social phenomenon is expressed in
numeric terms that can be analyzed by statistical methods to deduct facts based on realities and
established truths.
26
The research adopted the simple random sampling for this study. Respondents were chosen to represent
professionals mostly involved from the planning to the construction phase of the project. Architects,
Builders, Civil engineers, Quantity surveyors and Town planners were the respondents of the research.
In view of the fact that the central limit theory states that a sample size of thirty (30) and above, is large
enough for any research work (Dawdy and Wearden, 1985). A total of two hundred and fifty-three
questionnaires were administered to the construction professionals within Abuja. Two hundred and
eighteen questionnaires were received adequately filled giving a percentage response of 86%.
The impact of the factors was measured on a 5-point likert scale ranging from 1 to 5. The numbers
correspond to: 1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly agree
Relative Importance Index (RII) =∑𝑓𝑥
∑𝑓×
1
𝑘 .............................1
Where,
∑fx = is the total weight given to each attributes by the respondents.
∑f = is the total number or respondents in the sample.
K = is the highest weight on the Likert scale.
4 Findings and Discussion From Table 1. it can be deduced that a greater percentage of the respondent are Builders (54.1%),
Architects (20.6%), Quantity Surveyors (14.2%), Civil Engineers (11.1%) and Town planners (10%).
The research has included stakeholders involved from planning, tender and construction stage.
Regarding the year of working experience of the respondents, 40.8% was the highest percentage
corresponding to 11-15years, followed by 16-20years with 21.1% of respondents, showing that a larger
percentage of the respondents were quite experienced. On the highest academic qualification of the
respondents 44.4% are first degree holders with a few 4.2% holding a doctorate degree.
Table 1. Respondents Profile
S/N Variable Option Frequency
(Nr)
Percentage
(%)
1 Professional : a) Architect 45 20.6
b) Builders 96 44.0
c) Quantity Surveyors 31 14.2
d) Civil Engineer 24 11.1
e) Town planners 22 10.0
Total 218 100
27
2 Working
Experience :
a) 0-5years 32 14.7
b) 6-10yeras 28 12.8
c) 11-15years 89 40.8
d) 16-20years 46 21.1
e) 20years and above 23 10.6
Total 218 100
3 Highest
Qualification
a) Ordinary National
Diploma (OND)
36 16.5
b) Higher National
Diploma (HND)
44 20.2
c) Bachelor’s Degree 97 44.4
d) Post-Graduate
Diploma/ Masters
32 14.7
e) Doctorate Degree 09 4.2
Total 218 100
(Source: Field Survey, 2015)
Table 2. Professional Ethics
S/N Option Frequency Percentage (%)
1 Is professional code of conduct
needful
a) Yes 201 92.2
b) No 17 7.8
Total 218 100
2 Have you had any training on
professional ethics
a) Yes 133 61
b) No 85 40
Total 218 100
3 Ever experienced unethical
conduct among professionals
a) Yes 206 94.5
b) No 12 5.5
Total 218 100
28
4 Have you ever reported unethical
conduct among professionals
c) Yes 183 84
d) No 35 16
Total 218 100
(Source: Field Survey, 2015).
The research inquired on the perception of respondents on the need for professional code of ethics. 92%
agreed that there is a need for professional code of ethics in the Nigerian construction industry while
7.8% think it is not necessary. As the industry strives to eradicate unethical behaviours, it is agreed that
professional code of ethics is a step in the right direction.
From Table 3. it can be seen that 61% of respondents have had training on professional ethics while
39% have not. This figure is low because all individual practicing in the industry should abide by the
code of ethics of his profession. If an individual has not had training on ethics he/she cannot apply it.
The low level of registration with professional could be said to be responsible
On unethical conduct in the industry, 94% of respondents have experience one or more unethical
conduct among professionals while only 4% have not. This figure is not surprising. It also reaffirms the
need for professional ethic compliance in the construction industry. Professionals do not report
unethical conducts among professionals in the Nigerian construction industry. 84% have never reported
as shown in Table. 2. This shows that the rate of reporting unethical conduct or behaviour of other
professionals is low. This could be said to have encouraged unethical practices in the industry.
Table 3. Unethical Practices in the Construction Industry
Frequency
Unethical Practices 1 2 3 4 5 (∑f) ∑fx Mean RII Rank
Bribery - - 20 31 167 218 1019 4.67 0.93 1st
Nepotism - 02 06 98 112 218 974 4.47 0.89 2nd
Exaggeration of professional capability - 03 18 98 99 218 947 4.34 0.87 3rd
Collusive tendering/unethical tendering
practices
- 09 14 115 80 218 920 4.22 0.84 4th
Dishonesty and unfairness - 04 53 64 97 218 908 4.16 0.83 5th
Negligence - 20 21 91 86 218 897 4.11 0.82 6th
Compromise on quality - 15 35 101 67 218 874 4.01 0.80 7th
Altering of construction document - 38 17 88 75 218 854 3.92 0.78 8th
Tender manipulation;
Negligence - 17 69 71 61 218 830 3.81 0.76 9th
Professional ineptitude - 41 77 56 44 218 757 3.47 0.69 10th
Supplanting 20 34 56 92 16 218 704 3.23 0.65 11th
Bid shopping 45 42 19 80 32 218 666 3.06 0.61 12th
Source: Field Survey, (2015)
29
Where: 1= Strongly Disagree, 2= Disagree, 3= Undecided, 4=Agree, 5=Strongly Agree
Unethical practices in the construction industry are presented in Table 4. It can be seen that
bribery (RII= 0.93) was ranked the highest occurring unethical practice observed. This
followed closely by nepotism (RII= 0.89); exaggeration of professional capability (RII=0.87),
collusive tendering/unethical tendering practices (RII=0.84) and dishonesty and unfairness
(RII=0.83).
Bribery is the most highly ranked unethical practice according to respondents. Government
officials are the most affected and it is mostly offered by individuals in the private sector.
Bribery is one unethical practice that that occurs at every stage of the lifecycle of a construction
project. At the planning stage to get approval, at tender stage to get contracts and at construction
stage before a contractor get payment for the work valued or valuation.
Nepotism occurs frequently in the Nigerian construction industry. Projects are sometime
awarded based on religious, tribal or political affiliation instead of competence and capability.
Collusive tendering also occurs. An example of unethical tendering practices is when staff of
the client organisation especially in government projects give out consultant/in-house estimate
to contractors to aid them in wining contract bids. Individuals and companies alike are guilty
of exaggerating their capabilities. This is occurring when they include someone’s profile that
is not their staff in the companies’ profile to help boost their capability to win contracts.
Individuals also exaggerate when presenting their capabilities to impress client. Nigerian
construction contractor also compromise quality to make profit.
Table 4. Causes of unethical Practices
Frequency
Causes 1 2 3 4 5 (∑f) ∑fx Mean RII Rank
The participation of non-professionals in the
industry;
- 11 23 35 149 218 976 4.48 0.90 1st
The fragmented nature of the industry - 29 - 36 153 218 967 4.44 0.89 2nd
Inadequate of convictions in corruption cases - - 15 147 56 218 913 4.19 0.84 3rd
Low income levels of professionals 03 21 18 71 105 218 908 4.17 0.83 4th
Effect of politics on public works/ political
interference;
09 12 18 83 96 218 899 4.12 0.82 5th
Availability of loop holes in project
monitoring
11 15 34 51 107 218 882 4.05 0.81 6th
Fear for status relegation after retirement - 29 11 116 62 218 865 3.97 0.79 7th
Collision between officials and contractors - 20 45 97 56 218 843 3.87 0.77 8th
Greediness and personal interests; 17 57 34 66 44 218 717 3.29 0.66 9th
(Source: Field Survey, 2015)
Where: 1= Strongly Disagree, 2= Disagree, 3= Undecided, 4=Agree, 5=Strongly Agree
The participation of individuals who are not professionals has been identified as major causes of
unethical behaviour in the industry. They don’t belong to any professional body in the industry or have
registration with any council regulating their practice. Because they are not professionals they don’t
have knowledge of ethics and they tend to act unethically. Up until 2015 any individual can register a
30
construction company. There has been significant improvement because a registered professional in
that field is needed to register a company in that area. For example, a registered Builder is needed to
register a building construction company. The construction industry in Nigeria has seven (7)
professions. The industry is fragmented. Every profession has its code of ethics. There is no single code
of ethic for the industry.
Lack of convictions in most unethical practice cases in Nigeria is a major factor that has been
encouraging unethical practices. There are very few cases of convictions in corruption and unethical
practice cases in Nigeria and the construction industry even though stakeholders have agreed that there
is high prevalence of unethical and corrupt practices in the construction industry in Nigeria. When
individuals who were suspected to acting unethically and are corrupt are not convicted. Others would
be encouraged because they know they wouldn’t be punished. The low income and high cost of living
is also a major cause of unethical behaviour. This affects both civil servants and professional. They act
unethically to get additional income.
Table 5: Proposed steps to improve professionalism and ethic compliance in the construction industry
Description Expected Action Duration Evaluation
Ethics Training and
Registration into
professional bodies
Training on
Ethics/Registration with
professional bodies before
practice
Taking up membership by
individuals/ Ethical
training by professional
bodies
2016-
2021
2019
Database The country need to
establish a strong dataset
for Professional bodies
Legal backing with
Government support
2016-
2021
2018
National Building
code
The code would establish
a clear cut boundaries and
definition of the duties of
each professional as well
as the corresponding
restriction of practice to
all professions
Need Act parliament for
legislation and support
from Government to
enforcement
2016-
2021
2017
New and more
feasible penalty for
defaulters /
Reviewing professional
code of ethics. To include
new clauses and
punishment in line with
current practices/ The
Professional Bodies
should at intervals review
the professional ethics to
accommodate checkmate
recent unethical conducts
Need legal backing with
Government to tackle
changing ethical issues/
Amending code of ethics
and law
2016-
2021
Yearly from
2016
Source: Researcher
31
The individuals need to register with their professional bodies before practice. Awareness should be
raised among both individuals and clients on the need to employ professional services. These
professionals’ bodies should be able to give proper training on ethics and professional practice which
will help professionals when responding to unethical situations. The industry needs to establish a strong
database for professionals which are currently unavailable. There is the need to have a National Building
Code to restrict and regulate the industry. The Building code will establish clear cut boundaries and
definition of the duties of each professional as well as the corresponding restriction of practice to
registered members. This needs legal backing with Government and Parliamentary support. The role of
the professional bodies should appoint monitoring committee to monitor and ensure that only registered
members practice. Clients both private and public should appoint only registered professionals which
are in the database of professional bodies.
When professional ethics are breached by members, the professional bodies should thoroughly
investigate cases and make the outcome public to either punish or vindicate the individual(s) concerned.
Applying sanctions to unethical acts is an important step toward establishing accountability. Sanctions
should be centred on legislation to criminalise unethical behaviours. Punishment for unethical
behaviour should be reduced as some fines are now insignificant because some of these laws were
passed over 20 years ago and are insignificant today.
The Professional bodies should at intervals review the professional ethics to accommodate and
checkmate emerging unethical conducts and behaviours. There is need for legal backing from the
Government to tackle changing ethical issues. The professional bodies should report to facilitate
consequent review of the ethics.
5 Conclusion and Recommendations The importance of ethics cannot be over emphasized in our world today. Ethics and professionalism is
one of the most important aspects in business and in the life of a professional which can guarantee long
term success. Unethical practices are prevalent during construction project delivery in Nigeria as seen
from various literatures and from the findings of this research. There is need to strengthen and improve
professional ethics in the industry. The study concludes that bribery, nepotism, exaggeration of
professional capability, dishonesty and unfairness and unethical tendering practices are the most
occurring unethical practice in the Nigerian construction industry. The study also concludes that the
large participation of non-professionals in the industry, the fragmented nature of the industry,
inadequate convictions in corruption cases and low income levels of professionals are the cause of
unethical practices in the construction industry.
The study recommends training on ethics and professionalism at all level in the industry. It should be
included in the syllabus of undergraduate in tertiary institutions Clients and the general public need to
be educated on the need to engage only professionals on their projects. This would go a long way in
improving the image of the industry which has been tainted by activities of quacks participating in the
industry. The 6-year actions plan suggested in this study could be a useful tool in improving
professionalism and ethics when implemented.
6 Acknowledgement It is important to note that this study is part of a research thesis appraising professional ethics
compliance in building project delivery in Abuja – Nigeria.
7 References
32
Abdul-Rahman, H., Wang, C & Xiang W,Y. (2010), How professional ethics impact construction
quality: Perception and evidence in a fast developing economy. Scientific Research and
Essays. 5(23), pp. 3742-3749.
Ameh, J.O & Odusami, K.T. (2010b), ‘Nigerian building professionals’ ethical ideology and
perceived ethical judgement’, Australasian Journal of Construction Economics and
Building, 10 (3), pp. 1-13.
Ameh, O. J. & Odusami, K. T. (2010), ‘Professionals’ Ambivalence toward Ethics in the Nigerian
Construction Industry’, Journal of Professional Issues in Engineering Education and
Practice, 136(1).
Bayles M.D. (1989), Professional Ethics. Second Edition, Belmont Publishing Company, California.
Bowen, P., Akintoye, A., Pearl, R. & Edwards, P.J. (2007), ‘Ethical behaviour in South African
construction industry’, Construction Management and Economics, 25 pp. 631-648.
Liu, A. M. M., Fellows, R., & Jess, N. (2004), “Surveyors perspectives on ethics in
organizational culture”, Engineering, Construction and Architectural Management,
11(6), pp. 438–449.
Muya, M. & Mukumbwa, B. (2013), Integrity Systems in Construction Organizations in Zambia
International Journal of Architecture, Engineering and Construction 2(2), pp. 106-119.
National Bureau of Statistics. (2015). Nigerian Construction Summary Report (2010-2012).
Nawaz, T. & Ikram, A. (2013), ‘Unethical Practices in Pakistani Construction Industry’, European
Journal of Business and Management, 4(5).
Oladinrin, O.T & Ho, C.M (2016). Embeddedness of codes of ethics in construction
organizations, Engineering, Construction and Architectural Management, 23 (1), pp.75 –
91.
Olatinji, O.A. (2007), ‘Conflict of interest within Construction Practitioners: Quantity Surveying,
Case study’, Surveying and Built Environment, Vol. 18(1), pp. 35-50
Oyewobi, L. O., Ganiyu, B. O., Oke, A. A., Olaawo, A. W., & Shittu, A. A. (2011),
‘Determinants of unethical performance in the Nigerian construction industry’, Journal of
Sustainable Development, 4(4), pp. 175–182.
RICS. (2000). Professional Ethics Guidance Note: Part 1 Introduction, RICS Professional
Regulation and Consumer Protection Department, London.
Shakantu, W. and Chiocha, C. (2009). Corruption in the construction industry: The case of
Malawi. RICS COBRA Research Conference, University of Cape Town, Cape Town,
South Africa, 1568-1576.
Transparency International (2005). Global corruption report 2005, Pluto Press, London.
33
Confirmatory Factor Analysis of Contractors’ Safety
Policy Zakari Mustapha, Clinton Aigbavboa and Wellington Didi Thwala
Department of Construction Management & Quantity Surveying,
University of Johannesburg, South Africa
Email: zakari.mustapha1967@gmail.com
Abstract:
Health and Safety (H&S) compliance has been problem to majority of Small and
Medium-Sized Enterprises (SMEs) contractors’. The purpose of the study is to perform
a Confirmatory Factor Analysis (CFA) on safety policy of contractors’. A face-to-face
method of questionnaire administration was adopted among the SMEs contractors in
Ghana. Findings from Structural Equation Modelling (SEM) analysis confirmed that
the Rio and the Cronbach’s alpha coefficients were over 0.70 criteria for acceptability
on the internal consistency. There was a significant influence of contractors’ safety
policy features on the H&S compliance. Hence, strong in predicting H&S compliance.
The article makes a significant contribution towards SMEs contractors’ safety policy
through the use of SEM. The practical contribution of the article is the application of
the safety policy model by contracts and its enforcement by the Ministry of Water
Resources, Works and Housing.
Keywords: Construction, Compliance, Health and Safety, Policy
1 Introduction
The well-being of workers among Small and Medium-Sized Enterprises (SMEs) contractors is
affected by the high rate of accidents at their workplaces. SMEs contractors are faced with
difficulties in sourcing financial resources, expertise and staff which have significant effect on
safety regulations compliance (Department of Occupational Safety and Health Annual Report
(DOSH, 2008). The said difficulties have limited their purchasing power for equipment and
training of employees (Ofori & Toor, 2012; International Labour Office (ILO, 2005). SMEs
contractors H&S compliance in relation to safety policy were found to be lacking. Moreover,
SMEs contractors form the bulk of the contractors in Ghana and provide operational flexibility
to the larger firms as sub-contractors (Ofori & Toor, 2012; ILO, 2005). It is presumed that the
identified contractor’s safety policy constructs found in literature will be effective in measuring
contractors’ safety policy for H&S compliance in the Ghanaian cultural context. The purpose
of this study is to carry out a confirmatory factor analysis of safety policy features for use in
H&S compliance study among SMEs contractors in Ghana. The article begins with an
overview of a literature review on the topic in question. The methodology adopted for the study
is presented, followed by the findings of the research. Finally, conclusions are drawn and
recommendations made. The article makes a significant contribution towards contractors’
safety policy features and provides significant insight into SMEs contractors H&S compliance
improvement.
1.1 Occupational Health and Safety of SMEs Contractors’
34
Report from the International Labour Organisation (ILO, 2005) has shown that majority of
large companies concentrate on a few specialized core areas due to demand for flexibility
arising from globalization. Outsourcing and subcontracting have been attributed to the large
number of SMEs, micro-enterprises and self-employed workers (ILO, 2005). Most of the SMEs
contractors operate in the informal economy beyond any coverage by the formal Occupational
Safety and Health (OSH) or inspection services because they are not adequately covered by
safety and health legislation (ILO, 2005). Occupational hazards and risks are recognized to be
more widespread in SMEs contractors than in large enterprises due to their unwillingness to
seek relevant advice on H&S inspection (ILO, 2005). Construction H&S as posited by Furter
(2011) has become one of the top ten risks. Research has also shown that legislation or targeted
regulations can influence H&S performance of either a project, industry or a stakeholder
(Construction Industry Development Board (cidb, 2008). It is not sufficient to provide safe
equipment, systems and procedures if the culture is not conducive to a healthy and safe working
environment (Institution of Occupational of Safety and Health (IOSH, 2004). Since, culture
creates a homogeneous set of assumptions and decision premises in which compliance occurs
without surveillance (Grote, 2007).
It is also argued that a positive culture leads to both improved H&S as well as organisational
performance (Dingsdag, Biggs, Sheahan & Cipolla, 2006). Behaviour is a product of culture
just as much as accidents are a product of the prevailing culture (Wiegmann, Zhang, von
Thaden, Sharma & Mitchell, 2002). Wiegmann et al. (2002) further argued that sustained
improvement in H&S is not possible without cultural change. OSH culture can be described in
terms of the informal, cultural aspects of an organisation. The latter can have an impact on how
OSH is perceived and dealt with, and on whether people are aware of OSH-related issues and
act in a safe and healthy way (European Agency for Safety and Health at Work (EU-OSHA,
2011). 'OSH culture' - can be seen in terms of the relationship between organisational culture
and OSH. OSH culture is about how an organisation’s informal aspects influence OSH, either
positive or negative. This is possible through the following two steps: i. Setting the values and
norms, and underlying beliefs and convictions, through which workers deal with or disregard
risks; ii. Influencing the conventions for (safe or unsafe, healthy or unhealthy) behaviour,
interaction, and communication (EU-OSHA, 2011). OSH culture can be assessed as part of a
process of organisational improvement. It is also perceived and dealt with among workers in
an organisation and whether workers are aware of OSH-related issues and act in a safe and
healthy way. The knowledge and information gained from such a cultural approach, can in turn
be very useful in the process of changing OSH-related policies, processes, and practices step
by step, adapting them to the existing local context and culture, and eventually leading to better
OSH performance (EU-OSHA, 2011).
The key issue for employers, business managers and OSH professionals to strive for excellence
in the field of OSH, is to ensure that occupational accidents and work related ill health are
prevented as much as possible, and that safe and healthy behaviour among all employees is
promoted (EU-OSHA, 2011). Policy formulation, implementation and monitoring are the
responsibility of government and are vital indicators that determine compliance of H&S among
SMEs contractors. However, an organisation’s H&S policy statement details out how it will
ensure a healthy and safe work environment. Individual policies need to be developed for
specific hazards and issues. Policies should be supported by procedures that provide the step-
by-step instructions on how policies will be achieved (Construction Design and Management
Regulations 2007 (CDM 2007). It has also been indicated in Section 2 of Health and Safety at
Work (HSW) Act 1974 that if an organization employs more than five people, it must have a
written H&S policy (CDM 2007). However, the latent construct for the study is Contrators
35
Safety Policy (CSP) and its indicator variables are safe storage of equipment, safe and healthy
work environment, safe storage of formwork and false work and do not service equipment
which is in operation. The first step towards the management systems approach to OSH and is
reflected in the Occupational Safety and Health Convention of 1981 (No. 155). Although, the
Act deals with OHS and working environment in a comprehensive manner, but it is largely a
policy rather than a prescriptive instrument. The Occupational Safety and Health Convention
of 1981 (No. 155) also provide priority to the formulation, implementation and periodic review
of a national policy to prevent accidents and injury to health arising from or that is linked with
occurrence of accident in the course of work. It also seeks to minimize, as far as possible the
causes of hazards inherent in the working environment (ILO, 2005). Moreover, the scope and
coverage of OSH provisions has evolved from a focus on industrial safety to one on workplace
safety and health, from protection to prevention and assessment of risks. Modern standards
reflect not only on collective responsibilities to workplace safety and health, but also the
respective roles, rights, responsibilities and areas for cooperation of and between employers,
workers and their representatives (ILO, 2005).
It is the responsibility of the H&S personnel to provide general H&S advice, and also advice
relating to construction H&S issues (Lingard & Rowlinson, 2005; Carpenter, 2006a) for
employees. Occupational Health and Safety (OHS) is core to the successful long-term
sustainability of any business and fortunately in South Africa, Health and Safety (H&S) is a
legislatively compliant criterion, enforced by the OHS Act 85 of 1993 and the Department of
Labour (Action Training Academy, 2014). Health policy is best formulated through rigorous
and objective assessment of data. Modern health policy poses complex legal, ethical and social
questions. Hence, the goal of health policy is to protect and promote the health of individuals
and the community. Government officials can accomplish this objective in ways that respect
human right (Gostin, n.d.). Table 1 shows the contractors’ safety policy conceptual variables.
Table 1: Contractors’ safety policy conceptual variables
Source: Researcher
2 Research Methodology
This section presents the methodology used during the questionnaire administration. From the
eight- hundred questionnaires administered, 558 questionnaires were returned at the end of the
survey. The sample size of 588 obtained for the study is considered as large (Kline, 2005). A
sample size less than 100 cases will be difficult to analyse when Structural Equation Mdeling
(SEM) is used as an analytical tool (Harris & Schaubroeck, 1990; Kline, 2005). The minimum
sample required for SEM analysis should be 200 respondents (Bollen, 1989). This requirement
was used by Bentler and Chou (1987). The variable ratio of an ideal SEM model has been
suggested by Tong (2007) to be at least 5:1. This implies, a SEM model with 10 observed
variables should have more than 50 respondents. There are 66 hypothesised observed variables
and the ratio to sample size for the current study is 8.45:1. Therefore, variable ratio to sample
Latent construct CSP construct Indicator variables Label
Contractors’ Safety Policy
(CSP)
Four (4) dependent
variables.
Five (5) independent
variables.
Eight (8) free parameters.
Five fixed non-zero
parameters.
Safe storage of equipment CSP 1
Safe and healthy work
environment
CPS 2
Do not service equipment
which is in operation
CPS 3
Safe storage of formwork and
false work
CPS 4
36
size meets the requirement recommendation in literature by Tong (2007). The sample data of
558 was finally taken through random sampling before carrying out an Exploratory Factor
Analysis (EFA) and Confirmatory Factor Analysis (CFA) respectively. 269 samples were
realised for the EFA analysis and 289 samples for CFA analysis. The study adopted a
quantitative method of data collection. A face-to-face method questionnaire administration was
carried out among Small and Medium-Sized Enterprises (SMEs) contractors in the major cities
(Accra-Tema, Kumasi and Takoradi) in Ghana. Structural Equation Modeling (SEM) software
version 6.2 was employed in the data analysis. The factor structure of the constructs was
assessed by the SEM software. The conceptual variables were then tested as a prior using SEM
of the questionnaire survey results (Hu & Bentler, 1999).
3.1 Model testing
The maximum likelihood method was used for the construct parameters. Consideration was
given to Yuan, Lambert and Fouladi’s coefficient, since psychometric data have a tendency not
to be normally distributed. This means that if Yuan, Lambert and Fouladi’s values showed
significance deviation from normality, the Satorra-Bentlet scale statistics (robust) would be
used as these have been found to perform adequate under such conditions (Bentler,1990). The
construct validity for the variables was conducted to demonstrate the extent to which the
constructs hypothetically relate to one another in order to establish the score reliability. The
measurement invariance (MI) for the contractors’ safety policy features was determined based
on the examination of the residual covariance matrix from CFA output results as opposed to
the correlation matrix. The MI ensures that the attributes would relate to the same set of
observations in the same way. While the covariance matrix establishes the variables that
adequately measure the contractors’ safety policy constructs. After the CFA was performed,
all indicator variables with an unacceptable high residual covariance matrix greater than 2.58
were dropped. This implies that the identified indicator variables do not sufficiently measure
the contractors’ safety policy features regardless of their importance in other cultural contexts
and previous studies.
Bryne (2006) and Joreskog and Sorbom (1998) opined that residual covariance matrix greater
than 2.58 are considered large. Therefore, in order for a variable to be described as well-fitting
in measuring a construct such as contractors’ safety policy, the distribution of residual
covariance matrix should be systematically and centred on zero (Bryne, 2006; Joreskog &
Sorbom, 1998). This procedure was adopted as a means to ensure that the indicator variables
were measuring the latent constructs. The assumption of measurement invariance is mostly
tested in CFA (Meredith, 1993) in order to allow for comparison of indicator variables under
the same condition. In the current article, CFA was used for the assessment of measurement
invariance across latent variables. This procedure was adopted by Aigbavboa and Thwala
(2013) and Musonda (2012).
4 Findings and Discussion
This section provided demographic information on the individual respondents and the firms.
The analyzed results for the descriptive data were the respondent’s background information
including their individual information and the company information. A total of 269 samples
were realised for the EFA after the random sampling. The responses represent 82.2% (N = 221)
males and 17.8% (N = 48) females, as shown in Table 2.
Table 2: Gender
Gender Frequency Percent (%)
Male 221 82.2
37
Female 48 17.8
Source: Researcher
Table 3 shows that majority of the respondents (32.7%; N=88) were between the ages of 26-
30years, followed by the age group of 31-35years (20.8%) and the aged range 20-26years and
36-40 years constituted (14.1%) each respectively of the sample.
Table 3: Age Group
Age Group Frequency Percent (%)
Less than 20years 7 2.6
20-25years 38 14.1
26-30years 88 32.7
31-35years 56 20.8
36-40years 38 14.1
41-45years 23 8.6
46years and above 18 6.7
Missing 1 0.4
Source: Researcher
The highest education level of the majority of the sample respondents was National Diploma
or Certificate (34.9%; N = 94) and the least of the sample respondents was Post-Graduate
degree (10.0%; N=27) as shown in Table 4.
Table 4: Highest Qualification
Qualification Frequency Percent (%)
Senior School Certificate 42 15.6
National Diploma or Certificate 94 34.9
Bachelor’s Degree 90 33.5
Post-Graduate 27 10.0
Missing 16 5.9
Source: Researcher
Table 5 shows that a large number of the respondents (38.3%) have worked in the firm between
2 -5years, followed by year group of 6-10years (28.6%) and the year range 31years and above
constituted the least (1.5%) of the sample.
Table 5: Tenure in the Firm
Tenure Frequency Percent (%)
2-5years 103 38.3
6-10years 77 28.6
11-15years 32 11.9
16-20years 30 11.2
21-25years 11 4.1
26-30years 10 3.7
31years and above 4 1.5
Missing 2 0.7
Source: Researcher
Majority of the respondents (27.1%; N=73) indicated their firms have been in existence in the
range of 15-20 years, followed by the year range of 5-9 years; N=64) and the firm with the year
range of 21-30 years constituted the least (11.9 %; N=32) of the sample as shown in Table 6.
Table 6: Existence of Firm
Existence Frequency Percent (%)
5-9years 64 23.8
10-14years 62 23.0
38
Source: Researcher
Table 7 shows that majority of the respondents were employed by the private firms (62.1%;
N=167), followed by public (24.5%, N=66) and the sole proprietorship has the least number of
respondents (13.0; N=35) of the sample.
Table 7: Firm Ownership
Ownership Frequency Percent (%)
Private 167 62.1
Public Liability 66 24.5
Sole Proprietorship 35 13.0
Missing 1 0.4
Source: Researcher
Majority of the ongoing projects were under public liability (50.9%; N=137), followed by
private firms (39.8%; N=107) and the sole proprietorship constituted the least (5.6%; N=15) of
the sample as shown in Table 8.
Table 8: Ongoing Projects
Ongoing Frequency Percent (%)
Private 107 39.8
Public Liability 137 50.9
Sole Proprietorship 15 5.6
Missing 10 3.7
Source: Researcher
Table 9 Majority of the respondents (66.9%; N=180) were carrying out Building Construction
Works, followed by Civil Engineering Works (30.1%; N= 81) and Other Works has the least
of the respondents (1.5%; N=4) of the sample.
Table 9: Type of Projects
Type Frequency Percent (%)
Building Construction 180 66.9
Civil Engineering 81 30.1
Other 4 1.5
Missing 4 1.5
Source: Researcher
Majority of the respondents (43.9%; N= 118) indicated the National level as the geographical
spread of their firm, followed by Regional (26.8%; N= 72) and the International constituted the
least number of respondents (7.8%; N= 21) of the sample as shown in Table 10.
Table 10: Geographical Spread
Geographical Spread Frequency Percent (%)
Metropolitan 57 21.2
Regional 72 26.8
National 118 43.9
International 21 7.8
Missing 1 0.4
Source: Researcher
15-20years 73 27.1
21-30years 32 11.9
31years and above 35 1.3.0
Missing 3 1.1
39
Table 11 show that a large number of the respondents (31.2%; N=84) worked with D2/K2 class
of contractors, followed by D3/K3 class (30.9 %; N=83) and the D4/K4 class constituted the
least (9.3%; N=25) of the sample.
Table 11: Classification of Firm
Classification Frequency Percent (%)
D1/K1 67 24.9
D2/K2 84 31.2
D3/K3 83 30.9
D4/K4 25 9.3
Missing 10 3.7
Source: Researcher
D1/K1 - D4/K4 (Building & Civil Engineering Contractors) classification, from the lowest to
the highest based on their financial standing, equipment holding, qualification and number of
permanent employees.
4.1 Measurement model for contractors’ safety policy
Table 1 shows four (4) indicator variables (CSP 1, CSP 2, CSP 3 and CSP 4) with acceptable
residual covariance matrix. The acceptability of residual covariance matrix was as a result of
its symmetrical and centred on zero (Byrne, 2006:94; Joreskog & Sorbom, 1988) deemed well-
fit for a model. The four-indicator model provides good measures of residual matrix and
evidence of convergent validity. The assessment of the CSP model goodness-of-fit was based
on the four indicator variables. Some scholars (Bollen, 1998; Bryne, 2006; MacCallum,
Browne & Sugawara, 1996) have suggested a minimum of four indicator variables. Therefore,
the data obtained fall within the minimum requirement. Robust maximum likelihood method
was used because the analysis of Yuan, Lambert and Fouladi’s values showed that data
deviated significantly from normality (Yuan, Lambert and Fouladi = 262.0696). The
examination of the Bentler-Weeks structure representation for the approved construct revealed
that CSP construct has four (4) dependent variables, five (5) independent variables and eight
(8) free parameters. The number of fixed non-zero parameters was five (5).
Table 12 shows that the sample data on CSP measurement model yield an S – Bχ2 of 3249.5
with 1861 degrees of freedom. The associated p-value was determined to be 0.0000. The chi-
square value advocated that the difference between the sample data and the postulated
contractors’ safety policy features measurement model was significant. From these values, the
chi-square value was determined to be 1.75. The normed chi-square is the procedure of dividing
the chi-square by the degree of freedom. The normed values up to 3.0 or 5.0 are recommended
(Kline, 2005). The ratio of S – Bχ2 to the degree of freedom was lower than the lower limit
value of 3.0 suggesting a good fit of the data to the construct (Byrne, 2006).
Table 12: Robust fit indexes for contractors’ safety policy features construct
Fit Index Cut-off value Estimate Comment
S – Bχ2 3249.5
df 0≥ 1861 Good fit
CFI 0.90≥ acceptable
0.95≥ good fit
0.794 Acceptable
RMSEA
Less than 0.05 with
confidence interval (CI)
0.00-0.05 “good fit”
0.051
Good fit
40
95%
NFI Greater than 0.90 “good fit”
0.629 Acceptable
NNFI Greater than 0.80.
“good fit”
0.777 Acceptable
RMSEA 95% CI 0.048: 0.054 Acceptable
range
Source: Researcher
Table 12 shows the goodness-of-fit indexes. The comparative fit index (CFI) of 0.794 was
found to be slightly lower than the cut-off value for good fit model. A model is said to be good
fit if the CFI is greater or equal to the cut-off value of 0.95 (Hu & Bentler, 1999; Joreskog &
Sorbom, 1998). This indicates a drop (difference of 0.156) in the CFI value, hence the model
can be described to have an acceptable fit (Schreiber et al., 2006; Hu & Bentler, 1999) though
not well fitting. However, the robust mean square error of approximation (RMSEA) with 95
per cent confidence interval was found to be 0.051 (lower bound value = 0.054 and the upper
bound value =0.048) which is within the acceptable range for a good fit model (MacCallum et
al., 1996). Moreover, both the normed fit index (NFI) and non-normed fit index (NNFI) were
found to be within the acceptable range of 0.629 and 0.777 respectively (Schreiber et al., 2006;
Hu & Bentler, 1999). Evaluation of RMSEA (95% CI), CFIs, NFIs and NNFIs indicated an
acceptable fit of the measurement model, but not very good for a government support features
factor.
4.2 Testing the direct influence of contractors’ safety policy (CSP) features on overall
health and safety compliance
Determination of the internal consistency for the CSP measurement model was made possible
through the examination of the Rio coefficient and the Cronbach’s alpha coefficient to establish
reliability. Kline (2005) posited that the desired multivariate reliability coefficient should fall
between zero and 1.00. Cronbach’s alpha and the Rho Coefficient of Internal Consistency were
examined to determine the score reliability. The Rio coefficient of internal consistency was
found to be 0.964 which was above the minimum value of 0.79. The Cronbach’s alpha was
found to be above the minimum value 0.70 at 0.937. High levels of internal consistency and
internal reliability were as shown in Table 13.
The examination of the magnitude of the parameter coefficients led to the determination of the
construct validity. Hence, high parameter coefficients greater than 0.50 indicate a close relation
between the factor and the indicator variable. Hair, Anderson, Tatham and Black (1998) posited
that a parameter coefficient of 0.50 is interpreted as 25 per cent of the total variance in the
indicator variable being explained by the variable (factor). In this case, a parameter coefficient
has to be between 0.50 and 0.70 or greater to explain about 50 per cent of the variance in an
indicator variable. Hence, the inspection of the standardized parameter coefficient shown in
Table 13 shows that they were significantly high (values from 0.747 to 0.604). The minimum
estimate of 0.604 suggested that the measured factor accounts for 9.540 of the Z-statistics in
predicting the overall health and safety (H&S) compliance. The Z-statistics for each indicator
variables by the endogenous variables revealed that the scores were significant at 5 percent
level.
Table 13: Reliability and construct validity of CSP model
41
Indicator
Variable
Stad.
Coeff. (λ)
Z- Stat. R2 Factor
Loading
Sig.@5%
level?
CSP 1
CSP 2
CSP 3
CSP 4
0.471
0.787
0.629
0.573
6.509
10.710
10.021
9.506
0.602
0.779
0.381
0.605
0.5632
0.5187
0.5898
0.4125
Yes
Yes
Yes
Yes
Source: Researcher
Cronbach’s alpha = 0.937; Rio coefficient = 0.964
(Robust statistical significance at 5% level)
** SEM analysis norm (Kline, 2005) – One variable loading per latent factor is set equal to
1.0 in order to set the metric for that factor
*Parameter estimates are based on standardized solutions
Moreover, the assessment of the inter-factor correlation (R2) values for the contractors’ safety
policy feature indicator measures revealed that only one indicator value was close to the desired
value of 1.00, therefore not significant in predicting the contractors’ safety policy H&S
compliance. The inter-factor correlation test of statistics (Z-stats) which functions as a Z-
statistics test shows that the estimate is significantly different from zero. However, the R2 did
not significantly measure the R2 variable. The statistical assessment of the score results showed
that the influence of this factor on the R2 variable was weak (indirect). This is not withstanding,
the fact that the combined results revealed that it has a good indirect association in the
prediction of the overall H&S compliance.
4.3 Discussion of results
Findings from the study show that contractors’ safety policy indicator variables satisfied
internal reliability and the construct validity criteria. The Rio value was above the minimum
value of 0.70 (Table 13). The construct validity criteria were justified by the magnitude and
statistical significance of all parameter coefficients. The CFA analysis of the contractors’ safety
policy feature indicator revealed that four indicator variables passed the test and were used for
the assessment of the contractors’ safety policy measurement model goodness-of-fit.
Moreover, the indicator variables (safe storage of equipment, safe and healthy work
environment, safe storage of formwork and false work and do not service equipment which is
in operation) were closely associated with the dependent variable (contractor’s safety policy).
Further assessment of the Z-statistics accounted for each measure by the indicator variables
revealed that the scores were significant, since two Z-statistics values were close to 10.00 and
two were above 10.00. These results suggest that the direct influence of these variables on the
H&S compliance was strong (direct).
The government is responsibility for the H&S policy formulation. Moreover, the
implementation and monitoring of H&S policy among contractors by government officials will
serve as an important indicator that will determine contractors’ compliance. These findings
concur with the findings of Lingard and Rowlinson, 2005; Carpenter, 2006. Conducting a
confirmatory factor analysis to confirm the factorial validity of the contractors’ safety policy
features is very important because of its application in H&S study among contractors in Ghana.
42
The analysis of confirmatory factor analysis made it possible to characterize and identify
specifically the factors of contractors’ safety policy which have statistically significant
influence on the contractors in Ghana. Hence, contractors will find it important to implement
and monitor the safety policy formulated by the government in relation to their established
safety policy to ensure H&S compliance.
5 Conclusion and Recommendations
The postulated prior was analysed using SEM software with EQS version 6.2. The SEM
process was undertaken as both EFA and CFA of the prior variables. The CFA analysis
revealed that four indicator variables were successful in the factorial validity test conducted.
The four indicator variables used for the assessment of the contractors’ safety policy
measurement model goodness-of-fit are found to be a contributing factor to Health and Safety
(H&S) compliance. Further findings indicated that the Z-statistics for the four indicator
variables were within the acceptable range. The robust fit indexes had an acceptable fit, while
RMSEA value and the RMSEA with 95 per cent confidence interval produced an acceptable
range. Moreover, the parameter estimates were statistically significant and dealt with
successfully. Hence, the measurement model for contractors’ safety policy features had an
adequate fit to the sample data. The CFA result shows that only few variables were classified
as predictors of contractors’ safety policy in other cultural contexts from the literature review
to determine contractors’ safety policy in Ghana. Other studies that have used different research
methods on the determinants of support from the government are in agreement with the above
view.
This research supports the theory confirmation that measurement of indicator variables should
be the first stage of theory testing. It is therefore recommended that a checklist of items defining
the factors of contractors’ safety policy features should be made available to guide all
contractors’. Such basic requirement should have an influence on H&S compliance. It becomes
paramount to integrate H&S policy into the management systems of SMEs contractors at all
levels of construction. Moreover, the effective formulation and implementation of H&S policy,
regular education and training within the H&S policy should be encouraged both by the
government and the parties involved. The formulation of the government policy and its
implementation will enable contractors’ to provide safe and healthy work environment for all
their employees. Moreover, SEM software with EQS version 6.2 should be used to analyse the
variables that may be considered in the future for the development of H&S compliance projects.
The Ministry of Water Resources, Works and Housing should enforce the use of safety policy
by the contractors.
6 References
Aigbavboa, C.O. and Thwala, W.D. (2013) Confirmatory factorial validity of neighborhood
features among South African low-income housing occupants, Journal of Economics and
Behavioral Studies, 5(12), pp. 825-837.
Action Training Academy (2014). Occupational Health and Safety Compliance-Training-
Equipment, available at: http://www.actiontrainig.co.za [accessed 08 April 2015].
Bentler, P.M. (1990) Comparative fit indexes in structural models, Psychological Bulletin,
107(2), pp. 238-246.
Bentler, P.M. & Chou, C.P. (1987). Practical Issues in Structural Modeling. Sociological
Methods and research, 16(1), pp. 78-117.
Bollen, K.A. (1998) Structural Equations with Latent Variables, John Wiley & Sons, Inc., New
York.
43
Byrne, B.M. (2006) Structural Equation Modelling with EQS- Basic Concepts, Applications
and Programming, Lawrence Erlbaum Associates, Mahwah.
Carpenter, J. (2006) Developing guidelines for the selection of designers and contractors under
Construction (Design and Management) Regulations 1994, Norwich, Health and Safety
Executive.
Construction (Design and Management) Regulations 2007 (CDM 2007) Managing health and
safety in construction. Approved Code of Practice.
Construction Industry Development Board (cidb, 2008) Development through
Partnership.Construction Health and Safety in South Africa, available at:
http://www.asocsa.org [accessed 08 April 2015].
Department of Occupational Safety and Health Annual Report (DOSH) (2008), Department of
Occupational Safety and Health: Labour and Human Resources Statistics 2008, available
at: http://www.mohr.gov.my/ (accessed 20 February 2015).
Dingsdag, D.P., Biggs, H.C., Sheahan, V.L. and Cipolla, C.J. (2006) A construction safety
competency framework: Improving OHS performance by creating and maintaining a safety
culture, Brisbane: Cooperative Research Centre for Construction Innovation. Disaster
Management Institute (DMI) nd. Accident Causation Theories.
European Agency for Safety and Health at Work (2011) Occupational Health and Safety
Culture Assessment- A Review of Main Approaches and Selected Tools, Working
Environment Information, Working Paper, ed. Terence N. Taylor, T.N. (EU-OSHA),
Luxembourg: Publications Office of the European, available at: http://europa.eu/[accessed
02 May 2016].
Furter, E. (2011) Construction health and safety accidents have ‘dropped by half in five years,
Occupational Health and Safety, Environment and Quality Management, available at:
http://www. Sheqafriac.com [accessed 26 February 2016].
Gostin, L. (n.d.) “The Formulation of Health Policy by three Branches of Government.”
Institute of Medicine, Society’s Choices: Social and Ethical Decision Making in
Biomedicine, Washington, DC: The National Academies Press, 1995, available at:
http://www.nap.edu/r(accessed [accessed 02 May 2016].
Grote, G. (2007) Understanding and assessing safety culture through the lens of organizational
management of uncertainty, Safety Science, 45: pp. 637-652.
Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998) Multivariate Data Analysis,
5th edn, Prentice Hall, Englewood Cliffs, New Jersey.
Harris, M.M. and Schaubroeck, J. (1990) Confirmatory modeling in OB/HRM: Technical
issues and applications. Journal of Management Information Systems, 16, pp. 337-360.
Hu, L. and Bentler, P.M. (1999) Cut-off criteria for fit indices in covariance structure analysis:
conventional criteria versus new alternatives, Structural Equation Modelling, Vol. 6(1),
pp. 1-55.
International Labour Office (2005) Promotional framework for occupational safety and health
International Labour Conference, 93rd Session 2005, Report IV (1), International Labour
Office Geneva.
Institution of Occupational of Safety and Health (IOSH, 2004) Promoting a positive culture -
a guide to health and safety culture, 4.2. Leicestershire.
Joreskog, K.G. and Sorbom, D. (1998) PRELIS: A Program for Multivariate Data Screening
and Data Summarization. A Preprocessor for LISREL, 2nd edn, Scientific Software,
Mooresville.
Kline, R.B. (2005) Principles and Practice of Structural Equation Modeling, 2nd edn, Guilford
Press, New York.
Lingard, H. and Rowlinson, S. (2005) Occupational Health and Safety in Construction Project
Management. Spon Press 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN.
44
MacCallum, R.C., Browne, M.W. and Sugawara, H.M. (1996) Power analysis and
determination of sample size for covariance structure modelling. Psychological Methods,
1, pp. 130-149.
Meredith, W. (1993) Measurement invariance, factor analysis and factorial invariance.
Psychometrika, 58, pp. 525-543.
Musonda, I. (2012). Construction Health and Safety (H&S) Performance Improvement. A
client-Centred Model. Unpublished DPhil in Engineering Management. University of
Johannesburg. South Africa, available at: http://www.ujdigispace.uj.ac.za [accessed 02
June 2014].
Ofori1, G. and Toor, S.R. (2012) Leadership development for construction SMEs, in
Proceedings of the POC 2012 Conference, Working Paper Proceedings, Engineering
Project Organizations Conference, Rheden, The Netherlands, 10-12 July 2012.
Schreiber, J.B., Nora, A., Stage, F.K., Barlow, E.A. and King, J. (2006) Reporting structural
equation modeling and confirmatory factor analysis results: A review, The Journal of
Educational Research, 99(6), pp.323-338.
Tong, D.Y. (2007) An Empirical Study of E-Recruitment Technology Adoption in Malaysia:
Assessment of Modified Technology Acceptance Model, Multimedia University,
Malaysia.
Wiegmann, D. A., H. Zhang, T. L. von Thaden, G. Sharma, and A. A. Mitchell (2002) A
Synthesis of Safety Culture and Safety Climate Research, University of Illinois Aviation
Research Lab Technical Report ARL-02-03/FAA-02-2.
45
Influence of Health and Safety Practices on Performance
of Construction Projects in Abuja 1Richard Jimoh, 1Luqman Oyewobi, 2Kabir Ibrahim and 1Kadiri Abibu
1Department of Building
Federal University Technology, Minna, Nigeria
Email:1rosney@futminna.edu.ng 2Construction Management Department
Nelson Mandela Metropolitan University, Port Elizabeth, 6031, South Africa
Abstract:
In most developing countries, health and safety consideration in construction project delivery
is not given much priority, and employment of safety measures and practices during
construction is considered a burden. Although significant progress has been made over the
years, the need to continually improve the health and safety practices on construction sites
cannot be over-emphasised as a result of the dangerous nature of the industry. Hence, this paper
assessed the influence of health and safety practices on the performance of construction
projects in Abuja, with the use of questionnaire survey and personal observation. Findings
indicated that there was no statistical significant relationship between health and safety
practices and the project objectives (cost, time and quality). Furthermore, the personal
observations carried out showed that the level of compliance in terms of terms of safety rules
and scaffolding and materials storage/handling was fair. The study concluded that health and
safety practices have no influence on project objectives due to the little importance attached to
health and safety practices. Health and safety plan should be made mandatory for all contractors
during bidding process in order to improve health and safety practices and by extension
construction performance. The implication of the study on contractors is that adhering to health
and safety practices may go a long way in ensuring that cost, time and quality objectives are
met thereby making sure that clients have better value for their investment.
Key words:
Construction industry, Health and safety, and Performance
1 Introduction
In Nigeria, Occupational health and safety programmes were first introduced when the country
was a British colony (Onyejeji, 2011). Though there is no reliable data on accident cases in
construction, because contractors do not report accidents at appropriate ministry nor keep
proper records on accidents (Agwu and Hilda, 2013). Construction industry in Nigeria needs
special attention as far as safety is concerned and this is because the industry harbours a lot of
quacks and questionable tradesmen, most building contracts in the rural areas both private and
government contracts fall into the hands of illiterate “money bags’’ who have taken over
constructing jobs in Nigeria (Makinde, 2014).
Many people according to Agwu and Hilda (2013), have met their untimely death on
construction sites in Nigeria, while some others have lost their hands or limbs from construction
related injuries and fatalities due to some unplanned and uncontrolled events. Laufer and
Ledbetter (1986) describe fatalities as chance-caused events that are normally not given to
direct observation but rather most methods are based on post-factum measurement. Fatalities
can result in direct and indirect cost. Direct costs of construction fatalities are: medical bills,
46
premiums for compensation benefits, liability and property loss while the indirect costs are:
time lost in attending burial ceremonies, time lost in fatality investigations, down time of
damaged equipment and losses arising from site closure (Agwu and Hilda, 2013).
However, the poor safety performance of the construction industry has been a cause for concern
(Haslam et al., 2005) even though the industry, contributes to the economic development of
any developing nation (Kheni et al., 2008), and especially in an expanding economy like
Nigeria (Ibironke, 2004; Shittu & Shehu 2010). Okeola (2009) averred that at least 50% of the
investment in various development plans is primarily in the construction and the industry is the
highest employer of labour after agriculture in developing countries. The construction industry
in Nigeria generates almost 70% of the nation’s fixed capital formation, in spite of that, its
performance within the economy is very poor (Arazi & Mahmoud, 2010).
The synergy between health and safety and other project parameters (cost, environment,
productivity, quality and schedule) that would have been created which will have given rise to
better performance within the industry is lacking (Smallwood, 1996 cited in Smallwood, 2002).
Hence, due to this challenge bedevilling the construction industry with respect to health and
safety performance, the paper assessed the influence of health and safety practices on the
performance of construction projects in Abuja, Nigeria.
2 Literature Review
2.1 Health and Safety Practices in the Construction Industry
In most developing countries, health and safety consideration in construction project delivery
is not given much priority, and employment of safety measures and practices during
construction is considered a burden (Mbuya and Lema, 1996). However, in the Nigerian
construction industry according to Oresegun (2009), health and safety is viewed as an
inevitable aspect of construction since the only time an employee will perform his duties is
when he or she is in good health, sure of a safe working condition and assured of good health
care even when an accident occur. It is based on this view that most construction firms in
Nigeria would need to improve their health and safety practices as the rise in technological
advancements in the construction industry will lead to an upsurge in construction accidents.
Datta (2000) also added that the construction sector of developing countries also demonstrates
poor performance in respect of health and safety due to the absence of any rigid safety and
construction laws.
The health and safety performance of the construction industry remains a glaring challenge and
efforts to tackle the challenges that comes with this developmental initiative by many nations
including Nigeria are minimal (Okoye, and Okolie, 2014), hence Diugwu and Baba (2014)
argued that Nigeria falls within the category of countries having no adaptive health and safety
laws and regulations, where organisations allocates little resources to health and safety
management, rarely keep, report, or release accurate records of accidents and injuries on site,
leading to poor health and safety performance. They further argued that effective management
of health and safety is motivated by various factors of which could be centred on the need to
abide by existing rules and regulations, a consideration of human lives that are involved (socio-
humanitarian perspective), or on the direct and indirect cost involved (financial-economic
perspective).
Okolie and Okoye, (2012) asserted that the institutional and regulatory framework for
construction health and safety is highly fragmented and poorly implemented and call for urgent
47
need for provision of adequate and enforceable health and safety regulations for construction
operations as well as the establishment of construction industry training institutes including
trade centres in different parts of Nigeria. Olatunji and Aje (2005) opined that though
prequalification has gained tremendous support and popularity in contract procurement in
Nigeria, health and safety factors of contractor performance are not popularly prioritized. In
the same vein, Idoro, (2011) revealed that all categories of contractors operating in the Nigerian
construction industry do not perform better than each other in terms of health and safety and
hence calls on all the stakeholders in the industry to improve their health and safety
performance. The results of health and safety non-performance in Nigerian construction
industry are untold and can be seen in the number of fatalities and injuries arising from
construction activities across the country (Awodele and Ayoola, 2005; Dimuna, 2010; Ayedun
et al., 2012).
2.2 Construction Performance in Developing Countries
According to Ashford (1989), construction performance in developing countries can be
improved by the commitment of government and other relevant stakeholders, whose decisions
are key to performance in the construction industry. Most companies in the construction
industry use performance measurement to judge their project performances both financially or
otherwise and they use the results in comparing and contrasting their firm’s performance with
other firm so as to increase their firm’s productivity. Takim and Akintoye, (2002) stated that
construction project is acknowledged as successful when it is completed on time, within
budget, and in accordance with specifications and in accordance to stakeholder’s satisfaction.
Managing construction project for effective project performance according to Shigenobu and
Takayuki (2009), is the ability and capability of identifying the system, controlling the work
and accepting its output efficiently and effectively under required conditions. Lock (2007)
stated that the importance of effective project management for effective performance is to be
able to predict the dangers and problems, plan, organize and control activities for the project to
be completed within scheduled. According to Manuele (2003), the construction industry has
hinged the successful management of construction projects on the traditional parameters of
cost, time and quality. The growing rate of construction accidents has increased the awareness
of construction industry on health and safety, thereby involving its inclusion as part of project
performance criteria. But this can be achieved according to Goetzel (1999), by inculcating
safety culture in employees, which is directly related to the productivity and profitability of
organizations.
The construction industry in Nigeria generates almost 70% of the nation’s fixed capital
formation, in spite of that, its performance within the economy is very poor (Federal Office of
Statistics, Abuja as cited in Arazi and Mahmoud, 2010). Falemu-Ojo (2009) revealed that
quality of materials and workmanship in the Nigerian construction industry is not satisfactory
and that the problem lies in the use of inappropriate materials supplied to sites and inefficient
supervision of workmen which affects the construction performance. In a related development,
Balogun (2005) stated that most construction projects in Nigeria fail due to poor contractors’
performance which he characterized as poor workmanship, rework, low productivity, late
completion, cost overruns, high accidents rate, poor work practice and site conflicts. The last
decade however exposed the declining level of clients’ satisfaction from the built facilities as
a result of poor quality performance in addition to the perennial problems of time and cost
overruns in the Nigerian construction industry (Arazi & Mahmoud, 2010). Defects can result
in reduction of durability, strength and satisfaction to be derived from the project.
48
Galliker (2000) pointed out that organization’s employees safety culture has a direct
relationship with employees’ productivity, in view of the fact that assigned tasks can only be
safely accomplished when the work environment is safe and conducive for the execution of the
assigned duties, be it construction, manufacturing or servicing, thus, any phenomenon that
affects human production capacity will invariably affect organizational productivity hence
improving workers wellbeing offers the company the opportunity of enhancing its
performance.
3 Research Methodology
The research used a combination of questionnaire survey and observation for data collection
for the study, where 80 questionnaires were randomly self-administered to construction
professionals in small, medium and large sized construction firms in Abuja-Nigeria and 10
active construction sites were observed in order to determine their level of compliance in terms
of site management. Random sampling technique was adopted in order to eliminate bias in
sampling as illustrated by Morenikeji (2006). The methods used were based on the works of
Famakin et al. (2012) adopted survey; Cheng, Ryan and Kelly (2012) used survey and Shibani,
Saidani and Alhajeri (2013) adopted survey and interview. The data obtained from the survey
was analysed using Kendall tau to determine the influence of health and safety practices on
project objectives of cost, time and quality. Furthermore, the observations were analysed using
mean score and the results were ranked. Cut-off points indicated below to determine the
consensus based on the 5 point Likert scale was used.
1.0-1.49 Very poor; 1.50-2.49 Poor; 2.50-3.49 Fair; 3.50-4.49 Good; ≥4.5 Very good
4 Findings and Discussion
Table 1: Categories of Respondents by profession Profession Frequency Percentage
Architect 12 21.4
Builder 15 26.8
Civil Engineer 8 14.3
Quantity surveyor 5 8.9
Others 16 28.6
Total 56 100.0
Source: Researcher
The table indicates that 12 of the respondents were architects representing about 21.4% of the
total respondents. 15 were builders representing about 26.8%. 8 were civil engineer
representing about 14.3%. 5 of the respondents were quantity surveyor representing 8.9%. 16
of the total respondents were from others representing about 28.6%.
Table 2: Numbers of Workers Numbers of workers Frequency Percentage
1-49 28 50
50-249 16 28.6
250 12 21.4
Total 56 100.0
Source: Researcher
From the table above, it is shows that 50% of the respondents were employed by firms with
workers ranging from 1-49, 28.6% represents firms with workers ranging from 50-249 and
49
finally 21.4% represents those with workers above 250. From the table, that those with workers
from 1-49 has the largest percent and this could skew the results obtained.
4.1 Hypothesis Testing
To determine the statistical significant relationship between influence of health and safety
practices and the performance indicators (Quality, Cost and Time), three hypotheses were
formulated and Kendall tau test was used to determine the level of statistical significance as
presented below.
4.2 First Hypothesis
Null Hypothesis Ho: there is no statistical significant relationship between influence of health
and safety practices and quality.
Table 3: Influence of Health and Safety Practices on Quality VARIANCE P-
value
Significant
(2-tailed)
Significant if P<a=0.05
Health and safety practices 1.000
0.188
Not Significant
Quality performance 0.467
Source: Researcher
Table 3 above shows the summary of test of statistical significant relationship between health
and safety practices and quality. From the table above it can be deduced that health and safety
practices do not have influence on quality. Since the significant (2-tailed) value for all the
responses should be less than or approximately equals to a=0.05, therefore it can be concluded
certainty that there is no statistical significant relationship between the two parameters
measured. Hence the Null hypothesis is accepted.
4.3 Second Hypothesis
Null Hypothesis Ho: there is no statistical significant relationship between health and safety
practices and cost.
Table 4: Influence of Health and Safety on Cost VARIANCE P-value Significant
(2-tailed)
Significant if P<a=0.05
Health and safety
practices
1.000
1.000
Not Significant
Cost performance 0.000
Source: Researcher
Table 4 shows the summary of test of statistical significant relationship between health and
safety practices and cost. Based on the result, it can be concluded that there is no statistical
significant relationship between health and safety practices and cost. Hence the Null hypothesis
is accepted.
50
4.4 Third Hypothesis
Null Hypothesis Ho: there is no statistical significant relationship between health and safety
practices and time.
Table 5: Influence of Health and Safety Practices on Time VARIANCE P-value Significant
(2-tailed)
Significant if P<a=0.05
Health and safety
practices
1.000
0.348
Not Significant
Time performance -0.333
Source: Researcher
From the table, it can be concluded that there is no statistical significant relationship between
the health and safety practices and time at 95% confidence level. Hence the Null hypothesis is
accepted.
4.5 Analysis of the Observations
Ten active construction sites were visited to observe how their sites were managed in terms of
the following; compliance with safety rules and scaffolding and materials storage/handling.
Table 6: Safety rules s/n SAFETY RULES Level of compliance MS Rank Decision
1 2 3 4 5
A Hard hats 0 0 4 3 3 3.9 1 Good
B Shirts with sleeves
worn.
1 4 1 2 2 3.0 2 Fair
C Work shoes worn 2 2 0 6 0 3.0 3 Fair
D Work areas safe and
clean
0 4 2 4 0 3.0 4 Fair
E Provision for fall
protection for their
employees.
4 2 4 0 0 2.4 5 Poor
Source: Researcher
The table above shows the safety rules carried out to determine the ten firms’ compliance level,
Hard hats came first with a Mean Score of 3.9 which indicate it is being worn on sites, shirts
with sleeves worn, work shoe worn and work areas safe and clean came second with Mean
Score of 3.0, 3.0, 3.0 respectively and lastly provision for fall protection for their employees
came third with Mean Score of 2.4 and it indicates poor compliance among the list.
Table 7: Scaffolding and material storage/handling
51
s/n SCAFFOLDING AND
MATERIAL
STORAGE/HANDLING
Level of
compliance
MS Rank Decision
1 2 3 4 5
A Properly cross-braced 0 5 3 2 0 2.7 3 Fair
B Proper guardrails and toe
boards 4 1 2 2 1 2.5 4 Fair
C Scaffold planks capable of
supporting at least four (4)
times the maximum
intended load
0 1 1 5 2 3.0 1 Fair
D Materials are sited at least
two (2) feet from edge of
excavation site.
4 2 2 1 1 2.3 5 Poor
E Proper protective gear
worn when handling
chemicals.
2 3 2 1 2 2.8 2 Fair
Source: Researcher
Scaffold planks capable of supporting at least four (4) times the maximum intended load with
Mean Score of 3.0, came first, Proper protective gear worn when handling chemicals with
Mean Score of 2.8 came second, properly cross-braced with Mean Score of 2.7came third,
proper guardrails and toe boards with Mean Score 2.5 came fourth, while materials are sited at
least 2 feet from edge of excavation with Mean Score of 2.3 came fifth. This indicates medium
level of compliance, so more emphases need to focus on improving the use and management
of scaffold.
The above results are not surprising due to the 50% responses received from the respondents
that were employed in small sized construction firms as shown in Table 2. Okongwu (2010)
that stated firms do not comply with health and safety provisions; Windapo and Jegede (2013)
echoing the same thing stated that compliance level of indigenous construction firms in terms
of health and safety policies and procedures was low. This study is consistent with Famakin et
al. (2012) that stated that construction health and safety is not given adequate attention in the
same way as project parameters of cost, time and quality. In a related development, Shibani,
Saidani and Alhajeri (2013) stated that some safety managers in the United Arab Emirates
showed more concern for cost than health and safety. However, the study was different from
Cheng, Ryan and Kelly (2012) that was undertaken in Hong Kong where more priority is
accorded health and safety issues than what is obtainable in this study area especially when
small sized firms are involved.
5 Conclusion The influence of health and safety practices on the performance of construction projects in
Abuja was assessed. Based on the study, health and safety practices do not have influence on
construction project performance in terms of quality, cost and time parameters. Furthermore,
the results of the observations carried out indicated that the level of compliance with regards
to safety rules and scaffolding and materials storage/handling could be deemed to be fair.
Health and safety plan should be made mandatory for all contractors during bidding process in
order to improve health and safety practices and by extension construction performance. The
implication of the study on contractors is that adhering to health and safety practices may go a
long way in ensuring that cost, time and quality objectives are met thereby making sure that
clients have value for their money.
52
6 References Agwu, M. O. and Hilda, E.O. (2013). Fatalities in the Nigerian Construction Industry: A Case
of Poor Safety Culture; British Journal of Economics, Management & Trade, 4(3), 431-
452.
Arazi, B. I. and Mahmoud, S. (2010). Framework for Evaluating Quality Performance of
Contractors in Nigeria. International Journal of Civil & Environmental Engineering,
10(01), 34-39.
Ashford, J. L. (1989). The Management of Quality in Construction, London E& FN Spon.
Awodele, O. A., and Ayoola, A. C. (2005). An Assessment of Safety Programs on Construction
Sites. In: Journal of Land Use & Development Studies, 1(1), 1-13.
Ayedum, C.A., Durodola, O.D., and Akinjare, O.A. (2012). An Empirical Ascertainment of
the Causes of Building Failure and Collapse in Nigeria. Mediterranean Journal of Social
Sciences. 3(1), 313-322.
Cheng, E.W.L, Ryan, N and Kelly, S (2012). Exploring the perceived influence of safety
management practices on project performance in the construction industry. Safety
Science, 50, 363-369
Datta .M, (2000). Challenges Facing the Construction Industry in Developing Countries
Gaborone, Botswana, Proceedings of the 2nd International Conference on Construction
in Developing Countries, 15-17.
Dimuna, K.O. (2010). Incessant Incidents of Building Collapse in Nigeria: Challenges to
Stakeholders. Global Journal of Researches in Engineering, 10(4), 75-84.
Falemu-Ojo, A. (2009). Relationship Between Collapse and Quality of Material and
workmanship in Nigeria. Proceedings of the Royal Institution of Chartered Surveyors
Construction and Building Research Conference (COBRA) University of Cape Town,
South Africa, 10-11th September
Famakin, I.O, Makanjuola, S.A, Adeniyi, O and Oladirin, T.O (2012). Impact of construction
health and safety regulations on project parameters in Nigeria: Consultants and
contractors view. FUTY Journal of the Environment, 7(1), 114-122
Galliker, D. (2000). Betriebe in Bestform, GesundheitQualitat and
Umweltschutzauseinemguss, Wiesbaden.
Goetzel, R. (1999). Health and Productivity Management II, Measuring and Reporting
Workforce Productivity, Best Practice Report, Houston.
Haslam, R.A., Hide, S.A., Gibb, A.G.F., Gyi, D.E., Pavitt, T., Aikinson, S. and Duff, A.R.
(2005). Contributing Factors in Construction Accidents. Applied Ergonomics, 36, 401-
415
Ibironke, O. T. (2004). Building Economics. Birnin-Kebbi, Nigeria: TimlabQuanticost.
Idoro, G. I. (2011). Comparing Occupational Health and Safety (OHS) Management Efforts
and Performance of Nigerian Construction Contractors. Journal of Construction in
Developing Countries,16(2), 151-173
Diugwu, I.A and Baba, D.L (2014). A Health and Safety Improvement Roadmap for the
Construction Industry. KICEM Journal of Construction Engineering and Project
Management, 4(1), 37-44.
Kheni, N. Gibb, A. G. F., and Dainty, A. R. J. (2008). Health and Safety Management in
Developing Countries: A Study of Construction SMEs in Ghana. Construction
Management & Economics, 26(11) 1159-1169
Laufer, A. and Ledbetter, W.B. (1986). Assessment of Safety Performance Measures at
Construction Sites. Journal of Construction Division, ASCE. 112(4), 530-542.
Lock, D. (2007). Project Management (9th Edition). UK: Ashgate Publishing Limited.
53
Makinde, J. (2014). Assessments of Safety Measures on Building Sites (A Case Study of
Minna, North Central Nigeria; Greener Journal of Environmental Management and
Public Safety 3(1), 001-008.
Manuele, F. A. (2003). On the Practice of Safety. New Jersey: John Wiley & Sons.
Mbuya, E. and Lema, N.M. (1996). Towards Development of a Framework for Integration of
Safety and Quality Management Techniques in Construction Project Delivery Process.
International Journal of Quality. 14(5), 1–15.
Morenikeji, Wole. 2006. "Research and Analytical Methods." For Social Scientists, Planner
and Environmentalists. Nigeria: Jos University Press
Okeola, O.G. (2009). Occupational Health and Safety (ohs) Assessment in the Construction
Industry. Available at www.scribd.com
Okolie, K.C. and Okoye, P.U. (2012). Assessment of National Culture Dimensions and
Construction Health and Safety Climate in Nigeria. Science Journal of Environmental
Engineering Research, 2012, Article ID sjeer-167.
Okongwu, S.E. (2010). Effective safety and health planning on construction sites in Onitsha
and Awka of Anambra State. Unpublished MSc thesis submitted to the Department of
Building, Nnamdi Azikiwe University, Awka
Okoye, P. U., and Okolie, K. C., (2014). Exploratory Study of the Cost of Health and Safety
Performance of Building Contractors in South- East Nigeria. British journal of
Environmental sciences, 2(1) 21-33.
Olatunji, O.A. and Aje, O. I. (2005). An Assessment of the Use of Prequalification in
Contractors’ Selection in Construction Project Delivery: Challenges for Quantity
Surveyors. Proceedings for 2005 Quantity Surveyors’ National Convention, Malaysia.
Onyejeji, N., (2011). Nigeria Public Policy Global Policy Brief, No 18, January. Available at
www.bc.edu/agingandwork assessed 21/3/2013.
Oresegun, D. (2009). Health and Safety: The Nigerian Perspective. Available at
www.scribd.com.
Shibani, A, Saidani, M and Alhajeri, M (2013). Health and safety influence on the
construction project performance in United Arab Emirates. Journal of Civil
Engineering & Construction Technology, 4(2), 32-44
Shigenobu, O. and Takayuki, A. (2009). Japanese Project Management: KPM – Innovation,
Development and Improvement: Modern Institute of Management. Japanese
management and International studies, 3.
Shittu, A. and Shehu, M.A. (2010). Impact of Building and Construction Investment on the
Nigerian Economy during the Military Era (1991 – 1998) and Civilian Era (1999 - 2006).
Nigerian Journal of Construction Technology and Management. 11(1&2), 89-98.
Smallwood, J.J. (2002). The influence of health and safety (H&S) culture on H&S
performance. In: Greenwood, D (Ed.) Proceedings of the 18th Annual ARCOM
Conference, 2-4 September 2002, University of Northumbria. Association of
Researchers in Construction Management
Takim .R, and Akintoye .A. (2002). A Conceptual Model for Successful Construction Project
Performance. Paper presented at the Second International Postgraduate Research
Conference in Built and Human Environment, University of Salford, Salford, 11-12
April.
Windapo, A.O. and Jegede, O.P. (2013). A study of health, safety and environment (HSE)
practices of Nigerian construction companies. The Professional Builder, 4(1), 92-103
54
Exploring the Impact of Team Members’ Behaviours on
Accident Causation within Construction Projects Victor Okorie1, Fidelis Emuze2 and John Smallwood 3
1 University of Benin, Benin City, Nigeria, Email: v.okorie@yahoo.com 2 Central University of Technology, Free State, Bloemfontein, South Africa, Email:
Email: femuze@cut.ac.za 3 Nelson Mandela Metropolitan University, Port Elizabeth, South Africa,
Email: Smallwood.john@nmmu.ac.za
Abstract
The South Africa Construction Regulations recognise the contributions of each member of a
project team to health and safety (H&S) improvement. Notably, the regulations mandate the
propagation of certain behavioural traits from clients, designers, project managers, quantity
surveyors and contractors involved in project execution so as to improve construction H&S
performance in the industry. This paper therefore reports on a study that explored the impact
of H&S leadership styles and behaviours of these key project participants in terms of accidents
and injury causation. A structured questionnaire, which was designed to obtain information on
H&S contributions of these key project participants, was used for data collection. The resultant
descriptive and inferential statistics shows that clients’ and their consultants’ and contractors’
H&S leadership styles and behaviours have a significant influence on construction H&S
performance in South Africa. However, it was also noted that unethical behaviour found in
clients organisation in terms of procurement process and contract award to contractors without
adequate H&S records and competencies have a serious challenge to the improvement of H&S
performance in the industry. It was also observed that H&S is often not designed into project,
project H&S plans are not integrated, while no or little financial provision is made for site H&S
management. Overall these suggest trend towards poor leadership styles and behaviour in
construction. The study therefore recommends that clients, consultants and contractors should
demonstrate visible leadership and commitment towards projects H&S particularly during the
early planning stages for improvement and sustainability of workplace H&S culture.
Keywords:
Behaviour, Construction, Health and Safety, Leadership, South Africa
1 Introduction
Accident and fatality statistics in the construction sector all over the world have remained
roughly the same since the early 1990s (Brauer, 2006; Sherratt and Farrel, 2012). It has also
been observed that H&S related legislation, regulations, and management systems are not
enough to further improve construction H&S performance. According to Lees and Austin
(2011), the typical top-down control approaches to H&S management and rules enforcement
no longer achieves the desired results. Nevertheless, H&S legislation, regulations and
management systems have brought success to accident and injury prevention in the workplaces
(cidb, 2009). Lees and Austin (2011) further argue that such successes are limited as workplace
accidents are on-going.
Lutchman, Maharaji and Ghanem (2012) maintain that inadequacies in rule enforcement and
management oversights have led to the search for better ways of managing construction H&S.
Sherratt and Farrel (2012) and Lutchman et al. (2012) argue that understanding human
dynamics or behaviours in relation to industrial H&S is better than focussing on legislation,
55
regulations and H&S management systems. In addition, the behavioural science approach to
H&S management according to Krause (1997) postulated that behaviour change will lead to
the expected change in attitude. Lutchman et al. (2012) point out that the behaviour-based H&S
management concept was developed on the premise that workplace H&S can be better
managed by understanding human behaviour. Sherratt and Farrel (2012) elucidate that
behaviour-based H&S is proactive, objective, and fosters problem-solving perspectives by
identifying human behaviours as it relates to the root causes of workplace accidents, and then
analyses the problems before they occur.
Krause (2003) maintains that to achieve long-term change in H&S related performance, it is
necessary to examine the behaviours and leadership styles exhibited by the key project
participants. In support of the relationship between project teams’ behaviours and positive
workplace H&S outcomes, Wu and Fang (2012) state that behaviour-based H&S management
systems are likely to have their greatest impact if directed upwards (key project teams). On this
note, Lutchman et al. (2012) maintain that it is participants’ behaviours and their leadership
styles that are critical in creating and sustaining a positive H&S culture in an organisation
Globally, industry leaders are calling for prudent approaches to reduce the levels of workplace
fatalities and injuries. Economic and social impacts of construction site accidents and incidents
around the world have added more voice to this call. Flin and Yule (2003) affirm that the
ultimate success of H&S performance in any organisation is largely dependent upon the quality
of leadership. Therefore, the underlying theme to improving H&S performance in the South
African construction industry is the leadership quality and commitment, which must cascade
or permeate across all the key project leaders in the construction project delivery chain.
Therefore, examining the key project participants’ leadership styles and behaviours relative to
project H&S will help in understanding the root causes of site accidents and incidents. This
study therefore seeks to examine how leadership styles and behaviours of the key project
participants contribute to accidents and injuries causation in the South African construction
industry.
2. Literature Review 2.1 Leadership styles and H&S behaviour of key projects leaders/participants
Concern about poor construction site H&S performance has tended to focus attention
exclusively on unsafe behaviours and unsafe acts of workers in the form of mistakes,
omissions, and violation of rules (Krause, 1997). At-risk work practices or unsafe behaviours
may be connected as site workers are always in the front line of physical on-site activities.
According to Krause (2003), workers’ activities at operational levels exposed them to the
proximal cause of adverse events. Behaviours related to distant causal factors such as clients
poor H&S leadership styles and behaviour (Lutchman et al., 2012) and project related H&S
behaviours of consultants such as designers, project managers, quantity surveyors (cidb, 2009
and contractors’ poor H&S management and leadership styles at all levels (Hopkins, 2007)
precipitate the at-risk behaviours of workers on site.
Flin and Yule (2003) noted that much emphasis on workers’ unsafe behaviours were at the
expense of good designs and related critical H&S leadership styles of the key project
participants’ and contractors’ H&S management systems at all levels. Stressing the importance
of leadership and behaviour of the key project participant for effective H&S management,
Geller (2008) assets that the key project participants have important roles to play in improving
construction sites H&S performance.
2.1.1 Clients’ H&S leadership roles and behaviour
56
The clients as the owner of projects have a substantial influence on the way in which a project
is runs (cidb, 2009). Oloke (2010) asserts that the governance of any project begins and ends
with the clients. Clients’ H&S leadership roles and behaviour at the early projects stage are
critical factors for effective H&S management. According to Behm (2005), clients have pivotal
leadership roles in improving construction H&S particularly decisions made at the early project
planning phase through the appointment of the design team, contractors’ selection and
provision of financial resources for H&S matters.
The strong link between effective leadership and positive H&S outcome, found outside
construction, underpins the assertion that improvement and sustainability of workplace H&S
culture rest squarely on clients’ visible leadership and behaviour. Ironically, in the developing
countries, clients lack of visible leadership; unethical behaviours and non-adherence to the
procurement process have been found to be contributing to poor H&S performance in the
industry (cidb, 2011).
2.1.2 Designers’ H&S leadership roles and Behaviour
Haupt (2011) argues that the thrust of designing for H&S into projects lead to a reduction of
site accidents and incidents. Behm (2006) states that designers (architects/engineers) have a
duty and responsibility to design-in safety into construction during the design process. He
further states that designers can use their knowledge and influence to design-in safety features
that will improve the actual construction of the projects, as well as its maintenance after
completion. However, it has been found that designers lack in integrity and commitment in
their designs decisions and the consequences have been site accidents and incidents
Oloke (2010) emphasises that those involved with the designing and planning of construction
projects should demonstrate visible leadership and commitment from the inception stage to
construction and maintenance. Designers should recognise their important roles concerning
human lives as demanded by their professional codes of conduct by exercising due diligent and
care when designing.
2.1.3 Project managers’ roles leadership and behaviour
Project managers, in terms of their contractual relationship with clients have important
leadership roles to play in ensuring that construction projects achieve the desired quality
including workers’ H&S from inception stage to completion (cidb, 2009). Research conducted
by Smallwood and Venter (2002) among member practices of the Association of Construction
Project Managers (ACPM) in South Africa indicated that project managers can contribute to
optimal H&S performance in the industry.
Project managers as project leaders can influence construction H&S performance during the
project design stage. The Project Management Body of Knowledge (PMBOK) identifies
project managers’ roles that can influence projects H&S performance: facilitation of financial
provision for H&S; pre-qualification of contractors on H&S, and integrating H&S into projects.
The above identified scopes of work placed important leadership roles on the shoulders of
project managers relative to projects H&S management. In addition, the cidb (2009) reports
noted that project managers’ leadership roles is more visible on project sites when they monitor
contractors’ H&S plans, conduct site H&S meetings and visit sites regularly to ensure that
contractors conform to projects H&S plans.
57
2.1.4 Quantity surveyors’ leadership roles
Paucity of funds is one of the major factors contributing to contractors’ poor site H&S
intervention. Inadequate allocation of financial resources for H&S during the early project
planning or at the tendering stage by quantity surveyors is one of the major factors contributing
to contractors’ poor site H&S intervention (Brauer, 2006). However, adequate financial
provision for H&S can be realised in the contract documents by quantity surveyors (Olatunji,
Sher and Gu, 2011). Arguably, when a contractor compromises workers’ H&S due to lack of
funds, the resultant effect will be injuries and fatalities on sites.
Prudent management of financial resources on site has been linked to better quality of work
and worker’s H&S. Lack of commitment in preparation of interim valuations certificates on
monthly bases by quantity surveyor could impact negatively on contractors’ cash flow which
will result in lack of funds for site H&S management.
2.1.5 Contracting organisations’ leadership roles and behaviour
Contractors have duties and responsibilities under the law to carry out construction activities
without causing harm to workers and the general public. It is the leadership styles at all levels
of management in the contracting organisations that determines how construction process will
be plan, organise, control, and monitor to ensure that workers’ H&S are optimised. Leadership
have been noted as the critical factors that drives organisational H&S policy. Hopkins (2007)
maintains that achieving and sustaining organisational H&S culture required leadership skills
not only management skills. Similarly, Lutchman et al. (2012) argue that the implementation
of an organisation’s H&S policy is largely dependent upon leadership commitment at all levels
of management in an organisation.
Leadership according to Flin and Yule (2003), entails transparency, honesty, and trustworthy.
However, these leadership qualities found in the Western world are lacking among top
management and site managers in the Sub-Sahara Africa countries (Lutchman et al., 2012).
Sunindijo and Zou (2012) point out that lack of intelligence and interpersonal skills has been
found to negatively impact on site H&S.
Managers are the conduit between management and workers and they shape workers
understanding by communicating to them the company’s work ethics (Geller, 2008). Studies
comparing low and high accident rates on construction sites indicated that on sites where
managers demonstrate good quality leaders, a planner, an organiser, and good role model to
others such sites have excellent performance in both workers’ safety and quality of work
(Hinze, 2006). These leadership qualities are lacking among site managers in South Africa,
and they impose serious challenge to the improvement of projects H&S performance.
3 Research Methodology
To achieve the objectives of this study, a literature survey was conducted in the areas of
construction H&S management and leadership, which resulted in the formulation of structured
questionnaires. Questionnaires were distributed to clients, project managers, architects,
consulting engineers, quantity surveyors, and site managers. The main purpose of the
questionnaire was to explore the influence of H&S leadership and behaviours of the projects
team in terms of accidents and injuries causation. One hundred and seventy (170)
questionnaires were distributed, seventy-five were returned, and this resulted in a response rate
of 44.1%. The response rate achieved for this research is similar to that achieved in other
58
surveys (Collins, 2008; Sutrisna, 2009). It could be inferred from Sutrisna (2009) and Dainty
(2008) that performing statistical analysis of survey data based upon a response rate equal to
or above the threshold of thirty (30) is acceptable. Thus, a 44% response rate which was
achieved in this survey provides reasonable data for analysis.
3.1 Data analysis and interpretation of findings
The majority of the responses (70%) were received from clients, architects, project managers,
quantity surveyors, and site managers. Over 67% of the respondents have been involved in
construction for the past 10 years; 70% have tertiary qualifications; 59% hold management
positions, and 40% are managing members or principals. A 5-point Likert-scale measurement
was used to obtain the opinions of the respondents and to analysis the results. Leedy and
Ormrod (2010) maintain that Likert scales are effective to elicit participants’ opinions on
various statements. The statistical (version 10.0) was used to generate the descriptive and
inferential statistics. When using Likert scales, it is imperative to calculate and report
Cronbach’s alpha coefficients as well as the internal consistency and reliability (Gliem and
Gliem, 2003). Maree and Pietersen (2007) suggest the following guidelines for the
interpretation of Cronbach’s alpha coefficient: 0.90 – high reliability; 0.80 – moderate
reliability, and 0.70 low reliability. The questionnaire survey shows a high reliability
Cronbach’s alpha of 0.90.
4 Findings and Discussion
The questionnaire seeks to investigate respondents’ perceptions of the influence of H&S
leadership styles and behaviour of the key project participants in terms of accidents and injury
causation. Tables 1, 2 and 3 indicate the respondents’ perceptions of the extent to which
identified statements relative to key project participants contribute to poor H&S performance.
The tables are presented in terms of percentage responses to a scale of 1 (minor) to 5 (major),
and an MS ranging between 1.00 and 5.00.
4.1 Clients’ H&S leadership styles and behaviour contributing to poor H&S
performance
Table 1 indicates the respondents’ perceptions of the extent to which identified statements of
client’s leadership styles and behaviour contribute to poor H&S performance. It is notable that
7 MSs were above the midpoint of 3.00, with an average MS of 3.37. The respondents perceive
that all the identified statements relative to clients’ H&S leadership styles and behaviour in
Table 1 contribute significantly to poor H&S performance in the South African construction
industry. Findings of this study corroborated literature survey; Behm (2005) and Oloke (2011)
pointed out the importance of clients’ H&S leadership styles and behaviour in terms of
adequate provision of financial resources for H&S and awarding of contract to contractors with
good H&S records.
Table 1 Client’s H&S leadership styles and behaviour contributing to poor H&S performance
Statement
Un
sure
Response (%)
MS
Ra
nk
Minor………………………..Major
1 2 3 4 5
Failure to ensure that contractor has made
adequate financial provision for H&S 2.1 7.0 11.2 23.8 32.9 23.1 3.54 1
Awarding of contract to incompetent
contractors 1.4 6.3 16.9 22.5 30.3 22.5 3.46 2
Inadequate addressing of H&S matters during
contract negotiation or tendering process 2.5 3.5 18.9 31.5 23.1 19.6 3.36 3
59
Source: Researcher
4.3 Consultants’ H&S leadership styles and behaviour contributing to poor H&S
performance
Table 2 indicates the respondents’ perceptions of the extent identified statements related to
project consultants’ H&S leadership styles and behaviour contribute to poor H&S performance.
It is notable that 8 MSs were above the midpoint of 3.00, with an average MS of 3.43. It also
indicates that the respondents perceived that project consultants’ leadership styles and
behaviour contribute to poor H&S performance. The respondents perceive that the identified
statements in Table 1 contribute significantly to poor H&S performance in the industry. The
findings supported literature survey in that designer (architects/engineers) has duty and
responsibility to design-in safety into construction during the design process (Behm, 2005;
Haupt, 2011. The findings also supported research conducted by Smallwood and Venter (2002)
among member practices of the ACPM that poor monitoring of project H&S plans
implementation among project managers in South Africa marginalise H&S performance. In
addition, the work of Olatunji et al. (2011) corroborated the findings that inadequate financial
provision for H&S in the contract documents by quantity surveyors contribute to poor H&S
performance.
Table 2 Consultants’ H&S leadership styles and behaviour contributing to poor H&S
performance
Statement
Un
sure
Response (%) M
S
Ra
nk
Minor…………………………Major
1 2 3 4 5
H&S information not incorporated into design 9.1 8.4 13.3 30.8 23.1 15.4 3.64 1
Lack of prequalification of contractors on
H&S 3.5 9.8 15.4 33.6 26.6 11.2 3.51 2
Faulty and complex design 6.3 5.6 11.9 40.6 12.7 13.9 3.47 3
H&S not included in the contract documents 5.6 12.6 18.2 25.2 23.1 15.4 3.40 4
H&S information not recorded on drawings,
schedules and specifications 7.7 6.9 20.3 32.2 22.4 10.5 3.39 5
Poor monitoring of project H&S plans
implementation on site 5.6 11.9 16.2 29.4 25.9 10.49 3.36 6
Project H&S plans not integrated into project 5.6 9.8 18.2 33.6 21.7 11.2 3.33 7
Poor choice of procurement system 11.9 10.5 16.5 33.6 18.9 11.2 3.30 8
Source: Researcher
4.4 Contractors’ H&S management systems contributing to poor H&S performance
Table 3 below indicates the respondents’ perceptions of the extent that contractor related H&S
management practices and leadership contribute to poor H&S performance. It is notable that 8
MSs were above the midpoint of 3.00, with an average MS of 3.44.
Table 3 Contractors’ H&S management systems contributing to H&S performance
Lack of prequalification of contractors on
H&S 2.8 4.9 18.2 28.7 28.0 11.2 3.35 4
Inadequate provision of financial resources for
H&S 0.7 8.4 16.8 26.6 30.1 17.5 3.31 5
Non adherence to procurement process 6.3 8.4 19.6 34.3 18.9 12.6 3.28 6
Inadequate monitoring to ensure that
contractors comply with the H&S plan 4.2 12.0 21.1 32.4 19.0 11.3 3.26 7
60
Source: Researcher
It also indicates that the respondents perceived that contracting organisations’ leadership styles
and behaviour contribute to site accidents and incidents. The respondents perceive that the
identified statements in Table 3 contribute significantly to poor H&S performance in the South
African construction industry.
The findings supported literature survey that most proven H&S management systems in the
developed countries are lacking in the Sub-Sahara African countries (Lutchman et al (2012).
The cidb (2009) reports identified the following areas that South African construction
contractors are lacking: management commitment at all levels, lack of worker participation and
involvement in H&S, poor H&S training of workers and inadequate provision of financial
resources for H&S.
5 Conclusions and Recommendations
Based on the reported research, it can be concluded that key project participants’ leadership
styles and behaviours could lead to improvement of H&S performance. Behaviour change and
commitment towards projects H&S by the key project participants, particularly during the early
projects planning is imperative for improvement and sustainability of workplace H&S culture.
The study recommends that:
Clients as the owner and financier of developmental projects should appoint consultants
with proven H&S competencies and provide all necessary financial resources for projects
H&S;
Designers must behaviour in most ethical manner by designing in H&S into the projects;
Project managers as the coordinator and facilitator must demonstrate visible leadership
and commitment towards project H&S by ensuring that H&S competent contractors are
appointed and diligently monitor contractors on projects H&S plans implementation on
site;
The quantity surveyors as the financial experts should ensure that adequate funds are
allocated for H&S in the contract documents and see to the prequalification of contractors
during the tender process/negotiation, and
The leadership styles and behaviour of contractors at all levels of management are critical
for improving site H&S performance and sustainability of workplace H&S culture.
Statement
Un
sure
Response (%)
MS
Ra
nk
Minor………………………….…Major
1 2 3 4 5
Inadequate site management
commitment to H&S 3.5 2.8 9.1 25.2 32.9 26.6 3.71 1
Non-conformance to H&S plans 2.8 4.2 5.6 27.9 36.4 23.1 3.69 2
Inadequate provision of financial
resources for H&S 3.5 2.1 9.7 30.8 20.9 20.9 3.62 3
Inadequate H&S training 2.1 2.1 10.5 28.7 36.4 20.3 3.61 4
Poor H&S culture 2.1 6.3 6.9 27.9 34.3 22.9 3.59 5
Inadequate top management
commitment to H&S 3.5 3.5 8.4 30.1 34.9 19.6 3.57 6
Lack of worker participation and
involvement in H&S 1.4 4.2 7.7 32.9 34.3 19,6 3.51 7
Infrequent H&S meetings 2.1 6.9 15.4 34.3 33.6 7.7 3.20 8
61
6 References
Behm, M. (2005) Linking construction fatalities to design for construction safety concept,
Safety Science, 43(8), 589-611.
Brauer, L.R. (2006) Safety and health for engineers, 2nd ed. New Jersey: Wiley-Interscience
Construction Industry Development Board (2009) Construction Health and Safety in South
Africa: Status and Recommendations. Pretoria: CIDB.
Construction Industry Development Board (2011) Construction quality in South Africa: a client
perspective. Pretoria: CIDB.
Flin, R. & Yule, S. (2003) Leading for safety; industrial experience. Quality and Safety Health
Care, 3(20, 45-51.
Geller, E.S (2008) People-based leadership: enriching a work culture for world class safety.
Professional Safety, 53(3), 35-40.
Gliem, J.A. & Gliem, R.R. (2003) Calculating, interpreting Cronbach’s alpha reliability
coefficient for Liket type scales. In: 21th Annual Midwest Research-to-practice Conference
on Adult, Continuing and Community Education, 8-10 October, Columbus: Ohio, pp.82-
88.
Haupt, C. (2010), Controlling Exposure to Physical Hazards, In McAleenan, P. and Oloke, D.
ed. ICE Manual of Health and Safety, London: Thomas Telford, pp. 149-162.
Hinze, J.W. (2006) Construction safety, New Jersey: Prentice- Hall Inc.
Hopkins, A. (2007) What are we to make of safe behaviour programme? Safety Science 44(7),
583-589.
International Labour Organisation (2005) Safety and health in construction, Geneva: ILO.
Leedy, P.D. & Ormrod, J,E. (2010, Practical research: Planning and design, 8th edition, Upper
saddle River, New Jersey: Pearson.
Lutchman, C., Maharaji, R. & Ghanem, W. (2012) Safety management: A comprehensive
approach to developing a sustainable system, 1st edition, Boca Raton: CRC Press.
Lees, H. & Austin, J. (2011) The case for behaviour-based safety in construction. Proceedings
of the Institution of Civil Engineers: Management, Procurement and Law, 164(1), 3-7.
Maree, K. and Pietersen, J. (2007), Surveys and the use of questionnaire, In: Maree, K. (Ed.).
First steps in research. Pretoria: van Schaik Publisher, pp. 155-170.
Krause, T.R. (1997) The Behaviour-based Safety Process: Managing Involvement for an
Injury-Free Culture. 2nd Edition, New York: John Willey & Sons.
Krause, T.R. (2003) A behaviour-based safety approach to accidents investigation.
Professional Safety: 45(12), 342-356.
OLoke, A.O. (2010) Responsibility of Key Duty Holders in Construction Design and
Management. In McAleenan, C. & Oloke, D. ed. ICE Manual of Health and Safety in
Construction, London: Thomas Telford, 29-37.
Olatunji, O.A., Sher, W. &Gu, N. (2011) Building Information and Quantity Surveying
Practice, Emirates Journal for Engineering Research, 15(1), 67-70.
Republic of South Africa 2003, Government Gazette No 25207; Construction Regulations
2003, Pretoria.
Sherratt, F. and Ferrell, P. (2012) Behavioural and Cultural Safety Programme: Evaluation
from the UK site Perspective: Construction Management and Economics, 25(6), 371-383.
Smallwood, J.J & Venter, D. (2002) The Influence of Project Managers on Construction Health
and Safety in South Africa. The Australian Journal of Construction Economic and
Building, 2(1), 57-69.
Sutrisna, M. (2009) Research Methodology in Doctorial Research: Understanding the
Meaning of Conducting Qualitative Research: Working Paper Presented in ARCOM
Doctorial Workshop, Liverpool, John Moores University, May, 12.
62
Sunindijo, Y.R. and Zou, P.X.W. (2012) The influence of project personnel’s emotional
intelligence, interpersonal skill, and transformational leadership on construction safety
climate development: International Journal of Project Organisation and Management 5(1),
1-13.
Wu, H. and Fang, D. (2012) Enhancing the Sustainability of BBS Implementation in
Construction- Psychological and Organisational Perspectives: Journal of Construction
Engineering and Management. 36(6), 89-101.
63
Making Project Team Decisions Using Choosing by
Advantages on a Concrete Task Project LG Mollo1, FA Emuze2 and F. Geminiani3
1.3Department of Building and Human Settlement Development,
Nelson Mandela Metropolitan University, 2Department of Built Environment, Central University of Technology, Free State
Email: lmolloa@cut.ac.za, femuze@cut.ac.za, fl.geminiani@nmmu.ac.za
Abstract:
Team dynamics on project sites influence decisions and actions that in turn produce several
outcomes: good or bad. In an environment where project performance related to a range of
parameter is a problem, improvement mechanism must be deployed. Such a mechanism is
“choosing by advantages” (CBA), which is a lean construction tool. CBA is a decision-making
system that assists project parties in deciding a course of action among competing alternatives.
To explore the use of the CBA tool in a project, the concrete work team in a project was selected
for assessment. Case study method is chosen for this project to discover the decision-making
process adopted by project team. The case study covers two unit of analysis: ready mixed and
site batched concrete tasks. The unit of analysis are judged according to the importance of
advantages (IofA) scores. However, this exploratory work is on-going and future research
would tackle limitations of analytic generalisation.
Keywords:
Choosing by Advantages, Concrete, Decision-Making, Project team
1 Introduction
A decision-making method is important because it influences project outcomes. According to
Arroyo, Tommelein and Ballard (2013), the decision-making process influences project team
decisions, actions, and performance results. Therefore, if performance results matters, then the
decision-making methods also matter. Haymaker, Chau and Xie (2013) state that decision-
making method depends virtually entirely on project team input to construct and organize the
basis needed for a decision.
Project performance produced by the project team has been disapproved and criticized for
failing to meet the expectations of clients and end-users (González, Shahbazpour, Toledo, &
Graell, 2014). Historically, developing countries such as South Africa have always been a
victim of poor performance (Emuze and Smallwood, 2012). To address the poor performance
outcomes, the project team must work together to select a decision-making process in order to
strengthen and improve project performance (Emuze, 2012). Kwon, Park, and Lim, (2014)
stated that the continual and unavoidable existence of poor performance relating to concrete
defects continues to be one of the primary causes of schedule and cost overrun in construction.
Concrete quality management on site is done by site managers, and there are various
challenges, which site managers are failing to address (Kwon et al., 2014).
Construction defects caused by concrete task are influenced by several factors and the study by
Kwon et al. (2014) describes the causes of defects for concrete works on site: It involve the
preparation of building materials in the form of cement, reinforced steel bar, aggregates, sand
and water. The process of casting concrete starts when contractor set the formwork, then install
reinforced steel, then pour concrete, allow the concrete to cure, and remove the formwork
64
(Senthilkumar and Shafee, 2013). The high demands for concrete materials has lead the
concrete specialist to design modern concrete mixtures (substituting one (old) cement with
another (new) cement), and this may have influenced poor performance (Caldarone, 2009). The
most common problems resulting from these modern concrete mixtures include early loss of
workability, unreliable setting behavior, and poor strength development (Caldarone, 2009).
However, the literature contends that decision-making pitfalls can be prevented by using CBA.
CBA is defined as the decision-making system, which must be based on the importance of
advantages within a project team (Parrish and Tommelein, 2009). It is essential for the project
team to design a decision-making method during the design stage, because crucial decisions
are taken during the design stage (Abraham, Lepech and Haymaker, 2013). To this end, Suhr
(1999) developed the CBA method as a decision-making system that considers the advantages
among alternatives and makes comparison by considering the advantages obtained. Suhr
(1999) set the benchmark for project team who are investigating decision-making of the
project. He contends that there is no right or wrong decision when deciding among a set of
alternatives because the disadvantage of one alternative could be the advantage of the other.
Sound decision can be detected if project team leave out decisions, which affect the project
negatively. Alternative sound methods are defined as “the application of statistics to serve its
purpose precisely and reply to answer the correct questions” (Koga, 2005). Hence, the CBA
method is a decision-making system that comprises methods for almost all kinds of decisions
during the construction process regardless of the scope of work.
2 Literature Review
In the United States of America (USA) where the concept began, CBA has been used since
1980 by U.S. Forest Service, but it is only recently making inroads into the Architecture,
Engineering and Construction (AEC) industry (e.g. Parrish and Tommelein 2009, Lee,
Tommelein, and Ballard 2010, Koga 2012, Abraham, Lepech and Haymaker 2013, Arroyo,
Tommelein and Ballard 2014). Furthermore, CBA is mainly used with complex projects with
its analysis that creates all-inclusive or transparent view, which allow the selection of the best
possible clarification based on the information available (Haapasalo, Aapaoja, Björkman and
Matinheikki, 2015). In construction, few decisions are based on a transparent decision-making
process because decisions tend to be mostly influenced by discussions or arguments that only
few or top project team provide (Arroyo, Ballard, and Tommelein, 2014).
CBA method helps project teams to choose alternatives, which will be able to achieve the goals
of the project (Legmpelo, 2013). Rubrich (2012) states that CBA starts when the client decides
to invest in construction and ends when the contractor completes the project. The technique
involves various decision-making methods to close gaps in complicated construction decisions
(Haymaker et al, 2013). CBA is a lean tool that is increasing in awareness and use.
CBA method is characterized and detailed by the following terms: alternative, factors, criterion,
attributes, advantages and importance of advantages (Suhr, 1999). CBA is one of the best
decision-making methods, because it differentiates the non-money and money decisions. Non-
money decisions are labelled to any decision, which results with no cost difference between
alternatives and money decision are labelled to any decision problems, which results in cost
difference between alternatives (Abraham et al, 2013). The CBA method is designed to
accommodate either large or small projects through: Simplified Two List Method (STLM) and
Tabular Method (TM). STLM is designed for simple project comprising two alternatives of the
equal cost estimate of the project. TM is suitable for complicated projects, mostly when the
project decision comprises multiple alternatives, when there are different information’s to be
65
judged and the entire project team are involved in the decision-making process (Arroyo et al,
2014). The application of TM is described in the figure below:
-
Figure 1: CBA steps (adapted from Arroyo et al, 2014)
3 Research Methodology
The study aimed to understand the project team decision-making process incidental to the
completion of a concrete task. To understand the problem around the aim, a case study was
conducted in Bloemfontein, South Africa. A case study method was selected as recommended
by Yin (2014). He stated that a case study method can be adopted in situation when the
researcher asks “how” and “why” questions, when there is little or no control over the
behavioural events and lastly when the focus of the study is a present phenomenon. This study
supports the nature of the question which ask “How can the project team use CBA decision
making mechanism to choose a concrete task?” The design of this study is a single case study,
because this study is based on single case project. The project involves the construction of the
New North Eastern Waste Water Treatment Works, hereafter referred to as ‘the case project’
in Bloemfontein. This project was selected based on its nature; this project uses tons of
concrete. The unit of analysis determined the research design and identified the type of data
which the researcher collected as described by Yin (2014). The study was conducted between
May and June 2016 as part of the master’s study. A semi-structured interviews were conducted
with the project team, made up of the member of the construction teams (two construction
managers, two site engineers, one foreman, and one site quantity surveyor) and the consulting
engineers (three resident engineers), which resulted with a total of nine (9) interviews.
However, the client did not form part of the interviews because the consulting engineers
manages the project for the client, as the principal project manager.
1. Classify alternatives
2 Describe factors
3. Describe the essential/want criterion of factors
4. Summarize the attribute of each
alternative
5. Choose the advantages
6. Choose the importance of each advantage
7. Asses cost data
66
4 Findings and Discussion
3.1 Initial Results from Case Study
The case study procedure describes the steps that the researcher followed for applying CBA in
this project. The researcher studied the literatures to understand the concept of decision-making
process used in the construction industry. Later, the researcher studied the impacts of CBA
method on project delivery and performance, and how a CBA method affects the performance
of the project team. The project was identified and the details of the project was retrieved from
the Mangaung Metropolitan database. The researcher introduced the CBA application through
discussions and questions aided by presentation to the project team. In addition, the researcher
presented the relevant information for the decision-making process, the process for obtaining
the information, and assumptions behind the data presented. The researcher was able to identify
the two alternatives (ready mixed concrete and site batched concrete). From the engagement
with the project team the researcher was able to articulate the relevant factors, criterion and
attributes for this study. The project team recognized the benefits of CBA method even though
they expressed that they will not have time to analyse their decision-making through CBA
methods, because of the construction culture in South Africa, the construction team is not part
of the project until appointment of the project. However, for this case project the researcher
found that the member of the construction teams has already chosen ready mixed concrete for
the project.
4.2 Step by Step CBA Application
The researcher adopted TM for this case project, TM is described in Figure 1. However, Table
2 summarizes the CBA steps (from step 1 to step 6) that was taken by the researcher to choose
the best alternatives between ready mixed concrete and site batched concrete. The project team
identified 11 factors which the researcher used in step 2, in step 3, the researcher had to
understand the importance within the factors, so the construction manager and site engineer
explained the purpose of the factors and how the factors reveal significant differences among
alternatives. The project team helped the researcher to summarize the criterion and attributes
of this study in step 3 and 4. From the information, which was presented from step 1 to step 4,
the project team and the researcher was able to conclude step 5 and 6 by choosing the
advantages of attributes within alternatives and the importance of advantages (Imp) was
determined by the project team through a scale of 0 to 100 as indicated in Table 1 and 2. The
Importance of advantages (IofA) is determined by the project team through a scale of 0 to 100.
Where 100 is given to the most important advantages. In order to give the IofA to the other
advantages, the researcher compared the advantages (Adv) to the most important advantage
(Imp). The project team calculated the IofA score by comparing criterion of the factors with
the attributes of the factors. Table 1 shows an example which was used to calculate the IofA
score.
67
Table 1: Importance of Advantages (IofA) Score
Factors Attributes of Alternative 1 (Ready
mixed Concrete)
Attributes of Alternative 2 (Site Batched
Concrete)
Quality Control The slump test and cube test are taken
before placing the concrete
Concrete mix design and aggregates must
be inspected before batching and slump
test and cube test must be taken before
placing the concrete
IofA Score (0 to
100)
50 25
Source: The researcher
The highlighted attributes have the advantage over the other attributes of the alternative. CBA
method is determined by the advantages between alternatives. The preferred attribute is
determined by the advantage between attributes of two alternatives. The advantages between
alternative is calculated according to this formula: righteous
A= (PA-LPA)
A: Advantages
PA: Preferred Attributes
LPA: Least Preferred Attributes
Equation 1: Advantages Calculation Formula (adapted from Arroyo et al, 2014)
An example of how the advantages between alternatives were calculated:
Factors: Site Supervision
Criterion: Fewer is better
Attributes: Alternative 1: It requires 1 supervisor to monitor the concrete.
Alternative 2: It requires 2 supervisors to monitor the concrete.
Calculation of the advantages for Alternative 1
A = (PA-LPA)
A =?
PA = 1 supervisor
LPA: 2 supervisor
A = (1-2)
Adv.= 1 supervisor
Calculation of the advantages for Alternative 2
A = (PA-LPA)
68
A =?
PA = 1 supervisor
LPA: 1 supervisor
A = (1-1)
Adv.= 0 supervisor
Note: the calculations are grounded based on the criterion rule of the factors, in this example
the fewer the site supervisor the better. This is the reason why alternative 1 has a better result
than alternative 2 judging from the alternatives attributes.
Table 2: CBA Steps 1 to 6 for case project
Alternative 1
Ready mixed concrete
Alternative 2
Site batched concrete
Factors
1. Quality
Control
Criterion Easier is better
Attributes The slump test and cube test are
taken before placing the concrete
Concrete mix design and aggregates
must be inspected before batching
and slump test and cube test must be
taken before placing the concrete
Advantages Adv: Over
Alternative 2
Imp: 50 Adv: No Imp: 25
Factors
2. Workability
Criterion Faster is better
Attributes It takes 25 minutes to prepare 6
cubes of concrete
It takes 55 minutes to prepare 6
cubes of concrete
Advantages Adv: 30 Imp: 60 Adv: 0 Imp: 45
Factors
3. Site
Supervision
Criterion Fewer is better
Attributes It requires one (1) supervisor to
monitor the concrete
It requires two (2) supervisor to
monitor the concrete
Advantages Adv: 1 Imp:20 Adv: 0 Imp: 10
Factors
4. Compressed
strength
Criterion Higher than 35 Mpa
69
Attributes 35 Mpa designed strength and are
crushed 7 and 28 days after
placement
35 Mpa designed strength and are
crushed 7 and 28 days after
placement
Advantages Adv: Not
comparable
Imp: 50 Adv: Not
comparable
Imp: 50
Factors
5. Formwork
Criterion Stronger is better
Attributes The formwork shatter must be
installed adequately and not kicked
out by concrete
The formwork shatter must be
installed adequately and not kicked
out by concrete
Advantages Adv: Not
Comparable
Imp: 50 Adv: Not
Comparable
Imp: 50
Factors
6. Concrete
placement
Criterion Faster is better
Attributes It takes 10 minutes to place
concrete per cube
It takes 20 minutes to place concrete
per cube
Advantages Adv: 10 Imp: 70 Adv: 0 Imp: 35
Factors
7. Concrete
compaction
Criterion Slower is better
Attributes It takes 10 minutes to compact
concrete per cube
It takes 10 minutes to compact
concrete per cube
Advantages Adv: Not
Comparable
Imp: 50 Adv: Not
Comparable
Imp: 50
Factors
8. Labours
Criterion Fewer is better
Attributes It requires 3 labours to work with
concrete per cube
It requires 8 labours to work with
concrete per cube
Advantages Adv: 5 Imp: 90 Adv: 0 Imp: 35
Factors
9. On-site
transportation
Criterion Faster is better
Attributes It takes 5 minutes to move concrete
from the truck to the placing area
It takes 15 minutes to move
concrete from the batch station to
the placing area
Advantages Adv: 10 Imp: 60 Adv: 0 Imp: 20
Factors
10. Concrete
Curing
70
Criterion Slower is better
Attributes It takes 7 days for the concrete to
reach its potential strength
It takes 7 days for the concrete to
reach its potential strength
Advantages Adv: Not
comparable
Imp: 100 Adv: Not
comparable
Imp: 100
Factors
11. Health and
Safety (OHS)
Criterion Lower risk is better
Attributes The risk of health and safety to
workers is low
The risk of health and safety to
workers is low
Advantages Adv: Not
comparable
Imp: 100 Adv: Not
comparable
Imp: 100
Sum of
IofA
700 520
Source: The researcher
The IofA score results shows that alternative 1 (Ready Mixed Concrete) has higher score than
Site Batched Concrete, which makes it more preferable.
Step 7: Evaluate concrete cost data
The decision-maker can compare the IofA vs. cost of the alternatives (CoA) in the figure below.
Figure 2: IofA vs. CoA (Source: The researcher)
Based on Figure 2, the researcher asked the project team especially the member of the
construction team, if it is worth paying an amount between R3 000.00 to R3 500.00 for 35 Mpa
ready mixed concrete per cube, instead of paying an amount between R2 000.00 to R2 500.00
Ready Mixed
Concrete
Site Batched
Concrete
0
100
200
300
400
500
600
700
800
0 500 1000 1500 2000 2500 3000 3500
Imp
ort
an
ce o
f A
dv
an
tag
es (
IofA
)
Cost of Alternative (CoA)
BLOEMFONTEIN
71
for 35 Mpa site batched concrete per cube. The project team stated that even though they could
cut cost by choosing site batched concrete, but there are factors which cannot be ignored when
using a site batched concrete; wastage and theft of materials, handling and storage of materials,
labours, plant hired and plant operation, supervision, and site transport equipment. All this
factors needs money to be maintained and they can be avoided through ready mixed concrete.
Again ready mixed concrete is subject to SANS 878 requirement, and the concrete supplier
was approved by South African Ready-mix Association (SARM). SANS 878 compel the ready
mixed company to transport the concrete to the site within the permissible range of slump for
a period of 30 minutes from the arrival at the site.
5 Conclusions
The case study confirmed the application of the CBA method in decision-making. The study
provides insights about the rationale over the choice of ready mixed concrete and site batched
concrete by providing questions that the project team should ask in discovering the best
alternative. Thus, CBA methods could provide the correct framework when choosing among
competing alternatives that have significant implications for project performance. The decision
of the project team is insightful as the alternatives have similar factors that were judged based
on their IofA scores. The study suggests that the score behind every IofA should be analysed
using the facts and differences among the alternatives and opinion of the project team and how
the advantages of one alternative will affect the other alternative. This realisation resonate
within the CBA literature. Furthermore, the project team stated that even though the site
batched concrete is less economical than ready mixed concrete, they favour the IofA score
since site bathed concrete has numbers of factors which cost money to maintain them such as
wastage, material storage, batching plant and trucks to transport the concrete, supervision, and
more labours on site. This exploratory work is on-going and future research would tackle
present limitations of analytic generalisation, among others.
6 Acknowledgements
The researcher acknowledges the financial support of the National Research Foundation –
Thuthuka Funding Instrument and Stefanutti Stocks Civil KZN Team for taking part of this
study.
7 References
Abraham, K., Lepech, M. and Haymaker, J. (2013). Selection and Application of Choosing by
Advantages on a Corporate Campus Project. Proceedings IGLC-21, July 2013 | Fortaleza,
Brazil (pp. 349-358). Stanford, California: Stanford University.
Arroyo P., Tommelein, I.D. and Ballard G. (2013). Using ‘choosing by advantages’ to select
ceiling tile from a global sustainable perspective. Proceedings IGLC-21, July 2013 |
Fortaleza, Brazil (pp. 309-313). California: Product Development and Design
Management.
Arroyo, P., Ballard, G. and Tommelein, I.D. (2014). Choosing by Advantages and Rhetoric in
Building Design: Relationship and Potential Synergies. Proceedings IGLC-22, June 2014
(pp. 391-408). Oslo, Norway: Design Management.
Caldarone, M.A. (2009). High Strength Concrete: A Practical Guide. London and New York.
Taylor & Francis.
Emuze, F.A and John Smallwood, J.J. (2012). Bridging public works project performance gaps
in South Africa. Proceedings of the ICE-Management, Procurement and Law, 165, 111-
118.
72
Emuze, F.A. (2012). Performance Improvement in South African Construction. Port
Elizaberth: PhD Thesis: Nelson Mandela Metropolitan University.
González, V., Shahbazpour, M., Toledo, M. and Graell, J. (2014). Understanding the Supply
Relationships of Geothermal Power Generation Projects in New Zealand. In B. T. al
(Ed.), 22nd Annual Conference of the International Group for Lean Construction (pp.
1044-1056). Oslo, Norway: IGLC and Akademika forlag
Haapasalo, H. Aapaoja, A. Björkman S. and Matinheikki, M. (2015) Applying the choosing by
advantages method to select the optimal contract type for road maintenance. International
Journal of Procurement Management, 8, pp. 643-665.
Haymaker, J. Chau, D.H. and Xie, B. (2013). Inference - Assisted Choosing by Advantages.
Proceedings IGLC, July 2013. 21, pp. 339-348. Fortaleza, Brazil: Product Development &
Design Management.
Koga, J. (2005). CBA: Paradigm Shift or Pipedream? CVS AIA LEED AP, 1-11.
Kwon, O., Park, C., and Lim, C. (2014) A Defect Management System for Reinforced
Concrete Work Utilizing BIM, Image-Matching and Augmented Reality, Journal of
Automation in Construction, 46, 74-81.
Legmpelo, N. (2013). On-Site Construction Versus Prefabrication. Massachusetts Institute of
Technology, 1-117.
Parrish K. and Tommelein, I.D. (2009). Making Design Decisions Using Choosing by
Advantages. 17th Annual Conference of the International Group for Lean Construction,
501-510.
Rubrich, L. (2012). An introduction to Lean Construction: Applying Lean to Construction
Organizations and Processes. United States of America: WCM Associates LLC.
Shehu, Z., Endut, I.R., Akintoye, A. and Holt, G.D. (2014). Cost overrun in the Malaysian
construction industry projects: A deeper insight. International Journal of Project
Management, 32, 1471-1480.
Suhr, J. (1999). The Choosing by Advantages Decision-making System. California: Westport.
Yin, K.Y. (2014). Case Study Research Design and Methods. (5, Ed.) Thousand Oaks,
California: SAGE Publications.
73
Assessment of Construction Risks and Mitigation
Strategies in Public Private Partnership (PPP) Projects in
Abuja, Nigeria Isah Yahaya1, Winston Shakantu2, Richard Jimoh3, Ibrahim Saidu4
1, 2&4Department of Construction Management, Nelson Mandela Metropolitan University,
Port Elizabeth, South Africa 3Department of Building, Federal University of Technology, Minna, Nigeria
E-mail: s214344924@nmmu.ac.za, winston.shakantu@nmmu.ac.za,
isahyahaya50@gmail.com
Abstract:
Mismanagement of risk factors that come into play during the construction phase of a PPP
project can result into non-actualisation of the PPP project / non-conformity with the project
schedule. The research aims to assess the construction risks associated with PPP projects, as
well as to recommend how best such risks can be mitigated. The research employed the use of
the quantitative method from which a total of 306 questionnaires were administered from which
213 were retrieved using the simple random sampling technique to construction professionals
and private construction developers, who have executed PPP projects in the Federal Capital
Territory (FCT), Abuja. The collected data were analysed using the descriptive method (the
mean score method, relative importance index and the ranking method). The study revealed
that the most important risks factors associated with PPP projects were construction cost
overrun, construction time delay, interest rate fluctuation, availability of finance, and excessive
variation in project specification. The risk mitigation tool appropriate for the PPP models
(Build-Operate-Transfer [BOT], Build-Operate-Own-Transfer [BOOT] and Design-Build-
Operate-Transfer [DBOT]) was the Insurance Policy. Based on these findings, it can be
concluded that effective management of construction PPP risks would translate into a timely
completion of PPP project. It was recommended that, in exploring options for the mitigation of
construction risks in PPP projects, clients and developers should consider insurance,
contingency plans and contingency sums in descending order of preference.
Keywords:
Construction, Mitigation strategies, PPP, PPP Models, Risks
1 Introduction
Traditionally, government has prevailed infrastructure funding in Nigeria (Obi & Ofonyelu,
2015 and U-Dominic, Ezeabasili, Okoro, Dim & Chikezie, 2015). Until the 1980s, when
reclaims were introduced to confront the dwindling oil revenue that challenged state capability
for infrastructure provisioning (Annimashaun, 2011). However, due to the increase in the
demand for infrastructure; inadequate public resources to meet present and future desires; and
acceptance of a better role for the private sector in providing infrastructure, alternative methods
of funding public facilities and services have been adopted by the public sector (Nigeria Public
Private Partnerships Review [NPPPR], 2012 and U-Dominic et al. 2015), Li et al. (2001)
established that Nigeria eventually develop a foremost measure towards getting at the
advantage of PPPs due to enactment of the Infrastructure Concession Regulatory Commission
(Establishment) Act (“then ICRC Act”) in 2005 which allows for private sector involvement
in infrastructure development projects and establishes the ICRC as the regulator of PPPs
projects.
74
The decision to embark on a building project therefore has inherent element of risk (Adelusi,
2009). It was observed by Jagboro (2007) that risks are unwanted negative consequence of an
event of which the possible outcome can be identified, predicted and quantified. Dada (2010)
and Odimabo and Oduoza (2013) opined that the risk factors in building construction that are
not given proper attention in developing countries such as Nigeria lead to poor quality work,
cost and time overruns. Thus, Uher (2003) saw risk management as an organised way of
looking at areas of risk and finding out how each should be handled. Lots of PPP projects have
failed and even deserted causing suffering, not only to the promoter, but also to the lending
funding institutions (Ranjan, 2010).
Previous studies in this field included that of Meruyn (2001) who concluded that proper risk
management, identification, assessment, allocation and mitigation are essential for achieving
success in project. The ability to actively create and develop collaborative relationships is an
essential asset for managing PPP project networks (Pauget & Wald, 2013). Grimsey & Lewis
(2002) analysed the principles involved in PPP and depicting on practical experience of
assessing such projects to present a framework for evaluating the risks. Chohra et al. (2008)
recommended that risk transfer mechanisms should be develop for mega-construction projects
under PPP; the guiding principle should be a balanced risk allocation. In a related development
Patrick et al. (2008) opined that optimal risk identification, assessment, allocation and
management in PPP bring about value for money and protection of the public interests. Nur &
Batu (2011) reviewed risk allocation in public-private partnership project and revealed that risk
factors are clustered into 10 groups namely: political, construction, legal, economic, operation,
market, project selection, project finance, relationship and natural factor; and that the highest
score frequency factors are change in law, delay in project approvals and permits and land
acquisition. Mohammed et al. (2012) examined risk allocation in PPP projects in Nigeria and
establish that the public sector choses to retain most political, legal and social risks, and share
most micro level risks and force majeure risk; while the majority of micro level risks were
preferred to be allocated to the private sector. The cited works did focus specifically on the
assessment of general construction risks and their mitigation strategies. However, they did not
link these risks to PPP projects in Abuja, Nigeria. This study is thus concerned with studying
risk encountered in construction of PPP project and making recommendation on how best such
risks can be successfully mitigated.
2 Risk Analysis and Management in PPPs
Risk occurs due to unforeseen result that can have direct consequence on the project
(UNESCAP, 2011). Rouse (2010) indicated that risk analysis is the procedure of determining
and examining the dangers to individuals, business concern and public authority presented by
potential natural and human-caused unfavourable actions. Olugbodi (2012) stressed that, risk
management is a most important worry of the government and private agency in setting any
PPPs project; hence, risk sharing is one of the main reasons why PPPs exist in the first place.
Rostami (2016) opined that risk identification plays a key role in the success of managing risk.
KarimiAzar et al. (2011) noted that risk analysis can provide avenue for knowing the origins
of project risk and enable management to develop directed corrective action. The key tools and
techniques in risk identification and analysis according to Rostam (2016) are: brainstorming,
interviews, Delphi, check-lists, hazard analysis and critical control points, environmental risk
assessment, structure “what if”, scenario analysis, business impact analysis, root cause
analysis, failure effect mode analysis, event tree analysis, cause and effect analysis and
consequence and probability matrix. However, Rouse (2010); and Rot (2008) concluded that
risk analysis may either be quantitative or qualitative. In quantitative risk analysis, there is
75
effort to find out the chances of many unfavourable actions and the probable level of the losses,
if certain event happens. While qualitative risk analysis, which is more applicable, involves
understanding the different threats, finding the degree of exposed and making counter measures
when an attack occurs? (Hillson, 2004). Quantitative and qualitative risk analysis includes the
following:
Interviewing: Interviewing techniques are employed to assess probabilities and the impact of
attaining a particular goal due to input from stakeholders and expertise in particular field. In
the interview, it is always important to mix to obtain the optimistic (low), pessimistic (high)
and probable situation for a particular goal (Thaheem, 2012).
Probability distributions: This method describes how chances are spread upon events.
Probability distributions are used to graphically demonstrate risk chances, indicating the
probability density functions. For each probability distribution, the vertical axis indicates the
chances of the risk event and the relative likelihood, and the horizontal axis depicts the impact
(time or cost) of the risk event (Thaheem, 2012). Others include, scenario analysis, sensitivity
analysis and brainstorming (Hillson, 2004; Thaheem, 2012).
3 Research Methodology
Mixed method of both quantitative and qualitative research was employed. The research
population was PPP construction projects within Abuja, Nigeria. The sampling frame for this
study constituted government ministries, parastatals that were involved in construction work,
construction developers and private firms that were into PPP works within Federal Capital
Territory (FCT), Abuja. A total of 306 questionnaires were administered using the simple
random sampling method, from which 213 (69.6%) were returned. The rationale for the simple
random sampling was that every data source in the population has an equal chance of being
included in the sample. The professionals included: 30 Builders, 50 Quantity surveyors, 68
Architects, 62 Civil Engineers, 50 Mechanical/Electrical Engineer, and 46 Estate Surveyors
some of whom are private construction developers in PPP work within Abuja.
The questionnaires were developed to capture the key issues in the research (PPP construction
project risks and their mitigation strategies). Though, the first part captured the demographic
of the respondents. The collected data were analysed using descriptive method which included:
the mean score method, relative important index, and ranking method.
The collected data from the questionnaire were analysed using the descriptive statistical
methods which included: percentages, charts, mean-score distribution, relative importance
index and ranking method. The mean score method involves assigning numerical values to
respondents' ratings of importance, for example strongly agree (5 point), agree (4 points) in
this order. Relative Frequency Index (RFI) was employed for two purposes: for ranking and
determination of significance of different factors of the data collected. The premise of decision
for the ranking was that, the factor with the highest Relative Frequency Index (RFI) is ranked
1st and others in such subsequent descending order (Nurudeen, 2002). It was used to analyse
the issues relating to management of construction risks in public private partnership
infrastructure projects in Abuja. The results of the analyses were presented in Tables and
Figures1, 2, 3.
4 Findings and Discussion
76
This section presents and discusses the results of the descriptive analyses performed on the
issues relating to construction related risks and their mitigation strategies in PPP projects
4.1 Various PPP Arrangements in Place
The PPP projects were categorised into six classes as shown in Figure 1, to give as much
information as possible. Infrastructure projects made up five of the categories, while housing
was the sixth category. Build-Operate-Transfer (BOT) was the most popular model for housing
projects; this was also true for road projects, 8 of which were let contracted using the BOT
model. Port infrastructure was concessioner through Operate-Maintain-Transfer (OMT) and
Rehabilitate-Operate-Transfer (ROT) models. Water supply infrastructure was solely
contracted using BOT model, while railways infrastructure contracting was shared equally
between BOT and SOM (Supply-Operate-Maintain). Two instances were observed of housing
projects being concessioned using Rehabilitate-Lease-Operate-Transfer (RLOT) model.
Figure 1: Types of PPP projects sited in different states in Nigeria (source: Researcher)
The bulk of PPP projects covered in the sample obtained in this study were owned by
government as shown in Figure 2. Privately owned PPP projects were contracted under BOT
and RLOT models only. Public projects appeared to favour the BOT model, under which 12
projects were contracted. DBFT (Design-Build-Finance-Transfer) and ROT (Rehabilitate-
Operate-Transfer) were also noticeably popular models.
Figure 2: PPP Model (Source: Researcher)
0
2
4
6
8
10
Abuja Anambra Enugu Kwara Lagos Niger Onitsha Taraba VariousStates
Nu
mb
er
of
PP
P p
roje
cts Housing Infrastructure_General
0
10
20
Others BOT DBFT DBO OMT RLOT ROT SOM
Num
ber
of
PP
P p
roje
cts
PPP ModelsFig 2. Ownership of projects and type of PPP models applied
Private Public
77
The type of PPP projects in terms of ownership was examined in Fig 3. Private PPP projects
existed only in the housing subsector. All of the infrastructure PPP projects were under public
ownership. Of these, roads were the dominant type of project (numbering 11 projects). Housing
was also an important area for publicly-owned PPP projects, with 6 projects currently ongoing.
There were 2 projects each for the public sector in the general infrastructure sector, ports, and
railways. There was only 1 water supply infrastructure PPP project.
Figure 3: Types of PPP project and Ownership of projects (Source: Researcher)
4.2 Construction Risks Associated with PPP Projects
Construction risks that were associated with PPP projects in Table 1 were identified using two
measures of the quantity of responses received from the sample. These were the Mean Score
and the Relative Importance Index (RII). While the Mean Score allowed responses to be located
in terms of the response option most favoured by respondents, the Relative Importance Index
allowed an item to be ranked in terms of the importance accorded it by respondents among its
peers.
For instance, in Table 1, the risk variable (Construction Cost Overrun) had a Mean Score of
3.98, which indicated that the weighted average of the responses received was close to the
response option coded as ‘4’ on the Likert scale, which represents ‘Often’. The risk variable
also had an RII of 0.79, which meant, it was the most important risk factor associated with PPP
projects, in the opinion of the respondents to the study.
The risk factors that ranked as the five most important risks associated with PPP projects were
(i) construction cost overrun, (ii) construction time delay, (iii) interest rate fluctuation, (iv)
availability of finance, and (v) excessive variation in project specification. Conversely, the risks
that were considered to be of lesser importance to PPP projects were: (a) inconsistency in
design, (b) poor quality workmanship, and (c) change in tax regulation. The mean scores of
these three risks showed that respondents felt that the risks were rarely associated with PPP
projects; the RII of the three risks were also the lowest obtained for the analysis.
Table 1. Construction Risks Associated with PPP Projects
S/N
o
Risk Variable
Codes Variables
Mean
Scores
Relative
Importance
index (RII) Ranking
1 Q8 Construction Cost Overrun 3.98 0.79 1
2 Q9 Construction Time Delay 3.76 0.74 2
3 Q30 Interest Rate Fluctuation 3.46 0.69 3
4 Q14 Availability of Finance 3.27 0.65 4
02468
1012
Nu
mb
er
of
PP
P p
roje
cts
Private Public
78
S/N
o
Risk Variable
Codes Variables
Mean
Scores
Relative
Importance
index (RII) Ranking
5 Q13
Excessive variation in project
Specification
3.29
0.65
4
6 Q29 Material inflation 3.22 0.64 5
7 Q15 Inadequate approved budget 3.18 0.63 6
8 Q19 Late design alteration 3.00 0.60 7
9 Q10 Contractual dispute 3.03 0.60 7
10 Q12 Poor contract management 3.00 0.59 8
11 Q17 Inadequate estimate 2.86 0.57 9
12 Q18 Design ambiguity 2.83 0.56 10
13 Q16 Lack of proper project brief 2.84 0.55 11
14 Q28 Lack of experience 2.78 0.55 11
15
Q22
Lack of communication
between sub-contractors,
contactors/suppliers
2.75
0.53
12
16 Q20 Geotechnical condition 2.55 0.51 13
17 Q27
Lack of commitment among
consultants 2.54 0.51 13
18 Q26
Lack of communication
between consultants 2.56 0.50 14
19 Q25
Differences in working
method and know-how 2.48 0.50 14
20 Q11 Force majeure 2.73 0.49 15
21 Q23
Shortage of materials and
equipment 2.48 0.49 15
22 Q21 Inconsistency in Design 2.54 0.48 16
23 Q24 Poor Quality Workmanship 2.45 0.48 16
24 Q31 Change in Tax Regulation 2.39 0.48 16
Source: Researcher
4.3 Risk Mitigation Strategies in PPP Projects
The responses considered most appropriate to risks that occur in projects carried out under
different PPP models were determined using a mean score, which located responses in terms
of the response option most favoured by the respondents, and the Relative Importance Index
(RII), which ranked items in terms of the importance, accorded them by respondents. The PPP
models considered in this section of the study included Build-Operate-Transfer (BOT), Build-
Operate-Own-Transfer (BOOT) and Design-Build-Operate-Transfer (DBOT).
4.4 Appropriate Risk Responses for Different Models of PPP Projects
The Table 2 shows that the risk response considered most appropriate for all of the three
different PPP models (Build-Operate-Transfer (BOT), Build-Operate-Own-Transfer (BOOT)
and Design-Build-Operate-Transfer (DBOT) was the ‘risk reduction’ with a mean score of 4.06
and relative important of 0.73. The least appropriate response was the ‘risk retention’, which
had both the least mean score and lowest RII value 3.15 and 0.57 respectively.
Table 2. Responses to risk most appropriate to different models of PPP projects
S/N
o
Risk Response
Codes Response
Mean
Scores
Relative Importance
index (RII) Ranking
1 Q101 Risk Reduction 4.06 0.73 1
79
2 Q100 Risk Transfer 3.92 0.71 2
3 Q102 Risk Avoidance 3.43 0.62 3
4 Q103 Risk Retention 3.15 0.57 4
Source: Researcher
4.5 Appropriate Tools for Risk Mitigation for Different Models of PPP Projects
The Table 3 shows that the risk mitigation tool considered most appropriate for all of the three
different PPP models (Build-Operate-Transfer (BOT), Build-Operate-Own-Transfer (BOOT)
and Design-Build-Operate-Transfer (DBOT) was the ‘insurance policy’. This tool had a mean
score of between 4.13 and 4.44. The RII for Insurance Policy also ranged between 0.73 and
0.79.
The least appropriate tool was the ‘contingency sum’, which had both the least mean score and
lowest RII value. Notwithstanding this however, it was obvious that the difference between the
most and least appropriate tools for risk mitigation was not very wide; this probably indicates
that all of the tools suggested in the study were considered appropriate by respondents, differing
only in degree.
Table 3. Tools for Risk Mitigation most appropriate to different models of PPP projects
S/No Risk Mitigation Tools
Codes Tools
Mean
Scores
Relative
Importance index
(RII)
Ranking
1 Q104 Insurance Policy 4.44 0.79 1
2 Q105 Contingency Plan 4.28 0.76 2
3 Q106 Contingency Sum 4.13 0.73 3
Source: Researcher
4.6 Summary of the Research Findings
The most popular model for housing, road and water projects was Build-Operate-Transfer
(BOT);
The most important risks associated with PPP projects were: (i) construction cost overrun,
(ii) construction time delay, (iii) interest rate fluctuation, (iv) availability of finance, and
(v) excessive variation in project specification. However, the risks that were considered to
be of lesser importance to PPP projects were (a) Inconsistency in design, (b) Poor quality
workmanship, and (c) change in tax regulation.
“Risk reduction” was the most appropriate risk response for BOT, BOOT and DBOT while
“risk retention” was the least appropriate risk response for the models
“Insurance policy” was considered as the best tool to mitigate identified risks in BOT,
BOOT and DBOT projects. Contingency Plan and Contingency Sum were also considered
appropriate by respondents, to a lesser degree.
5 Conclusion and Recommendations
Mismanagement of risk factors that come into play during the construction phase of a PPP
project can result into non-actualisation of the PPP project / non-conformity with the project
schedule. The research aims to assess the construction risks associated with PPP projects, as
well as to recommend how best such risks can be mitigated.
80
This study found that most housing and road projects were contracted using the Build-Operate-
Transfer (BOT) model, in which ownership remains with the client, while the developer
operates the project to recover investment for a specified period of time. Water supply and
railways infrastructure PPP projects have also been executed using BOT model. Other models
that have also been applied to currently ongoing projects in Nigeria include Rehabilitate-Lease-
Operate-Transfer (RLOT, applied to housing projects), Operate-Maintain-Transfer and
Rehabilitate-Operate-Transfer ((OMT, ROT; both were applied to seaport projects) and
Supply-Operate-Maintain (SOM, which has been applied to railways infrastructure).
It is concluded that the most important risks associated with PPP projects were: (i) construction
cost overrun, (ii) construction time delay, (iii) interest rate fluctuation, (iv) availability of
finance, and (v) excessive variation in project specification. By comparison, the risks that were
considered to be of lesser importance to PPP projects were: (a) inconsistency in design, (b)
poor quality workmanship, and (c) change in tax regulation.
It is also concluded that ‘risk reduction’ was the most appropriate risk response for projects
carried out under BOT, BOOT and DBOT model, while ‘risk retention’ was the least
appropriate risk response. In order to mitigate the identified risks, ‘insurance policy’ was
considered the best tool for all three PPP models (BOT, BOOT and DBOT). This was in
preference to ‘contingency plan’ and ‘contingency sum’ as risk mitigation tools. Based on these
findings it can be concluded that effective management of PPP Risks would translate into a timely
completion of PPP project. Based on the findings and conclusions of this paper, the following
recommendations were made:
The specific circumstances and requirements of each PPP project should be examined in
detail, in order to design the most appropriate model for the project. This would forestall
situations where the BOT model is applied without discrimination to majority of projects,
even where it is apparent that the projects differ widely in almost all respects;
Clients that might be considering embarking on PPP projects should bear in mind that the
following five construction risk factors would require special attention, in order to avoid
adverse consequences on the project. The risk factors requiring close scrutiny are (i)
Construction Cost Overrun, (ii) Construction Time Delay, (iii) Interest Rate Fluctuation,
(iv) Availability of Finance, and (v) Excessive variation in project Specification. The
design of the PPP contract should be such that would make adequate provision for the
mitigation of these risks, and
In exploring options for the mitigation of construction risks in PPP projects, clients and
developers could consider insurance, contingency plans and contingency sums in
descending order of preference.
6 References
Adelusi A.K. (2009). Assessment of risk and risk management stages in Nigerian Construction
Industry. Unpublished B. Tech degree thesis, Department of Quantity Surveying, Federal
University of Technology, Akure, Nigeria.
Annimashaun, A.M. (2011). Public-Private Partnership as a Policy Strategy of Infrastructure
Financing in Nigeria. Retrieved on 24th Feb, 2013 from njpg.pactu.edu.np/njpgfiles/4.
Chohra, M. Shiyu, M. and Hu, C. (2008). PPP Risk Transfer Mechanism in the Specific
Project. Case of MAGTAA Desalination Seawater Station in Algeria. Retrieved on
January,16, 2012 from M Chohra, M Shiyu, Cu wbiconpro.com
81
Dada, J.O. (2010). Strategies for Mitigating Risk in Construction Projects. Risk Management
in Construction. Proceedings of the 40th annual general meeting/conference of the
Nigerian Institute of Building.
Grimsey, D. and Lewis, M.K. (2002). Evaluating the Risks of Public-Private Partnerships for
Infrastructure Projects. International Journal of Project Management, 20 (2), 107-1
Hillson, D. (2004). Effective opportunity management for projects–exploiting positive risk.
New York: Marcel Dekker.
Jagboro, G.O. (2007). An evaluation of the impact of risk on project cost overrun in the
Nigerian construction industry. Journal of Financial Management of Property and
Construction, Nigeria, 12, 37 – 44.
KarimiAzar, A, Mousavi, N.S. Farid-Mousavi, S.F., Hosseini, S. (2011). Risk assessment
model selection in construction industry. Journal of Expert Systems with Applications,
38, 9105– 9111
Meruyn, K.L. (2001). Risk management in Public Private Partnership. Discussion paper,
Centre for Globalization and Europeanization of the Economy, School of International
Business and Enterprise, University of south Austria, Adelaide, South Australia.
Mohammed, I.Y., Bala, K. and Kunya, S.U. (2012). Risk Allocation Preference in Public-
Private Partnership Infrastructure Projects in Nigeria, Building Programme. Journal of
Engineering and Applied Science, Cenresin Publications, Nigeria, 4.
NPPPR (2012). Nigeria Public Private Partnership Review: Where are we? 1(1). Retrieved on
April 15, 2012; from www.detailsolicitors.com/media/archive2/.../pppreview.pd
Nur A.A.K. and Batu P.J. (2011). Risk Allocation in Public-Private Partnership (PPP) Project:
A review on risk factors. International Journal of Sustainable Construction Engineering
&Technology, 2, (2), Retrieved on 13th March, 2013 from
http://penerbit.uthm.edu.my/ojs/index.php/IJSCET.
Obi, B. & Ofonyelu, C.C. (2015). Public-Private Partnership (PPP) In Nigeria: A
Game Theoretic Conjecture of Low-Level Equilibrium in the Power
Industry Applied Economics and Finance, 2 (4), Retrieved on 25th September,
2016 from http://aef.redfame.com
Olugbodi, K. (2012). Assessment of selected public-private partnership projects in the FCT,
Abuja. Unpublished Master of Science Degree thesis. Department of Urban and Regional
Planning Faculty of Environmental Design Ahmadu Bello University, Zaria, Nigeria.
Odimabo, O.O. and Oduoza, C.F. (2013). Risk Assessment Framework for
Building Construction Projects’ in Developing countries. International Journal
of Construction Engineering and Management. 2(5) 143-154
Patrick, X.W.Z., Shouqing, W. and Dong, F. (2008). A life-cycle risk management framework
for PPP infrastructure projects. Journal of Financial Management of property
and Construction. 13(2), 123-142.
Pauget, B. and Wald, A. (2013). Relational Competence in Complex
Temporary Organizations: The Case of a French Hospital Construction Project
Network. International Journal of Project Management, 31, 200
Ranjan, A. (2010). Successful delivery of public private partnership for infrastructure
development. Retrieved on December, 24th 2012; from www.jiit.at.in/upload/Ranjan.
Rostami, A. (2016) Tools and Techniques in Risk Identification: A Research
within SMEs in the UK Construction Industry Universal Journal of Management,
4(4), 203-210.
Rot, A. (2008) IT Risk Assessment: Quantitative and Qualitative
Approach Proceedings of the World Congress on Engineering and Computer
Science WCECS 2008, October 22 - 24, San Francisco, USA
82
Rouse, M. (2010). Essential guide to business continuity and disaster recovery plans.
Risk analysis, Australia: CW Europe.
Thaheem, J. (2012) A review of quantitative analysis techniques for construction project risk
management, Creative construction conference, Budapest, Hungary.
Uher, T. (2003). Programming and Scheduling Techniques, Sydney, UNSW Press.
UNESCAP (2011). A Guidebook on Public-Private Partnership in Infrastructure. United Nation
Economic and Social Commission for Asia and the Pacific. Retrieved on 27th
December, 2012 from www.unescap.org/ttdw/common/.../PPP/text/ppk.pdf.
U-Dominic, C.M., Ezeabasili A.C.C., Okoro, B.U., Dim, N.U., Chikezie, G.C. (2015). A
Review of Public Private Partnership on some Development Projects in
Nigeria International Journal of Application or Innovation in Engineering &
Management (IJAIEM), 4(3), 64-75.
83
Decision to Engage Nominated Subcontractors on
Construction Projects in Nigeria Anita Adamu and Winston Shakantu
Department of Construction Management
Nelson Mandela Metropolitan University, Port Elizaberth
Email: s213505622@nmmu.ac.za, winston.shakantu@nmmu.ac.za
Abstract:
Engaging subcontractors on construction projects is common practice in the building industry.
Though nominated by the consultants acting on behave of the client, nominated subcontractors
must also be engaged under the main contractor. The decision to nominate this category of
subcontractors rests with the client consultants of any given project. The objective of this study
is to identify factors that influence decisions to nominate subcontractors on construction
projects in Nigeria. The research adopts a quantitative method of inquiry, with the aid of closed-
ended questionnaires. 10 factors identified from the related literature were placed on a five-
point Likert scale to measure the relative importance of each factor when considering
nominated subcontracting. A simple random sampling technique was used to self-administer
the questionnaires to construction consultants within Abuja metropolis. A total of 34 duly
completed questionnaires were analysed using descriptive methods (percentages, mean and co-
efficient of variation). Nature of specialist work and a need for speedy completion of the project
were ranked very important factors that influence decision to nominate subcontrators on
construction projects in Nigeria. However, factors such as project uncertainties, maintaining
business relationships and site location have less influence on decision to engage these
subcontractors. In conclusion, the study found that the most important factors relate to two of
the three project parameters (cost, time, quality). While specialist works is to quality, speedy
completion is to time, this suggests the need to encourage specialisation and skill consolidation
by subcontractors rather than general contracting.
Keywords:
Construction projects, Decision, Nominated subcontractors, Subcontracting, Nigeria
1 Introduction
Subcontracting is common practice in the construction industry owing to the fragmented nature
of construction Project. ‘Fragmented’ in this context refers to the work packages in a single
project with each requiring specific skill to accomplish. In line with this, (Bamisile, 2004)
reports that a variety of subcontractors that specialise in a wide range of work packages are
engaged on most building projects in Nigeria, most of these specialists also possess specialised
plants and equipment for their particular type of works.
Subcontractors are engaged to perform specific work on a project, while the main or general
contractor performs basic work operations (Arditi & Chotibhongs, 2005). The extensive
practice of subcontracting implies that project success is highly susceptible to the performance
of subcontractors involved (El-Mashaleh, 2009). The success and performance of typical a
construction project are determined by three key parameters which are time, cost and quality.
The factors that influence decisions to engage subcontractors (third party) by the prime parties
84
(main contractor and client) on a building constructions projects are all linked to the project
success parameters. The objective of this paper is to identify the factors that influence clients
of projects to nominate particular subcontractors for some aspects of works.
The first section of the paper has provided a background and the objective of the study. The
second section of the paper presents an articulated concept of subcontracting in the construction
industry. A nested section reviews briefly nominated subcontracting which gently guides the
survey method adopted and explained in the third section. The fifth section discusses the
research findings from which conclusions were drawn.
2 Subcontracting in the Construction Industry
Subcontract work packages are usually included and clearly defined in the main contract of
which qualified subcontractors for specific works may price (Peurifoy, Schexnayder, &
Shapira, 2006). Nominated, named and domestic subcontracting are the three categories of
subcontracting in the construction industry. Subcontract work packages are usually included
and clearly defined in the main contract of which qualified subcontractors for specific works
may price (Vilasini, Neitzert, Rotimi, & Windapo, 2012).
Provisions for subcontracts are included in the Joint Contract Tribunals (JCTs) that prescribes
how each should be conducted. The contractual arrangements between the main contractor and
the subcontractors are similar to those between the client and the main contractor. However,
subcontractors are only responsible to the main contractor in the performance of their
subcontracts (Nunnally, 2011). The construction industry in Nigeria has been shaped by the
training and the operation over the years of British contract practices, procedures and
procurement methods (Oladapo, 2003). Approaches to the construction procurement in the
British construction industry are basically as follows:
Traditional: Single stage and two stage tendering;
Single source: Design and build; Package deal; Turnkey;
Management: Management contracting; construction management, and
Partnering.
The primary distinguishing features of all the different procurement systems can be accounted
for by three basic characteristics. Firstly, the responsibility for the design and construction of
the facility, and whether this should be placed on separate organisations or on a single
organisation. Secondly, whether the principal contractor should construct the works or manage
the construction process. The third feature is the remuneration basis for work done (Edum-
Fotwe, McCaffer, & Majid, 1999). Subcontractors have been used in building projects to
execute specialist operations, but, particularly during the post-1945 period, the use of
subcontractors increased, notably in the basic building trades which were traditionally the
provinces of contractors’ directly employed operatives (Fellows, Langford, Newcombe, &
Urry, 2009).
Subcontract arrangements may be categorised based on the outsourcing decisions made at
project onset or functional participation among many others. Subcontracts based on
outsourcing depends on capacity, specialisation and economic justification (Vilasini et al.,
2012). Subcontract arrangements in the context of the construction industry can be employed
in all the different procurement procedures (Edum-Fotwe et al., 1999). Management
contracting procurement approach is based on 100% subcontracting because the main
85
contractor takes the role of general manager of the construction process while various
subcontractors execute distinct work packages of the project (Murdoch & Hughes, 2002).
Partnering approach to procurement is rooted in principles of collaboration, as such,
involvement of subcontractors is minimised because the collaboration is between the
client/consultants and the main contractor for a given project (Fryer, Egbu, Ellis, & Gorse,
2004).
2.1 Factors that Influence Subcontract Decisions
Site based nature of production in the construction industry makes activities highly prone to
uncertainties in terms of climate and other site conditions, in addition to availability of
resources required for works within the local environment. Therefore, decision to subcontract
out aspects of works is a strategic plan to cope with long-term uncertainties (Usdiken, Sozen,
& Enbiyaoglu, 1988). This allows the main contractor to avoid the employment of a stable
workforce and invest in fixed resources under conditions of fluctuating demand, serving as an
external buffering mechanism, absorbing uncertainties arising from the availability of
resources and operational condition (Sozen & Kucuk, 1999).
The strategy (subcontracting) deals not only with long-term environmental uncertainties but
buffer the technical core of the organization against short-term contingencies (Sozen & Kucuk,
1999). Moreover, the greater the complexity and uncertainty the greater the use of
subcontractors, and in this way, specific services are bundled and presented to the main
contractor and eventually to the client (Sözen & Kayahan, 2001). However, subcontracting can
improve product quality because it uses specialized manpower; fixed costs are less because
equipment maintenance and under-utilised manpower are eliminated (Shimizu & Cardoso,
2002).
Subcontracting is also driven by the lack of specialized capabilities and know-how, in addition
to the need for reducing costs and legal risks. Building contractors tend to subcontract much of
their production, because of the relatively wider range of technological inputs of building
projects and liability concerns (Costantino & Pietroforte, 2004). A continuous project
complexity and the highly competitive nature of the construction industry, often makes a
construction project to be executed by several subcontractors (Wang & Liu, 2005)
2.2 Nominated Subcontracting
There are several circumstances under which an employer would wish to nominate or name a
subcontractor with whom the main contractor must enter into a contract, these include:
Ensure the chosen subcontractor has a proven track record for good work;
Use a subcontractor with whom the employer has developed a long-term business
relationship;
Base the selection of the subcontractor on a basis other than the lowest bidder;
Some specialist work requires a longer lead time than the project construction program
would allow, and
The design team may wish to ensure the quality of the design input from the specialist
subcontractor (Murdoch & Hughes, 2002).
The practice of nomination is peculiar to the UK and certain parts of its former colonies. The
procedure is also found in those countries whose standard building contracts are based on major
UK forms. Nominated subcontracting for building works are done in accordance with the
86
conditions given in clause 35 of the JCT 1998, where the circumstances that permit nomination
include; the expenditure of a provisional sum included in the contract bills or in any instruction
of the Architect (acting on behalf of the employer) requiring a variation to the extent that:
It consists of additional work to the contract drawings and specifications described by or
referred to in the contract bill, and
Any supply and fixing of materials or goods or any execution of work by a nominated
subcontractor in connection with the additional work (Ndekugri & Rycroft, 2014).
3 Research Methodology
The first two sections are products of an intensive literature search that provided the
background and theoretical underpinning of nominated subcontracting in the construction
industry. The background of the paper clarified that the research seeks understanding factors
that influence nominating subcontractors on building projects. However, some factors were
identified during the review of related literature. Therefore, the need for adapting the
quantitative method of research rather than qualitative for the next phase was justified because
the factors have been identified.
3.1 Survey Design
A close-ended structured questionnaire was designed as the survey instrument which was
administered to consultants of construction project clients within Abuja. The use of close-ended
questionnaire in this study was embraced because of its ability to generate data extensively
when administered to more respondents. The survey solicited the opinion of respondents on
the importance of 10 identified factors that influence decision to nominate subcontractors on
construction projects in Nigerian.
Twenty construction organisations that undertake consultancy services for building
construction projects under the Federal Capital Development Agency (FCDA) were considered
in the survey. A total of 100 questionnaires were self-administered randomly to professionals
within these organisations. 52 were returned, however only 34 of the returned were completed
correctly and therefore useful for the study. On a five-point Likert scale, respondents rated the
degree of importance attached to each of the ten factors presented on the questionnaire. The
scale was presented thus: 1= unsure; 2=Not Important; 3=Less Important; 4=Important;
5=Very Important.
Abuja being the Federal capital city of Nigeria, its geographical location in the heart of the
country is the major reason for its selection for the survey. Moreover, most of the strong and
reputable construction firms operate head offices in the capital city, besides a lot of construction
activities are following the on-going development of the model city and other infrastructural
expansion.
Data Analysis
The Mean Score (MS), a measure of central tendency was used to analyse responses on the
importance of the 10 factors that influence decisions to nominate subcontractors to undertake
aspects of construction projects. The mean score of the responses to each factor is compared to
the hypothesised mean of the 5-point Likert scale used in this study (hypothesised mean is the
mid-point value of 3). The significant importance or otherwise with the notion being tested was
determined by comparing the mean score with 3 (Coakes & Steed, 2009). This implies that any
87
result significantly different from this value of 3 is assumed to be either positive or negative to
the notion being tested (Pullin & Haidar, 2003). The coefficient of Variation (COV) was used
to compare the variability of means expressed as a percentage. The factors were ranked based
on the MS, but the COV was very useful in ranking the factors especially were the factors had
same MS.
4 Findings and Discussion
In order to determine the personal profiles of the individuals who provided information during
the field survey, respondents were asked to provide details of their professional and educational
qualifications, years of experience in active construction projects.
Table 1. Certified Specialisation of Respondents
Profession Response (%)
Architecture 29
Building 24
Civil engineering 9
Electrical engineering 6
Quantity surveying 32
Others -
Total 100
Source: Researcher
Table 1 presents the primary certified profession of the respondent in a construction related
field. Quantity surveyors out-numbered other professionals that participated in this survey
(32%), although architects constitute 29% of the total respondents and 24% are builders. Only
9% and 6% of the total respondents are civil engineers and electrical engineers. The statistics
gives an indication of a relatively wide sampling of within key professions (Architecture,
Building, Quantity surveying) in the building construction industry.
Table 2. Educational Qualification of Respondents
Qualification Response (%)
Doctorate -
Masters 44
Bachelors 38
Post Graduate Diploma 9
Higher National Diploma 9
Ordinary National Diploma -
Others -
Total 100
Source: Researcher
The level of educational training of those that constitute the various groups involved in
subcontracting is revealed by their qualifications. Table 2 shows that 44% of the respondents
hold a Masters degree in their specific construction related profession. 38% hold a Bachelors
degrees, while those with Post graduate diploma (PGD) and Higher national diploma (HND)
summed up to only 18% .
Table 3. Experience of Respondents
Experience Response (%)
Less than 5years 14
88
5 to 10years 18
11 to 15years 18
Above 15years 50
Total 100
Source: Researcher
Experience acquired over the years in projects execution tends to sharpen the technical skills
of the project participants there by having a positive impact on project delivery. The results
shown in Table 3 on the experience of the respondents revealed that half (50%) of those from
the clients’ organisations have over 15years of experience, 18% of them have between 10 and
15years work experience, another 18% have between 5 and 10years, the remaining (15%) have
less than 5years work experience.
Table 4. Respondents Position
Position Response (%)
Director 27
Project Manager 47
Technical Staff 26
Total 100
Source: Researcher
The highest percentage of the respondents (47%) are project managers in the respective
organisation and 27% are directors. Therefore, majority (74%) of the respondents are members
of strategic management of the construction organisations where the surveys were conducted.
This implies that the data generated has high credibility with high level of reliability. In
selecting any aspect of works for subcontracts, certain factors must be considered which will
aid in deciding and justifying the need to nominate subcontractor(s) for specific work items.
Table 5. Importance of factors that Influence Decision to Nominate Subcontractors
Factor MS CV (%) RANK
Nature of Specialist work 4.09 18.4 1
Speedy completion of project 3.65 24.6 2
Better quality of workmanship 3.65 27.7 3
Project complexity 3.59 24.8 4
Main contract procurement method 3.15 36.8 5
Scope of work 3.38 37.2 6
Site location 2.79 37.1 8
Project uncertainty 2.79 37.4 7
Maintaining good business relationship 2.74 45.7 9
Reduced overall contract sum 2.41 48.1 10
(Source: Adamu and Shakantu, 2016)
Nature of specialist work (4.09) has the highest mean score based on the result of analysis
conducted in this study, it also returned the least coefficient of variation (18%) and therefore
ranked number 1 factor amongst the 10 factors understudied. Need for speedy completion of
project and achieving better quality of workmanship had the second highest mean score (3.65),
however, speedy completion of project is ranked number 2 factor based on its coefficient of
variation (24.6%) against (27.7%) better quality of workmanship. project complexity, main
89
contract procurement method and scope of work were ranked 4th and 5th factors respectively.
Reduced overall contract sum (10th) and maintaining good a business relationship (9th) are least
likely to influence decision to nominate subcontractors on construction projects.
5 Conclusions
The 1st ranked factor in the order of importance (Nature of specialist work) in this study
suggests that quality is paramount and has a major influence on clients’ decisions to nominate
particular specialist subcontractors, perhaps the contractors has an outstanding record on
executing that particular work on previous projects. A logical conclusion on the 2nd ranked
most influential factor (Speedy completion of works) is that subcontractors that specialise on
certain work aspect acquire intensive skill on that particular works and acquire and continually
improve on technological skills in the area and also acquire necessary resources which may not
be economical for the main contractor to purchase and tie down finances. The result also
implies that the need to cut down project cost is the least factor that would influence nominating
subcontractors, similarly maintaining good a relationship with a particular subcontractor is a
top factor in considering nominating a subcontractor.
6 References
Arditi, D., & Chotibhongs, R. (2005). Issues in Subcontracting Practice. Journal of
Construction Engineering and Management, 131(8), 866-876.
doi:doi:10.1061/(ASCE)0733-9364(2005)131:8(866)
Bamisile, A. (2004). Building Production Management. . Lagos-Nigeria: The Professional’s
Instruction Manual Foresight Press limited,.
Coakes, S. J., & Steed, L. (2009). SPSS: Analysis without anguish using SPSS version 14.0 for
Windows: John Wiley & Sons, Inc.
Costantino, N., & Pietroforte, R. (2004). Production arrangements by US building and non‐building contractors: an update. Construction Management and Economics, 22(3), 231-
235.
Edum-Fotwe, F., McCaffer, R., & Majid, M. (1999). Sub-contracting or co-contracting:
Construction procurement in perspective. Paper presented at the 2nd International
Conference on Construction Industry Development, and 1st Conference of CIB TG29
on Construction in Developing Countries, Construction Industry Development in the
New Millennium., In University of Singapore, Singapore.
El-Mashaleh, M. S. (2009). A Construction Subcontractor Selection Model.
Fellows, R. F., Langford, D., Newcombe, R., & Urry, S. (2009). Construction management in
practice: John Wiley & Sons.
Fryer, B., Egbu, C. O., Ellis, R., & Gorse, C. (2004). The practice of construction management
(3rd ed.): Blackwell publishing.
Murdoch, J., & Hughes, W. (2002). Construction contracts: law and management: Routledge.
Ndekugri, I., & Rycroft, M. (2014). JCT98 Building Contract: Law and Administration:
Routledge.
Nunnally, S. W. (2011). Construction Methods and Management: Prentice Hall.
Oladapo, A. M. (2003). Overview Of Procurement Systems And Project management. Paper
presented at the The NIQS 2-day Workshop on International Procurement Systems and
Project Management, Abuja-Nigeria.
Peurifoy, R. L., Schexnayder, C. J., & Shapira, A. (2006). Construction Planning, Equipment,
and Methods (7th ed.): McGraw-Hill Higher Education.
90
Pullin, L., & Haidar, A. (2003). Managerial values in local government-Victoria, Australia.
International Journal of Public Sector Management, 16(4), 286-302.
Shimizu, J. Y., & Cardoso, F. F. (2002). Subcontracting and cooperation network in building
construction: a literature review. Proceedings IGLC-10, Gramado-RS.
Sözen, Z., & Kayahan, O. (2001). Correlates of the length of the relationship between main
and specialist trade contractors in the construction industry. Construction Management
& Economics, 19(2), 131-133.
Sozen, Z., & Kucuk, M. A. (1999). Secondary subcontracting in the Turkish construction
industry. Construction Management & Economics, 17(2), 215-220.
Usdiken, B., Sozen, Z., & Enbiyaoglu, H. (1988). Strategies and Boundaries: Subcontracting
in Construction. Strategic Management Journal,, 9(6), 633-637.
Vilasini, N., Neitzert, T., Rotimi, J. O., & Windapo, A. O. (2012). A framework for sub-
contractor integration in alliance contracts. International Journal of Construction
Supply Chain Management., 2(1), 17-33. doi:DOI 10.14424/ijcscm201012-17-33
Wang, W.-C., & Liu, J.-J. (2005). Factor-based path analysis to support subcontractor
management. International Journal of Project Management, 23(2), 109-120.
91
Conceptual Evaluation Ideas for the Infrastructure
Delivery Improvement Programme in South Africa Thabiso Monyane1, Fidelis Emuze2 and Gerrit Crafford3
1, 2 Department of Built Environment,
Central University of Technology, Free State, South Africa
Email: tmonyane@cut.ac.za / femuze@cut.ac.za 3 Department of Construction Economics,
Nelson Mandela Metropolitan University, South Africa
Email: gerrit.crafford@nmmu.ac.za
Abstract:
A doctoral study has been embarked upon with the intentions of addressing cost management
problems encountered on Infrastructure Delivery Improvement Programme (IDIP) in South
Africa. Given that poor cost performance constitute hindrance to the realization of project
goals, it is imperative to eliminate it from IDIP construction projects. The theoretical paper
highlights the idea that a target value design (TVD) as a concept is able to tackle cost
performance issues when it is implemented appropriately. Therefore, a case study evaluation
research design has been selected for the study so that better cost management decisions and
actions could be promoted in IDIP projects. The focus of the evaluation will be on IDIP projects
in the Free State province of South Africa. The focus favours depth as opposed to breadth of
intended findings of the study.
Keywords:
Construction, Cost, Infrastructure, target value design, South Africa
1 Introduction
The construction industry has proven the significant role it plays in the economy of any country
whether a developed or developing the country. Cooper and Slagmunder (2004) suggest that
construction firms of today are faced with an immense competition and they must manage their
costs aggressively if they are to survive the recent business environment. The decision to build
is never an easy one and the cost of the building is an influencing factor on the sponsor’s final
decision whether to proceed or halt the project. However, all construction projects face similar
problems of improving their cost performance. Ali and Kamaruzzan (2010) mention the
importance of controlling construction cost because in developing countries, cost management
approaches has proven to be the less effective when compared to time management (Ramli,
2003). Construction projects are unique and they tend to assume a greater dimension of
complexity as they increase in size. Before the concept of TVD become popular in the lean
construction lexicon, Nicolini et al. (2000) have reported the use of target costing in
construction. Target costing is understood to be the cost management tool for reducing the
overall cost of a product over its entire life cycle with the help of top management and active
contribution of members of the supply chain (Nicolini et al., 2000). According to Ballard and
Reiser (2004), designing to target cost is a product development practice that converts cost into
a design criterion rather than a design outcome. Target costing played a substantial role
according to Ballard and Reiser (2004) on a case study project in United States of America
(USA), which suggested that it contributed to delivering the project within budget and on time,
more value was provided to the client than would otherwise have been provided, and the
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provider, made a reasonable profit over time, TC metamorphoses to TVD, which was firstly
introduced in 2002 and has since become more commonly used in construction industries in
the USA (Zimina et al., 2012). The first successful TC project was documented in 2004 by
Ballard and Reiser in the USA (Do, Chen & Ballard, 2014). The case study project was
delivered based on a Design-Build contract that integrates lean construction principles and
practices, including target costing and Last Planner System (LPS) of production.
Comparatively, a similar project constructed in the non TVD method was delivered 10 months
late and costs 15% more than the case study project (Ballard and Reiser, 2004). The non-TVD
project may have been delivered late because observation was that traditional practice of
construction is contract centred and with assignments defining and balancing the objectives of
various participants in terms of time, health and safety, costs, errors, and quality.
Within the South African context, little is known about the application of TVD although it has
been applied to the construction industry abroad and provided tremendous value in improving
cost performance (Ballard & Reiser, 2004; Ballard 2009; Ballard & Rybkowski 2009; Zimina
et al. 2012). “the Main idea of TVD is to make a client’s value (design criteria, cost, schedule
& constructability) a driver of design, thereby reducing waste & satisfying or even exceeding
the client’s expectation” (Zimina et al., 2012). Hence this study is important due to the need
for the development of innovative practice in South African construction. The industry in South
Africa appears to be lagging behind in implementing best cost performance practices. The
paper will first clearly establish the various costing model in use in South Africa through an
exploratory literature review. Then the study will go deeper into defining what TVD is, the
process of TVD, and then describing why there is a need for change in construction practices.
To support the expanded use of TVD, a research opportunity, therefore, exists to investigate
how TVD can systematically be applied to public projects in South Africa. Literature Review
1.1 Challenges of existing cost management practices
Projects running over budget were reported in other developing countries but not yet in South
Africa. Then Ramabodu and Verster (2010) first established a presence of cost overruns being
a problem in South Africa but with emphasis on the Free State province. Furthermore, the study
then went on to identify the factors contributing to cost overruns and rank them in order of
importance to raise the awareness among professionals of the construction Industry. The study
used the perception of professionals to identify those factors they deem to be contributing to
cost overruns without being backed by any data to support the findings. In addition, the study
does not suggest any remedy to try and minimise the reoccurrence of cost overrun in
construction projects.
Nimbona and Agumba (2014) in their research conducted found out that the main cause of
unsuccessful construction projects in South Africa was financial problems (clients’ financial
capacity, late payment, unreliable source of finance), which comes back to the fact that cost is
an important parameter of project success. Innovative ways of solving this problem such as
TVD provide a great opportunity for the SA construction industry to deepen our understanding
of the challenges in applying target costing in contracting as well as the necessary
modifications and adaptation to the approach necessary to make it suitable for the South Africa
construction.
1.2 Outcomes of existing cost management practices
Potts (2008) describes cost management, as the process which is necessary to ensure that
planned development of a design and procurement of a project is such that the price for its
construction provides value for money (VFM) and it is within the limits anticipated by the
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clients. The management of costs in a project is a common thread running through the entire
life of a project. The feasibility of a project depends on its cost and financial viability and the
project is not complete until the last payments and paperwork have been completed. Caruthers
et al. (2008) state that the management of costs begins with the financial feasibility study,
progresses through all the costs that are required to purchase all the resources needed by the
project, through to using cost control to ensure that all work that is done is properly completed
1.3 Outcomes of existing cost management practices
Cost estimation is utilised as a tool to forecast the probable cost of a project or as an indication
guide of the approximate cost of a project before it can be constructed. Current costing models
that are used in construction industry needs to be improved for better project performance.
Jamieson (1971) highlighted the extra cost of construction in South Africa caused by clients in
rushing to take a project out on tender and the repercussion of expediting the process is
detrimental to the success of the project, due to extra costs in construction and bad design.
Similarly, Dawson (1972) reiterated on the immense increase of escalation which appears to
have been the outcome of the high tempo of development which has characterized the last ten
years in particular in South Africa. In addition, Dawson (1972) elaborated further that tenders
submitted for major works during those times appeared to be as much as 100 percent (and even
more) higher than they would have been ten years ago, and how can such state of affairs be
justified?
The cost of construction seemed to escalate immensely during the 1960s to the 19770s, Dawson
(1972) made an example with the cost of the Orange River Scheme that has escalated
approximately four times and that other works planned by the Department of Water Affairs
involving original estimates amounting to Rl42 million in 1960 are likely to now cost in excess
of R500 million then how can we possibly plan for the future with a degree of certainty?
According to Flybjerg, Holm and Buhl (2002) cost are underestimated in almost 90% of the
projects, and that on average actual cost are 28% higher than estimated costs. Due to this
phenomenon of lack of forecasting, Flybjerg, Garbuio, and Lovallo (2009) further suggests that
this can be attributed to three underlying reasons: 1) delusions or honest mistakes; 2) deception
or strategic manipulation of information or processes; 3) bad luck.
1.4 Costs are shaped by action rather than result from action
According to Ballard and Reiser (2004), a traditional practice in construction propels the
architect to provide a drawing to some degree of completion, estimate its cost and if that is not
to the desired outcome of costs, alter the design so the costs can be brought up to the desired
budget. Furthermore, Ballard and Reiser (2004) claim that arguably this approach is wasteful,
yielding rework and frustration, and perhaps generates less value for customers and providers
than alternatives. The adoption of TVD makes it possible to achieve the objective of the project
where the cost act as an input to design and design process is a collaborative iterative process
constantly updating cost to align client’s requirement with their constraints. In past decade,
TVD implementation has proved to be very successful in delivering client’s needs in a set target
cost below the market price (Ballard, 2009).
1.5 Negative influence of behaviour
Several forms of negative influence from cost management systems on behaviour have been
identified in the literature, ranging from claim culture to manipulation of bids and performance
measurements (Hanid et al., 2011). Behaviour which relates to the attitude of planning for
claims on construction projects for profit maximizing. This kind of attitudes is singled out by
94
Rooke, Seymour and Fellows (2003) whereby the idea that the industry has a culture which is
opportunistic, prone to conflict and resistant to change is a byword in construction. To add to
that, it is argued that price competitive tendering has resulted in a habitual tendency amongst
contractors to expend more effort on generating profit from claims than from improved
construction methods (Rooke, Seymour and Fellows, 2004). The same kind of attitudes can be
seen in the procurement of contractors in the public sector. Accountability constitutes a central
pillar to public procurement (Soudry, 2007). The construction industry has been identified as
the most corrupt sector in the world (de Jong, Henry & Stansbury, 2009). Research undertaken
by Bowen, Edwards & Catell (2012) reported that opportunities for corruption were found to
arise across almost the entire range of activities involved in the building procurement process,
but clustered mainly in the tendering and tender evaluation stages. In addition, Bowen et al.
(2012) indicate that the process of appointing contractors and professional consultants are
allegedly subject to manipulation at times. Tender interference and tender irregularities were
reflected within most of the data in terms of corrupt practices.
1.6 Performance of traditional cost models
This section is intended to highlight mostly why current traditional cost models are performing
poorly, but on the other hand, it also addresses again the importance of why this study is worth
being undertaken. Bowen and Edwards (1985) point out that a need for a new paradigm shift
or the ‘information explosion’ in the field of cost modeling and price forecasting will take place
only from the pursuit of academic knowledge. This phenomenon is intriguing as Bowen and
Edwards (1985) further reiterate that there has been no published evidence of a demand from
consumers for more realistic price forecasting, nor of any recent development work on cost
modeling being conducted by QSs in South Africa. Even to date, the status quo remains the
same. However, the Association of South African Quantity Surveyors recently updated the
second edition guide to elemental cost estimating and analysis for building works in 2013 after
being used for 15 years unchanged. With costs spiraling out of control on so many projects
globally, infrastructure projects of all types are experiencing cost overruns. Flyvbjerg Nils and
Werner (2003) name this a “performance paradox”. What is interesting is the update of the
guide to elemental cost estimating, is that in the foreword, the update was requested to examine
whether there was a need to revise and possibly expand the 1998 and 2003 editions to
accommodate changes that have taken place in the industry since those versions were published
(ASAQS Guide to elemental cost estimating 2013). The reason posed by the committee on
updating the previous editions of the guide to elemental estimating obviously noticed that
change was necessary in order for the profession to be still relevant.
‘Traditional’ cost models have come under heavy criticism before, regression models, Bills of
quantities (BOQ) and elemental estimating methods to not explain the system they represent
(Bowen, Wolvaardt and Taylor 1987). Wilson (1982) cited by Nguyen, Tommelein, Ballard
(2008) attest further criticism of the reliance of traditional models on the use of historical data
to create deterministic estimates of building or components without explicit qualification of
their integral changeability and improbability.
1.7 What is target costing and Target Value Design?
The woes recorded in subsections 2.1-2.6 is now been addressed by lean construction
researchers with new concepts. Target costing (TC) is originally introduced in japan under the
name Genka Kikaku as an expression that clearly connotes it as an overall strategic approach
to reducing costs and not only as costing technique (Nicolini et al., 2000). TC in view of Ballard
and Reiser (2004) is a product development practice that converts costs into design criterion
rather than a design outcome. A description of TC in construction terms by the exact words of
95
Ballard (2007) is the practice of constraining design and construction of a capital facility to a
maximum cost. However, Cooper and Slagmunder (2004) define TC as a technique used to
manage the future profits of firms. Once this target cost has been established, value engineering
(VE) is used to find ways to improve the product design so that the target coast can be achieved.
The TC process reverses the traditional method of costing, whereby the market price is first
determined if the product will sell and then the desired profit is then subtracted to give the
designers the cost to which they must design the final product. The below formula clearly
explains the concept better (Clifton, Bird, Albano, and Townsend, 2004). However, according
to Shingo (2005), Toyota production team used a different formula to improve the cost
performance of a product:
Selling price – Cost = Profit
Shingo (2005) explains that the customer is the one that decides the selling price, and profit is
what remains after subtracting the cost from it. While TC proved very successful in new
product development in the manufacturing sector, its application in a capital intensive sector
such as the construction has been somewhat limited. Thus, target costing has metamorphosed
into target value design (TVD) in lean construction. TVD became an adaptation of TC to
project production systems (Nguyen et al., 2010). TVD became more than just costs, added
more value such as constructability, time, safety, work structuring, etc. (Lichtig 2005) cited by
(Nguyen 2010). TVD is “a management practice that drives design to deliver customer value
within project constraints it rests on a production management foundation and treats cost as an
outcome of PSD, operation, and improvement” (Ballard 2009). TVD turns current design
practice upside-down: (1) Setting the Target Cost for design: “Rather than estimate based on a
detailed design, design based on a detailed estimate”, (2) Work Structuring: “Rather than
evaluate the constructability of a design, design for what is constructible”, (3) Collaboration:
“Rather than design alone and then come together for group reviews and decisions, work
together to define the issues and produce decisions then design to those decisions”, (4) Set-
Based Design: “Rather than narrow choices to proceed with design, carry solution sets far into
the design process”, and (5) Collocation: “Rather than work alone in separate rooms, work in
pairs or larger groups, face to face.” (Macomber et al., 2008). TVD is not to be confused as a
project delivery system on its own, but forms part of one of the important element of the lean
project delivery system that is integrated project delivery (IPD).
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2 Research Methodology
2.1 Research Problem formulation
Infrastructure delivery is the pillar of economic activity of countries, especially developing
countries. The significance of infrastructure is responsible for the decision of the South African
government to contribute substantial investment to developments through several programmes.
In fact, in South Africa, infrastructure development is a vehicle for enhanced economic growth
and social development. However, increasing infrastructure development investments appears
to be moving in tandem with poor delivery performance, especially in relation to cost. Some
of the challenges include under spending, poor planning, cost overruns, quality issues and clear
project failure (National Treasury 2016). There are rigorous efforts to build greater delivery
efficiency in the public sector. In brief, present costing models in use in South African
construction are failing to assure the best cost performance. To attempt a remedy and forestall
the continuation of poor cost performance, an evaluation of the state of affairs in a major
delivery programme is required. The evaluation is intended to propose best practices
discovered in the use of the principles of TVD (Ballard and Reiser, 2004; Macomber et al.,
2008; Nicolini et al., 2000; Forbes and Ahmed, 2011) is the idea espoused in this study
2.2 Adopted Research Process
The design adapted for this study is evaluation research. The purpose of evaluation as a
methodology is to serve the public good by improving policies and programmes through policy
and data analysis that proceeded from carefully researched and accurate information (Alkin,
2013). The IDIP programme to be evaluated fits well with the sentiments of Alkin (2013), as
it is an initiative by the public sector to improve infrastructure delivery for the good of the
public and data is readily available for evaluation. The goal of evaluation research is a good fit
for use regarding the IDIP programme. The goal of IDIP is to improve the efficiency and
effectiveness of the delivery of public sector infrastructure through developing and
institutionalizing best practice systems and tools and building capacity. IDIP supports the
provincial departments that deliver infrastructure to effectively render and sustain
infrastructure and contribute towards provincial growth and development strategies (National
Treasury 2016). The main question of this study is: “How would Target Value Design impact
the delivery of infrastructure projects”? The IDIP programme outlines how infrastructure
projects can be improved holistically including pricing strategies recommended to complete
projects within the stipulated budgets. However, the IDIP improvement concentrates
specifically more on other delivery mechanism and deems costs to be improved as results of
improving on other delivery mechanisms.
The research design is a technique that unites the data collected with the conclusion to be drawn
on the initial research questions posed (Yin 2014). Alkin’s (2013) view on evaluation is
explained as a “retrospective assessment of the performance of programs (policies, programs,
projects, and processes) that have been implemented by the public sector or other bodies”.
Evaluations are classified as either formative or summative (Weinberger, 2009). This study
will be conducted using the summative evaluation as its purpose is primarily to provide
information in assisting stakeholders to make a judgment about how to proceed with a program,
that may include whether to adopt, continue, discontinue or expand the program (Weinberger,
2009). The evaluation intends to support innovative exploration of evolving approaches for
addressing problems, and also adapting an existing programme to a new context in terms of
cost certainty. The summative evaluation is appropriate since there is an annual assessment of
97
the IDIP’s progress being conducted. The evaluation will be conducted on a case study of
projects executed under the IDIP in the Free State province of South Africa.
Develop Research Question
Outcomes of current cost models / Why
current cost models are performing poorly
TC vs. TVD
Policy implications of applying TVD in IDIP
Questionnaire Survey
Literature review
Examine recorded IDIP project performance
Identify costing issues
Evaluation Research – Case Studies
Identify deficiencies in existing cost
management practices
Develop protocol to introduce TVD in IDIP
projects
Test the protocol
Conclude and suggest guidelines
Quantitative Qualitative
Identify gap
In-Depth Interviews
System Dynamics Logic Model
Figure 1: Proposed Research process for the evaluation of IDIP
Figure 1 presents the proposed research process for the study. The literature review will be
conducted to develop the knowledge base of the research. A number of in-depth interviews will
be conducted with the authors of the IDIP programme to gather information about how the
program addressed cost improvement. Furthermore, a questionnaire survey of the authors of
the IDIP assessment review committee, and professionals involved in IDIP projects will be
carried out for an explanation of the effectiveness and efficiency of the IDIP on cost
performance in order to help identify deficiencies in current cost management practice.
The issue of the first cost on construction projects will be examined and the traditional design
and tender procurement will be looked at. The interviews and questionnaires will also provide
a comprehensive understanding of what questions would have to be answered to overcome the
barriers of implementing TVD.
The results of the interviews and questionnaire survey will be used to develop a strategy to
introduce TVD in IDIP projects. That will also assist to develop a case study plan. Developing
a strategy to introduce TVD was based on the deficiencies identified in the current cost
management practices in the local construction industry at large. Interviews and questionnaires
will be used to document the process and information flow of the current practices. The
documentation will identify opportunities for improvement through TVD.
98
3 Conclusions
The South African government identified infrastructure delivery as a mechanism for enhancing
the economy of the country. However, the delivery of infrastructure projects has been plagued
with performance issues of which cost is a major component. To attain the goal of global
competitiveness, the public sector had to improve the way infrastructure is delivered by various
provincial departments. Although the government is addressing the noted problems through
the IDIP, the poor cost performance remains a major problem. Rather, cost overrun is
consistently reported on IDIP projects.
To address the cost management problems experienced on the IDIP projects, an evaluation
research is proposed for this study so the possible use of TVD could be advanced for IDIP
projects in South Africa.
4 Acknowledgement
The author(s) wishes to acknowledge the National Research Foundation – Thuthuka Funding
Instrument – 93968 that has made this study possible.
5 References
Ali, AS, Kamaruzzaman S.N. (2010), Cost performance for building construction projects in
Klang Valley. Journal of Building Performance ISSN: 2180-2106 Vol 1 Issue 1 2010.
Alkin, M.C. (2013), Evaluation Roots: A wider perspective of theorists’ Views and Influences,
2nd edition, SAGE.
Association of South African Quantity Surveyors (ASAQS) (2013), Guide to Elemental
Estimating & Analysis for Building Works. Johannesburg: ASAQS.
Ballard, G. (2007), Target costing in the construction industry, Powerpoint presentation, P2SL
2007 Conference - February 7, 2007, http://p2sl.berkeley.edu.
Ballard, G. (2009), “An Update on Target Value Design.” Presentation Slides, Design Forum,
June 18-19, St. Louis, MO. Available at
http://www.leanconstruction.org/files/Forum_Meetings/Design_Forum_June09/2_Update
_on_Target_Value_Design/2_TVD_Update_ppt.pdf.
Ballard, G. & Reiser, P. (2004), "The St. Olaf College Fieldhouse Project: a case study in
designing to target cost", 12th Annual Conference of the International Group for Lean
Construction, pp. 234.
Ballard, G. & Rybkowski, Z.K. (2009), "Overcoming the Hurdle of First Cost: Action Research
in Target Costing", Construction Research Congress 2009@ sBuilding a Sustainable
FutureASCE, pp. 1038.
Bargstädt, H. & Blickling, A. (2005), "Determination of process durations on virtual
construction sites", Proceedings of the 37th conference on Winter simulationWinter
Simulation Conference, pp. 1549.
Bowen, P.A., Edwards, P.J. (1985), "Cost Modelling and price forecasting: practice and theory
in perspective", Construction Management and Economics, No. 3, pp. 199-215.
Bowen, P.A., Wolvaardt, J.S. and Taylor, R.G. (1987), “Cost Modeling: A Process-Modeling
Approach”. Building cost modelling and computers, 15-24, London, E&FN Spon.
Bowen, P., Edwards, P. and Cattell, K. (2012), 'Corruption in the supply chain: South African
construction managers' experiences', in K. Michell, P.Bowen, K.Cattell (ed.) Delivering
99
Value to the Community, Cape Town, South Africa, 23-25 January 2012, pp. 300-
305. International Journal of Project Management, vol. 28, no. 3, pp. 285-295.
Carruthers, M, Steyn, H, Basson, G, du Plessis, Y, Kruger, D, Pienaar, J, Prozesky-Kutschke,
B, van Eck, S, and Visser, K. (2008), Project Management: A multi-disciplinary Approach,
second revised edition, FPM Publishing, ISBN 978-0-620-39357-7.
Clifton, M.B., Bird, H.M.B., Albano, R.E. and Townsend, W.P. (2004). Target Costing:
Market-Driven Product Design, New York, Marcel Dekker, Inc.
Cooper, R. & Slagmulder, R. (2004), Interorganizational cost management and relational
context. Accounting, Organizations, and Society, 29, 1-26.
Dawson, S, E. (1972), Estimating, Tendering and Construction Problems and Their Impact On
Budgeting For Capital Works, THE CIVIL ENGINEER in South Africa, reproduced by
SABINET Gateway.
de Jong, M., Henry, W.P. and Stansbury, N. (2009), Eliminating corruption in our
engineering/construction industry. Leadership and Management in Engineering, 9:3, 105–
111.
Do, D., Chen. C, Ballard, G., and Tommelein, I,D. (2014), Target Value Design as a Method
for Controlling Project Cost Overruns, Proceedings IGLC-22, June 2014 | Oslo, Norway.
Flyvbjerg, B., Holm, M.S. & Buhl, S. (2002), "Underestimating costs in public works projects:
Error or lie?", Journal of the American planning association, vol. 68, no. 3, pp. 279-295.
Flyvbjerg, B., Nils, B. and Werner, R. (2003), Megaprojects and Risk: An Anatomy of
Ambition (Cambridge University Press).
Flyvbjerg, B, Bruzelius, N, and Rothengatter, W. (2003), Megaprojects and risk: an anatomy
of ambition, Journal of the Transportation forum Vol.43, No 1 pp. 143-145.
Flyvbjerg, B., Garbuio, M., and Lovallo, D. (2009), Delusion and deception in large
infrastructure projects: two models for explaining and preventing executive disaster.
California Management Review, 51(2), pp.170-193.
Hanid, M., Siriwardena, M. & Koskela, L. (2011), "What are the big issues in cost
management?", RICS Construction and Property Conference, pp. 738.
Jamieson, A. R. (1971), The costs of construction, THE CIVIL ENGINEER in South Africa,
reproduced by SABINET Gateway.
Macomber, H., Howell, G., and Barberio, J. (2008), “Target-Value Design: Nine Foundational
Practices for Delivering Surprising Client Value.” The American Institute of Architects,
Practice Management Digest. Available at
http://www.aia.org/nwsltr_pm.cfm?pagename=pm_a_112007_targetvaluedesign.
Accessed January 2016.
National Department of Treasury, Public Finance Management Act 1 of 1999, Standard for
Infrastructure Procurement and Delivery Management (SIPDM),
www.treasury.gov.za/idip/Pages/default.aspx Accessed 22 March 2016.
Nicolini, D., Tomkins, C., Holti, R., Oldman, A. & Smalley, M. (2000), "Can target costing
and whole life costing be applied in the construction industry?: evidence from two case
studies", British Journal of Management, vol. 11, no. 4, pp. 303-324.
Nguyen, H.V., Tommelein, I.D. and Ballard, G. (2008), “Process-Based Cost Modeling to
Support Lean Project Delivery.” In Tzortzopoulos, P. and Kagioglou, M. (Eds.) (2008).
Proceedings of the 16th Annual Conference of the International Group for Lean
Construction (IGLC 16), July 16-18, Manchester, UK. Available at
http://www.iglc.net/conferences/2008_Manchester/ConferencePapers/Nguyen_Tommelei
_Ballard_Process_based_cost_modeling_to_support_lean_project_delivery.pdf
Potts, K, (2008), Construction cost management: learning from case studies, ISBN 0-203-
93301-X Master e-book ISBN. Taylor & Francis.
100
Ramabodu, M.S, & Verster, J.J.P. (2010), An evaluation of cost overruns in public sector
projects: In the Free State province of South Africa. Fifth Built Environment Conference,
Durban, 18 – 20 July 2010.
Ramli M,. (2003), The need for systematic project management in construction industry.
Malaysia: Macroworks.
Rooke, J., Seymour, D. & Fellows, R. (2003), ‘The Claims Culture; A Taxonomy of Industry
Attitudes’, Construction Management and Economics, 21(2):167-174.1
Rubrich, L. (2012), An Introduction to Lean Construction: Applying Lean to Construction
Organizations and Processes, WCM Associates LLC, ISBN 10: 097933313X.
Rybkowski, Z.K. (2009), The Application of Root Cause Analysis and Target Value Design to
Evidence-Based Design in the Capital Planning of Healthcare Facilities,
Shingo, S. (2005), A study of the Toyota Production System from an Industrial engineering
view point, Revised edition, CRC Pres Taylor & Francis, ISBN 0-915299-1-8.
Soudry, O. (2007), “A principal-agent analysis of accountability in public procurement”, in
Piga, P.
Weinberger, E.R. (2009), "A program evaluation of school-wide positive behavior support in
an alternative education setting". Dissertations. Paper 57.
Yin, R. (2014), Case study Research: Design and Methods, 5th Edition, SAGE, ISNB 978-1-
4522-4256-9.
Zimina, D., Ballard, G. & Pasquire, C. (2012), "Target value design: using collaboration and a
lean approach to reduce construction cost", Construction Management and Economics, vol.
30, no. 5, pp. 383-398.
101
Risk Management Framework for Property Development
Projects: Real Estate Demand Z Shrosbree1, B Botha2 and R Cumberlege3
1, 2Department of Quantity Surveying,
Nelson Mandela Metropolitan University, South Africa
Email: roy.cumberlege@nmmu.ac.za 2Department of Construction Management, Nelson Mandela Metropolitan University,
Summerstrand, Port Elizabeth, South Africa
Email: Brink.Botha@nmmu.ac.za
Abstract:
This study aims to determine the perceived effectiveness of risk management in property
development projects and the influence that several factors such as real estate demand, have on
the overall success or failure of a project. The study addressed the manner in which risk and
uncertainty in property development can be measured and contained by the developer of a
project. A literature review was conducted of the relevant literature relating to risk
management and factors that influence property development projects. The information
obtained was used to develop a questionnaire which was distributed to a sample of different
construction professionals. The data obtained from the completed questionnaires were analysed
and interpreted in terms of the objectives of the research. The findings from the questionnaire
confirmed that it is essential to identify possible risks that might arise during the development
of the project and to make provision for these risks. It is highly important that the risks and
uncertainties influencing property development are known to the developer to effectively
manage these uncertainties and risks in order to increase the chances of project success. The
research only takes into consideration the perceptions of South African Construction
Professionals involved in Property Development. This research furthermore introduced a risk
management framework which will assist construction professionals who are involved with
property development. The framework will also support developers in contributing to the
planning of new projects.
Keywords:
Property development, risk management, real estate development
1 Introduction
Successful property development is critical to our economy and our everyday lives. As Winston
Churchill stated, “We shape our buildings, and afterwards our buildings shape us” (Bulloch &
Sullivan, 2010: 78).
“Property development is the process directed at the increase in value of an existing property
(underdeveloped or developed) by the application of resources” (Cloete, 1998: 109).
Property development is an exciting, occasionally frustrating, and increasingly complex
activity involving the use of scarce resources. It is a high-risk business that often involves large
sums of money tied up in the production process, providing a product that is relatively
indivisible and illiquid (Wilkinson et al., 2008).
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Fisher and Robson (2005) point out that risk is an ever-present aspect of business, and risk
taking is necessary for profit and economic progress. Speculative property development is
popularly perceived as a ‘risky business’, yet, as with other entrepreneurs, developers have
opportunities to manage the risks they face. Variables such as unknown future demand, risks
and uncertainty are key elements of property development projects (Wiegelmann, 2012). A
developer can manage risks in one of two fundamentally different ways: one risk at a time, on
a largely compartmentalised and decentralised basis; or all risks viewed together within a
coordinated and strategic framework (Nocco & Stulz, 2006).
Finke, Belasco and Huston (2010) describe property risk management as a fundamental aspect
of individual financial planning. The property development business requires a great awareness
of risk and its management. This not only stems from the risky nature of the development
process and inherent complexity but also from the regulatory, capital market and stakeholders’
pressures which call for great awareness of risk and risk management.
Several vital variables influence the way in which projects run from inception to close out
stage. These vital variables, when identified and made provision for, can lead to the ultimate
success of the property development project.
It is the primary goal of the property developer to ultimately address the manner in which risk
and uncertainty in property development can be measured and contained (Coleskie, 2014). For
risk and uncertainty to be measured and contained it first has to be known by the developer.
This paper makes use of theory and an empirical analysis and is intended as an introduction to
the risk processes associated with property development. The problem statement to the study
could be formulated that property developers do not identify possible risks associated with
project development in order to facilitate adequate risk management throughout the project. It
practically sets out variables that influence risk during the process of property development,
with special focus on real estate demand.
The key motive behind most developments is to develop a property which can ultimately be
marketed at a profit. In order to maximise that potential profit, a developer will wish to create
a property which is in demand and can be disposed of rapidly, either through rental or sale, at
the best possible price (Millington, 2000).
Demand for new properties may result from a large range of factors including population
growth; the increased purchasing power of the population; changing age patterns of the
population; movements of the population; changing consumer preferences; current shortages
of the supply in the relevant type of property; current inadequacies of quality in the stock of
the relevant type of property; changes in technology, in industrial practices, in marketing
practices, etc. which render existing properties obsolete; and the need for more appropriately
located properties than the current stock provides.
The objectives of this study is to prove that risk and several other variables influence the
success or failure of the property development process.
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2 Literature review
2.1 An approach to risk management in property development risk
Cooper and Chapman (1987) believe that "Risk is the exposure to the possibility of economic
or financial loss or gain, physical damage or injury, or delay, as a consequence of the
uncertainty associated with pursuing a particular course of action".
Risk Management
Risk Management is the act or practice of dealing with risk. It includes risk planning, assessing
(identifying and analysing), handling and monitoring. Managing risk means minimising,
controlling and sharing of risks, and not merely passing them off onto another party (Hatami
& Behsan, 2012).
Risk Management Process
The risk management process consists of the procedures and rules for the identification,
assessment, control and documentation of all potential risks, as well as the control of the
effectiveness of the measures taken to reduce risk. The interest in risk management in property
development is increasing in order to manage all the challenges that developers are facing
concerning internal operations as well as external relations (Gehner, 2008).
According to Wiegelman (2012), the risk management process consists of the following four
phases.
Risk Identification
Risk identification involves a detailed examination, through which potential risk may be
uncovered and appropriate responses formulated. This phase deals with identifying any
disruptive factors, and the effects thereof, on the development process (Wiegelman, 2012).
The risk profile of development must be identified in order to determine what can possibly go
wrong and how it can come to pass throughout the development process (Burger, 2008).
Further analysis is critical for successful risk management because only those risks that have
been identified can be analysed and controlled. The developer needs to achieve a degree of risk
identification that is all inclusive and as up-to-date as possible, for any errors will only be
realised at a later stage when it is too late and can threaten the project. The risk identification
phase is generally complex and time consuming (Kendrick, 2009).
2.1.2 Risk assessment
Cowen (2005: 5) defines risk assessment as: “the process of evaluating identified risks and the
interrelation between risks.” To acquire an overview of the actions needed in respect of the
risk identified, these risks need to be analysed and evaluated. The point is to obtain an
understanding of the expected value and the degree to which risk may threaten the success of
the development. The amount of data and the specific data quality is of great importance for
effective risk assessment, which can be seen as a critical success factor in risk management.
2.1.3 Risk control
After the risks have been identified and evaluated it must be determined which of the identified
risks need further attention. During this phase, appropriate control mechanisms must be chosen
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to deal accordingly with each risk. When choosing the control mechanism, the advantages and
costs of each alternative must be determined, and the financial implications, general policy
regarding risk and specific goals of the developer must also be considered. (Wiegelman, 2012;
Gehner, 2008).
2.1.4 Risk monitoring
During this phase, the operating processes are examined by comparing them to the planned
standards. Risk monitoring’s prime focus is to evaluate units and functions of the risk
management process. According to Wiegelman (2012), it is intended to determine the
following:
that the determent goals have been met;
that the risk management strategy or approach abides with risk policy;
that the risk culture is in place, and
that the responsibilities have been clearly defined.
2.2 Real estate demand
Property developers and investors need to determine the level of effective demand for an
envisaged project before a decision is taken to go ahead, and before the detailed design of a
project is determined. The key motive behind most developments being to develop a property
which can ultimately be marketed at a profit, in order to maximise that potential profit, a
developer will wish to create a property which can be disposed of rapidly, either through rental
or sale (or both) at the best possible price (Millington, 2000).
In the early stages of the development process, market research ought to be done to identify
what the current demand is for new housing and other forms of property.
The demand of Real Estate/Property depends entirely on four key driving factors:
Market Size (Population, Employment).
Income/Wealth.
Prices of Substitutes.
Expectations.
2.2.1 Market Size
Market size variables that drive the demand for real estate include population, employment,
and output, depending on the property type under consideration. For example, in the case of
housing and retail the relevant exogenous determinant is the number of households; while in
the case of office space, the most relevant market size variable is office employment. In the
case of industrial space demand, the relevant size variables include output, as well as
warehouse and distribution employment (Wheaton and Torto, 1990). The effect of market size
on real estate demand is positive, that is, for the same price level and larger market size a greater
quantity of real estate will be demanded in terms of either square footage or number of units.
2.2.2 Income/wealth
Income/wealth directly affects the demand for retail and residential real estate in the sense that,
keeping prices constant as income increases, more households can afford to buy a house and a
greater rand amount is available for retail spending. Therefore, increases in real income or
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wealth should be associated with increases in the number of housing units and the square
footage of retail space demanded.
2.2.3 The price of substitutes
The price of substitutes could also induce shifts in the demand for real estate. For example, for
a given level of single-family housing prices, increases in apartment rents are likely to induce
a shift of the demand curve for single family-housing to the right. Such a shift is likely to occur
because, as renting becomes more expensive relative to owning a house, some renters may find
home-ownership more attractive. Similarly, in the office market, as rents in the Class A market
rise, some firms may be forced to seek space in the Class B market where rents are more
affordable. In such a case, the demand schedule for Class B space will shift to the right in order
to reflect the greater amount of office space demanded in response to rent increases in the Class
A market.
2.2.4 Consumer/firm expectations
Consumer/firm expectations may induce shifts in demand for the different types of real estate.
For example, expectations of higher prices or rents in the future may result in increases in the
number of housing units or the amount of office space demanded. Similarly, growth
expectations on the part of firms may also induce shifts in the demand for commercial real
estate. For example, an office firm in a market that is growing rapidly may require a greater
amount of space in anticipation of future expansion than an identical firm would require in a
stable market that does not foresee any expansion potential.
3 Research Methodology
A quantitative research approach was followed in order to achieve the objectives of the study.
The population consisted of South African Construction professionals involved in Property
Development. A sample of hundred (100) professionals were randomly selected.
A pilot study was conducted in order to identify any potential problems with the questionnaire.
The questionnaire had values that corresponded to decisions (1-strongly disagree, 2-disagree,
3- neutral, 4- agree, 5- strongly agree). The recommendations that were made during the pilot
study were subsequently recorded and the various amendments were made to the questionnaire.
The questionnaire was e-mailed to the respondents including a covering letter, together with a
link to an electronic web-based survey. After completion of the questionnaire by the
respondent, the data were automatically captured, and then converted to Excel for analysis.
The questionnaire was divided into eight sections, with the first section relating to the general
demographics of the respondent. Sections 2 to 7 was concerned with the vital factors that
influence projects from inception to close out stage. Section 8 dealt with real estate demand.
The completed questionnaires were carefully analysed for any potential encoding that could
skew the findings and those items were removed from the study, once they had been identified.
4 Findings and Discussion
4.1 Demographics
Twenty-five (25) completed questionnaires were received which represents a response rate of
25%.
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Twenty-two (88%) males and three females (12%) contributed to the survey. The age
categories for the survey ranged in five-year intervals, with the majority (32%) aged 60 years
or older. Only one (4%) of the respondents were between 25 and 29 years old.
Twelve (48%) of the respondents are fully employed and thirteen (52%) of the respondents are
self-employed. The qualifications of the respondents, ranged from an undergraduate degree to
a post graduate degree.
Twenty-two (88%) of the respondents completed their property development projects in the
private sector while three (12%) of the respondents completed their property development
projects in the public sector.
Majority of the respondents (32%) indicated that they developed buildings for mixed use
purposes while only three (12%) of the respondents developed buildings for industrial use only.
4.2 Risk in property development projects
Table 1 indicates a mean score of 4.65 (88% of respondents agreeing to strongly agreeing)
proving that property development practitioners identify risk during property development
projects. Risk identification involves a detailed examination, through which potential risk may
be uncovered and appropriate responses formulated. This phase deals with identifying any
disruptive factors, and the effects thereof, on the development process. Respondents also
indicated, with a mean score of 4.46 (88% of respondents agreeing to strongly agreeing), that
risk was monitored throughout all different stages of the project. Majority of practitioners
(92%) indicated with a mean score of 4.24 (agreeing to strongly agreeing), that risk was dealt
within a professional manner and not simply passed on to another party. Only 4% of the
respondents disagree with this statement. These five broad inquiries of risk in property
development projects were all taken into consideration by respondents during the developments
and impacted the property development projects.
Table 1: Risk during property development projects
Aspect Unsure
Response (%) MS Rank
1 2 3 4 5
Risks associated with the specific
project were identified 8 0 0 4 24 64 4.65 1
Risk was monitored throughout all
different stages of the project. 4 0 0 8 36 52 4.46 2
Risk management process helped
identify all the variations that
occurred to the project
4 0 0 8 40 48 4.42 3
The influence of risk elements
were forecasted for this project 0 0 0 8 44 48 4.4 4
Risk was dealt with in a
professional manner and not
simply passed on to another party.
0 0 4 4 56 36 4.24 5
Source: Researcher
Table 2 indicates the descriptive statistics above, with regard to risk in property development
projects. An overall mean score of 4.288 indicates that risk has a large impact on property
development projects. The mode of 5 and median of 4, indicate that the majority of the
respondents strongly agree that the different aspects of risk need to be considered and
provisions need to be made during property development projects.
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Table 2: Descriptive statistics of risk in property development projects
Descriptive Statistics Overall
Mean 4,28 4,4 4,24 4,28 4,24 4,288
Mode 5 5 5 5 4 5
Median 5 4 4 5 4 4
SD 1,4 0,645497 1,090871 1,1 0,723418 1,0145395
N 25 25 25 25 25 125
Source: Researcher
4.3 Real estate demand in property development projects
Table 3 below clearly indicates, with a mean of 4.36 (96% of respondents agreeing to strongly
agreeing), that most property development practitioners assessed real estate demand during the
property development projects. Property Developers need to determine the level of effective
demand for an envisaged project before a decision is taken to go ahead, and before the detailed
design of a project is determined. The local economy was also a very influential factor, with a
mean of 4.36 (92% of respondents agreeing to strongly agreeing), when determining the
demand for new developments. 64% of the respondents agreed that the predicted growth in
development in the next 10 years exceeds current market demand, with 32% of the respondents
being neutral about this statement, and 4% of respondents disagreeing. These four broad
inquiries of real estate demand were assessed and taken into consideration to determine whether
real estate demand has an impact on property development projects.
Table 3: Aspects of real estate demand considered during property development project
Aspect Response (%) MS Rank
1 2 3 4 5
The demand for the product was
adequately assessed 0 0 4 56 40 4.36 1
The local economy was an influential
factor when determining the demand for
the development
0 0 12 52 36 4.32 2
Numbers of sales or rental requirements
were considered with demand data 0 0 20 56 24 4.04 3
The development for growth of
development in the next 10 years exceed
the market demand currently
0 4 32 56 8 3.68 4
Source: Researcher
Table 4 indicates the descriptive statistics above, with regard to real estate demand in property
development projects. An overall mean of 4.1 indicates that real estate demand impacts
property development projects. The mode and median both being 4, indicate that the majority
of the respondents agreed that the different aspects of real estate demand are considered during
property development projects.
Table 4: Descriptive statistics of real estate demand in property development projects
Descriptive Statistics Overall
Mean 4,36 3,68 4,04 4,32 4,1 4,36
Mode 4 4 4 4 4 4
Median 4 4 4 4 4 4
SD 0,568624 0,690411 0,675771 0,6271629 0,689019 0,568624
N 25 25 25 25 100 25
Source: Researcher
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5 Conclusion
This paper has examined the degree to which property development practitioners take risk and
real estate demand into consideration during property development projects. Miles, Berens,
Eppli and Weiss (2007: 3) did not understate the risky nature of property development by
saying that “few business ventures are as heavily leveraged as traditional real estate
development projects, magnifying the risk of ruin but also increasing the potential for high
returns to equity." It is important to also take the positive aspects of risk into account, it allows
for the possibility not just to produce attractive profits when development is completed, but
also to maximise long term returns by the positive management of risk (Coleskie, 2014:63).
A lack of understanding, implementation of risk management and risk awareness exposes
developer organisations to disruptive processes and unnecessary threats, restricting the
realisation of opportunities on the one side and the avoidance of threats on the other side. The
price of poor risk management processes can result, not only in the failure of individual
projects, but also whole projects.
It is imperative to note that 85.8% of the respondents strongly agreed that risk is vital and needs
to be identified in the earliest of phases during a project. Some of the biggest decisions for the
success of the project are being made during the early stages of a project, during this stage it is
also where a high level of uncertainty occurs. It is therefore necessary that potential risks are
identified, assessed and allowed for at the beginning of any project. The early identification of
opportunities and risk, as well as the ability to manage these pro-actively, are critical for
property development success.
82% of the respondents agreed that real estate demand is a major factor during the project
processes and it is necessary to take the four key driving factors; market size (population,
employment); income/wealth; the prices of substitutes and the firm’s expectations into account
during the planning of the property development project.
The study identified that 64% of the respondents agreed that the predicted growth in
development in the next 10 years exceeds current market demand, with 32% of the respondents
being neutral about this statement, and 4% of respondents disagreeing.
The objectives of the study have been achieved and by means of literature and an empirical
analysis.
6 Recommendations for Further Research
The most important phase of risk management in property development process is the risk
identification phase as once most of the possible risks have been identified the developer can
assess, control and monitor the risk that is known to them. Therefore, property developers
should focus on making sure they know what risks might affect their projects as without the
knowledge of what risks the project has, it is highly unlikely to go ahead with the project, and
if the project goes ahead it is likely the project will be unsuccessful. According to Kendrick
(2009:40), the developer needs to achieve a degree of risk identification that is all inclusive
and as up-to-date as possible, for any errors will only be realised at a later stage when it is too
late and can threaten the project. The risk identification phase is generally complex and time
consuming.
109
7 References
ASX Corporate Governance Council. 2010. Corporate Governance Principles and
Recommendations. 3rd ed. Australia: Australian Securities Exchange.
Baker, R.D. 1991. Time-cost relationships in construction. University of Florida
Bulloch, B. and Sullivan, S. 2010.The key to the real estate development process. Cornell real
estate review
Cadman, D and Austin- Crowe, L. 1991. Property Development. 3rd Edition. Spon. Cooper,
D. and Chapman, C (1987) Risk analysis for large projects: models, methods and cases.
John Wiley and Son. Chichester, UK.
Coleskie, G. 2013. Bloemfontein: Risk and uncertainty in property development. (Honours).
Bloemfontein Department Quantity Surveying and Construction Management, UFS.
Cooper, D. and Chapman, C. 1987. Risk analysis for large projects: models, methods and cases.
John Wiley and Son. Chichester, UK.
Cowen, N. 2005. Risk Analysis and Evaluation. 2nd ed. Wiltshire: Antony Rowe Ltd.
Finke, M, Belasco, E, & Huston, S 2010, Individual Property Risk Management: Journal of
Probability & Statistics, 1: 1-11.
Fischer, P. and Robson, S. 2006. The Perception and Management of Risk in UK: Journal of
Property Research, 23(2): 135-161.
Gehner, E, 2008. Knowingly taking risk. 1st ed. Netherlands: Eburon Academic Publishers.
Hatami, F. and Behsan, H. 2012. Evaluation and Investigation of Risk Management in Iranian
Construction Industry: Journal of Life Science: 9(4):387-399.
Kendrick, T. 2009. Identifying and Managing Project Risk: Essential Tools for Failure-
Proofing Your Project. 2nd ed. New York: AMACOM
Kohl, N. Schafers, K. and Schulte W. 2009. Corporate Governance. Doctoral. Germany:
University of Regensburg Johnson, G., Scholes, K. & W hittington, R. 2006. Exploring
corporate strategy, text and cases. Harlow: FT Prentice Hall
MacLaran, A. 2003. Making Space: Property Development and Urban Planning. 1st Ed. Arnold
Miles M.E., Berens G.L., Eppli M.J. & Weiss M.A. 2007. Real Estate Development: Principles
and Process. 4th ed. Urban Land Institute.
Millington A.F. 2000. Property Development. 1st Ed. Routledge.
Nocco, B.W. and Stulz, M. 2006. Enterprise Risk Management: Theory and Practice: Journal
of Applied Corporate Finance, 18(4): 1-13.
Storey, J., Bate, P., Buchanan, D., Green, R., Salaman, G. and Winchester, N. 2008.New
governance arrangements in the NHS: emergent implications, Working Paper No. 3,
NHS/SDO, London.
Wheaton, W. and R. Torto. 1994. Office Rent Indices and their Behaviour through
Time.Journal of Urban Economics, 35, 121-139
Wiegelman, T.W. 2012. Risk management in the Real Estate Development Industry. Institute
of Sustainable Development & Architecture, Bond University, Australia.
Wilkinson, S. and Reed, R. 2008 Property Development. 5th ed. London: Routledge.
Winch, G.M. and Carr, B. 2001, Processes maps and protocols: understanding the shape of the
construction process: Construction Management and Economics, 19: 519-531.
Worldometers. 2015. Population of South Africa. [ONLINE] Available at:
http://www.worldometers.info/world-population/south-africa-population/. [Accessed 10
May 2015].
110
Clients’ Knowledge of Procurement Systems and Its
Influence on Construction Project Performance Windapo, AO1, Adediran, AA2 and Rotimi, JOB3
1,2Department of Construction Economics and Management, University of Cape Town 3School of Built Environment and Engineering, Auckland University of Technology
Email:1abimbola.windapo@uct.ac.za, 2ADDABD001@myuct.ac.za, 3jrotimi@aut.ac.nz
Abstract:
The choice of construction procurement system varies from one project to the other, depending
on a number of information clients have on general operations within the built environment
circle, and this could influence project performance either positively or negatively. This study
investigates the procurement system frequently used on construction projects in South Africa
and whether clients’ knowledge about construction procurement systems influence project
performance objectives. Extant literature was reviewed to establish the most important project
performance objectives, the common procurement systems used in the construction industry
and factors within project procurement systems that influence project performance objectives.
Data collected from three expert clients in the South African construction industry was
analysed using Analytical Hierarchy Process (AHP) to determine the rank of client project
performance criteria, while Pearson Product Moment Correlation was used in establishing the
relationship between the level of clients’ knowledge and project performance. It was found that
the common procurement systems used are traditional, followed by management oriented and
integrated procurement systems. In addition, it emerged that the client's knowledge, within
procurement systems influence the achievement of project performance objectives. Based on
these findings, the study concludes that there is some inappropriateness in the procurement
systems being selected by clients in South Africa. If procurement systems are better selected,
it could give better chances of successful project outcomes.
Keywords:
AHP, Clientele, Knowledge, Performance, Procurement, Risk
1 Introduction
Building procurement system is the combination of activities carried out to attain a new
building (Masterman, 1992). The process requires the active involvement of project owners
(clients) as they set the pre-conditions directed towards the effective attainment of specific
project objectives (Ratnasabapathy & Rameezdeen, 2010). According to the CIOB (2010),
procurement involves the selection of the most suitable organizational structure which will be
responsible for the design and construction of the project. Procurement systems used in the
construction industry are broadly characterised as Traditional (Separated and cooperative)
procurement systems, Integrated (design and build) procurement systems and Management
Oriented (Love et al., 1998; Alhazmi & McCaffer, 2000; Cooperative Research Centre (CRC),
2008; Windapo & Rotimi, 2012).
According to Bowen et al. (1999), CIOB (2010) and Thwala and Mathonsi (2012), building
procurement systems have inherent characteristics which allow them to meet certain project
performance criteria. The Construction Industry Development Board (cidb) (2014) established
that in the South African context, the selection of procurement methods is influential to
achieving clients’ and project objectives. Bowen et al. (1999), Windapo and Rotimi (2012) and
Mathonsi and Thwala (2012) identify factors within procurement systems that address the
111
achievement of different client and project objectives, such as project characteristics, client
characteristics and ease of administration.
Lam et al. (2003) and Luu et al. (2003) noted that common occurrences of client dissatisfaction
coupled with a wide range of procurement systems to select from, results in the construction
industry seeking to select more efficient approach to procurement systems, in order to better
the performance criteria on building projects. Rwelamila and Meyer (1999), Chan (2000) and
Lam et al. (2003) have noted that the emergence of new procurement systems has led to a shift
from traditional methods to more efficient integrated systems that enables better achievement
of project objectives.
Rwelamila and Meyer (1999) found that there is little knowledge of the different procurement
systems and their variations and that there is inappropriateness in the selection of procurement
systems. In South Africa, where there is a focus on traditional procurement systems in project
delivery (Rwelamila & Meyer, 1999), the cidb Construction Industry Indicators (CIIs)
highlighted the dissatisfaction of clients to the quality of works delivered, condition of the
facility at handover, non-resolution of defective work during the construction period by the
main contractor and the overall poor quality of materials used (cidb, 2011). It has therefore
become less viable to use traditional procurement systems. There is limited research, and in the
context of the South African construction industry, into whether clients’ knowledge of
construction procurement systems, which determines their selection of appropriate
procurement systems influences project outcomes. This study intends to fill this gap in
knowledge by examining whether the knowledge of the client about project procurement
systems influence project performance objectives.
The study proposes that clients’ knowledge of procurement system is a key factor within
procurement systems that impacts on project performance. To conduct the study and test this
proposition, firstly, an analytical review of extant literature pertaining to construction
procurement systems and factors within the system that impacts on project performance, is
undertaken. Thereafter, empirical data through a quantitative research approach that includes
expert interviews and questionnaires are collected, and finally, the deductions from the
findings, provide conclusions and recommendations that address the problems of the study.
2 Procurement systems, client project performance criteria and factors
within procurement systems that impact on project performance
This section presents a review of the main procurement systems used in the construction
industry, the client project performance criteria and factors within procurement systems that
affect project performance objectives. Finally, it presents a theoretical framework that details
the elements and relationships to be investigated in the research.
2.1 Overview of procurement systems
The following subsections outline the procurement systems used in the construction industry.
Traditional procurement systems
The traditional method of procurement has been in existence and was the only procurement
system available to clients for many years. According to the CRC (2008) and CIOB (2010), it
is the system which is best understood by clients. Notably, the traditional system has
classifications that separate the functions of design and construction (Mfongeh, 2010; Windapo
112
& Rotimi, 2012). Two separate organizations (design and construction) enter into different
contracts with the client (Mathonsi & Thwala, 2009). The variants of the traditional
procurement system are the lump sum, provisional quantities and cost reimbursement.
Integrated Procurement Systems
In Integrated procurement systems, the project design and execution phases are handled by one
organization which takes responsibility for both aspects of project procurement. The client can,
therefore, enter into one agreement with an organization which will facilitate the project
delivery process. The underlying concept is that one organization will be responsible for the
project in terms of outlining client requirements, design and construction. The main contractor
responsible for the project can have different contracting teams involved in the project (Lam et
al., 2003). Each of these systems facilitates the project delivery process in a cohesive manner
by integrating the design and construction phase (Molenaar et al., 1999; Thwala & Mathonsi,
2012). There are a number variant strategies that can be defined under the integrated
procurement system. The range of variants which include, design and build, build operate and
transfer, public-private partnership, private finance initiative, and package deal or turnkey
procurement.
Management Orientated
Management oriented procurement systems, have a structure in which the project would be
managed by a construction manager. The construction manager works with the design team
and other consultants in producing designs and the team also manage the physical work carried
out on site by the contractors (Mathonsi & Thwala, 2012). The CRC (2008) mentions that there
are several forms of management procurement systems which include management
contracting, construction management and design and manage. In management contracting, the
main contractor has direct contractual links with all the sub-contractors and is in charge of all
the works on site.
Commonly used procurement systems in South Africa
Procurement systems used in South Africa are derived from British Models (Rwelamila &
Meyer, 1999; Mathonsi & Thwala, 2012). In previous studies done by Rwelamila and Meyer
(1999), Grobler and Pretorius (2002), Mbanjwa and Basson (2003) it was found that Southern
Africa utilizes the traditional procurement more often than other procurement systems followed
by management oriented and integrated systems. These studies reflect that traditional
procurement system is still the preferred and widely used procurement method in South Africa.
2.2 Client project performance criteria
According to Bowen et al. (1999), Brown and Adams (2000) and Ng et al. (2002), there is
always an expectation that time cost and quality would be considered as project performance
criteria and in literature, these criteria are cited more often than others. According to Chan et
al. (2002), the priority of the project performance criteria – cost, time, quality, health and
safety, environmental considerations, and sustainability, which represents client needs, differs
depending on the perspectives of the client. Understanding criteria which are prioritized by
clients should assist clients in developing a method of selecting best fitting procurement
systems for their projects.
113
2.3 Factors within procurement systems that impact on project
performance
Studies by Masterman (1992), Windapo and Rotimi (2012) and Love et al. (1998) suggest that
there is a relationship between project success and the procurement system chosen for the
delivery of the project. According to CRC (2008), each type of procurement system has its
strengths and weaknesses depending on its inherent characteristics, making some procurement
systems better suited to a set of performance objectives than others. Thwala and Mathonsi
(2012) found that the factors which would influence the selection of the applicable
procurement, are factors which touch on all stages of the project.
In several studies (e.g. Mbachu & Nkado, 2006; CRC, 2008; Thwala & Mathonsi, 2012; and
Kumaraswamy & Dissanayaka, 1998), a number of factors which can be applicable to various
types of procurement systems are identified, these factors consist of - clients level of knowledge
(represents the client’s level of knowledge and their ability to communicate their needs);
client’s level of control (the responsibility which the client assumes on the project); risk
allocation (gives an indication of how much risk and whether the risk has been fairly assigned
to the contractor and other parties in the project organisation); accelerated project delivery (the
need for a project to be completed in a shorter duration than another project of an identical
nature, technical complexity and size); technical complexity of the project (translates into the
client’s need for the project to be highly specialized and technologically advanced; political
considerations (external and uncontrollable environmental factors which host issues relating to
empowerment, business controls, fiscal policies, taxes, statutory regulations, which influences
the client and the client’s business during the project); and social consideration (socio-political
or socio-cultural factors such as cultural influences, social stigma, gangsterism, workers’
morale to work, health and labour union demands, which can affect the internal environment
of the project).
2.4 Analytical and conceptual framework of the study
The impact of the client’s knowledge and their ability to communicate their needs on project
performance, within the three identified procurement systems are further investigated in this
study. The conceptual framework upon which this study is based is adapted from studies by
Kumaraswamy and Dissanayaka (1998), Bowen et al. (1999), The CRC (2008), Mfongeh
(2010) and Mathonsi and Thwala (2012). Previous research by Kumaraswamy and
Dissanayaka (1998), further supported by Mathonsi and Thwala (2012) show that clients’ level
of experience/knowledge have an impact on most of the sub-systems of a procurement system.
There is, however, limited research that examines whether the level of experience/knowledge
possessed by a client influences project performance.
3 Research Methodology
The study employs a quantitative research approach involving expert interviews and a
questionnaire survey in collecting empirical data from a sample of expert clients, expert client
representatives and experienced construction professionals. The objective of the study required
a population knowledgeable in the outcomes of procurement systems used on construction
projects. The sample size of the study consisted of 693 quantity surveyors, construction
managers, project managers, architects and engineers randomly selected from a population of
2563 construction professionals listed in the Professions and Projects Register 2015 Directory
in South Africa. At the end of the survey period, 121 responses were obtained, which translates
114
into a 17.5% response rate. The questionnaire survey gathered information pertaining to the
professionals’ knowledge of the range of available procurement systems and the performance
of projects on which they were used.
Data collection was done in two rounds. The first round consists of conducting expert
interviews to determine the important client objectives and their respective weights, based on
a range of common criteria made available in the questionnaire. In the second round,
questionnaires were distributed via Surveymonkey.com to evaluate the level of influence of the
clients’ knowledge on project performance. The respondents were asked to rate the
performance of the identified project according to the client objectives of time, cost, quality,
H&S, sustainability and environmental considerations. The objectives were each assigned a
rating on a scale of 1 to 10. ‘1’ being “very poor” and ‘10’ being “excellent”. The data obtained
from the survey were analysed using descriptive statistics – means, percentages; the Analytical
Hierarchy Process (AHP) – a multi-criteria analysis used in determining in numerical terms,
the importance of each of the criteria; and inferential statistics – the Pearson Product correlation
test ‘‘ to determine the strength and direction (positive or negative) of a linear relationship
between the level of client knowledge and project performance index (PPI).
4 Findings and Discussion
In this section, the empirical data collected through the questionnaire survey are presented,
analyzed and discussed.
4.1 Demographics of Survey Respondents
The data obtained in the questionnaire survey indicated that 27% of the respondents were
quantity surveyors and another 27% were construction managers, 11%, 13%, 9% were project
managers, engineers, and architects respectively. A further 13% were other professionals such
as health and safety managers working in the construction industry. The data collected also
shows that 63% of the respondents have more than 21 years of experience and 78% have
worked on more than 21 projects in the construction industry. These results suggest that the
respondents must have been fully exposed to different construction experiences, knowledge,
and projects and could, therefore, provide valuable information relevant to this study.
4.2 Analytic Hierarchy Process (AHP)
The AHP questionnaire used for ranking client performance factors was completed by 3 clients
who included 2 Quantity Surveyors working in the private sector as client representatives and
a construction manager working in the private sector. Pairwise comparisons included client
performance criteria established in literature review as shown in Table 1.
Table 1. Matrix for Average Aggregate Scores
Client
Performance
Criteria
Time Cost Quality H&S Sustain-
ability
Env.
considerations
Weight
Time 1.000 0.667 4.000 2.733 2.667 3.333 0.281
Cost 1.500 1.000 3.667 3.000 3.333 4.000 0.329
Quality 0.250 0.273 1.000 3.333 3.000 3.333 0.164
H&S 0.366 0.333 0.300 1.000 1.111 2.000 0.086
Sustainability 0.375 0.300 0.333 0.900 1.000 2.333 0.086
Environmental 0.300 0.250 0.300 0.500 0.429 1.000 0.055
115
Considerations
Key: H&S = Health and Safety
All the respondents’ pairwise comparisons of the criteria were averaged and a mean score was
developed for each. Table 1 shows the matrix developed for all the three respondents and the
clients' performance criteria weighting in the following order: cost, time, quality, H&S, and
sustainability ranked equally and finally environmental considerations. The order outlined by
the rank of the client performance criteria is understood to be the order as perceived by expert
client representatives to be important for client satisfaction.
4.3 Projects studied and level of performance
The respondents were asked to consider a particular project which they are familiar with. This
was so that the respondents would be in a particular mind set when answering the questions
that followed. Based on this inquiry, it was found that 70% of the projects identified by the
respondents were procured using the traditional procurement system, followed by management
oriented (18%) and integrated procurement systems (12%). It was also found that 65.5% were
public sector projects while 34.5% were private sector projects. Table 2 gives a summary of
the responses collected in the survey, categorized according to the particular procurement
strategy used for the projects and a weighted mean average that indicates how each of the
client's objectives performed in the different procurement systems and overall in the Project
Performance Index (PPI).
Table 2 suggests that overall, in terms of total aggregate performance levels, the integrated
procurement method was perceived to provide clients with the best project outcomes, followed
by the management oriented and lastly, by the traditional method of procurement. In terms of
client criteria, it was found that integrated methods of procurement achieved the best overall
outcome in five key areas of time, cost, quality, sustainability and environmental
considerations.
Table 2. Average PPI Scores based on Client Criteria distributed by Procurement Methods
Procurement
Method
Time Cost Quality H&S Susta-inability Environmental
Considerations
PPI
(AHP Weights) 0.281 0.329 0.164 0.086 0.086 0.055
Traditional 6.94 7.37 7.71 7.73 7.33 6.94 7.314
Integrated 7.73 8.00 8.55 8.36 8.64 8.18 8.117
Management
Oriented
7.56 7.31 8.25 8.44 8.06 7.81 7.733
Average Scores 7.41 7.56 8.17 8.18 8.01 7.64
Source: Researcher
4.4 Relationship between the Level of Client’s Knowledge and Project
Performance
The level of the client’s knowledge and experience of project procurement systems were
plotted against their corresponding Project Performance Index (PPI) according to the
procurement methods used and illustrated in Figures 1 to 3, while the test of correlation of the
relationship between client’s knowledge and PPI is presented in Table 3.
116
Table 3. Pearson Relationship between PPI and Client Knowledge distributed by Procurement Methods
Variable R calculated d.f. R tabulated Significance
Traditional Procurement 0.366** 60 0.325 0.01
Integrated Procurement 0.872*** 9 0.872 0.001
Management Oriented System 0.535* 14 0.514 0.05
Source: Researcher
Table 3 shows that the knowledge of the client as a procurement system factor are significantly
and positively related to project performance. However, this knowledge has a more significant
level of relationship in the integrated procurement system followed by the traditional
procurement and then management oriented procurement system. Further interrogation of the
data collected (see Figures 1-3) also show that a positive relationship exists between the
knowledge of the client and project performance within the different procurement systems. The
slope of the trend line suggests that the more the clients’ knowledge of procurement system,
the higher is the project performance. Figure 2 also shows that 77% of the change in the project
performance within projects procured through the integrated methods of procurement is
explained by changes in Clients’ knowledge levels.
4.5 Discussion of Findings
The survey findings suggest that cost is the highest weighted construction project performance
criteria, followed by time and cost; and that the traditional procurement systems is frequently
used on projects in South Africa. Furthermore, integrated procurement systems provide clients
with the best overall project outcomes; and that there is a significant positive relationship
between the clients’ knowledge of procurement systems and project performance within the
different procurement systems. However, the integrated procurement system shows the best fit
between clients’ knowledge levels and project performance. Findings of this study align with
previous studies by Rwelamila and Meyer (1999), Grobler and Pretorius (2002) and Mbanjwa
and Basson (2003), who found that Southern Africa utilizes traditional procurement more often
than other procurement systems, followed by management oriented and integrated systems. It
also aligns with earlier studies that consider time, cost and quality as key project performance
criteria (see Bowen et al., 1999; Brown & Adams, 2000; Chan et al., 2002; Ng et al., 2002).
Figure 1: Relationship between level of Client’s knowledge and PPI in Traditional
procurement systems
y = 0.5419x + 2.6171R² = 0.1336
0
2
4
6
8
10
0 2 4 6 8 10
Pro
ject
Per
form
ance
In
dex
(P
PI)
Client's Level of Knowledge
117
Figure 2: Relationship between level of Client’s knowledge and PPI in Integrated
procurement systems
Figure 3: Relationship between level of Client’s knowledge and PPI in Management oriented
procurement systems
In addition, the results of this study confirm the results of previous studies such as Masterman
(1992), Love et al. (1998) and Windapo and Rotimi (2012), that there is a relationship between
project success and factors such as clients’ knowledge levels and their ability to communicate
their needs, which would influence the selection of an appropriate procurement method. There
were no previous studies that considered whether the level of knowledge possessed by a client
influences project performance, which are key findings of this study.
5 Conclusion
This study examines the procurement systems frequently used on construction projects in South
Africa and whether clients’ knowledge of procurement systems influence project performance.
The study found that traditional procurement is the most frequently used procurement system
on projects in South Africa and that the clients’ knowledge of procurement system is
significantly and positively related to project performance and project performance has the best
fit with client's knowledge level within the integrated procurement system. Based on these
findings, it can be concluded that the client’s limited knowledge of procurement systems in
South Africa, influence their selection of inappropriate procurement systems in project
delivery, despite the emergence of more efficient procurement systems. It is therefore
recommended that clients should make better-informed decisions, in order to increase the
chances of successful project outcomes. The research conducted is limited to projects in South
y = 1.0617x - 0.9814R² = 0.7721
0
2
4
6
8
10
0 2 4 6 8 10
Pro
ject
Per
form
ance
In
dex
(P
PI)
Client's Level of Knowledge
y = 0.7522x + 1.4965R² = 0.286
0
2
4
6
8
10
0 2 4 6 8 10
Pro
ject
Per
form
ance
In
dex
(P
PI)
Client's Level of Knowledge
118
Africa and therefore, caution should be taken when generalizing the findings and conclusions
drawn to another context.
6 Acknowledgement
The authors would like to acknowledge with thanks, the assistance of the following people in
conducting the survey and interviews: Tinotenda Jeketera, Mishara Naidoo and Yudish
Sumputh.
7 References
Alhazmi, T., and McCaffer, R. (2000). Project Procurement System Selection Model. Journal
of Construction Engineering and Management, 126(3), pp.176-184.
Bowen, P., Pearl, R. and Edwards, P. (1999). Client briefing processes and procurement
method selection: A South African study. Engineering, Construction and Architectural
Management, 6(2), pp.91-104.
Brown, A. and Adams, J. (2000). Measuring the effect of project management on construction
outputs: a new approach. International Journal of Project Management, 18(5), pp.327-335.
Chan, A. (2000). Evaluation of enhanced design and build system – a case study of a hospital
project. Construction Management and Economics, 18(7), pp.863-871.
Chan, A., Scott, D. and Lam, E. (2002). Framework of Success Criteria for Design/Build
Projects. Journal of Management in Engineering, 18(3), pp.120-128.
cidb, (2011). Construction quality in South Africa; A client perspective. Pretoria: cidb.
cidb, (2014). The cidb Construction Industry Indicators: Summary Results. Construction
Industry Indicators. Pretoria: cidb.
Chartered Institute Of Building (CIOB) (2010). Procurement in the construction industry 2010.
Berkshire: The Chartered Institute of Building.
Cooperative Research Centre (CRC) (2008). Building Procurement Methods. CRC
Construction Innovation. Brisbane: Icon.Net Pty Ltd.
Grobler, K. and Pretorius, L. (2002). An Evaluation of Design-Build as a Procurement Method
for Building and Civil Engineering Projects in South Africa. Journal of the South African
Institution of Civil Engineering, 44(1), pp.13-19.
Kumaraswamy, M. and Dissanayaka, S. (1998). Linking procurement systems to project
priorities. Building Research & Information, 26(4), pp.223-238.
Lam, E., Chan, A., and Chan, D. (2003). Why is Design-Build Commonly Used in the Public
Sector? An Illustration from Hong Kong. AJCEB, 3(1), p.53.
Love, P., Skitmore, M. and Earl, G. (1998). Selecting a suitable procurement method for a
building project. Construction Management and Economics, 16(2), pp.221-233.
Luu, D., Thomas Ng, S. and Chen, S. (2003). A case-based procurement advisory system for
construction. Advances in Engineering Software, 34(7), pp.429- 438.
Masterman, J. (1992). An Introduction to Building Procurement Systems. London: E & FN
Spon.
Mathonsi, M., and Thwala, W. (2009). Investigation of Factors That Influence the Selection of
Procurement Systems of the South African Construction Industry. CIDB Paper 13.
Mathonsi, M. D, and Thwala, W. D (2012). Factors influencing the selection of procurement
systems in the South African construction industry. African Journal of Business
Management, 6(10).
Mbachu, J., and Nkado, R. (2006). Conceptual framework for assessment of client needs and
satisfaction in the building development process. Construction Management and
119
Economics, 24(1), pp.31-44.
Mbanjwa, S. and Basson, G. (2003). The Use and Effectiveness of Construction Management
as a Building Procurement System in the South African Construction Industry. Master of
Science (Project Management). University of Pretoria.
Mfongeh, N. (2010). The constraints of using design and build for the procurement of
construction projects in South Africa. Master’s degree. University of the Witwatersrand.
Molennar, K., Songer, A. and Barash, M. (1999). Public Sector Design/Build Evolution and
Performance. Journal of management engineering, 15, pp.54-62.
Ng, T., Luu, D. and Chen, S. (2002). Decision Criteria and Their Subjectivity in Construction
Procurement Selection. AJCEB, 2(1), p.70.
Ratnasabapathy, S., and Rameezdeen, R. (2010). A Decision Support System for the Selection
of Best Procurement System in Construction. Built-Environment Sri Lanka, 7(2).
Rwelamila, P. and Meyer, C. (1999). Appropriate or Default Project Procurement Systems?
Cost Engineering, 41(9).
Thwala, W., and Mathonsi, M. (2012). Selection of Procurement Systems in the South African
Construction Industry: An Exploratory Study.
Windapo, A. and Rotimi, J. (2012). Determining project performance criteria and key
procurement methods in Nigeria: Client's perspective. Joint CIB W070, W092 & TG72
International Conference on Facilities Management, Procurement Systems and Public
Private Partnership - Delivering Value to the Community. Emerald, pp.250 - 259.
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Determinants of Building Construction Costs in South
Africa A Windapo, S Odediran, A Moghayedhi, A Adediran and D Oliphant
Department of Construction Economics and Management, University of Cape Town,
Rondebosch, 7701, Cape Town, South Africa.
E-mail: abimbola.windapo@uct.ac.za
Abstract:
Completing projects within cost is the target of most clients on any construction project.
However, the achievement of this desire is just an imagination in the construction industry,
because procurement and execution environments for projects are hostile and unpredictable.
This study examines the determinants of building construction costs in South Africa and
whether changes in the cost of certain resource factors such as construction equipment, labour
and materials can be related to changes in building construction costs. The study employs a
longitudinal cross-sectional quantitative research design approach and makes use of literature
review and historical data obtained from institutional and governmental databases to identify
the determinants. The data collected were analysed using time series analysis to confirm the
trends in the cost of the resource factors and its alignment to the changes in building
construction cost. After that, it makes use of an appropriate predictive modelling tool or causal
analysis in establishing the determinants of construction cost. The results show that the price
indices of construction equipment (EI), labour (LI) and materials (MI) have a gentler slope
when compared with the Building Cost Index (BCI). It also emerged that later levels of the
BCI are significantly and positively related to EI. The findings infer that the key determinant
of increase in building construction costs in South Africa is equipment costs. Contractors and
public or private sector clients in South Africa must utilize construction equipment optimally
on projects, and these pieces of equipment should not be left idle on project sites or plant yards.
Appropriate provisions should be made of equipment utilization policies which allow the joint
ownership of equipment by contractors to mitigate the problems of cost increases. There are
widely unexamined assumptions as to what resource factors are responsible for the growth in
building construction costs in South Africa. Also is the similar high risk and uncertainty
affecting the South African construction industry as a result of these fluctuations. The results
of the study extend the knowledge of the resource factors responsible for building construction
costs increases.
Keywords:
Construction Equipment, Cost data, Labour, Materials, South Africa
1 Introduction
It is the desire of every client to achieve value for money on any construction project. This
desire is often not met on most projects because of the unforeseen events and unpredictable
factors influencing costs of projects at the planning and development stages. This study,
therefore, examines factors that determine the cost of a construction project in South Africa. It
also investigates whether the change in the cost of construction resources influences the trends
in building costs. The outcome of this study informs contractors and public and private clients
of the likely level of increases in the cost of construction work, to predict future changes in the
costs of construction projects. Hence, the paper presents in Section 1 an introduction, outline,
and rationale of the study to readers. Section 2 describes a critical review of the literature on
121
the drivers of construction cost. Chapter 3 discusses the method employed in collecting the
data reported in the paper, while Section 4 outlines the findings emanating from the data
analyzed and the results were related to the existing knowledge on drivers of construction costs.
Section 5 presents the conclusions drawn from the results and highlights future research.
2 Identification and Review of Construction Cost Drivers
Construction costs are the portion of hard costs usually associated with the construction
contract, including the cost of materials, the labour and equipment costs necessary to put those
elements in place. Overhead costs, which include both job site management and the contractors'
standard cost of doing business are added to this.
Theoretical underpinning and constructs of the notable drivers of cost of construction work
proposed in this research are aligned to the findings of previous studies by Odediran and
Windapo (2014); American Institute of Architects (2013); Olatunji (2010); Skitmore et al.
(2006); Lowe et al. (2006); Sawhney et al. (2004), Ng et al. (2000); Akintoye et al. (1998);
Fitzgerald and Akintoye (1995); Chau (1990); Eastman (1986); and Snyman (n.d). Based on
literature review (see Tables 1 and 2), the drivers of construction costs are classified into –
Resource factors (labour, material and plant); Project factors (competition intensity, profit
margin, overhead cost, space available for construction, management skills provided, type of
structure/design and construction methods used); Macroeconomic factors (demand and supply
of construction work, finance or loan cost, inflation, transportation costs, energy costs,
exchange rates and fuel price); construction work items (excavation, concrete work, formwork,
reinforcement work, mechanical, electrical and plumbing installation etc.); and stakeholder
requirements (professional fees and transaction costs).
Table 1: Resources Factors Based on Previous Studies
Resource
Factors
Relevant studies No.
Cited Odediran &
Windapo (2014)
Skitmore et
al. (2006)
Sawhney et
al. (2004)
Eastham
(1986)
Snym
an
(n.d.)
Labour ✓ ✓ ✓ ✓ ✓ 5
Materials ✓ ✓ ✓ ✓ 4
Equipment/
Plant ✓ ✓ ✓ ✓ 4
Sub-
contractors
✓ 1
Source: Researcher
Table 2: Project Factors Based on Previous Studies
Project Factors Relevant studies No.
Cited Skitmor
e et al.
(2006)
Sawhne
y et al.
(2004)
Akintoy
e (2000)
Fitzgerald
&
Akintoye
(1995)
Eastham
(1986)
Snyman
(n.d.)
Contracting
practices
✓ ✓ 2
Location ✓ ✓ 2
Size of project ✓ ✓ 2
Contract/project
duration
✓ ✓ 2
Tender period ✓ ✓ 2
122
Quality of market
information
✓ ✓ 2
Bargaining
Power of Unions
✓ ✓ 2
Variations in
materials
✓ 1
Labour
Productivity
✓ 1
Equipment Usage ✓ 1
Weather ✓ 1
Soil conditions ✓ 1
Quality standards
expected
✓ 1
Anticipated use ✓ 1
Overhead cost ✓ 1
Degree of
competition
✓ 1
Method of
construction
✓ 1
Site constraints ✓ 1
Source: Researcher
The focus of this study will be of the contribution of resource factors to the cost of construction.
Resource elements are the inputs used in the production process to produce an output – the
final building or infrastructure product in development. According to Odediran and Windapo
(2014); Skitmore et al. (2006); Sawhney et al. (2004); Eastham (1986); and Snyman (n.d),
resource factors contributing to the cost of construction work in no particular order, are cost of
construction equipment, labour, building materials and specialist sub-contractors. Building
materials and materials will be used interchangeably in this paper.
3 Research Methodology
There are significant numbers of earlier studies either on cost forecasting or prediction in South
Africa (Bowen, 1993; Snyman, 1989a; Snyman, 1989b; Bowen and Edwards, 1985; and
Bowen, 1980). Historical cost data are mostly used for the purpose of predicting the future
levels of construction costs as they provide trends in prices and reliable information than
macroeconomic variables (Smith, 1995; Tysoe, 1981). This study examines resource factors –
construction equipment, labour and building materials that are established in the literature. The
study determines the relationship between the cost of these resource factors and construction
costs and adopts a longitudinal cross-sectional survey research design in data collection.
A desk-top study that employs data collection methods involving data mining in achieving the
research aim. The determinants of construction costs were established using historical
information obtained from institutional and government databases (Stats SA, Bureau of
Economic Research (BER)/Medium-Term Forecasting Associates (MFA) archives. The
data/indices obtained were after that analyzed using descriptive tools to confirm the trends in
the construction cost and after that, a predictive modelling tool or causal analysis to establish
the determinants of building construction costs. Ashuri and Lu (2010) noted that the causal
methods assume that the independent explanatory variables determine the variables to be
predicted in the form of regression models. Ruddock (2008) acknowledged that regression and
correlation are usually considered together in expressing a relationship between two variables.
Simple or linear regression finds straight-line hypothesized relationships only, and
mathematically represents this as equation (1):
123
= + b (1)
Where b = slope of the line of best fit (estimate/regression line)
= values of the independent variable (that is resource factors in this study)
= values of the (hypothesized) dependent variable (that is BCI in this study)
= -intercept/constant
The Building Cost Index (BCI), which is a measure of the trends in the estimate of the cost
required to complete a construction project, were used in the study as a measure of the growth
in building construction cost. While the indexes of the resource factors – labour, material, and
equipment, were used as a measure of the cost of the resource factors. The Labour Cost Index
(LI) is a measure of the trends in the all-in-rate (payroll taxes and profits) of the skilled workers
obtained from Department of Trade and Industry (Dti) records. The Building Material Price
Index (MI) is a measure of the trend in changes in the prices of volatile construction materials.
The indicator of building materials price trends used in this study is obtained from the published
Building Materials Production Price Index available in the Stats SA archive. Also, the Plant
Cost Index (EI) is used to measure the change in plant costs on a quarterly basis, is made up of
construction equipment/plant hire rental (Stats SA, 2010).
According to Dysert (2008), regression modelling is a mathematical representation of cost
relationships that provide a logical and predictable correlation between the physical or
functional characteristics of a project (plant and process system) and its resultant cost. The
process of regression modelling, therefore, lends itself towards the course of finding the
significance between independent variables that have direct effects on a dependent variable, a
contextual environment, which is typified by the construction process. Advantages of
regression modelling for estimating purposes is the provision of efficiency regarding
developing estimates in a shorter period. Linking quantitative inputs to algorithms to provide
quantitative outputs, often allows two estimators to come to the same conclusion regarding
cost, and it is flexible as it allows a range of independent input variables that have been derived
from historical data (Black, 1984).
4 Findings and Discussion
Historical data collected from BER/MFA data and analyzed is presented and discussed in the
following sub-sections.
4.1 Trends in Historical Cost Data for Construction Costs and Resource Factors
The study sought to know descriptively, the trends in the historical cost data for construction
costs and the resource factors (construction equipment, labour, and building materials) in South
Africa. The results of this inquiry are presented in Figures 1 and Table 3.
Table 3. Distribution of Building Cost, Labour, Material and Equipment Indices by Year (2010-
2015)
Date Building Cost
Index (BCI)
Normalized
Labour Index (LI)
Normalized
Material Index (MI)
Normalized
Equipment Index (EI)
2010Q1 145,7 174,5 216,5 188,3
124
2010Q2 144,8 176,4 218,3 187,9
2010Q3 142,0 177,8 218,9 186,7
2010Q4 142,4 178,6 219,9 186,7
2011Q1 140,8 181,2 223,3 186,0
2011Q2 149,2 184,5 225,5 187,9
2011Q3 147,8 187,4 228,3 189,2
2011Q4 156,7 189,4 230,5 187,9
2012Q1 153,3 191,8 233,1 185,9
2012Q2 156,1 193,2 234,5 186,5
2012Q3 161,4 194,1 235,5 187,4
2012Q4 164,9 194,3 236,7 188,2
2013Q1 171,0 197,3 239,5 189,8
2013Q2 165,7 198,7 240,8 191,5
2013Q3 173,3 200,3 242,9 194,9
2013Q4 171,8 201,1 244,9 196,8
2014Q1 179,2 203,3 247,1 198,7
2014Q2 186,6 205,3 249,0 200,3
2014Q3 191,2 206,8 249,9 200,8
2014Q4 194,3 207,0 250,7 200,6
2015Q1 198,2 207,7 250,5 202,2
2015Q2 186,3 210,4 250,5 202,8
2015Q3 196,2 212,0 250,9 203,6
2015Q4 197,0 212,4 247,3 208,2
Source: BER/MFA Data (2016)
Table 1 and Figure 1 compares the trends in Building Cost Index (BCI), Construction
Equipment Index (EI), Labour Index (LI) and Material Index (MI). The result shows that the
indices of equipment, labour, material have a gentler slope when compared with BCI. MI has
a wider differential when compared to BCI. While the EI and LI have smaller differentials
when compared to BCI, the growth rate of MI and LI are proportional except for the growth
rate of EI which is not uniform over the years. There was an overlap in the growth rate of LI
and EI in the year 2011 and 2012, meaning that the indices are to some extent unrelated.
Moreover, the BCI, LI, and EI grew proportionally showing that they have the same growth
rates.
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Figure 4: Comparing the Trends in Material, Labour, Equipment Indices and the BCI
4.2 Multiple Regression between BCI, LI, MI and EI
Further investigation was undertaken to find out whether there is any significant relationship
between BCI (dependent variable) and LI, MI and EI (independent variables) using multiple
regression analysis. Table 4 shows the results of the multiple regression analysis at 95%
confidence level between BCI, LI, MI and EI4.
Table 4 demonstrates that:
The correlation between Building Cost Index (dependent variable) and Labour Index,
Materials Index and Equipment Index (independent variable) is very high (0.961556313)
means 96% correlation – the combined changes in labour, materials, and equipment indices
explains 96% of the changes in BCI;
Significance Value of Error is minuscule (2.56297E-14) meaning that the error is not
significant; and
At 95% confidence level the P value of the intercept is 1.85276E-07<0.05, Labour Cost is
0.855670171>0.05, Materials Cost is 0.08363076>0.05 and Equipment Cost is
0.000101165<0.05. The P values of the intercepts mean that the constant values of the
intercept and Equipment cost are significant, but Labour cost and Materials Cost are not
significant.
The relationship between BCI and the resource factors can be modeled as BCI = -298,06 +
1,25*EI.
Table 4. Multiple Regression between Building Cost Index, Labour Index, Material Index
and Equipment Index (95%)
Regression Statistics
Multiple R 0,98
R Square 0,96
Adjusted R
Square
0,96
Standard Error 4,17
Observations 24
0
50
100
150
200
250
300
Degree 2: BER Building Cost Index
Normalized index of material
Normalized Index of Labour
Normalized index of equipment
126
ANOVA
df SS MS F Significance F
Regression 3 8689,86 2896,6
2
166,75 2,56297E-14
Residual 20 347,43 17,37
Total 23 9037,29
Coeffici
ents
Standa
rd
Error
t-Stat P-value Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -298,06 38,40 -7,76 1,85276E
-07
-378,17 -217,96 -378,17 -217,96
Labour 0,10 0,52 0,18 0,855670
171
-0,99 1,18 -0,99 1,18
Material 0,87 0,48 1,82 0,083630
760
-0,13 1,86 -0,13 1,86
Equipment 1,25 0,26 4,83 0,000101
165
0,71 1,78 0,71 1,78
Source: Researcher
Based on these findings, it can be inferred that a unit increase in the price of equipment will
lead to 25% increase in the cost of building construction. However, there was no significant
relationship between building construction cost and the cost of materials and labour.
5 Conclusion and Further Research
The primary objective of any pricing regime should be to ensure that there is an efficient
allocation of resources and an understanding of the indicators and drivers that will aid decision
making, in managing cost related to the construction sector. This study examines the
determinants of building construction costs in South Africa and whether changes in the cost of
certain resource factors such as construction equipment, labour and materials can be related to
changes in building construction costs. Overall, the research observed that although there is a
gradual increase in construction cost, this is not increasing proportionally with inflation and
that there is a significant positive relationship between construction costs and equipment costs
when historical cost data are analyzed. It also emerged that a unit increase in the price of
construction equipment will yield 25% increase in building construction cost. Based on these
findings, it can the study concludes that equipment use is a major determinant of building
construction costs in South Africa and that increases in equipment costs will yield
proportionally significant increases in construction costs.
Based on these findings, the study recommends that contractors and public or private sector
clients in South Africa must utilize construction equipment optimally on projects, and these
pieces of equipment should not be left idle on project sites or plant yards. Appropriate
provisions and policies should be made to allow the joint ownership of equipment by
contractors to mitigate the problems of cost increases. The study also proposes that further
research is undertaken using actual construction projects in validating the results obtained in
this study.
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6 Acknowledgement
This paper is a product of a wider study into the Drivers of Construction Costs funded by the
Construction Industry Development Board/DPW in South Africa. The authors are grateful for
the contributions from both agencies.
7 References
American Institute of Architecture. (2013). Construction Costs. Retrieved from American
Institute of Architecture.:
http://www.aia.org/aiaucmp/groups/aia/documents/pdf/aiab097618.pdf
Akintoye, S.A., Bowen, P. and Hardcastle, C. (1998). Macro-economic leading indicators of
construction contract prices. Construction Management and Economics, 16, 159-175
Ashuri, B., & Lu, J. (2010). ‘Time Series Analysis of ENR Construction Cost Index’ ASCE
Journal of Construction Engineering and Management, 136(11), 1227-1237
Black, J. H. (1984). Application of parametric estimating to cost engineering. Association for
the Advancement of Cost Engineering.
Bowen, P A (1980). An investigation into the feasibility of producing an econometric cost
model for framed structures. Unpublished MSc (Construction Management) Thesis,
Department of Building, Faculty of Engineering, Heriot-Watt University, Edinburgh.
September.
Bowen, P A and Edwards, P J (1985). Cost modelling and price forecasting: practice and theory
in perspective. Construction Management and Economics, 3, 199-215.
Bowen, P A (1993) A communication-based examination of price modelling and price
forecasting in the design phase of the traditional building procurement process in South
Africa. Unpublished Ph.D. Thesis, Department of Quantity Surveying, University of Port
Elizabeth.
Bureau of Economic Research (BER) (2016). Building and Construction – First Quarter,
BER, Stellenbosch
Chau, K.W. (1990). On the estimation of the price trend and output growth rate of the Hong
Kong construction industry. Journal of Real Estate and Construction, 1, 46-59
Department of Trade and Industry (dti) (2011). Data. Retrieved March 01, 2012, from
dti.gov.za: http://www.dti.gov.za/econdb/cssrap/
Dysert, L. R. (2008). An Introduction to Parametric Estimating. Association for the
Advancement of Cost Engineering.
Eastham, R.A. (1986). Contractors’ perceptions of factors influencing tender prices for
construction works. M.Sc. thesis. Department of Surveying, University of Salford.
Fitzgerald, E., and Akintoye, A. (1995). The accuracy and optimal linear correlation of UK
construction tender price index forecasts. Construction Management and Economics, 13(6),
493-500.
Lowe, D. J., Emsley, M. W., & Harding, A. (2006). Predicting Construction Cost Using
Multiple Regression Techniques, ASCE Journal of Construction Engineering and
Management, 132(7), 750-758.
MFA (Medium-Term Forecasting Associates) (2016). Report on Building Costs: Second
Quarter 2016. Stellenbosch, South Africa.
Ng, S. T., Cheung, S. O., Skitmore, R. M., Lam, K. C., & Wong, L. Y. (2000). Prediction of
tender price index directional changes, Construction Management and Economics, 18(1),
843-852.
Odediran, S.J. and Windapo, A.O. (2014). Systematic review of factors influencing the cost
performance of building projects In Laryea, S., and Ibem, E. (Eds). In: Proceedings of 8th
128
Construction Industry Development Board (cidb) Postgraduate Conference, 10-11
February, University of the Witwatersrand, Johannesburg, South Africa, pp. 501-520.
Olatunji, O.A. (2010). The impact of oil price regimes on construction cost in Nigeria.
Construction Management and Economics, 28, 747–759
Ruddock, L., (2008) Approaches to Economic Modelling and Analysis, In Knight A and
Ruddock L (eds.) Advanced Research Methods in Built Environment, Wiley-Blackwell:
The United Kingdom, pp.51-62.
Sawhney, A., Walsh, K.D. and Brown IV, A. (2004). International comparison of cost for the
construction sector: towards a conceptual model. Civil Engineering and Environmental
Systems, 21(3), 151-167
Skitmore, M., Runeson, G. and Chang, X. (2006). Construction price formation: Full-cost
pricing or neoclassical microeconomic theory? Construction Management and Economics,
24(7), 773-783
Smith, A.J. (1995). Estimating, Tendering, and bidding for construction: Theory and Practice,
Macmillan, London.
Snyman, G.J.J. (1989a). When is a recession not a recession? A somewhat lighthearted look at
the business cycle and forecasting. Juta’s South African Journal of Property, 5(1), 11-17.
Snyman, G.J.J. (1989b). How the business cycle influences building costs. Juta’s South African
Journal of Property, 5(3), 38-44.
Snyman, G.J.J. (n. d). Using knowledge of the business cycle to forecast building costs.
Building Economists, P O Box 7119, Stellenbosch, 7599, South Africa.
Stats Online, 2011, Key Indicators, Retrieved October 17, 2011, from
www.statssa.gov.za/keyindicators/keyindicators.asp
Tysoe, B.A. (1981). Construction cost and price indices: Description and use, E & F.N., Spon,
London.
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Influences of Cultural Differences on Construction Project
Delivery: A case of Gauteng Province Khotso Matobole, Oluwabukunmi Ogunsanya and Clinton Aigbavboa
Department of Construction Management and Quantity Surveying,
University of Johannesburg, South Africa.
Email: khotso55@gmail.com, kunmiayopo@gmail.com, caigbavboa@uj.ac.za
Abstract:
The Construction Industry is by nature one of the most diverse working environments. The
South African Construction Industry is not an exception to this rule. The Industry has witnessed
great diversity in its workforce mix at all levels since the return to democracy in 1994. Thus,
peoples from erstwhile segregated communities are brought together to work in achieving a
common project objective. The intricate influence of this cultural mix and the pressure it exerts
on the project teams’ ability to deliver on its mandate is the motivation for this study. This
paper provides insight into the influence of culture and cultural difference on teams working
together towards project delivery. The study adopts a mixed method approach by use of
interviews and questionnaires through a convenience sampling of construction professionals in
the Gauteng Province, South Africa. Findings from this research confirm that factors such as
sociability, masculinity, power, equity, individualism, avoidance, collectivism are cultural
dimensions prominent in multicultural teams. The influences of cultural aspects that rank
highest are irritation due to misunderstanding, encouraging team building, motivating workers
to work harder. The study concludes that while a lot has been done in integrating project teams
from different cultures in the South African construction industry efforts should be
concentrated on mitigating the effect of masculinity and irritation due to misunderstanding. It
is recommended that Project Managers and Construction managers should more sensitive to
the influence of cultural dimensions and deploy cultural awareness and appropriate leadership
styles in mitigating its effects while channeling the positive influences towards organizational
benefits. This research has provided insight into intrinsic cultural dimensions among
construction industry workers in the Gauteng Province of South Africa and provides useful
policy input for the Construction Industry Development Board and industry practitioners at
large. The research is limited to the experiences of Construction Industry professionals in the
Gauteng Province of South Africa due to the constraint of time.
Keywords:
Construction, Contractors, Culture, Projects
1 Introduction
South Africa's construction industry has become widely diverse especially following the
adoption of democracy in 1994. Effective tools like the Broad-Based Black Economic
Empowerment have assisted in the diversifying the construction sector hence the researchers,
Thwala & Khumalo (2009), argue that it is unlikely not to have multicultural construction
professional teams in a contractor firm in South Africa. Cultural differences within a contractor
firm are important as these can help establish a working environment that offers mutual respect,
understanding, support as well as the appreciation of individuals and their contributions
(Emuze and James, 2013). Jiang and Pretorius (2011) acknowledged that cultural differences
have an effect on communication which in turn influences various project management
functions such as negotiations, team building, conflict resolutions as well as other contract
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processes. Also, Jiang and Pretorius (2011) further illustrated that cultural differences can
affect various project management procedures and practices and that effective team
management of the cultural differences is essential for project delivery.
There exists a fundamental link between culture and performance as well as the outcomes of a
construction project. Different cultures in a single environment have the ability to exert various
influences to the efficient management of the project. The influences of cultural differences
have a relationship with the leadership and teamwork of a project (Ogunsanya, Aigbavboa and
Thwala, 2015). With that said, adverse influences of cultural differences could also ultimately
assist in project delivery because lessons are learnt and people overcome their culture shock.
Culture shock occurs when people migrate into a foreign culture (Greg and Larson, 2003) and
become mentally puzzled by the cultural dimensions of that foreign culture.
Also, the first objective of any project is to fulfil the needs of the customer or client. Knutson
and Bitz (1991) define Project Management as the execution of systematic processes such as
planning and scheduling; controlling the project and its expenditure; decision making; and
management of resources to produce an end product. Project management has become a critical
component in the successful management of the human resource and thus, the management of
cultural differences within a construction project. A fundamental phenomenon common to all
cultures is the communication aspect, which is a significant contributor towards effective
project management and ultimately, the accomplishment of a project. Successful projects are
the core attributes of a successful construction company.
Despite the aforementioned, Ochieng and Price (2010) believe that there is a lack of empirical
information to conclude that cultural factors influence projects. Thus, earlier studies by Thwala
and Khumalo (2009), Jiang and Pretorius (2011), Emuze and James (2013), and Ogunsanya,
Aigbavboa and Thwala (2015), have studied different aspects of culture in the construction
industry in South Africa. However, the gap is in identifying the attributes that influence cultural
relationships in the industry the most at the project level. This is the gap this paper seeks to fill.
The aim of this study is to identify cultural factors that influence human relationships and to
investigate the influence of cultural differences on construction projects in the Gauteng
Province in South Africa. The paper undertakes a critical review of literature on culture and
cultural differences, cultural models and its dimension to the management of cultural
differences. Thus, progresses to use a mixed method design to ascertain construction
professional experience of identified features in the literature and concludes with a
recommendation for project managers and industry practitioners.
2 Literature Review
2.1 Culture and Cultural Differences
Culture is a vastly complex aspect of people’s daily lives and thus it remains difficult to
conclude its exact meaning. Numerous researchers have their own connotations as to what
culture means although it remains a vivid concept. Trompenaars and Hampden-Turner (1998)
define culture as the collective ways in which groups of mutually understanding people
interpret the society and the world as a whole. Chan and Tse (2003) suggested that the essence
of culture is the systematic beliefs, views, practices, rules, behaviour, perspectives as well as
worldviews shared within a society and it has been carried down from generation to generation
ultimately becoming a norm. Goffee and Jones (1996) mention that culture is an outcome of
how people relate to one another. It surrounds us and shapes our vision of the world and how
we interact with it. Culture is a major determinant of human behaviour because each culture
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tends to distinguish itself from another based on background, beliefs, values and reactiveness
to certain situations. Thus, it was observed that different societies may have different manners
of adopting and reacting to situations (Hofstede et al., 2010). It is from this standpoint that
South Africa can be investigated through several criteria such as location. The locations of
construction projects are vital in terms of cultural diversity to be encountered. As different
places within the country have different cultures due to the environment, historical
circumstances and standard of living experienced by the people.
Projects are the mobilizers of the human resource. Quite often, projects bring individuals and
companies together to complete a shared task. In most of these cases, the persons who come
together are from various and different cultural backgrounds (Rees-Caldwell and Pinnington,
2013). Many authors have explored the impacts of cultures towards projects and project
management systems but have frequently snubbed the internal influences on the people, which
ensure project delivery. Meng (2012) argues that project delivery can be vastly affected the
state of workmanship (whether poor or good). The human resource plays a vital role in the
production of any project and any mismanagement of this resource cause various delays, cost
overruns and other critical effects (Atkinson, 1999).
2.2 Cultural Models
Culture according to Hofstede (2005) can be portrayed through 3 layers of mental
programming. The 3 layers are: Individual, Collective and Universal. Hofstede illustrated the
theory by a pyramid as shown in Figure 1.
Figure 1: Hofstede’s Levels of mental programming (Hofstede, 2005)
The theory of Hofstede Mental Programming entails that the Individual level is the exclusive
personality which each person possesses. The Collective level is the obtaining of culture
through learning from specific groups of people while the Universal level is about the
inheritance of cultures through human nature such as survival instincts, etc. (Hofstede, 2005).
Culture is separated through many notions which have become stereotypes to some groups of
people. According to Gray and Larson (2003), it is “those notions that bind people together
thereby establishing common identities amongst them”.
Individual
Collective
Universal
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Edward Hall, in the year 1976, developed a rendition of culture in the Cultural Iceberg Model.
This model shows that a vast percentage of an individual's culture is implicit and unseen while
a minor proportion is explicit and observable. Hall (1976) Iceberg’s Model is illustrated in
Figure 2. Hall's research uncovered that the crucial aspects of culture in society are hidden
beneath the explicit culture seen daily, and thus, cultural dimensions are learnt.
2. 3 Cultural Dimensions
Hofstede (1984) shows that organisations are the biggest receptors of diverse cultures. Study
by Goffee and Jones (1996) identifies four culture types which are found in an organisation,
namely: Networked, Communal, Fragmented and Mercenary. In the research, two cultural
dimensions which are Sociability and Solidarity were identified. Sociability has its root in the
word social, and it means that the dimension has a lot of verbal, emotional and personal
interaction whereby people share certain aspects of themselves. The value of this dimension is
that the information is shared freely, there is a high sense of teamwork, and there is freedom of
expression which tends to spark creativity in return. In contrast, Solidarity is much more formal
and experienced in business setups. It renders a business relationship where one does what is
required of them to achieve a goal. This form of cultural dimension is based solely on creating
professional relationships designed to achieve a particular common purpose. This particularly
shows that Network culture has high sociability and low solidarity, the Communal culture is
high in sociability as well as solidarity. A Fragmented culture is low in both sociability and
solidarity, and lastly, the Mercenary culture is high in solidarity and low in sociability.
Furthermore, Hofstede (1983) derived four organisational-related cultural dimensions. The
initial dimension is Individualism vs. Collectivism which states that in an individualist societal
system people are more selfish and look after their self-interests. In these societies, individuals
were found having loose ties between one another. In contrast, the collective societal system
promotes togetherness with much stronger links between the people. This phenomenon
happens to such a degree that individuals pair themselves into unified groups (Hofstede, 1983).
The second dimension is Power Distance which is the acceptance and expectance of power
inequality. It shows that in an organisation there are powerful members and not so powerful
members. This meant that people accepted and expected inequality in the way power was
distributed. In an organisation, this occurs in the organisation structures and the positions
Surface Culture:
Explicit,
Easily Distorted,
Objective.
Deep Culture:
Implicit,
Not Easily Distorted,
Subjective.
Figure 2: Edward Hall’s Cultural Iceberg Model (Hall, 1976)
133
within the structures (Hofstede, 1983). The third dimension is Uncertainty avoidance. It
measures people's tolerance for ambiguous situations. This, however, is not risk avoidance
(Hofstede, 2011). Uncertainty avoidance is the level at which people are anxious and uncertain
of unstructured situations apparent. By avoiding, people tend to develop stringent behavioural
codes, laws and rules which become the norm (Hofstede, 1983). The fourth dimension
Hofstede came up with was Masculinity vs. Femininity which is a societal aspect. It entails the
division of genders in society whereby being a male is associated with masculinity and being
a female is associated with being feminine. Nevertheless, a masculine society is one that values
assertiveness, performance and accomplishments and a feminine society is one that’s modest
and values emotion and caring for others (Hofstede, 1983).
Hofstede later added to the four dimensions introducing the fifth and sixth dimensions. The
fifth being Long-Term vs. Short-Term Orientation which shows how societies or organisations
exhibit perseverance and a realistic future-oriented perspective on what the future may hold
rather than portraying a conventional and historical point of view (Hofstede, 2011). Indulgence
vs. Restraint focuses on people's state of happiness. This dimension shows the degree to which
people possess/don't possess a natural desire to enjoy life and have fun. Indulgence as a
characteristic expresses a sense of control of one's life, and restraint expresses strictness and a
perception of being helpless. A Restrained person conforms to the norms of society, and
everything else lies out of their control. (Hofstede, 2011). Hofstede's Cultural Dimensions have
been utilised from to time to time to measure various aspects of businesses and their human
resource, and each dimension has an index to which it is used as a scale in organisations to
evaluate the factors of cultures which are impacting the organisation on a daily basis.
2.4 Relationship between cultural differences and project performance
There is sufficient evidence in Literature that suggests a link between the two in that the cultural
factors such as the cultural dimensions can influence changes in behaviour and thus
productivity of staff. Maphosa (2015) argue that cultural differences do have a significant
influence on the way a project is executed. Ankrah (2007) further emphasised that the
involvement of different cultures (cultural dimensions) towards project performance can result
in various levels of performance encountered due to the unique nature of projects. Jin, Horii
and Levitt (2004) found that 40% of projects with cultural problems show poor performance.
Cultures control people's thoughts, actions and behaviours therefore in multicultural teams
within a construction project, people get to establish new relationships which can provide
positive contributions to the project regarding knowledge sharing, innovation, alternative
dispute resolutions, etc. Although, there must be thought and consideration for
misunderstandings and other negative impacts of multicultural teams (Ogunsanya et al., 2015).
There may be resentments and aggression between the cultures which can impact productivity,
efficiency and overall performance of the project.
Teams achieve construction project delivery through effective project management of cultural
differences amongst other factors. Project delivery and cultural differences have a mutual
relationship which is exposed in a study by Sumner and Slattery (2010) through team processes.
Team processes constitute the cultural characteristics of a construction project team, and the
processes manifest through the following: reliance (trusting one another in the team),
communication, problem-Solving, gratitude and mutual Goals. Overall, a construction project
primary internal operations are made up of the above team processes within the team. The
relationship of the cultural differences can also affect the contract procedures that are in place
134
for the project. The following literature identifies the methods available to the construction
industry to successfully manage cultural differences to complete the project.
2.5 The Management of Cultural Differences
2.5.1 Culture Caution and Awareness
Culture is increasingly becoming a critical issue on construction projects. The project
management role requires a high level of professional expertise and awareness of the cultural
influences and theories. Many construction companies are suffering from the plight of cultural
differences affecting their projects (Jiang and Pretorius, 2011). An initial step to managing
cultural differences is being aware of the cultures that exist in the company/ project, cultural
similarities and differences and the issues which are affecting the culture at that moment.
2.5.2 Management and Teamwork
The successful completion of a construction project depends heavily on the effectiveness of
the management systems in place. Evidently, the cultural differences encountered on every
project have an effect on the system (Kivrak et al., 2009). According to Kivrak et al. (2009)
the management of cultural differences should vary by the nature of the project. Although, the
authors also mentioned that maintaining good communication and building trust with workers
is imperative. The management of projects is therefore very crucial. In a typical construction
project, the top management would usually comprise of the Project Manager, who leads the
projects along with other men who are co-managers. The co-managers form part of
management as these have a contribution to the project and the decision-making.
2.5.3 Leadership style
Leadership styles are associated with the abilities of how people interrelate with the human
resources from whom performance is expected. This includes the relations of Client-Project
Manager, Project Manager- Co-managers, and Co-managers-employees. These leadership
styles, according to Goetsch and Davis (2006), are autocratic leadership, democratic leadership,
participative leadership, goal-oriented leadership, and situational leadership. The leadership
styles mentioned above are easily influenced by culture as well as other macro-economic
factors such as politics. According to Khumalo & Thwala (2009), the team leader must possess
sound understanding and awareness of cultural differences to lead the team in a productive
manner. Various cultural influences can impact on the choice of leadership style in construction
projects.
3 Research Methodology
The Mixed method research explores the schools of thought of both the Qualitative research
and the Quantitative research (Bryman and Bell, 2007). This approach came about as there was
a need to fill up the gaps of one research method (i.e. Qualitative) with some aspects or tools
from another research method (i.e. Quantitative). Creswell (2013) suggests that the mixed
method is of transformative nature which tends to transform certain designs or approaches
mostly from qualitative research to quantitative research. This study is of a social nature in that
it aims to investigate cultural differences and its various influences on construction project
delivery. Therefore, the mixed method design was adopted. The reason is that the study focuses
how respondent in the real world view their environment and obtains observation of how the
respondents feel about cultural differences and their influences to construction project delivery.
135
Sampling is a process of selecting a set of respondents who will act as representatives of the
entire population. According to Fridah (2002), a population is a set of people, in this case,
construction project professionals in the Gauteng province (N), which samples were drawn
from for a measurement of an investigation. The notion is that the sample's data can be used to
draw a conclusion about the population. According to the Construction Industry Development
Board (CIDB) registrar, the number of active Building Contractors in Gauteng (Grades 7-9)
are 199 (CIDB, 2015), while active Building Contractors in Johannesburg (Grades 5-9) are 52
(CIDB, 2015). For the purpose of this study, the contractors with a grade 7 status and above
were used. Hence the target population is 199 contractors. The choice of contractors from
grades 7-9 is because they are larger with more employees and the effect of cultural differences
would tend to be more observable as opposed to Grades 1-6. This study used the non-
probability sampling technique, particularly the convenience sampling due to the constraint of
time and cost.
4 Findings and Discussion
Results shows that out of the 42 usable questionnaires returned, the respondents’ demographics
are 24% - Black, 26% - Colored, 24% - White and 12% either Indian or Asian. Likewise, 17%
of the respondents were Construction project managers, 40% - Quantity Surveyors, 19% - Site
Engineers, 19% - Foremen and 5% others. From the analysis of data, 66% of the respondents
agree that different cultures in a project are more likely to create constructive relationships
while 34% of the respondents think otherwise. Having identified through literature that the
cultural dimensions experienced by multicultural project teams are diverse. Table 1 shows the
ranking of the respondents of these cultural dimensions in Gauteng Province.
Table 1: Cultural Dimensions experienced in multicultural project teams
Cultural Dimensions experienced in multicultural project
teams MIS SD RANK
High Sociability 3.738 3.873 1
Masculinity 3.571 3.847 2
Power distance 3.333 3.578 3
Equality 3.310 2.966 4
Individualism 3.190 2.702 5
Avoidance 3.143 3.847 6
Collectivism 3.143 3.286 6
Indulgence 3.095 3.507 7
Low Sociability 3.000 3.507 8
Femininity 2.643 3.578 9
MIS = Mean Item Score; SD = Standard Deviation
Furthermore, based on the ranking using the mean item score (MIS) and the standard deviation
(SD) for the findings suggest that the dominant cultural dimensions are: high sociability
(MIS=3.378; SD=3.873; RANK=1), masculinity (MIS=3.571; SD=3.847; RANK=2), power
(MIS=3.333; 3.578; RANK=3), equality (MIS=3.310; SD=2.966; RANK=4), individualism
(MIS=3.190; SD=2.702; RANK=5).
The interview findings reveal that different cultures will bring about more interaction between
the colleagues especially when there is a willingness to learn from one another. Contrary, other
participants showed that culture can bring about conflicts and frustrations caused by power and
136
some people being above others. These findings are similar to the results of Goffee and Jones
(1996), where a high sense of teamwork was experienced with the high sociability cultural
dimension. The results are also in agreement with Hofstede's (1983) findings where
masculinity, power distance and individualism were identified as some of the dimensions that
regulate cultural relationships amongst people and teams. Furthermore, the findings show that
equality is one of the major factors of cultures which influence relationships in construction
projects. This is not in agreement with Hofstede's (1983) as this is related to power distance
which implies that there always lies an expectance and acceptance of inequality within teams
in a construction project. Table 2 below reveals the respondents ranking of the influences of
cultural dimensions on a construction project.
Table 2: Influences of Cultural Dimensions
MIS = Mean Item Score; SD = Standard Deviation
The influences of these cultural dimensions vary in many instances. The findings observed that
the dominant influences are: causes irritation due to misunderstandings (MIS=3.476;
SD=3.782; RANK=1), encourages team building (MIS=3.476; SD=3.715; RANK=1),
motivates workers to work hard (MIS=3.429; SD=3.647; RANK=2), encouraging strictness of
management (MIS=3.381; SD=3.286; RANK=3).
Interview findings show that the dominant influences are the misunderstandings and
misconceptions as well as the demand for respect increases. Furthermore, there is also a sense
of mutual understanding within the teams. These influences are closely related to the findings
of Trompenaars & Hampden-Turner (1997) of the cultural factors which influence the business
industry, particularly the universalism vs. particularism and the internal vs. external control.
There is an alignment between the findings from the interviews and those from the
questionnaire administered as is observable from the above. Thus, the interviews confirm the
findings from the questionnaire survey. Having identified these factors effective management
of cultural dimensions is suggested according to the identified options discussed earlier. Project
Managers and industry practitioners will have to manage with culture awareness, team
development process and adequate leadership styles that reflects the needs of the time.
5 Conclusion
Influences of Cultural dimensions MIS SD RANK
Causing irritation due to misunderstanding 3.476 3.782 1
Encouraging team building 3.476 3.715 1
Motivating workers to work hard 3.429 3.647 2
Encouraging strictness of management 3.381 3.286 3
Inspiring discipline among workers 3.333 3.912 4
Enhancing worker productivity 3.333 3.782 4
Creating mutual understanding 3.333 3.130 4
Enhancing commitment of workers 3.310 3.912 5
Improving the achievement status 3.310 2.966 5
Creating support and involvement in one anothers lives 3.286 3.847 6
Encouraging cooperation in the project team 3.167 4.219 7
Affecting emotional expressions 3.000 3.912 8
Improving ascribed status 2.857 3.847 9
137
The findings from this study showed that the cultural factors such as high sociability,
masculinity and power were the top three cultural dimensions influencing people’s cultures in
the study environment. Furthermore, the influences of the cultural dimensions showed that the
misunderstandings due to irritation, team building, motivation for hard work, strictness of
management, inspiring of discipline to workers and the empowering of worker productivity
were the top six influences of the cultural dimensions and people’s individual cultures amongst
construction workers in Gauteng.
The study concludes that the understanding of cultural differences on construction projects will
lead to the improving of the understanding of different cultures, resolving conflicts efficiently,
promoting mutual understanding on the project, promoting efficient transfer of knowledge
throughout the whole project team, promoting the learning of new languages, alternative
dispute resolution negotiations as well as negotiations of contracts in the projects.
It is therefore recommended that project managers and construction managers should be
sensitive to note these cultural dimensions at play on their project teams and should also seek
to meaningfully attenuate the negative influences of cultural dimensions while promoting its
positive influence. It is also recommended that the use of appropriate leadership styles would
help project managers in handling multicultural teams. Thus, study provides useful planning
and management insight to managers and stakeholders in the construction industry towards the
attainment of greater team effectiveness and project delivery.
6 References
Ankrah, N.A. (2007). An Investigation into the Impact of Culture on Construction Project
Performance. PhD Thesis. University of Wolverhampton, United Kingdom.
Atkinson, A. R. (1999). The Role of Human Error in Construction Defects. Structural Survey,
17(4), pp. 231 – 236.
Bryman, A. and Bell, E. (2007). Business Research Methods. 2nd Edn., Oxford University
Press, Oxford.
Chan, E.H and Tse, R. Y. (2003). Cultural Considerations in International Construction
Contracts. Journal of Construction engineering and Management, 129(4), pp. 375 – 381.
Construction Industry Development Board (2015), Statistics and Register of Contractors.
Available online at https://registers.cidb.org.za/PublicContractors/Reports. Accessed 27
August 2015.
Creswell J.W. (2013). Research Design: Qualitative, Quantitative and Mixed method
approaches. Sage Publications.
Emuze, F and James, M. (2013) Exploring Communication Challenges Due to Language and
Cultural Diversity on South African Construction Sites, Acta Structilia, 20(1), pp. 44-65.
Fridah, M. (2002), Sampling in Research. Available Online at
https://www.uonbi.ac.ke/fridah_mugo/files/mugo02sampling.pdf. Accessed 4 May, 2015.
Goetsch,D.L and Davis, S.B. (2006). Quality Management: Introduction to Total Quality
Management for Production, Processing and Services, Pearson Prentice Hall.
Goffee, R and Jones, G. (1996). What Holds the Modern Company Together? Harvard
Business Review, 74 (6), pp. 133 -135.
Gray C. and Larson, E. (2003). Project Management: The Managerial Approach. 2nd Edn.,
McGraw-Hill, Irwin.
Hall. E.T. (1989). Beyond Culture. Anchor Books. California.
Hampden-Turner, C. and Trompenaars, F. (1997). Riding the Waves of Culture. London:
Nicholas Brealey.
138
Hofstede, G. (2011). Dimensionalizing Cultures: The Hofstede Model in Context, Online
Readings in Psychology and Culture, 2(1), p. 8.
Hofstede, G., Hofstede, G.J., Minkov, M (2010). Cultures and Organizations: Software of the
Mind. 3rd edn. McGraw-Hill Professional, New York. pp. 576.
Hofstede, G. (2005). Cultures and Organizations: Software of the Mind. 2rd edn. McGraw-Hill
Professional, New York.
Hofstede, G. (1984). National Cultures and Corporate Cultures. Communication between
Cultures. Belmont. CA: Wadsworth.
Hofstede, G. (1983). The Cultural Relativity of Organizational Practices and theories. Journal
of International Business Studies, pp. 75-89.
Jin, Y., Horii, T and Levitt, R.E. (2004). Modelling and Analysing Cultural Influences on
Project Team Performance. Proceeding of the NAACSOS conference at Carnegie Mellon
University, 2004.
Jiang, D and Pretorius L. (2011) Cross Cultural Communication Behaviour in International
Engineering Projects: Chinese and South African Perspectives. South African Journal of
Industrial Engineering, 22(2), pp. 54-67.
Khumalo, J and Thwala, W. (2009). The Effects of Different Cultural Backgrounds on
Teamwork on Construction Sites. Construction Industry Development Board, Paper 23.
Kivrak, S. Ross, A. and Arslan, G. (2009). Impacts of cultural differences on project success
ın construction. In: Dainty, A.R.J. (Ed) Proceedings of 25th Annual ARCOM Conference,
7-9 September 2009, Nottingham, UK, pp. 53-61.
Knutson J. and Bitz, I. (1991) Project Management: How to Plan and Manage Successful
Projects. New York. AMACOM.
Maphosa, S.G. (2015). The Impact of Cultural Differences on Construction Project
Performance. M. Ing. Thesis. Department of Engineering management, University of
Johannesburg.
Meng, X. (2012). The Effect of Relationship Management on Project Performance in
Construction. International Journal of Project Management, 30(2), pp. 188-198.
Ochieng, E and Price, A. (2010). Managing Cross Cultural Communication in Multicultural
Construction Project Teams: The Case of Kenya and the UK. International Journal of
Project Management, 28 (5), pp. 449 – 460.
Ogunsanya, O.A., Aigbavboa, C.O. and Thwala, W.D., (2015). Achieving Synergy through
Multi-cultural Project Teams. Proceeding of Fourth Construction Management Conference,
Port Elizabeth, South Africa. 29 November – 1 December, 2015. pp. 326 -334.
Rees-Caldwell, K and Pinnington, A.H. (2013). National Culture Differences in Project
Management: Comparing British and Arab Project Managers Perception on Different
Planning Areas, International Journal of Project Management, 31(2), pp. 212 – 227.
Sidumedi, K.S. (2010). An Investigation into the relationship between corporate culture of the
South African Construction Firms and Performance. M.Sc. Thesis. University of
Witwatersrand, Johannesburg, South Africa.
Sumner, M and Slattery, D. (2010). The Impact of Leadership Effectiveness and Team
Processes on Team Performance in Construction. International Journal of Construction
Education and Research, 6(3), pp. 179-201.
139
Effects of Material Waste Causes on Cost Overrun in
Abuja, Nigeria: A Project Planning Stage Perspective Ibrahim Saidu and Winston Shakantu
Department of Construction Management,
Nelson Mandela Metropolitan University, Eastern Cape, Port Elizabeth, South Africa,
Email: s214344924@nmmu.ac.za, Winston.shakantu@nmmu.ac.za
Abstract: Material wastage and cost overruns are global problems affecting construction projects. These
problems occur at different stages of a project, from planning, design, estimating, and
construction to project completion. The purpose of this paper is to examine the effects of
material waste causes and their control measures on project-cost overruns at the planning stage
of a project. The quantitative approach was adopted in this study. Interviews were purposively
conducted with thirty (30) construction professionals’ in Abuja from which a structured (tick-
box) questionnaire was ticked/marked by the researcher in the course of the interviews. The
results of the tick-box questionnaire were the ‘only data’ utilised in this research and were
analysed using the descriptive (cross-tabulation) and inferential method. The paper found that
material waste causes and their control measures have significant effects (very-high, high,
medium, low, and very-low) in causing or minimising cost overruns at the planning stage of a
project. It is recommended that management of material waste and cost overrun should be
revised based on the findings of this research as a reference document and included as part of
the pre-contract planning process for a project.
Key words:
Control measures, Cost overruns, Material waste, Project-planning stage
1 Introduction
Cost overruns and material waste are global problems which make it difficult for many
construction projects to be completed within their budget (Saidu & Shakantu, 2015; Ameh&
Itodo, 2013; Abdul-Rahman et al., 2013; Nagapan et al., 2012). Studies from different parts of
the world have shown that material waste from the construction industry represents a relatively
large percentage of the production costs. Thus, poor management of materials and waste leads
to an increase in the total cost of building projects (Ameh & Itodo, 2013). The problems of
material waste and cost overrun are occasioned by several causes at different stages of projects.
These include: the planning stage, estimating stage, design and design management stage, as
well as the construction stage. Identification of these causes at different stages and the
application of relevant control measures to minimise their occurrence is a step towards
alleviating the consequences (Mou, 2008; Oladiran, 2009; Nagapan et al., 2012; Saidu &
Shakantu, 2015).
Material waste is a problem requiring urgent attention in the construction industry. For
instance, Ameh & Itodo (2013) highlighted that in every 100 houses built in Nigeria, there is
sufficient waste material to build another 10 houses. Also, 10% of materials delivered to sites
in the UK end up as a waste that may not be accounted for (Osmani, 2011). Similarly, cost
overrun is a lingering problem which plague the construction industry for decades; and the
argument on how to reduce or totally remove it from projects has been ongoing among the built
environment professionals, project owners and the users for the past seventy years (Apolot et
140
al., 2010; Allahaim & Liu, 2012), but there is no substantial improvement nor significant
solution in mitigating its detrimental effects (Allahaim & Liu, 2012). Consequently, Ameh &
Itodo (2013) believed that building material wastage on construction sites accounts for cost
overruns. And this is as a result of the fact that, most managers of construction projects pay
little attention to the effects of material waste generated on cost overruns.
Many studies have been conducted in this field, for instance, Tam et al. (2007); Ameh & Itodo
(2013); Saidu & Shakantu (2015); Saidu & Shakantu (2016a); Saidu & Shakantu (2016b).
However, there is still a need for research that provides an empirical assessment of the material-
waste causes and the material waste control measures that have effects on cost overruns at the
planning stage of a project. In this line, Saidu & Shakantu (2016a) used a desktop methodology
/ literature review to examine the relationship between the material waste causes and those of
cost overruns at the pre-contract and the post-contract stages of projects. The study
recommended further study that would focus on the collection of empirical (field) data on these
issues in the construction industry. This recommendation led to the development of the problem
posed in this study that the empirical study on the effects of material waste causes and their
control measures on cost overruns at the planning stage of a construction project is suboptimal.
On this basis, this paper reports the findings of an empirical investigation on the effects of
material waste causes and their control measures on cost overruns at the planning stage of a
construction project.
2 Material Waste and Cost Overruns
Construction waste is generally classified into two main classes, namely: the physical waste
and the non-physical waste (Nagapan et al., 2012). The material waste comes from the
physical construction waste. This is the waste from construction, renovation activities,
including civil and building construction, demolition activities, and roadwork. It is, however,
referred by some directly as solid waste (Saidu & Shakantu, 2015). This type of waste
consists of material waste for recovery (re-use and recycling) or complete loss of materials
for landfill disposal (Saidu, 2016).
Conversely, the cost overrun comes from the non-physical construction waste which normally
occurs during the construction process. By contrast with material waste, the non-physical waste
relates to time overruns and cost overruns for a construction project. Ma (2011) defines waste
as not only associated with wastage of materials, but also to other activities such as repair,
waiting time, and delays.
Saidu & Shakantu (2015) emphasised that since the term ‘construction waste’ entails both the
physical and the non-physical waste, there is a relationship between material waste originating
from physical waste and cost overruns from the non-physical waste, since they both emanate
from the same waste family.
Saidu & Shakantu (2016a) highlighted through a desktop research that all the causes of material
waste also lead to cost overrun at the pre-contract and the post-contract stages of a project.
However, 96.9 percent and 81.8 percent of the causes of cost overrun also cause material waste
at the pre-contract and post-contract stages respectively. There is an 86.7 percent overlap
between the causes of material waste and those of cost overruns at all stages of a project. Other
causes which are not related are mostly, the micro-economic and macro-economic factors.
141
Furthermore, the material waste causes that are similar to the causes of cost overruns at the
planning stage of a project over the years, by different authors, and in different geographical
locations are presented in Table 1.
Table 1. Relationship between the causes of material waste and those of cost overruns at the planning stage of a
project
Sn
Causes of material
waste that are similar
to the causes of cost
overruns
Material Waste Cost overruns
Author and date Geographi
cal
location
Author and date Geographic
al location
1 Improper planning Babatunde (2012);
Nagapan et al. (2012)
Nigeria;
Batu,
Malaysia
Zewdu & Aregaw
(2015); Allahaim &
Liu (2012);
Ethiopian
projects;
Saudi Arabia
2 Over estimation to
accommodate variations
Nguyen et al. (nd);
Odusanmi, Oladiran &
Ibrahim (2012)
Geelong,
Australia;
Nigeria
Ahiaga-Dagbui &
Smith (2014);
Zewdu & Aregaw
(2015)
UK;
Ethiopian
projects
3 Lack of legislative
enforcement
Nagapan et al. (2012) Malaysia Allahaim & Liu
(2012)
Saudi Arabia
4 Inadequate site
investigation
Osmani et al. (2008);
Nagapan et al. (2012)
UK;
Malaysia
Subramani et al.
(2014); Chiktara
(2011)
India; India;
Turkey
5 Inadequate scheduling Nagapan et al. (2012) Batu,
Malaysia
Subramani et al.
(2014)
India
6 Poor communication
flow among members
Okorafor (2014);
Nagapan et al. (2012)
South
Africa;
Malaysia
Abdul Rahman et
al. (2013)
Malaysia
7 Improper co-ordination
of the entire project and
professionals
Al-Hajj & Hamani
(2011); Nagapan et al.
(2012)
UAE;
Malaysia
Abdul Rahman et
al. (2013); Zewdu
& Aregaw (2015)
Malaysia;
Ethiopian
projects
8 Unsatisfactory budget
for waste management
Al-Hajj & Hamani
(2011)
UAE Jackson (2002) Reading
9 Insurance problem Osmani (2011) UK Allahaim & Liu
(2012);
Saudi Arabia
10 Communication error
between client and
designer
Okorafor (2014);
Nagapan et al. (2012)
, South
Africa;
Malaysia
Abdul Rahman et
al. (2013)
Malaysia
11 Frequent demand for
design change
Osmani et al. (2008);
Nagapan et al. (2012)
UK;
Malaysia
Abdul Rahman et
al. (2013); Zewdu
& Aregaw (2015)
Malaysia;
Ethiopian
projects
12 Lack of awareness Okorafor (2014) South
Africa
Ameh Soyingbe &
Odusanmi (2010)
Nigeria
Source: Researcher
3 Research Methodology
The study covered building construction projects within Abuja, the Federal Capital Territory
of Nigeria. Abuja was selected because it is one of the metropolitan cities of Nigeria that has
the highest population of professionals within the built environment and has many on-going
construction projects.
Interviews were conducted with thirty (30) construction professionals (15 Project Managers
{PMs}, 9 Quantity Surveyors {QSs}, 5 Site Engineers {SEs}, and 1 Senior Technical Officer
{STO} of a waste management department) using purposive sampling technique on the issues
relating to material waste and cost overruns at the planning stage of a construction project. The
142
sample was purposive because only building-construction professionals (PMs, QSs, SEs and
STO) handling projects that are worth more than 1.6 billion Naira were consulted/interviewed.
Projects valued more than 1.6 billion Naira are likely to be handled by more experienced
professionals, who might be more familiar with the issues leading to material waste and cost
overruns than the projects of lesser value.
The research employed the use of ‘quantitative method’ that is rooted in the positivist research
paradigm. The research is quantitative because in the course of the interviews, a tick-box
structured questionnaire containing a lists of literature based information (waste causes and
control measures related to cost overrun) was ticked/marked by the interviewer / researcher, as
the respondents mentioned or commented on any of the issues in the tick-box questionnaire.
This was done to validate the literature based information by determining their frequencies of
occurrence. The results of the tick-box questionnaire were the ‘only research data’ utilised in
this study. Thus, the study must be quantitative rather than qualitative or mixed method
research.
The research employed the descriptive and the inferential analyses. The descriptive tool that
was used to analyse the data (tick-box structured questionnaire) was the cross tabulation
method. The results are presented in Tables 2 and 3. The responses from the tick-box
questionnaires are rated based on the cut-off points highlighted by Morenikeji (2006) in a five-
points Likert scale that, the material-waste causes and control measures that have percentage
of “90 to 100” are rated “very high effect”; 70 to 89% are rated “high effect”; 50 to 69% are
rated “moderate effect”; 30 to 49% are rated “little effect”; and 1 to 29% are rated “very little
effect” on cost overruns.
Inferentially, the analysis of variance (one-way ANOVA) was used to compare the means of
the results / views of the different respondents / professionals, to determine if there is a
statistically significant difference on the effects of material waste causes on cost overruns at
the planning stage of a building construction project. The interview guide is found on the
appendix page of this paper.
4 Findings and Discussion
This section presents and discusses the results of the tick-box questionnaires and ANOVA
analyses on the effects of material waste causes and their control measures on cost overrun at
the planning stage of construction projects
4.1 Material waste causes that have effects on cost overruns at the planning stage of
projects
It was apparent from Table 2 that the material-waste causes that have ‘very high effects’ (90-
100%) on project-cost overruns at the planning stage of a project were: (i) Inadequate site
investigation; (ii) poor communication flow among members; (iii) inadequate waste
management unit; (iv) improper planning of project risks; and (v) the lack of regular site
meetings at the planning stage. These results corroborate the findings of Le-Hoai et al. (2008),
Memon et al. (2010), Memon et al. (2011), Love et al. (2011), Flyvbjerg et al. (2004), Singh
(2009), and Allahaim and Liu (2013). They identified these issues as the major causes of cost
overruns in construction projects.
143
Coincidentally, the same results validate the findings of Babatunde (2012), Nagapan et al.
(2012), Osmani et al. (2008), Okorafor (2014), and many others on the causes of material waste
in the construction industry.
Percentages of 80, 73.3, 73.3 73.3, and 70 related to “improper co-ordination of the entire
project and professionals”, “improper planning”, “communication error between clients and
designers”, “inexperienced personnel / professionals in planning and waste management” and
“compliance with local authority in the case of local laws”, respectively, were deemed by the
respondents to have had ‘high effects’ in causing cost overruns; because they fall between 70
and 89 percent.
Conversely, the material waste causes that have very little effect on cost overruns were: (1)
improper plan for the establishment of a quality-control unit; (2) improper planning and
understanding of the method statement. These results are in line with the findings of
Malumfashi & Shuaib (2012) who highlighted ‘improper planning’ as one of the major causes
of project-cost overruns in the construction industry.
Table 2. Results of material-waste causes that have effects on cost overrun at the planning stage
Causes of material waste that have
effects on cost overrun at the
planning stage of a project
PM
QS
SE
ST
O
To
tal
Ra
nk
ing
Dec
ision
1 Improper planning 12 7 3 0 22 (73.3%) 7 High
2 Over estimation to accommodate
variations
2
0
0 0 2 (6.7%)
30 Very little
3 Lack of legislative enforcement 9 4 2 0 15 (50%) 13 Moderate
4 Inadequate site investigation 15 9 5 1 30 (100%) 1 Very high
5 Inadequate scheduling 8 4 1 1 14 (46.7%) 14 Little
6 Poor communication flow among
members
15 8 5 1 29 (96.7%) 2 Very high
7 Improper coordination of the entire
project and professionals
11 8 4 1 24 (80%) 6 High
8 Unsatisfactory budget for waste
management
11 5
3 1 20 (66.7%) 11 Moderate
9 Insurance problem 10 5 4 1 20 (66.7%) 11 Moderate
10 Poor plan for material standardization 3
1
0
0
4 (13.3%)
23 Very little
11 Inadequate waste management unit 13
9
5 1 28 (93.3%) 3 Very high
12 Improper plan for material waste re-
use & disposal
7
2
2 0 11(36.7%) 15 Little
13 Improper program of work 3 0 0 0 3 (10%) 27 Very little
14 Improper plan for site organization
and layout
5
2
1 0 8 (26.7%)
16 Very little
15 Lack of regular site meetings 14 9 4 0 27 (90%) 4 Very high
16 Liaise/compliance with local authority
in case of local laws
9
6
5 1 21 (70%)
10 High
17 Improper planning and understanding
of method statement
3
0
1 0 4 (13.3%) 23 Very little
18 Improper planning of project risks 14 9 3 1 27 (90%) 4 Very high
19 Lack of inclusion of waste
management in bidding process
0 0
1 0 1 (3.3%) 35 Very little
144
Source: Researcher
4.2 Material Waste Control Measures that have Effects on Cost Overruns at the
Planning Stage of a Project
It is apparent from Table 3 that the material waste control measures that have very high effects
in controlling cost overruns at the planning stage of a project were: (i) plan for early sub-soil
investigations; and (ii) proper co-ordination and communication among members at the
planning stage. The causes with high effects on cost overruns were: (a) establishment of a good
waste-management unit (b) regular site meetings (c) setting a target for material-waste
reduction; and (d) engaging experienced personnel in planning. The respondents believed that
adequate and early site/sub-soil investigation is needed for a project, in order to discover the
conditions and nature of the site, such as: the site topography, the water table, the soil-bearing
capacity, and the soil type, in order to reduce the risks of material wastage or additional cost
on the project. They also believed that “regular meetings” at the planning stage of a project
would help in supporting a free flow of communication among the members/professionals.
Conversely, the material-waste control measures that had very little effect on cost overruns
were: (1) proper insurance of work; (2) plan for the inclusion of waste management in bidding
and tendering process; and (3) re-improving process (learning from previous mistakes). These
are important measures for improving project performance at the planning stage of a project.
Learning from previous experience helps in solving the current problems. Hence, if these
measures are adopted as organisational policy, they would simplify other stages of a project.
These results support the conclusions of Abdul-Azis et al. (2013); and Brunes & Lind (2014)
on the organisational control measures for cost overruns in construction projects. These results
also confirm the findings of Saidu & Shakantu (2016a) who believed that material waste
control measures have effect in controlling cost overruns.
20 Improper plan for the establishment of
a quality control unit
5 0
0 0 5 (16.7%) 20 Very little
21 Inexperienced personnel in planning
and waste management
10 6
5 1 22 (73.3%) 7 High
22 Lack of re-improving process
(learning from previous mistakes)
2 0
1 0 3 (10%) 27 Very little
23 Poor harmonization of brief 2 1 2 0 5 (16.7%) 20 Very little
24 Poor knowledge of site conditions 1 2 0 0 3 (10%) 27 Very little
25 Cost related problems 1 3 0 0 4 (13.3%) 23 Very little
26 Improper plan for adequate staff
training and development
4 1
2 0 7 (23.3%)
18 Very little
27 Poor material estimation 3 1 0 0 4 (13.3%) 23 Very little
28 Lack of feasibility and viability
studies
4 1 1 1 7 (23.3%) 18 Very little
29 Inadequate identification of
construction techniques
0
1
0 0 1 (3.3%) 35 Very little
30 Plan for adequate site organization 4 3 1 0 8 (26.7%) 16 Very little
31 Improper plan for record of material
inventory
0
1 0 0 1 (3.3%) 35 Very little
32 Improper plan for adequate site
exploration
0
1 0 0 1 (3.3%) 35 Very little
33 Excess material delivery 0 1 0 0 1 (3.3%) 35 Very little
Client
34 Communication error between client
and designer
11 7
4 0 22 (73.3%) 7 High
35 Frequent demand for design change 4 1 0 0 5 (16.7%) 20 Very little
145
Table 3. The results of the material waste-control measures that have effects on cost overruns at planning stage
Source: Researcher
The material-waste control measures that started with the sign (*) in Table 3 were the newly
identified issues during the interview session with the respondents, which were not originally
in the interviewer’s/researcher’s tick-box questionnaire.
Control measures for material waste
that have effects on cost overrun at
the planning stage of projects
PM
QS
SE
ST
O
To
tal
Ra
nk
ing
Dec
ision
1 Plan for early sub-soil investigations 15 9 5 1 30 (100%) 1 Very high
2 Proper investment into waste reduction 6
3
3
0
12 (40%)
10 Little
3 Proper planning of construction
projects layout
6 5 0 0 11 (36.7%) 11 Little
4 Plan for inclusion of waste
management in bidding and tendering
process
2 2 1 0 5 (16.7%) 16 Very little
5 Enhance regulation execution of
related government departments
3 3 1 1 8 (26.7%) 12 Very little
6 Improved planning and scheduling 10 7 5 0 22 (73.3%) 5 High
7 Proper coordination and
communication
15 8 5 1 29 (96.7%) 2 Very high
8 Proper insurance 2 4 0 0 6 (20%) 15 Very little
9 Set a target for material waste
reduction
13 3 4 1 21 (70%) 7 High
10 Improve major project stakeholders’
awareness on resource saving &
environmental protection
2 1 0 0 3 (10%) 22 Very little
11 *Plan that will reduce frequent design
change
5 2 0 0 7 (23.3%) 14 Very little
12 *Plan for material standardization 3 2 0 0 5 (16.7%) 16 Very little
13 *Carrying design team along 2 1 0 0 3 (10%) 22 Very little
14 *Regular site meetings 14 7 5 0 26 (86.7%) 3 High
15 *Establishment of good waste
management unit
12 8 5 1 26 (86.7%) 3 High
16 *Re-improving process (Learning
from previous mistakes)
2 1 2 0 5 (16.7%) 16 Very little
17 *Legislative enforcement 11 5 1 0 17 (56.7%) 8 Moderate
18 *Adequate material waste estimation 4 1 0 0 5 (16.7%) 16 Very little
19 *Planning of project risks 9 3 3 0 15 (50%) 9 Moderate
20 *Proper harmonization of brief 3 0 2 0 5 (16.7%) 16 Very little
21 *Experienced personnel in planning 11 6 4 1 22 (73.3%) 5 High
22 *Identification of construction
technique
1 0 0 0 1 (3.3%) 27 Very little
23 *Feasibility and Viability studies 4 1 2 1 8 (26.7%) 12 Very little
24 *Buildability Analysis 3 0 0 0 3 (10%) 22 Very little
25 *Consideration of available
technology, resources and materials
3 2 0 0 5 (16.7%) 16 Very little
26 *Geophysical surveys 0 1 0 0 1(3.3%) 27 Very little
27 *interaction between different
designers (Architects and Engineer)
1 0 0 0 1 (3.3%) 27 Very little
146
4.3 Comparative Views of Respondents on the ‘Effects of Material Waste Causes and
Control Measures on Cost Overruns’ with respect to the Planning Stage of a Project
Table 4 shows the results of ANOVA analyses performed to compare the views of the
respondents (Project managers, Quantity surveyors, Site engineers and Senior technical officer)
on the ‘effects of material-waste causes and control measures on cost overruns’ at the of
planning stage of a project.
It was apparent from the analyses that the values of f-calculated (1.016 and 0.826) for the two
analyses (material waste causes and material waste control measures) were both less than the
f-tabulated value (1.701), respectively. The probability values (0.376 and 0.449) were both
greater than the 5 percent (0.05) significance level at 95 percent confidence level within the
mean-squared group of 4.11 to 4.18 and 6.16 to 7.45, respectively. The findings here are not
statistically significant (difference). These imply that the respondents have therefore the same
views on the effects of material waste causes and control measures on cost overruns at the
planning stage of construction projects in the industry.
Table 4. Test of differences in the professional views on the “effects of material-waste causes and control
measures on cost overruns”
Source: Researcher
5 Conclusion and Recommendations
Material waste and cost overruns are identified as global problems affecting the success of
many construction projects. These problems occur at different stages of a project, from
planning, design, estimating, and construction to project completion. The purpose of this paper
was to examine the effects of material waste causes and their control measures on cost overruns
at the planning stage of a project.
It was revealed from the literature that most material waste causes are similar to the causes of
cost overruns at different stages of projects and at different locations around the world.
It was found from the analyses that material-waste causes and their control measures were
identified to have significant (very-high, high, medium, low, and very-low) effects in
causing/controlling cost overruns at the planning stage of a project. Also, there was no
statistically significant difference in the views of the respondents on these issues. And so, the
respondents have the same views on the results of the effects of material-waste causes and
control measures on cost overruns at planning stage of a project.
S/n
Variables Type of
Analysis
Observation Inferences
𝑿𝟏 𝑿𝟐 𝑿𝟑 𝑿𝟒 Mean
squ
are
with
in
gro
up
F-cal F-tab Pro
bab
il
ity v
alue
Remark
1 PM QS SE STO One-way
ANOVA
4.18
4.11
1.016 1.701 0.376 Not
statistically
significant
(Difference)
Material waste causes that
have effects on cost
overrun
2 PM QS SE STO One-way
ANOVA
6.16
7.45
0.826 1.701 0.449 Not
statistically
significant
(Difference)
Material waste control
measures that have effects
on cost overrun
147
Based on these findings, it can be concluded that effective management of the identified
material waste causes at the planning stage of a project would translate into a reduction in the
level of cost overruns for projects. The study recommends that management of material-waste
causes should be encouraged, as it has the potential to minimise the rate of cost overruns for
projects. It is also recommended that management of material waste and cost overruns should
be revised based on the findings of this research as a reference document and included as part
of the pre-contract planning process for a project. Further research in this area can be conducted
to look at other stages of projects, most especially, the issues in the post contract stage.
6 References Abdul-Azis, A. A., Memon, A. H. Abdul-Rahmann, I. & Abd Karim, A. T. (2013), Controlling
Cost Overrun Factors in Construction Projects in Malaysia, Research Journal of Applied
Sciences, Engineering and Technology, 5 (8), PP. 2621-2629.
Abdul-Rahman, I., Memon, A.H. & Abd. Karim, A.T. (2013), Significant Factors Causing
Cost Overruns in Large Construction Projects in Malaysia, Journal of Applied Sciences,
13 (2), PP. 286-293.
Abdul-Rahman, I., Memon, A.H., Abdul-Azis, A.A. & Abdullah, N.H. (2013), Modeling
Causes of Cost Overrun in Large Construction Projects with Partial Least Square-SEM
Approach: Contractor's Perspective, Research Journal of Applied Sciences, Engineering
and Technology, 5(6) PP. 1963-1972.
Ahiaga-Dagbui, D.D. & Smith, S.D. (2014), Dealing with Construction Cost Overruns using
Data Mining, Construction Management and Economics, 32 (7-8), pp. 682-694.
Allahaim, F.S. & Liu, L. (2012), Cost Overrun Causes, the Framework in Infrastructure
Projects: Toward a Typology, Paper Presented at the 37th Annual Conference of
Australasian Universities Building Educators Association (AUBEA), Sydney, Australia,
4-6 July, University of Technology, Sydney, Edited Liu L.; Publisher: University of New
South Wales (UNSW), Sydney, pp. 1-15.
Al-Hajj, A. & Hamani, K. (2011), Material Waste in the UAE Construction Industry: Main
Causes and Minimisation Practices. Architectural Engineering and Design Management
(Heriot-Watt University Gate way), 7 (4), pp. 221-235.
Ameh, J.O. & Itodo, E.D. (2013), Professionals’ Views of Material Wastage on Construction
Sites, Organization, Technology and Management in Construction. An International
Journal, 5(1), pp. 747-757.
Ameh, O.J., Soyingbe, A.A. & Odusami, K.T. (2010), Significant Factors Causing Cost
Overruns in Telecommunication Projects in Nigeria, Journal of Construction in
Developing Countries, 15 (2), pp. 49–67.
Apolot, R., Alinaitwe, H. & Tindiwensi, D. (2011), An investigation into the causes of delay
and cost overrun in Uganda’s public sector construction projects. In: Mwakali, J. &
Alinaitwe, H. (Eds), Proceedings of the Second International Conference on Advances
in Engineering and Technology. 31 January – 1 February, Entebbe Uganda. Uganda:
Macmillan Uganda (Publishers) Ltd, pp. 305-311.
Babatunde, S.O. (2012), Quantitative Assessment of Construction Material Wastage in
Nigerian Construction Sites. Journal of Emerging Trends in Economics and Managent
Sciences 3 (3), pp. 238-241.
Brunes, F., and H. Lind. (2014), Policies to Avoid Cost Overruns: Critical Evaluation and
Recommendations. Working Paper, Section for Building and Real Estate Economics
Department of Real Estate and Construction ManagementCentre for Banking and
Finance (Cefin), School of Architecture and the Built Environment, Royal Institute of
Technology, Sweden, 2014, pp. 1-16.
148
Jackson, S. (2002), Project Cost Overruns and Risk Management. Paper, Whiteknights: School
of Construction Management and Engineering,The University of Reading.
Ma, U. 2011. No waste: Managing sustainability in construction. Surrey: Gower Publishing
Limited.
Mou, K. (2008), The Role of Government and Construction Waste. MSC Dissertation, The
Centre of Urban Planning & Environmental Management, University of Hong Kong,
Hong Kong, pp. 1-179.
Nagapan, S., Abdul-Rahman, I., Asim, A. & Hameed, A. (2012), Identifying Causes of
Construction Waste-Case of Central Region of Peninsula Malaysia, International
Journal of Integrated Engineering, 4 (2), pp. 22-28.
Nagapan, S., Abdul-Rahman, I. & Asmi, A. (2012), Factors contributing to physical and non-
physical waste generation in construction industry, International Journal of Advances in
Applied Sciences (IJAAS), 1(1), pp. 1-10.
Nguyen, B., Gupta, H. & Faniran, S. (n.d), Waste Minimization Strategiesin the Construction
Industry-A Geelong Case Study. Geelong, pp. 1-10.
Odusami, K. T., Oladiran, O. J. & Ibrahim, S. A. (2012), Evaluation of Materials Wastage and
Control in Some Selected Building Sites in Nigeria. Emirates Journal for Engineering
Research 17 (2), pp. 53-65.
Okorafor, C. (2014), An Empirical Investigation of Waste and Management Strategies Adopted
in the Construction Industry: A Case Study of the Tshwane Municipality. M.Tech
Dissertation, Department of Building Science, TSHWANE UNIVERSITY OF
TECHNOLOGY, PRETORIA, South Africa.
Oladiran, O.J. (2009), Causes and Minimisation Techniques of Materials Waste in the Nigerian
Construction Process. Fifth International Conference on Construction in the 21st
Century (CITC-V). Istanbul, Turkey, pp. 20-22.
Osmani, M., J. Glass, & A.D.F. Price. (2008), Architects ‘Perspectives on Construction Waste
Reduction by Design. Waste Management 28, pp. 1147–1158.
Osmani, M. (2011), Construction Waste. In: Letcher, T.M. & Vallero. D. (Eds). Waste: A
handbook for management. San Diego: Academic Press an imprint of Elsevier, 207-218.
Saidu, I.& Shakantu, W.M.W. (2015), A Relationship between Quality-of-Estimating,
Construction Material Waste Genration and Cost Overrun in Abuja, Nigeria. Fourth
Construction Management Conference, Nelson Mandela Metropolitan University, Port
Elizabeth, South Africa. Edited Emuze, F.A.; 95-104, 30 November-1st Dec., 2015.
Saidu, I. & Shakantu, W.M.W. (2016a), A Study of the Relationship between Material Waste
and Cost Overrun in the Construction Industry. The 9th cidb Postgraduate Conference
Cape Town, South Africa. “Emerging trends in construction organisational practices
and project management knowledge area. Edited Windapo, A.O.,124-134, Feb, 2-4,
2016.
Saidu, I. & Shakantu, W.M.W. (2016b), A Conceptual Framework and a Mathematical
Equaion for Managing Construction-Material Waste and Cost Overruns. World
Academy of Science, Engineering and Technology. International Journal of Social,
Behavioural, Educational, Economic, Business and Industrial Engineering, 10 (2), pp.
555-561
Subramani, T., Sruthi, P. S. & Kavitha, M. (2014), Causes of Cost Overrun In Construction.
IOSR Journal of Engineering (IOSRJEN) 4 (6), pp. 2278-8719.
Tam, V.W.Y., Shen, L.Y., & Tam, C.M. (2007), Assessing the Levels of Material Wastage
Affected by Sub-Contracting Relationships and Projects Types with their Correlations.
Building and Environment 42, pp. 1471–1477.
149
Zewdu, Z.T., & Aregaw, G.T. (2015), Causes of Contractor Cost Overrun in Construction
Projects: The Case of Ethiopian Construction Sector. International Journal of Business
and Economics Research, 4 (4), pp. 180-191.
150
An Assessment of Electronic Payment System among
SMEs in the Nigerian Building Industry Ibrahim AbdulHafeez1, Kabir Ibrahim2 and Tasiu Mustapha3
1Department of Building
Ahmadu Bello University, Zaria, Nigeria
E-mail: mscenv10656@gmail.com 2 Department of Construction Management
Nelson Mandela Metropolitan University, South Africa
Email: Ibrokb@yahoo.com 3Afribased Projects Ltd, Nigeria
Email: mustaphatasiu@yahoo.com
Abstract:
Most transaction in the Nigerian construction industry especially among small and medium
scale companies are done in cash. The study assesses electronic payment system in small and
medium sized construction companies with a view of enhancing adoption of electronic
payment system in the Nigerian building industry. The study adopted purposive sampling in
distributing. One hundred and thirty questionnaires among construction managers,
professionals, craftsmen and unskilled labourers on construction sites within Abuja Nigeria.
The use of E-Payment system was found to be low at the construction stage. The benefits of
adopting E-payment by the construction industry includes reduced risk of carrying cash,
improving transparency, reduction in corruption and time saving. Low level of literacy among
site operatives (semi-skilled and unskilled), low number of bankable site operatives, the high
level of ATM fraud, resistance to change and insistence on daily payment system are the most
highly ranked challenges of adopting E-payment system in the construction industry. This
study promotes adoption of IT in payment in the Nigerian construction industry. It will also
promote construction management among Small and Medium Sized construction contracting
firms in Nigeria and other developing countries.
Keyword:
E-Payment, Building Industry, Corruption, SME’s, Nigeria
1 Introduction
The construction industry plays a strategic role in the economy of many countries and is a
major development driver. The construction industry also provides a substantial source of
employment for professionals, artisans as well as unskilled labourers. All these categories of
labour in the industry are paid for the services they render. According to Business Dictionary
(2015), payment is a compensation or discharge for performance of an obligation or
reimbursement giving over something that is of satisfactory value to its recipient such as
money. Payment in form of wages and salaries are paid for labour in the construction industry.
Payments in the Nigerian construction industry are mostly made through exchange of direct
cash while paying site operatives of during purchase of equipment and materials to be used for
construction.
Advancements in information and communication technology (ICT) have influenced every
facet of life and has made it possible for changes in how industries and organizations work
151
today. Information technology has transformed subsistence societies into modernized societies.
The construction industry cannot ignore information technology. The industry has transformed
from paper, ink and pencil in designing to using computer programs like Building Information
Management (BIM), Auto CAD, and Revit. It is also experiencing changes from the traditional
paper-based process tendering to E- tendering (Oyediran and Akintola, 2011). One of the
changes the industry is also going through is making change electronic payment from cash
based payment.
Electronic cash is a system that allows individuals purchase goods or services without the
exchange of anything tangible. The term money still exists, but in an electronic form. The
Central Bank of Nigeria (CBN) in 2011 introduced the cashless policy which ensures efficient
and modern payment system is one of such which is geared to achieve the goal of being
amongst the top 20 economies by year 2020 (Vision 20: 2020). The policy through the
advanced use of information technology facilitates fund transfer. Developed countries of the
world, to a large extent, are moving away from paper payment instruments toward electronic
ones, especially payment cards.
According to Bankable Frontier Associates (2012), Nigeria has been grouped as a cash heavy
country. This and other reasons have led to the introduction of the cashless policy of the CBN.
The cashless policy of the CBN placed a daily withdrawal limits to N500, 000 for individuals
and N3million for corporate clients which is aimed at reducing (not eliminating) the amount of
physical cash (coins and notes) circulating in the economy and encouraging more electronic
based transactions. Nigerian Banks now offer new e-payment solutions which allow
instantaneous inter-bank fund transfers from various platforms like the mobile and internet.
Construction companies have been known to engage in transactions which are more than the
stipulated daily limits. The policy would have an impact in the performance of daily activities
of these companies and the industry as a whole. There have been reported cases of attacks and
robbery on construction site managers and professionals while carrying money to site to pay
operatives or while going to purchase equipment or materials with cash. This has led to the loss
of huge amount of money to be used for construction work and even loss of lives.
The construction industry in Nigeria has been accused of corruption. Where person in charge
of payment to site operatives (artisans and labourers) who are often paid in cash inflate the
number of people to be paid, thereby increasing the cost of construction and on the long run
reducing the profit margin to be earned by the company executing the project.
This study therefore assesses electronic payment system among SME’s in the Nigerian building
industry with a view to enhancing adoption of E-payment system and mitigating corruption in
the Nigerian building construction industry. The objectives are to; assess the level of adoption
of electronic payment system in the building industry in Nigeria and identifying the challenges
faced in adopting the electronic payment system in the Nigerian construction industry.
2 Literature Review
2.1 Construction Industry and Small and Medium Enterprise (SMEs)
Small and Medium Enterprises (SMEs) have been acknowledged worldwide as the catalysts
for rapid economic growth and sustainability. According to Azeez (2012), they are the driving
force behind job creation, income distribution and reduction of income disparities, export
earnings, poverty reduction, and wealth creation especially in developing economies. There are
152
different categories of small, medium and enterprises. Onugu (2005) classified SMEs in
Nigeria into Micro -with a labour size of not more than thirty (30) full-time workers and/or a
turnover of less than two million Naira (N2,000,000). Small with a workforce between eleven
(11) and seventy (70) full-time staff and/or with a turnover of not more than ten million Naira
(N10,000,000) in a year. And medium with staff strength of between seventy-one (71) and two
hundred (200) full-time workers and/or with an annual turnover of not more than twenty
million Naira (N20, 000,000).
According to the Nigerian Ministry of Labour and Industry micro enterprises have less than
ten (10) workers. Small enterprises have staff strength greater than ten (10) while Medium
enterprises have staff strength of greater than thirty (30). The Small and Medium Sized
Development Agency of Nigeria (SMEDAN) defines SMEs based on the following criteria: a micro
enterprise as a business with less than ten people with annual turnover of less than five million Naira, a
small enterprise as a business with 10-49 people with annual turnover of five to 49 million naira, while
a medium enterprise as a business with 50–199 people with an annual turnover of 50–499 million naira.
Globally, there is an increasing focus on small businesses as a key driver of economies and engine of
growth and development. Small businesses dominate the world business landscape and account for an
average of 98% of all enterprises in most economies (Azeez, 2012). Though it is difficult to obtain exact
and comparable figures on SMEs for developing countries, it is obvious that the role of SMEs is equally
important in the economies of developing and developed countries alike. It is important to note that
over 80% construction contracting firms in Nigeria are within the micro, small and medium
scale enterprises.
2.2 Electronic Payment Systems
Corruption has been identified as a complex, endemic, and multi-layered problem that threatens
the very existence of Nigeria and various efforts have been made by Nigerian government to
curb the menace. E-payment is the latest attempt initiated to curb corruption among other
objectives (Ayoola, 2013). Nigeria is cash based economy with retail and commercial
payments primarily made in cash. However, recent developments in information and
communication technology have influenced the role of money in economic activities. As a
result, we can now talk of electronic money and hence electronic banking.
According to Olanipekun et al. (2013), globally there is a shift from cash based transactions to
a cashless society because it has been seen as a more convenient method of payment and a
method of preventing crimes all the way from robbery of cash from individuals to the extent
of money laundering among crime syndicates and cash stockpiling at home by corrupt
government officials.
The adoption of information and communication technology in the banking sector is referred
to as electronic banking (e-banking) had a ripple effect in the Construction Industry in Nigeria.
The concept of electronic payment system in the construction industry started with the
introduction of the cashless policy of the Central bank of Nigeria even with the high volume
of active mobile phones in Nigeria, e payment system is still nascent. It is therefore imperative
to determine those factors that influence the rate of adoption
2.3 Cashless policy
In Nigeria, under the cashless economy concept, the goal is to discourage cash transactions as
much as possible. According to Omotunde et al. (2013) a cashless economy is an economy
where transaction can be done without necessarily carrying physical cash as a means of
153
exchange of transaction but rather with the use of credit or debit card payment for goods and
services. Cashless economy is not the complete absence of cash, it is an economic setting in
which goods and services are bought and paid for through electronic channels.
Cashless economy aims at reducing the amount of physical cash circulating in the Nigeria
economy and thereby encouraging more electronic–based transaction. The cashless society
envisioned and discussed herewith refers to the widespread application of computer technology
in the financial system. Some aspects of the functioning of the cashless economy are enhanced
by e-finance, e-money, e-brokering and e-exchanges. These all refer to how transactions and
payments are effected in a cashless economy. The Cash-Less Nigeria Policy was introduced
among other reason to reduce high security and safety risks, foster transparency and curb and
corruption/leakages (Shonubi, 2012)
Some of the ways transactions will be consummated under the new dispensation include the
following: (i) Automated Teller Machine (ATM): ATMs can be used for balance enquiry, cash
withdrawal, cash deposit, funds transfer and bill payment; (ii) Mobile Banking/Payments:
banking can be conducted from the convenience of mobile phones. It can be used for balance
enquiry, funds transfer, and bills payment; (iii) Internet Banking: Instant balance enquiry, funds
transfer, and other transactions can be made. Most banks require their customers to have a
token device for internet banking services. This is to give maximum security for internet
banking applications; (iv) Point-of-Sale (POS) Terminals: POS terminals allow customers to
receive card payments for sale of products and services. It also allows customers to make
commission from sales of third party products and services (e.g., recharge cards, bill payments,
etc); (v) Electronic Funds Transfer: Money can be transferred electronically from one account
to another.
2.4 Benefits of E-payment
Akhalumeh (2012) assert that the most significant benefit of the e-payment is reducing the risk
of carrying cash as that is easily amenable to armed robbery, theft and misplacement.
Omotunde et al. (2013) added that E-payment policy will increase employment; reduce cash
related robbery thereby reducing risk of carrying cash; cashless policy will also reduce cash
related corruption and attract more foreign investors to the country
E-payment will reduce high risk of cash handling which encourages robberies, thefts and other
cash related crimes; and curb inefficiencies and corruption which thrives through multiple
systemic leakages (Ayoola, 2013). According to Lamikanra (2012), the benefits of a cashless
society include shorter transaction timelines, increased transaction possibilities and
convenience, reduction in robberies since banks and individuals carry less cash, money trails
become obvious and traceable. The other benefits include increased convenience, more service
option, reduced risk of cash related crimes and access to credit, faster access to capital, reduced
revenue leakage and forestall the inherent risk in dealing with cash such as armed robbery,
theft, bribery and corruption.
3 Research Methodology
Research questionnaire was designed and administered to construction managers,
professionals, craftsmen and unskilled labourers on construction sites within Abuja Nigeria.
The field survey was carried out in Abuja. It was chosen because high rate of construction
activities and high concentration of professionals. A purposive sampling technique was used
154
in selecting the respondents. A structured interview was also undertaken with artisans who
can’t fill the questionnaire.
In view of the fact that the central limit theory states that a sample size of thirty (30) and above,
is large enough for any research work (Dawdy and Wearden, 1985). The total number of
questionnaires administered was One hundred and thirty (130). A total of 130 questionnaires
were sent for data collection out of which 98 were returned, giving a response rate of 75.38 per
cent.
The impact of the factors was measured on a 5-point likert scale ranging from 1 to 5. The
numbers correspond to: 1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 =
Strongly agree
4 Findings and Discussion
Table 1: Designation/Trade of Respondents
Designation Frequency Percentage
Architects 8 8.1
Builders 23 23.4
Construction Managers 11 11.2
Quantity surveyors 10 10.2
Civil Engineers 17 17.3
Artisans 20 20.4
Unskilled labourers 9 9.1
Total 98 100
(Source: Field Survey, 2015)
Table 1. shows the category of the respondents to the survey. 8% of respondents are Architects,
23% are Builders, 11% are Construction Managers, 10% are Quantity surveyors, 17% Civil
Engineers, 20% are Artisans and 9% are Unskilled labourers. This shows that respondents truly
represent stakeholders in the building industry in Nigeria
Table 2: Years of working experience
Years of experience Frequency Percentage
0-5 years 15 15
6-10 years 42 39
11-15 years 29 30
Above 15 years 13 13
Total 98 100
(Source: Field Survey, 2015)
On the year of experience of respondents, 15% of respondent have been in the industry for 0-
5 years. 39% have 6-10 years working experience, 30% of respondents 11-15 years and 13%
have worked in the industry for 15 years or more. It can be seen that respondents have good
years of experience in their field of practice.
Table 3: Awareness of electronic payment system
Type of response Frequency Percentage (%)
Aware 86 86
Not Aware 13 13
155
Total 125 100
(Source: Field Survey, 2015)
From the study it was found that 86% are aware of electronic payment systems while 13% of
the respondents are not. Awareness is a major step towards adoption. This is a step in the right
direction for adopting e-payment systems in the construction industry.
As shown in Table 4. it was established that 61% of respondents are willing to use the electronic
payment channels. While 39% are not keen on using e payment. This shows that there is
prospect for adoption of e-payment systems in the Nigerian construction Industry.
Table 4: Respondents Wiliness to use and accept E-payment system
Response Frequency Percentage (%)
Willing 60 61
Not-Willing 48 39
Total 98 100
(Source: Field Survey, 2015)
Table 5: Payment channels used at the construction stage
S/n Methods ∑𝐟 ∑fx Mean Position
1 Cash payment 98 470 4.8 1st
2 ATM 98 290 2.96 2nd
3 Electronic Funds Transfer 98 278 2.80 3rd
4 Internet banking 98 260 2.65 4th
5 Point-of-Sale (POS) Terminals 98 249 2.64 5th
6 Mobile banking 98 255 2.60 6th
(Source: Field Survey, 2015)
The research inquired in to the method of payment they use during construction. As shown in
Table 5 most transactions are made in cash(X=4.8), this is followed by ATM and Electronic
transfer with mean of 2.96 and 2.80 respectively. Internet banking (X=2.65) Point-of-Sale
(POS) Terminals (X=2.64) and Mobile banking (X=2.60) are the least used channels of
payment.
It can be seen that cash remains the most used method of payment in the Nigerian construction
industry. As most transactions are done in cash and can be prone to corrupt practices. The
findings also show that electronic payment systems are used but are far behind. This also shows
lack of adoption of e-payment in the construction industry. This is one of the main motivator
for carrying out this research.
156
Table 6: Benefits of adopting E-payment system in the Nigerian Construction Industry
S/n Benefits ∑𝐟 ∑fx Mean Position
1 Reduce the risk of carrying cash, 98 423 4.32 1st
2 Improving transparency, 98 413 4.22 2nd
3 Curb inefficiencies and corruption 98 400 4.08 3rd
4 Reduce cash related robbery 98 373 3.86 4th
5 Shorter transaction timelines 98 314 3.20 5th
6 Increased transaction possibilities and
convenience
98 309 3.15 6th
7 Increase employment 98 247 2.7 7th
8 Faster access to capital 98 223 2.27 8th
(Source: Field Survey, 2015)
Table 6 shows the benefits to be derived by adopting e-payment systems in the building
industry. Reduced risk of carrying cash was top with X=4.32, Improving transparency
(X=4.22), Curb inefficiencies and corruption (X=4.08) and reduce cash related robbery
(X=3.86) are the most ranked benefits of electronic payment in the industry.
The contracting companies are known for moving huge amount of cash from banks to material
suppliers, construction sites and site operatives which is very risky. This could lead to robbery
which has led to loss of live and money to be used for the project. This would affect the project
delivery. Transparency in the industry can be improved through adoption of e-payment. As
transactions can be easily tracked and traced through electronic payment. Inefficiency and
corruption can be reduced through electronic payment. This is good news as it is all agreed that
the industry is prone to corrupt practices and cash payment has aided this act.
Table 7: Challenges of adopting E-payment system in the Nigerian Construction Industry
S/n Challenges ∑𝐟 ∑fx Mean Position
1 Low level of literacy among site
operatives (semi-skilled and unskilled)
98 404 4.12 1st
2 Low number of bankable site operatives 98 399 4.07 2nd
3 The high level of ATM and internet fraud, 98 393 4.02 3rd
4 Resistance to change 98 385 3.93 4th
5 Insistence on daily payment system 98 381 3.89 5th
Inadequate number of bank branches 98 377 3.85 6th
6 Inadequate infrastructure which ranges
from network failure, inadequate ATM and
POS machines
98 372 3.80 7th
7 Low level of internet penetration 98 359 3.66 8th
8 Lack of suitable legal and regulatory
framework for e-payments
98 345 3.52 9th
9 Lack of reliable power supply 98 368 3.76 10th
10 Lack of Trust 98 376 3.84 11th
11 Lack of unique national identity system 98 245 2.50 12th
12 Ignorance/ lack public awareness 98 340 3.47 13th
Source; Field survey (2015)
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Table 7 presents the challenges faced in the adoption of the E payment system in the
construction industry. The study established that there are challenges being faced. Low literacy
among site operatives (semi-skilled and unskilled (X=4.12), low number of bankable site
operatives (X=4.07), the high level of ATM and internet fraud (X=4.02), resistance to change
(X=3.93), and insistence on daily payment system (X=4.02) are the major challenges to
adoption of the e payment system in the construction industry.
The literacy level of artisans and labourers has affected the adoption of e payment in the
industry, most of them cannot use and operate e payment channels. It is important to state that
most of the professional in the industry are paid through electronic channels; it is the site
operatives that are most affected. A good number of craftsmen do not own a bank account.
Therefore, they do not have means to receive payment electronically. This problem is not
peculiar to the construction industry because studies have revealed that less than 50% of adult
in Nigeria own a bank account. The high rate of internet and banking fraud in Nigeria has been
a discouraging factor. Nigeria has been described as a hub for internet fraud. This has
discouraged many from operating electronic payment channels.
Resistance to change has always been a challenge to new innovations. People believe in using
methods they are used to and resist innovations even if they are better. Paying site operatives
daily has negative effect on adoption of e-payment in the industry. Operatives insist on and
usually receive their wages daily especially among small and medium scale construction firms
in Nigeria. This would increase the cost to be incurred in making payment on e-payment
channels as banks would charge on each transaction. This has discouraged many firms from
using e-payment channels.
5 Conclusion and Further Research
The purpose of the study is to assess electronic payment system among SMEs in the Nigerian
building industry. The study concludes that the use of e-Payment system low at the construction
stage and cash was the most used method of payment. The benefits of adopting e-payment by
the construction industry includes reduce the risk of carrying cash, improving transparency,
reduction in corruption and time saving. A low level of literacy among site operatives (semi-
skilled and unskilled), a low number of bankable site operatives, the high level of ATM fraud,
resistance to change, and insistence on a daily payment system are the most highly ranked
challenges of adopting the e-payment system in the construction industry. Though the potential
for controlling corruption by means of e payment may be possible, it does not work in isolation
from other anti-corruption systems. E-payment does not work magic in a corrupt environment;
they are only as good as the people who utilize them-without integrity, cashless policy is
incapable of controlling corruption. The following steps can be taken in adoption:
Insisting that new employee have a bank account as a prerequisite for employment and
encouraging old employee to open one;
Procuring infrastructure both hard and software for implementation;
Training managers and site operatives on electronic payment channels and how to
utilize them, and
Implementation of electronic payment through various channels available.
6 References
Abdul-Azeez, A.D. (2012), Developing a prototype electronic document and record
management system (EDRMS) for small and medium building firms.
158
Unpublished Dissertation, Department of Building. Ahmadu Bello University
Zaria.
Akhalumeh, P. B. & Ohiokha, F. (2012), ‘Nigeria’s cashless economy: The imperatives’.
International Journal of Management & Business Studies, 2(2), pp. 31-36
Ayoola, T. (2013), The Effect of Cashless Policy of Government on Corruption in Nigeria.
International Review of Management and Business Research, 2(3).
Bankable frontier Associates (2013), What does the CBN’s Cash-less policy mean for
financial inclusion in Nigeria? Retrieved
http://www.cenbank.org/OUT/2012/CIRCULARS/BSPD/CIRCULAR%20TO%20
LL%20DEPOSIT%20MONEY%20BANKS.PDF
Dawdy, H. & Wearen P. (1985), Statistical Methods for research, Appollo Press, London
Lamikanra, B. (2012), Managing the transition to a cashless economy in Nigeria: The
Challenges and Strategies. Paper presented at The Nigeria Computer Society 24TH
National Conference July 25, 2012.
Olanipekun, W. D., Brimah, A. N & Akanni, L. F (2013), ‘Integrating Cashless Economic
Policy in Nigeria: Challenges and Prospects’. International Journal of Business and
Behavioral Sciences ,3(5).
Omotunde, M., Sunday, T, & John-Dewole A.T. (2013), ‘Impact of cashless economy in
Nigeria’. Greener Journal of Internet, Information and Communication Systems, 1
(2), pp.40-43
Onugu, B. A. N. (2005), Small and Medium Enterprise (SMEs) in Nigeria: Problems and
Prospects; Unpublished PhD Thesis submitted to St Clements University.
Oyediran, S.O., Akintola, A. A. (2011). A Survey of the state of the art of E-Tendering in
Nigeria. Journal of Information Technology in Construction. 16,557
Shonubi, A. (2012), Towards a cashless Nigeria: Tool and Strategies: Business Implications.
Paper presented at The Nigeria Computer Society 24th National Conference.
159
Community Engagement on Public Projects – Case Study
of Hammanskraal Pedestrian Bridge, Gauteng, South
Africa B.D.C. Rathenam1, I. Musonda2, A. Talukhaba3, N.L. Dabup4
13 Department of Building Sciences,
Tshwane University of Technology, South Africa
Email: chhanabd@gmail.com, TalukhabaAA@tut.ac.za 2 Department of Construction Management and Quantity Surveying
University of Johannesburg,
Email: imusonda@uj.ac.za 4Tsholetso Projects, Pretoria, South Africa,
Email: pdlami@gmail.com
Abstract:
Construction projects in the public sector have often been affected by major challenges with
regards to project ownership by stakeholders particularly the co-operation of local
communities. Various government policies and regulations exist which supports the
participation of small and medium scale enterprises within the built environment especially on
public sector projects. This research study investigated the influence of local communities on
public sector construction projects with a focus on the impact of the local community involved
in the construction of the Hammanskraal Pedestrian Bridge over the R101 in Hammanskraal,
Pretoria. Structured interviews were conducted with the main contractor, the professional team
involved in the project and the municipality officials overseeing the project. The findings show
that the stakeholders from the Hammanskraal community had a high degree of influence on the
project, unfortunately their influence on the project was negative.
Keywords:
Construction, Community, Projects, Stakeholders
1. Introduction The concept of stakeholder management in project implementation particularly with regards to
construction projects has gained grounds within the last decades. This is especially so with the
increased move towards environmental awareness and the impact of construction projects on
the environment and communities. Consequently, it has brought to the fore the issue of
stakeholders. Equally, stakeholder management has become extremely relevant to project
success. This according to Baharuddin, Wilkinson and Costello (2013) may be due to the fact
that stakeholders in construction are affected directly and indirectly by projects. At
implementation stage projects impacts on stakeholders optimistically and adversely due to the
effects and nature of projects during its life-cycle. Baharuddin et al. (2013) opine that
complications such as reworks, disagreements, cost escalations, inadequate communication,
and poor supply chain process are some of the challenges experienced from stakeholder conflict
during the construction phase. The above problems can be attributed to the fact that different
project stakeholders have differing goals and priorities, and it is, therefore, unlikely that all
stakeholder expectations can be met on a project.
Researchers have advised that it is imperative for stakeholders to understand the goals and
objective of the project and to be on board from the planning stage of the project. This
minimizes conflict and encourage ownership (Hammad, 2013; Baharuddin et al., 2014;
Molwus, 2013). However, it appears that not all of the critical stakeholders are involved right
160
from the inception of a project. Equally, there are few studies which have been conducted on
the implications and how critical it is for stakeholders to be involved in construction projects
right from the initiation phase.
This paper assessed the impact and level of community engagement during the project life
cycle of the Hammanskraal pedestrian bridge in Pretoria, Gauteng, South Africa
2. Literature review 2.1 Project stakeholders
Project stakeholders have been defined in various ways by various researchers and professional
bodies. Some researchers have argued that some of the definitions are too constricted, while
some argue that the definition is too wide (Molwus, 2013). Researchers have defined
stakeholders as the individuals, clusters, or businesses that can affect or be affected by a
resolution, task, or consequence of the project (PMBOK, 2013; Malkat and Byung - GYOO,
2012). Other researchers have categorized stakeholders, namely Olander (2007), Aaltonen and
Kujala (2008), Chinyio and Akintoye (2008), and Winch (2010) based on their characteristics
and disposition towards the project. Winch (2010) in particular, classified construction project
stakeholders into two categories according to their relationship with the client:
• Internal stakeholders which are those who have legal contracts binding with the client,
and
• External stakeholders which are those who although having direct interest in the project
do not necessarily have direct contracts with the client.
Winch (2010) further broke the two groups down as internal and external stakeholders. Internal
stakeholders are those grouped around the client on the demand side and those on the supply
side. The external stakeholders are subdivided into private and public actors. El-Gohary,
Osman, El-Diraby (2006) define project stakeholders as clusters or entities, individuals who
have stake in, or expectation of, the project’s performance including clients, project managers,
designers, subcontractors, suppliers, funding bodies, users and the community at large who has
power and are effected by the development directly and indirectly.
2.2 Stakeholder management
The importance of stakeholder management in construction projects has been emphasized and
reported by a number of studies according to Yang, Shen Ho, Drew, and Chan (2009). Yang et
al. (2013) further posit that the construction industry has failed dismally in effectively
managing stakeholders in the last decade. Even though studies conducted within the industry
have shown that some of the challenges of stakeholder management in construction projects
include: inadequate engagement of stakeholders, project managers having unclear objectives
of stakeholder management, difficulty to identify the “invisible” stakeholder, and inadequate
communication with stakeholders. This assertion is in line with a study by Molvus (2013),
which investigated the current practice of stakeholder management within the construction
industry. His survey results, revealed that stakeholder management has yet to be fully embraced
among the construction organizations.
Research conducted by Yang et al. (2013) on construction projects in Hong Kong determined
the top three critical success factors as effective in stakeholder management as managing
stakeholders with social responsibilities, namely economic, legal, environmental, and ethical;
exploring the stakeholders’ needs and constraints to the project, and communicating with and
engaging stakeholders properly and frequently.
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Molvus (2013) conducted a study on stakeholder management in the construction industry in
the United Kingdom. The results of his study indicated that; there is a strong need for internal
stakeholders to collaborate in undertaking stakeholder management in construction projects;
there is need to put in place feedback mechanisms and early warning signs to track change in
stakeholder interests / disposition throughout the project and finally that public hearings and
design charrettes were considered the most important stakeholder engagement instruments.
In trying to understand the interrelations among the critical success factors for stakeholder
management in construction, Molvus’s (2013), study showed that stakeholder analysis cannot
directly impact / influence project success. However, stakeholder engagement / empowerment
being the only construct found to directly influence project success depends on the
understanding of stakeholder dynamism which also depends very strongly on the results of
stakeholder analysis.
A study conducted by Malkat et al. (2012) relative to stakeholders of construction projects in
Dubai and adjacent regions, found that project managers ranked the highest and the community
is the lowest ranked, in terms of their influence on the projects.
An investigation on salient stakeholder attributes, assigning only one attribute, power,
legitimacy, and urgency to each stakeholder. The results gave an idea on the most significant
stakeholders that counts in terms of attribute. The stakeholders include the client, sub-
contractors, suppliers, financial firms, and community. Clients were found to be the core
stakeholders at 67.5%, respondents feel the need to adhere to client’s wish and keep him
satisfied. In additions, 81.8% of respondents believed that clients possess the power attribute.
For legitimacy and urgency, third parties, communities and sub-contractors accounted for
55.8% respectively (Malkat et al., 2012).
Initiating the engagement process in a project’s early phase ensures timely public access to all
relevant information and gives the stakeholders an opportunity to provide input into the project
design and the assessment of impacts (Baharuddin et el. (2014). Hammad (2013) agrees with
this and suggests that in today’s project environment, stakeholders are an integral aspect of the
successful delivery of projects as ever so often projects are motivated by the actions and
decisions of relevant stakeholders.
3. Research Methodology
The current study entailed a review of literature relevant to stakeholder management with
particular focus on stakeholder engagement. The search included investigations of journal
publications and materials from the academic community.
A case study on the Hammanskraal bridge project was conducted. To aid the empirical study,
a questionnaire was designed, based on a review of the available literature pertaining to
stakeholder management in construction projects.
The questionnaire was devised to understand which stakeholders had the most influence and
impact on the project delivery process and the stakeholder factors which caused delays on the
Hammanskraal bridge project. The questionnaire was framed and aligned to the major
challenges experienced on the Hammanskraal bridge project, in order to assist with
understanding the causes of conflicts and frictions on the project. The project was selected for
this study because it was a community based project and had multiple stakeholders.
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Respondents to the questionnaire included members of the professional team, client and the
contractor. The study was limited to this group of people as they were at the fore of the project
delivery process and were affected by the various challenges experienced on the project from
various stakeholders.
This study was limited to one project where the procurement process involved evaluating
experienced contractors as the project was a specialized one.
3.1 Case Study
A study was conducted on the construction of the Hammanskraal Pedestrian Bridge. The
Hammanskraal Pedestrian Bridge project entailed the construction of a Pedestrian Bridge
across the R101 (Route K97), linking the pedestrian walkway network between two major
business nodes adjacent to the R101. The business nodes serve the entire Hammanskraal area.
The project team identified the pedestrian bridge on the R101 in the Hammanskraal as a priority
project for non-motorized infrastructure for the safety of members of the Hammanskraal
community. The project was funded by the South African National Treasury under the
Neighbourhood Development Partnership Grant (NDPG), in conjunction with the City of
Tshwane. The South African National Treasury remained the client in the project although the
City of Tshwane took ownership of the Pedestrian Bridge post-construction. The project was
initially slated to be completed within five months. However, due to various challenges and
delays the completed date had to be extended for another seven months resulting in cost
overrun.
4. Research Findings
The Relative Importance Index (RII) method was used to rank the respondents’ perceptions in
order to determine which factors were ranked higher than others and hence considered more
important. The output from the analysis was presented in graphs, charts and tables.
The Relative Importance Index (RII) entails ranking of factors and groups in terms of their
importance level. A five-point likert scale was used to obtain ratings from respondents using a
scale of one (very low influence) to five (very high influence). Based on these ratings relative
importance indices (RII) for each element were obtained.
Twelve (12) individuals, who worked as professionals within the construction industry and
were directly involved in the construction of the Hammanskraal pedestrian bridge project, were
contacted via email and requested to participate in the completion of the survey. From the
selected twelve (12) individuals, nine (9) respondents completed and returned the
questionnaires.
The respondent population was made up of professionals within the built environment industry
with varying years of experiences in the industry. The first part of the questionnaire covered
the demographics information of the respondents indicating their experience, job title,
organisation, and the number of years their organisation has been operating within the industry
this provided an idea into the extent of their experience.
From the respondents a total of seven were graduates, one had a postgraduate degree and one
had a doctorate degree. Although all the respondents worked in the built environment, four of
them had experience of between 5-10 years, two had experience of 15-20 years and three had
experience of more than 20 years. The respondent’s ranged between, top, middle and junior
163
management levels. Although the project was funded by the public sector only two of the
respondents worked for the public sector and seven of the respondents worked for the private
sector.
The first objective of the research was to assess the extent to which stakeholders influenced the
Hammanskraal pedestrian bridge project. The findings were that stakeholders had a high
impact on the project with an aggregated relative importance index of 0.656. From the
summary of results in Table 1, it was observed that the stakeholders ranked most influential on
the project were the community (RII = 0.796), the Project Manager (RII = 0.778), the structural
Engineer (RII = 0.741) and the traders’ union committee (RII = 0.704). It is notable that the
result of the survey indicates that the community was more influential on the project than any
member of the professional team which is contrary to extant literature which suggests that the
project manager is the most influential stakeholder.
Table 1: Extent of stakeholders’ influence at the Hammanskraal Pedestrian Bridge project.
Stakeholders Unsure Low………..….……….…High
RII Rank
1 2 3 4 5
Community 0 0 0 0 2 7 0.796 1
Project Manager 0 0 0 0 3 6 0.778 2
Structural Engineer 0 0 0 1 3 5 0.741 3
Trader Union Committee 0 0 0 2 3 4 0.704 4
Contractor 0 0 0 3 1 5 0.704 5
Project Steering Committee 1 0 0 3 3 3 0.667 6
Community Liaison Officer 0 0 1 1 5 2 0.648 7
Gauteng transport and public
works department- Gautrans 0 0 1 3 2 3 0.630 8
City of Tshwane 0 0 2 1 3 3 0.630 9
Client 0 1 1 1 4 2 0.593 10
Material Suppliers 0 0 2 1 6 0 0.574 11
Local labour 0 0 2 4 2 1 0.537 12
Subcontractors 0 0 2 5 1 1 0.519 13
Source: Researcher
The second objective of the survey was to establish the nature of stakeholders’ influence on
the project. Table 2 indicates the nature of stakeholder influence on the Hammanskraal
Pedestrian Bridge project in terms of percentage responses to a scale of 1 (positive) to 5
(negative). The respondents attributed the top five stakeholders to have negatively influenced
the project as Hawker Committee (RII = 0.685), the community (RII = 0.611), the community
liaison officer (RII = 0.537), the project steering committee (RII = 0.444) and the local labour
(RII = 0.444). It is notable that in general the respondents can be deemed to perceive that the
local community and local community forums such as the hawker union had a negative
influence on the Hammanskraal Pedestrian Bridge Project.
Table 2: Nature of stakeholder influence on the Hammanskraal Pedestrian Bridge project.
Stakeholders Unsure Positive….……………..Negative
RII Rank
1 2 3 4 5
Hawker Committee 0 0 2 0 2 5 0.685 1
164
Community 0 1 2 0 2 4 0.611 2
Community Liaison Officer 0 0 3 3 1 2 0.537 3
Project Steering Committee 1 1 2 2 2 1 0.444 4
Local labour 0 1 3 3 2 0 0.444 5
Government Agency: Gautrans 0 3 1 4 1 0 0.389 6
Subcontractors 0 1 5 3 0 0 0.370 7
City of Tshwane 0 2 4 3 0 0 0.352 8
Material Suppliers 0 2 6 0 1 0 0.333 9
Contractor 0 3 5 1 0 0 0.222 10
Structural Engineer 0 7 1 1 0 0 0.222 11
Client 0 7 1 1 0 0 0.222 12
Project Manager 0 7 2 0 0 0 0.204 13
Source: Researcher
The survey also sought to determine the factors that influenced the delay on the Hammanskraal
pedestrian bridge project as a third objective in table 3. The survey found overall that
community factors emerged as the highest factors influencing delays overall in the project, all
of which exceed the aggregated relative importance index of 0.433. The respondents attributed
the top five factors influencing delay as Socio-political factors in the form of strikes, civil unrest
by the community (RII = 0.759), Local traders’ union Interference (RII = 0.667), Lack of
support from the local ward councilor (RII = 0.611), Bad public relation practices in dealing
with communities (RII = 0.611) and Conflict with local labour on site (RII = 0.574).
Table 3: Factors that influenced delays on the Hammanskraal Pedestrian bridge project
Statements Unsure Minor….……...……Major
RII Rank 1 2 3 4 5
Socio-political factors in the form of
strikes, civil unrest by the community 0 0 0 1 2 6 0.759 1
Local traders union Interference 0 1 1 0 2 5 0.667 2
Lack of support from the local ward
councilor 0 0 1 4 1 3 0.611 3
Bad public relation practices in dealing
with communities 0 0 0 4 4 1 0.611 4
Conflict with local labour on site 0 0 3 1 3 2 0.574 5
Lack of support from the community
liaison officer 0 0 3 2 1 3 0.574 6
Local plant & equipment hire rates
market related 0 1 1 2 5 0 0.537 7
Delayed approvals from government
agencies 0 3 0 1 3 2 0.519 8
Lack of support from government
agencies 0 2 1 4 0 2 0.481 9
Unavailability of plants and equipment 0 2 2 1 3 1 0.481 10
Disruption of site works due to health
and safety concerns 0 1 3 4 1 0 0.426 11
Late production of revised drawings by
engineer 0 2 4 2 0 1 0.389 12
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Disruption of site works due to
environmental concerns 0 2 3 3 1 0 0.389 13
Insufficient skills from the construction
team 1 2 2 2 2 0 0.370 14
Mistakes and discrepancies in design
documents 0 3 2 4 0 0 0.352 15
Late payment of labour’s wages by
contractor 0 1 6 2 0 0 0.352 16
Lack of clients understanding of the
design, procurement, and construction
processes
0 3 2 4 0 0 0.352 17
Inadequate design by the engineer 0 3 4 0 2 0 0.352 18
Late delivery of material to site 0 3 3 3 0 0 0.333 19
Incorrect material delivered to site 0 3 4 2 0 0 0.351 20
Lack of support from client 0 3 5 0 1 0 0.315 21
Change in material types and
specifications during construction 1 3 2 3 0 0 0.296 22
Inadequate communication between the
construction team and the project team 0 5 2 2 0 0 0.278 23
Inappropriate business practices 1 2 6 0 0 0 0.259 24
Late payment by client 0 7 2 0 0 0 0.204 25
Source: Researcher
5. Discussion and Conclusion
Literature study revealed that stakeholder management is vital in ensuring the success of a
construction project. It also showed that, although the local community is considered a
stakeholder, minimal consideration and engagement is given to the local community as a
stakeholder. The study conducted by Malkat et al. (2012) relative to stakeholders of
construction projects in Dubai and adjacent regions, indicated that stakeholders ranking based
on their highest influence on project spheres, revealed that project managers were the highest
ranked and the community was the lowest ranked in terms of influence. However, this survey
shows a contrary view. Amongst all the stakeholders on the Hammanskraal Pedestrian Bridge
Project, the local community proved to be the major influencers negatively influencing both
time and cost.
This could be attributed to the fact that South Africa is a developing economy this could be a
subsequent research topic. Understanding and exploring the influence of community
engagement on public projects would allow a possibility of improving time and cost measures
within construction projects. The survey ranked the client as the tenth most influential
stakeholder relative to the extent of influence (Table 1). However, findings also contradict
Malkat et al. (2012) study which reported that the client possess the power attribute. The
findings may be explained by the fact that the Hammanskraal pedestrian bridge project, was
funded by government.
For future research stakeholder engagement can be compared in both private and public sector
projects to determine which stakeholder has the most influence and the nature of that influence.
Finally, it is interesting to note that the respondents perceive the local community, and local
166
committees at the Hammanskraal pedestrian bridge Project to have a negative influence,
despite the fact that the bridge was constructed to ensure safe pedestrian crossing between the
major malls within the Hammanskraal community, and was prioritised by government to
alleviate fatalities on a major route. Consequently, a much more detailed study, which would
seek to establish the underlying causes would be insightful.
6 Acknowledgement
It is to be noted that this conference paper forms part of a pilot study for Author 1’s dissertation
for a Master of Technology in Construction Management, which involves the investigation of
the influences of communities on government projects.
7. References
Aaltonen, K., and Kujala, J. (2010). A project lifecycle perspective on stakeholder influence
strategies in global projects. Scandinavian Journal of Management, 26(4), 381-397.
Baharuddin, H., Wilkinson, S. and Costello, S. (2014). Enhancing features of early stakeholder
engagement in expressway projects. Proceedings of the 4th New Zealand Built
Environment Research Symposium (NZBERS). Auckland, New Zealand. 14 November.
ISSN 2324-1829 (Online).
Baharuddin, H. E. A., Wilkinson, S., & Costello, S. B. (2013). Evaluating Early Stakeholder
Engagement (ESE) as a Process for Innovation. Paper presented at the CIB World Building
Congress, Brisbane, Australia
Chinyio, E. A. and Akintoye, A. (2008). Practical approaches for engaging stakeholders:
findings from the UK, Construction Management and Economics, 26: 6, 591-599.
El-Gohary, N.M., Osman, H., El-Diraby, T.E. (2006). Stakeholder management for public
private partnership. International Journal of Project Management. Vol 24(2006). 595604.
Hammad S, (2013) Investigating the stakeholder management in construction projects in
the Gaza Strip. An MSc Thesis. The Islamic University – Gaza.
Jepsen, A. L. and Eskerod, P. (2009). Stakeholder analysis in projects: challenges in using
current guidelines in the real world, International Journal of Project Management 27, 335
– 345.
Malkat and Byung- GYOO, (2012) An Investigation on the Stakeholders of Construction
Projects in Dubai and Adjacent Regions. International Proceedings of Economics
Development & Research, Vol. 45, 2012, pp. 77-82. [13] Michigan D
Madhav, K. Rathod, H., Patel, H.R (2015) A review on stakeholder management for
construction industry. International Journal of Advanced Research in Engineering, Science
and Management. Vol 1, issue 4, pp. 1-6
Mathur V. N., Price A. D. F. and Austin S. (2008). Conceptualizing stakeholder engagement
in the context of sustainability and its assessment. Construction Management and
Economics, 26, pp. 601-9.
Molwus, JJ (2013) Stakeholder management in construction projects: a life cycle based
framework A PhD Thesis. Heriot Watt University, Edinburgh
Olander, S (2006) External Stakeholder Analysis in Construction Project. A PhD Thesis. Lund
University, Sweden
Olander, S. (2007). Stakeholder impact analysis in construction project management,
Construction Management and Economics, 25: 3, 277-287.
Project Management Institute (2013) A Guide to the Project Management Body of Knowledge
(PMBOK) Guide (5th Edition). Project Management Institute: Pennsylvania
167
Winch, G. M., (2010). Managing Construction projects: an information processing approach,
2nd Edition, Wiley-Blackwell, West Sussex, UK.
Yang, J., Shen G.Q., Ho M., Drew D.S. and Chan, A.P.C. (2009) Exploring critical success
factors for stakeholder management in construction projects. Journal of civil engineering
and management. 15(4): 337–348.
168
A Review of Factors Affecting Construction Labour
Productivity in Developed and Developing Countries Oluseyi Adebowale1 and John Smallwood2
1Nelson Mandela Metropolitan University
Adebowaleoluseyi@gmail.com 2Nelson Mandela Metropolitan University
John.smallwood@nmmu.ac.za
Abstract:
The construction industry remains a major player in the economic development of any nation.
As a result, a number of studies have addressed construction productivity over decades.
However, schedule overruns, cost overruns, and quality challenges remain the recurring issues
that impair the optimum performance of the construction sector. This paper reports on a survey
of the literature constrained in terms of selected construction productivity research conducted
during the last twenty-nine years. The findings obtained in the articles reviewed are presented
under related headings to determine the frequency of each factor. The study determined that
management-related, design-related, and material-related factors are the underlying issues
influencing construction productivity in developed and developing countries. The study
presents the need to measure the impact of productivity-influencing factors against each of
cost, quality and time as this has been unheeded in construction labour productivity related
research. Subsequently, a review of the existing body of knowledge in terms of the factors
influencing construction labour productivity across developed and developing countries is
presented. It is concluded that improved construction labour productivity will engender cost
effective, quality, and timeous project delivery to increase construction stakeholder
satisfaction. This will ultimately improve the contribution of the construction industry to the
Gross Domestic Product (GDP) in both developed and developing countries.
Keywords: construction, labour, overruns, productivity, quality
1 Introduction
In the global construction sector, labour productivity has a major effect on a nations’ economic
development (Chia et al., 2014). As such, the construction industry plays a strategic role in the
economic development of developed and developing countries (Kazaz et al., 2008), although
the factors influencing construction productivity in developed countries differ from those of
developing countries (Alinaitwe et al., 2007). Due to the significant contribution of
construction operations to the economic activities of developed and emerging economies, a
number of studies have addressed factors affecting construction productivity in the construction
industry. In spite of these studies, the construction industry continues to grapple with the
challenges of schedule overruns, cost overruns, and challenges related to the quality of
construction, which constitute part of the essential project objectives for successful project
delivery. These essential project objectives drive construction stakeholder satisfaction and
therefore, their performance is fundamental to the performance of construction projects. In
simple terms, schedule overruns, cost overruns, quality of project delivery, and the non-
satisfaction of stakeholders are significantly related to poor productivity in the construction
sector. As such, the importance of construction labour productivity to achieving construction
project goals necessitates the need for a considerable effort to salvage the deteriorating state of
labour productivity in the construction environment. The extant studies relative to construction
productivity have broadly explored critical productivity-influencing factors, however, there is
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still much to be done to improve labour productivity in the construction industry. Sezer and
Brochner (2014) maintain that official statistics have proven productivity in the construction
industry to grow more slowly than productivity in the manufacturing industry. In view of this,
researchers have proposed diverse interventions relative to their findings. However, it becomes
almost impossible to deliver a construction project without overrunning its predetermined
budget and schedule. Although the complexity of the construction sector in terms of its multi-
disciplinary nature is a contributing factor to this poor project performance. Notwithstanding,
the economic impacts of construction on project participants, the business of construction and
nations necessitate the need for more scientific research to mitigate the negative effect of poor
productivity in the construction industry. Essentially, the existing productivity related research
have not considered measuring the critical factors influencing labour productivity against each
of construction cost, quality, and time. Measuring the impact of construction productivity-
influencing factors on each of these project objectives will reveal the relationship of the
productivity-influencing factors and the project objectives. Thus, the question of which
productivity-influencing factors have more impact on each of cost, quality and time will be
answered to allow for further interventions. However, this research question will be best
answered through a measurable quantitative approach rather than qualitative means. The main
objective of this study, therefore, is to present the review of extant literature relative to factors
influencing construction productivity in developed and developing countries to determine the
significant productivity-influencing factors.
2 Literature Review
2.1 Labour productivity
Productivity is a multi-dimensional concept that could be understood in different contexts
depending on the objectives involved; the objective, in turn, defines the parameters required in
its assessment in relation to the benchmark used for its comparison (Durdyev & Mbachu,
2011). The phenomenon is not the measurement of the specific contribution of labour as a
single production factor, however, the term depicts the combined effect of materials, tools and
equipment, capital investment, managerial skills and the effect of the construction workforce
(cidb, 2015). Owing to the growing knowledge that productivity improvement is an essential
tool to sustain a thriving economy, assessing productivity is becoming more vital to economists
and policy makers of industries (Fadejeva & Melihovs, 2009). One of the most significant
factors that determine the entire performance level of organisations, regardless of its size, is
the productivity level of organisations (Kazaz & Ulubeyli, 2007). In essence, poor productivity
will adversely affect an economy as organisation systems and structures become ineffective
(Van Ark, 2014). Most commonly, productivity is widely expressed as the ratio of output to
input or vice-versa (Enshassi et al., 2007; Park et al., 2005; Phusavat, 2013), where both output
and input are mostly expressed in cost (Rivas et al., 2011). However, in the simplest sense of
the word, productivity implies the period of time spent by an employee who is actively involved
in a job being hired to do for the underlying purpose of producing the desired outcome based
on the predetermined job description (Ferreira & du Plessis; 2009; Teng, 2014). The ability to
satisfy the condition of time in producing the required or predetermined job description by
considering necessary requirements forms the baseline for determining productivity. The
subject is used as a determinant factor of how best the resources available are being utilised for
necessary decisions to be made within an organisation (Phusavat, 2013). Consequently, the
level of productivity of an organisation significantly depends on the way its production
processes are organised and coordinated (Caliendo & Rossi-Hansberg, 2012). Although, the
subject has become a common term that is widely employed by individuals and organisations
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with different knowledge and perceptions in terms of its meaning (Tangen, 2005). Holistically,
individual or group productivity is said to increase when the said individual or group produce(s)
more or better goods or services from the usual resources, or produce the same goods or
services from lesser resources (Tangen, 2005). Teng (2014) considers an increase and loss in
organisation productivity and therefore remarks that increased organisational outputs relative
to reduced corresponding inputs leads to improved productivity and vice-versa. Durdyev et al.
(2014) maintain that much significance is accorded to productivity due to its relevance to
organisation performance, its correspondent impact on the economy, and general standard of
living. Productivity has been widely categorised into two forms: (i) Partial factor productivity
(PFP) or single factor productivity (SFP) - considers single or selected input of an organisation
and, (ii) Total factor productivity (TFP) or multi-factor productivity (MFP) – considers all
organisation inputs and outputs (Jarkas, 2015). Notably, there are a considerable number of
input resources in the production process of an organisation. Workers play a significant role as
they determine the amount of goods produced within per labour unit of an organisation (Bures
& Stropkova, 2014). Chau (2009) note that labour productivity as single factor productivity is
a biased measure of productivity as long as there are other inputs that are ignored. Chau (2009)
state the need to compare organisation output to its inputs in order to determine the actual
organisation productivity. Park (2006) contends that TFP is commonly employed in economics
studies and has proved to be the sustainable source of long-term economic growth (Van Ark,
2014). Considering the complexity of the construction industry, total factor productivity might
be challenging as identifying all the input resources for construction operations may be
unrealistic. Certainly, construction productivity-influencing factors further influence the
conventional project objectives at varying magnitudes. However, the magnitude of the impact
of productivity-influencing factors on each project objective would better be quantitatively
determined.
2.2 Construction project schedule
Exceeding the date of project completion as specified in contract documentation, or exceeding
the agreed delivery time determined by the parties to the project, stems from different forms of
delay during project executions (Assaf & Al-Hejji, 2006). Project managers are saddled with
the responsibility of ensuring that activities are delivered as previously scheduled (Sambasivan
& Soon, 2007). However, delays have become a common experience during the delivery of
construction projects (Kaliba et al., 2009; Borse & Khare; 2016; Sambasivan & Soon, 2007).
Josephson and Chao (2014) determined that non-value adding time (waste) constitutes
approximately 35 % of the available time between activities, while the time spent on value
adding activities is significantly less. Borse and Khare (2016) attribute the underlying causes
of delays on construction projects to factors such as design errors, unexpected site conditions,
increases in project scope, weather conditions, and other project changes. Lack of proper tools
and equipment leads to an unproductive time of employee which is a direct consequence of
inappropriate site preparation, the unwillingness of company to purchase quality tools and
equipment and poor financial capacity of the company (Ghoddousi & Hosseini, 2012).
Sambasivan and Soon (2007) note that inadequate experience of contractors affects
construction project delivery time. Aibinu and Jagboro (2002) maintain that contractors and
clients jointly or separately contribute to delays on construction projects. The different forms
of delay that slow down the pace of construction operations include: (1) Excusable delays –
these are delays resulting from unforeseen factors outside the control of contractor and are not
attributed to their negligence (Akinsiku & Akinsulire, 2012); (2) Non-excusable delays – the
contractor is responsible for this category of delay, and (3) Concurrent delays - delays that
171
occur simultaneously with other delays, which could contribute to the formation of other delays
(Arditi & Pattanakitchamroon, 2006).
2.3 Cost overruns
Cost overrun denotes escalation in the amount of money required to deliver a project
considering the original budgeted amount (Kaliba et al., 2009). Memon et al. (2011) identify
cost as a major consideration during the project management life cycle and can also be
considered as one of the essential parameters for achieving project success. The effective
implementation of a construction project by keeping the execution under the control of the
predetermined cost is, however, reliant on an approach that requires sound engineering
judgement (Enshassi et al., 2010). Despite the awareness of the need for cost control, it is not
uncommon to see a construction project unable to achieve its objective relative to effective cost
delivery (Memon et al., 2011). Successful organisations, therefore, adopt policies to develop a
long-term cost effective business. Through prioritising the reduction of defects and
disturbances related to the project, several organisations expand their chances to oversee the
processes in order to reduce production cost (Josephson & Chao, 2014). Enshassi et al. (2010)
note that overrunning construction budget is predominant in the traditional or adversarial form
of contract, where the contract is awarded to the lowest bidder particularly in developing
countries. Memon et al. (2011) maintain that the trend of cost overrun is more severe in
developing countries where the phenomena occasionally exceed 100 % of the anticipated cost
of the project. Borse and Khare (2016) remark that the occurrence of construction cost overruns
is usually as a result of friction between clients, project managers, and contractors. Inadequate
allocation of funds and poor financial management by contractors are some of the underlying
causes of budget overrun on construction projects. Sun and Meng (2009: 566) maintain that
rework contributes to cost escalation through wasted labour and materials.
2.4 Quality in construction
Quality improvement is one of the important subjects of discourse in virtually all sectors
(Forsythe, 2015). According to Alinaitwe et al. (2007), quality is an essential parameter for
assessing construction project performance. Productivity does not only have to do with
completed task(s) over a period of time but also the quality of task(s) completed i.e. task(s)
completed in compliance with the specification. A poorly undertaken activity would attract
additional time and cost to rework such activity. As such, productivity determinant measures
should consider the quality of outputs. Therefore, it is safe to conclude that workers who have
completed their tasks at the required time but without the required quality are not productive.
Construction organisations, workers, and the general public have lost billions of dollars due to
the compromising of the quality of work (Loushine, et al., 2006). Dudek-Burlikowska (2011)
note quality as an important tool in market competition, as it serves as a dependable license of
obtaining the loyalty of the customer. The act of meeting the expectations of customers or
compliance with customers’ requirement is simply termed quality (Iyer & Jha 2005). Alinaitwe
et al. (2007) posit that some construction contractors are not quality management certified,
which indicates the likelihood of quality management standards being compromised. In
construction productivity related research, the effort to improve construction productivity has
been mostly concentrated on achieving timeous and cost effective delivery of construction
projects with minimum consideration for quality. Chen and Luo (2014) identify that the process
of quality control in the construction industry should begin with the preparing of quality
management plans that are based on construction documents, an explicit reference to the
quality of material and equipment, the accepted standards of work, and the inspection and
testing to be performed. Kazaz et al. (2008) state that productivity improvement could be
172
achieved through development in managing quality. Non-conforming materials and
management engender higher construction costs than expected as a result of the loss of
materials during construction (Memon et al., 2011). This could contribute to rework on
construction sites and hamper the progress of operations. Chen and Luo (2014) maintain that
one of the difficulties in quality management is that the current focus of quality control is the
final component with much less attention given to quality control during the construction
process. Besides, the practice of awarding construction contracts to contractors with the lowest
tender price is one of the challenges that affect quality in construction as the lowest bidders are
mostly unqualified contractors with a shortage of human and capital resources to deliver the
required service. Adequate training and development plans are also required of contracting
organisations to improve the skills of workers which would contribute to the quality of outputs.
3 Research Methodology
The study is based on the existing research relative to the factors affecting construction labour
productivity in developed and developing countries. The research reviewed labour productivity
studies undertaken in developed and developing countries over a period of twenty-nine years
(1987-2016). The selected and reviewed construction labour productivity journal papers were
published in highly rated journals. The journals include the International Journal of
Productivity and Performance Management, Journal of Construction Engineering and
Management, Journal of Civil Engineering and Management, International Journal of Project
Management, International Journal of Construction Management, Journal of Building and
Environment, Journal of Construction Economics and Building, Journal of Construction
Management and Economics. The headings under which literature search was conducted across
the journals include productivity in construction, construction labour productivity and factors
affecting construction labour productivity. The review of factors influencing construction
labour productivity was undertaken to determine trends in terms of the factors affecting
construction labour productivity in developed and developing countries. The highest rated
factors influencing labour productivity were identified in each of the studies. The factors were
subsequently examined, synthesised, and categorised under twelve different headings, namely
material, tools and equipment, design, management, labour, supervision, motivation, external,
health and safety, project finance, rework and technology related factors. To determine the
frequency of each labour productivity-influencing factor as identified in the studies, the
findings are presented in tabular form while each of the factors related to the aforementioned
headings was accordingly placed under relevant headings.
4 Findings and Discussion
Factors influencing construction labour productivity in developed and developing countries
173
174
Source: Researcher
5 Conclusions and recommendations
Material-related, tools and equipment-related, design-related, management-related, labour-
related, supervision-related and motivation related factors were determined to have
considerable influence on construction labour productivity. However, design and management-
related factors have the highest impact on construction labour productivity as each of these
group has a frequency of (9). Material-related factors follow with a frequency of (8), tools,
equipment and labour-related factors have frequencies of (7), supervision-related has a
frequency of (5) and motivation-related factors, a frequency of (4). The study, therefore,
recommends construction management to take cognisance of effective management of
construction projects through consistent employee training, adequate constructability review
of construction drawings, specifications and communication management at business and
project levels. Effective material procurement, planning and scheduling are essential to prevent
delays that stem from waiting for materials. The management should ensure the availability of
the right tools and equipment with effective maintenance plans and training of operatives to
ensure the right application. Essentially, the management should consider construction labour
and their line supervisors relevant to achieving construction project objectives. Thus, provide
the appropriate motivational system and participation in decision making to drive their
productivity. Future research should consider measuring the impact of productivity-influencing
factors on each of the conventional project parameters (cost, quality and time). This will reveal
the relationship of the productivity-influencing factors and the project parameters. Finally,
preliminary investigations are essential in any construction labour productivity related study to
determine the productivity-influencing factors peculiar to the region or country. This is because
the factors influencing construction labour productivity vary from country to country due to a
wide range of factors such as cultural inclinations.
6 References
Aibinu, A.A. and Jagboro, G.O., 2002. The effects of construction delays on project delivery in
Nigerian construction industry. International Journal of Project Management, 20(8), pp.593-
599.
Akinsiku, O.E. and Akinsulire, A., 2012. Stakeholders' Perceptions of the Causes and Effects of
Construction Delays on Project Delivery. Journal of Construction Engineering and Project
Management, 2(4), pp.25-31.
Alinaitwe, H.M., Mwakali, J.A. and Hansson, B., 2007. Factors affecting the productivity of
Building craftsmen‐studies of Uganda. Journal of Civil Engineering and Management, 13(3),
pp.169-176.
Arditi, D. and Pattanakitchamroon, T., 2006. Selecting a delay analysis method in resolving
construction claims. International Journal of Project Management, 24(2), pp.145-155.
Assaf, S.A. and Al-Hejji, S., 2006. Causes of delay in large construction projects. International
Journal of Project Management, 24(4), pp.349-357.
Borse, M. and Khare, P., Analysis of Cost and Schedule Overrun in Construction Projects,
International Journal of Innovative Science, Engineering & Technology, 3(1) pp. 383-386
Caliendo, L. and Rossi-Hansberg, E., 2011. The impact of trade on organisation and
productivity (No. w17308). National Bureau of Economic Research, pp.1393-1467
Chan, P.W. and Kaka, A., 2007. Productivity improvements: understand the workforce
perceptions of productivity first. Personnel Review, 36(4), pp.564-584.
Construction Industry Development Board (CIDB). 2015. Labour and work conditions in the
175
South African Construction Industry. Pretoria, South Africa: CIDB.
Chen, L. and Luo, H., 2014. A BIM-based construction quality management model and its
applications. Automation in construction, 46, pp.64-73.
Chia, F.C., Skitmore, M., Runeson, G. and Bridge, A., 2014. Economic development and
construction productivity in Malaysia. Construction Management and Economics, 32(9),
pp.874-887.
Dai, J., Goodrum, P.M. and Maloney, W.F., 2007. Analysis of craft workers' and foremen's
perceptions of the factors affecting construction labour productivity. Construction
Management and Economics, 25(11), pp.1139-1152.
Dai, J., Goodrum, P.M. and Maloney, W.F., 2009. Construction craft workers’ perceptions of
the factors affecting their productivity. Journal of Construction Engineering and
Management, 135(3), pp.217-226.
Dai, J. and Goodrum, P.M., 2010. Differences in perspectives regarding labour productivity
between Spanish-and English-speaking craft workers. Journal of Construction Engineering
and Management, 137(9), pp.689-697.
Dudek-Burlikowska, M., 2011. Application of estimation method of customer’s satisfaction in
enterprise focused on quality. Journal of Achievements in Materials and Manufacturing
Engineering, 47(1), pp.83-96.
Durdyev, S., Ihtiyar, A., Ismail, S., Ahmad, F.S. and Bakar, N.A., 2014. Productivity and
Service Quality: Factors Affecting in Service Industry. Procedia-Social and Behavioral
Sciences, 109, pp.487-491.
Durdyev, S. and Mbachu, J., 2011. On-site labour productivity of New Zealand construction
industry: Key constraints and improvement measures. Construction Economics and
Building, 11(3), pp.18-33.
Enshassi, A., Kumaraswamy, M. and Al-Najjar, J., 2010. Significant factors causing time and
cost overruns in construction projects in the Gaza strip: Contractors’
perspective. International Journal of Construction Management, 10(1), pp.35-60.
Enshassi, A., Mohamed, S., Mustafa, Z.A. and Mayer, P.E., 2007. Factors affecting labour
productivity in building projects in the Gaza Strip. Journal of Civil Engineering and
Management, 13(4), pp.245-254.
Fadejeva, L. and Melihovs, A., 2010. Measuring Total Factor Productivity and Variable Factor
Utilisation: Sector Approach, the Case of Latvia. Eastern European Economics, 48(5), pp.63-
101.
Ferreira, A. and Du Plessis, T., 2009. Effect of online social networking on employee
productivity, pp. 1-16
Forsythe, P., 2015. Monitoring customer perceived service quality and satisfaction during the
construction process. Construction Economics and Building, 15(1), pp.19-42
Ghoddousi, P. and Hosseini, M.R., 2012. A survey of the factors affecting the productivity of
construction projects in Iran. Technological and Economic Development of Economy, 18(1),
pp.99-116.
Hiyassat, M.A., Hiyari, M.A. and Sweis, G.J., 2016. Factors affecting construction labour
productivity: a case study of Jordan. International Journal of Construction Management, pp.1-
12.
Iyer, K.C. and Jha, K.N., 2005. Factors affecting cost performance: evidence from Indian
construction projects. International Journal of Project Management, 23(4), pp.283-295.
Jarkas, A.M., 2015. Factors influencing labour productivity in Bahrain's construction
industry. International Journal of Construction Management, 15(1), pp.94-108.
Josephson, P.E. and Chao, M., 2014. Use and non-use of time in construction of new multi-
dwelling buildings in Sweden. International Journal of Construction Management, 14(1),
pp.28-35.
Kaliba, C., Muya, M. and Mumba, K., 2009. Cost escalation and schedule delays in road
construction project in Zambia. International Journal of Project Management, 27(5),
pp.522-531.
Kaming, P.F., Olomolaiye, P.O., Holt, G.D. and Harris, F.C., 1997. Factors influencing
176
craftsmen's productivity in Indonesia. International Journal of Project Management, 15(1),
pp.21-30.
Kazaz, A. and Ulubeyli, S., 2007. Drivers of productivity among construction workers: A study
in a developing country. Building and Environment, 42(5), pp.2132-2140.
Kazaz, A., Manisali, E. and Ulubeyli, S., 2008. Effect of basic motivational factors on
construction workforce productivity in Turkey. Journal of Civil Engineering and
Management, 14(2), pp.95-106.
Lim, E.C. and Alum, J., 1995. Construction productivity: issues encountered by contractors in
Singapore. International Journal of Project Management, 13(1), pp.51-58.
Loushine, T.W., Hoonakker, P.L., Carayon, P. and Smith, M.J., 2006. Quality and safety
management in construction. Total Quality Management and Business Excellence, 17(9),
pp.1171-1212.
Makulsawatudom, A., Emsley, M. and Sinthawanarong, K., 2004. Critical factors influencing
construction productivity in Thailand. The Journal of KMITNB, 14(3), pp.1-6.
Memon, A.H., Rahman, I.A., Abdullah, M.R. and Azis, A.A.A., 2011. Factors affecting
construction cost in Mara large construction project: the perspective of project management
consultant. International Journal of Sustainable Construction Engineering and
Technology, 1(2), pp.41-54.
Naoum, S.G., 2016. Factors influencing labour productivity on construction sites: A
state-of-the-art literature review and a survey. International Journal of Productivity and
Performance Management, 65(3), pp.401-421.
Olomolaiye, P.O., Wahab, K.A. and Price, A.D., 1987. Problems influencing craftsmen's
productivity in Nigeria. Building and Environment, 22(4), pp.317-323.
Park, H.S., Thomas, S.R. and Tucker, R.L., 2005. Benchmarking of construction
productivity. Journal of Construction Engineering and Management, 131(7), pp.772-778.
Phusavat, K., 2013. Productivity Management in an Organization: Measurement and
Analysis. ToKnowPress Monographs, pp. 1- 214
Rivas, R.A., Borcherding, J.D., González, V. and Alarcón, L.F., 2011. Analysis of factors
influencing productivity using craftsmen questionnaires: A Case study in a Chilean
construction company. Journal of Construction Engineering and Management, 137(4), pp.312-
320.
Sambasivan, M. and Soon, Y.W., 2007. Causes and effects of delays in Malaysian construction
industry. International Journal of Project Management, 25(5), pp.517-526.
Sezer, A.A. and Bröchner, J., 2014. The construction productivity debate and the
measurement of service qualities. Construction Management and Economics, 32(6), pp.565-
574.
Sun, M. and Meng, X., 2009. Taxonomy for change causes and effects in construction
projects. International Journal of Project Management, 27(6), pp.560-572.
Tangen, S., 2005. Demystifying productivity and performance. International Journal of
Productivity and performance management, 54(1), pp.34-46.
Teng, H.S.S., 2014. Qualitative productivity analysis: does a non-financial measurement
model exist? International Journal of Productivity and Performance Management, 63(2),
pp.250-256.
Thomas, A.V. and Sudhakumar, J., 2013. Critical analysis of the key factors affecting
construction labour productivity–An Indian Perspective. International Journal of Construction
Management, 13(4), pp.103-125.
Van Ark, B., 2014. Total factor productivity: Lessons from the past and directions for the
future (No. 271). National Bank of Belgium pp. 1-2
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Traffic Demand Determinants: A Review of Long-Term
Scenario Effects Chioma Okoro, Innocent Musonda and Justus Agumba
Department of Construction Management and Quantity Surveying
University of Johannesburg, South Africa
Email: chiomasokoro@gmail.com, imusonda@uj.ac.za, jagumba@uj.ac.za
Abstract:
Transportation infrastructure provision is critical to the development of urban areas. Transport
infrastructure such as roads, bridges, and ports are increasingly becoming the corner stone in
determining the strength of cities, improving the quality of lives and overall socio-economic
development and growth of economies. However, these projects are stochastic in nature and
fraught with uncertainties which, if not accurately predicted, can lead to inadequate assessment
and management of risks. The aim of the present paper is to identify critical factors which
moderate traffic demand over a long period of time, and which should ideally be included in
transport demand forecasts. A detailed review of literature was conducted from online journals,
conference proceedings and theses using databases including Science Direct, Ebscohost,
Google, Emerald and ASCE Library. Fifteen of the studies which were directly related to the
subject matter were used to analyse and rank emerging factors. The level of economic activity
and introduction of new transport developments appeared to be the most influential factors
affecting travel demand. These findings provide valuable evidence for more accurate
estimation of travel demand forecasts to allow for adequate management of risks in
infrastructure planning, and for public policy.
Keywords:
Forecasting, infrastructure, planning, traffic demand, transport performance
1 Introduction Transport infrastructure, such as roads, railways, airports and bridges, facilitates mobility of
people and specialized products and services which are essential for development and growth
and enhances the value of land within the locality in which they are provided (Brown-
Luthango, 2011). They make the location of households and their business and social activities
more attractive and lucrative and increase demand for properties (Robins, 2015). Furthermore,
employment opportunities are created for unskilled workers during construction and taxi
ferrying of passengers to neighbouring areas (Robins, 2015). Suffice to say, transport
infrastructure contributes to economic growth and social welfare (Doll et al., 2009). However,
these projects are complex, stochastic and fraught with uncertainties, and if not accurately
predicted, can lead to inadequate assessment and management of risks. Transport infrastructure
such as highways and railways, usually start with a single primary function (for instance, the
interconnection of several urban nodes on a line of infrastructure), but in practice can become
very complex. Along the line, they have to deal with the varying emerging purposes and
interests in ever-changing and unpredictable context of possibilities, risks and constraints (Salet
et al., 2013).
Risk and uncertainty are issues of increasing concern in transport planning and inaccurate travel
demand forecasts represent a major source of risk in the planning of infrastructure projects
(Welde and Odeck, 2011). The proclivity to overestimate the demand for transportation
infrastructure projects is profound. Travel demand forecasts appear to be uncertain, highly
inaccurate and often displaying a concerning degree of bias (Nicolaisen et al., 2012).
According to Flyvberg et al. (2006), inaccurate forecasts, especially with a large margin, result
178
in substantial financial and economic risks which are profound, whatever the project. It appears
that for most rail transportation projects, overestimation is common, with an average of 106%
in 90% of the forecasted rail projects; while roadway traffic forecasts often underestimate the
actual demand.
Likewise, van der Westhuizen (2007) argue that road projects around the world tend to
notoriously underestimate demand by as much as 40%. In the author’s opinion, proper risk
analyses are not conducted and this results in substantially underestimated costs and risks.
These views are echoed in Nicolaisen et al. (2012) who studied road and rail projects in
Scandinavia and the United Kingdom and found an average overestimation of road projects by
11.12%. According to Nicolaisen et al. (2012), there was a tendency for non-toll road projects
to be underestimated, whereas toll road and rail projects were overestimated. Parthasarathi and
Levinson (2009) reached different conclusions, stating that highways, which have higher
volumes and functional classifications, were generally underestimated. Such transport projects
whose traffic demand forecasts were underestimated led to multi-million pound deficits
because it was much more expensive to add capacity to the existing fully used roads than it
was to build the capacity up front. The situation in South Africa is no different. Recently, it
was reported that the Gautrain service demand was also underestimated, with passengers
exceeding the forecasted number four years earlier than expected (Nicolaides, 2016).
Consequently, more trains are required to cater for the current demand.
Therefore, estimates of the financial viability of projects are heavily dependent on the accuracy
of traffic demand forecasts. Decision makers and investors base their investment decisions on
the outcome of transport service demand forecasts. Furthermore, for highway infrastructure,
traffic demand risk and risk factors associated with the project revenue are extremely critical
because revenue from the traffic volume is almost the only source of capital recovery and
profits from investments (Jeerangsuwan et al., 2014). Due to the complex interaction between
transport related activities and other parts of society, there is a wide range of impacts that are
desirable to evaluate when appraising transport infrastructure projects (Nicolaisen et al., 2012).
These include inter alia forecasting methodology used (Flyvberg et al., 2006; Nicolaisen et al.,
2012), incomplete information/availability/accessibility and type of data used (Locateli and
Mancini, 2010; Nicolaisen et al., 2012; Litman, 2016), road quality/capacity improvement
(Holmgren, 2013; Jeerangsuwan et al., 2014; Feng et al., 2015), managerial control, nature of
the project, and time lapses between construction life cycle phases (Flyvberg et al., 2006;
Holmgren, 2013). Other factors include variables related to the dynamics of demand for
transport service and particular modes. These include inter alia, tax policies and legislation
(Musso et al., 2012; Feng et al., 2012); competing alternative modes in terms of parking
availability, travel time, comfort, security, etc. (Wardman, 2006; Taylor, 2008; Zou et al.,
2011; Panou, 2014); level of economic activity (gross domestic product – GDP) (Wardman,
2006), living conditions and quality of life, cultural habits and societal norms (Zou et al., 2011;
Jarv et al., 2012); as well as demographic factors such as income, employment and age
(Nicolaisen et al., 2012).
Although these impacts have been extensively researched, there is a need to constantly update
parameters and framework of demand variables, in particular, to accommodate their influence
and make reliable decisions (Wardman, 2006; Holmgren, 2013). Moreover, it appears that few
studies have focused on factors which potentially influence transport service demand in the
long run. More often than not, short-term issues are often considered in forecasting models
whereas long-term variables which reflect underlying drivers are rarely incorporated (Havenga
and van Eeden, 2011). In contemporary times of major infrastructure spend in the developing
world, and in the developed world as well, where infrastructure spend is attempted as a
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stimulus, underlying determinants over far longer periods should be considered (Havenga and
van Eeden, ibid.). Furthermore, some literature focused on rail (Wardman, 2006) and air
(Panou, 2014) transport service demand.
The objective of the present paper is therefore to identify factors which influence the demand
for road transport service in the long run. The paper incorporates factors which chiefly motivate
the demand for road transport services in relation to potential scenarios which could manifest
in the long run. In the context of transport planning, scenarios adhere closely to the consensus
definition of “narratives or sets of assumptions that explore plausible trajectories of change”
(Liu, Balali, Wei and Peña-Mora, 2015), either in the short run (1 or 2 years), medium (5 to 7
years) or long run (more than 10 years) (Paulley et al., 2006; Musso et al., 2013). In addition,
road transport infrastructure will be dwelt on because as Jarv et al. (2012), Musso et al. (2012),
Holmgren (2013), Jeerangsuwan et al. (2014) and Litman (2016) rightly opined, inclusion of
factors which moderate the demand for a particular transport service is vital since projects
develop and perform differently while in operation. The succeeding section discusses the
method employed to conduct the study. Findings from the literature synthesis are presented
and discussed thereafter; followed by a concluding section.
2 Research Methodology
The present paper reports on an initial literature study on factors influencing travel demand,
especially in the long run. A detailed review was performed of literature spanning an 11-year
period from 2006 to 2016 from electronic databases and search engines including Science
Direct, Emerald, Ebscohost, Academic Search Complete, Google and ASCE. The following
keywords were used: demand, traffic, travel, transport. These were combined with other words
and phrases including long-term, short-term, forecasting, and highway services demand.
Various sources were consulted and a distillation of the extant literature was conducted using
journal articles, conference papers, magazine articles, book chapters, organisations’ web
articles, theses and dissertations. Articles were sought based on their possession of the
keywords and therefore relation to the subject. A total of 31 articles, which were all relevant to
the subject matter (traffic demand) were reviewed for the entire study, but only sixteen were
summarized in a table with the emerging themes (influencing factors) in order to rank and
identify the most influential factor or group of factors which could influence traffic demand
based on their percentage occurrence among the sampled studies.
3 Literature Review As stated earlier, scenarios which explore plausible trajectories of change such as new
developments, additional capacity or expansion, changes in policy and legislation, etcetera,
and their influence on traffic demand are reviewed in this section.
3.1 Highway Capacity Improvement
According to Nӕss et al. (2012), the traffic generating effects of road capacity expansion are
still often neglected in transport modelling and this omission can lead to grave bias in
environmental impact assessments as well as the economic viability of proposed road projects,
especially in situations where there is a latent demand for more road capacity. This study
assessed travel time saving, economic and environmental impacts of a proposed road project
in Copenhagen. The authors advocated the inclusion of induced traffic demand resulting from
capacity improvement or road expansion and its positive implications including travel time
savings, as well as negative consequences including noise and emissions. However, the study
did not include other long-term effects of road capacity expansion such as increased car
180
ownership, increase in land use and changes in commuter patterns, all of which positively
influence traffic demand.
Concurring with these views, Litman (2016), in his study, demonstrated the elasticity of traffic
volume in relation to road capacity expansion and found that more automobile-dependent urban
fringe development is encouraged with highway capacity improvement. In other words,
expanding urban roads brings about additional vehicle travel typically referred to as generated
traffic, which should be taken into account in traffic demand estimation.
In addition, capacity expansion results in reduced congestion. Congestion impacts on travel
behaviour by diverting traffic to alternative routes, destinations, times and modes, and reducing
trip length and frequency (Jarv et al., 2012). According to Litman (2016), roadway
improvements that alleviate congestion reduce the generalized cost of driving, making driving
cheaper per mile or kilometre in terms of travel time and vehicle operating costs. However,
Musso et al. (2012) argued that even when travelers appreciate the change in travel costs, their
travel behaviour is mostly affected by habits (such as leisure trips, workplace and residential
locations) which may eventually change gradually over the long run.
3.2 Level of Economic Activity
According to Musso et al. (2013), traffic demand is influenced by economic activity levels
(represented by the Gross Domestic Product) or trends in an economy. This study investigated
the effect of policy changes as a result of economic recession and subsequent price changes on
traffic demand on a Greek motorway corridor. The authors opined that over time, price effects
are taken into consideration by road users when making long-term decisions. The study further
revealed that the Greek economic recession which brought about budget adjustments and tax
policy changes increased fuel taxes and toll fares and as a result, traffic flows fell significantly
(20.5%) over a five-year period, especially on toll roads since people tended to avoid such
routes, a view shared in a South African study on the e-toll road project in Gauteng (Matsiliza,
2016). Although tax policies (added to fuel price) and toll road fares are sustainable means
through which federal governments fund infrastructure (Ngowi et al., 2006), unfavourable tax
policies and toll legislations result in unwelcome travel price increases and generalized cost,
which in turn have a long-run effect on traffic demand (Musso et al., 2012; Feng et al., 2012).
Similarly, Wardman (2006) reported that the level of economic activity causes variations in car
costs and journey times in Great Britain. Although this study dwelt on demand factors for rail
travel, it explored external factors which could influence diversion to other modes of transport
(including roads). The level of economic activity was identified as one of the external factors
which appear to be beyond the control of a particular transport mode.
The influence of economic activity was further evinced in Alasad et al. (2012) in which it was
opined that economic growth increases the level of income and thus purchasing power of
potential facility users. Additionally, more people could migrate to the area resulting in
increased demand. This mixed-methods study developed a system dynamics-based model to
determine interrelations between traffic demand factors which should be recognised in travel
demand forecasting models. However, only public-private partnership (PPP) projects were
included in the study.
3.3 Competing Alternative Transport Modes
Competing alternative modes of transport are external influences beyond the control of a
particular mode or form of transport (Wardman, 2006). Travel time, length of trip, frequency
of trips or waiting times, walking distance from stations as well as park-and–ride possibilities
181
influence decisions made about use of a particular mode of transport (Holmgren, 2013; Panou,
2014). According to Zou et al. (2011), commuters are increasingly paying attention to the most
economical mode of transport, the lowest energy consumption and pollution-free traffic modes.
Reasonable transport modes, which offer a swift, secure and comfortable trip, advance social
economy and reduce pollution and destruction of the environment to a maximal extent. In
addition, the ease with which desired destinations may be reached or the ease with which people
are able to participate in desired activities in different locations at a specific time determines
the use of a particular mode of transport (Taylor, 2008).
3.4 New Developments
According to Paaswell (2013), new transport developments increase access in a given locality
and results in travel time savings; and access increases demand for developments (not limited
to transport). Development in turn increases demand for travels, in addition to needs for
additional energy, water, new bandwidth for IT and communications, which in turn attracts
more people to the locality, resulting in urbanization and urban sprawl, which in turn increases
demand for transport service (Bhatta, 2010; Jarv et al., 2012). However, Nӕss et al. (2012)
argued that travel time saving benefits not materialize due to additional traffic, since demand
could become so high on the new infrastructure that congestion occurs.
In the study by Alasad et al. (2012), it was revealed that the introduction of new highways,
could have positive and negative, direct and indirect, systematic and localised effects on travel
demand. Employment opportunities and enhanced productivity due to additional economic
activities (such as construction, agriculture and manufacturing) may apparently sprout along
and around the new development, which can trigger a significant increase in employment and
income. This will in turn result in a positive impact on the local economy in general in terms
of establishment of businesses (such as restaurants, retail stores, and fuel and service stations)
along the highway and in the proximity of the development. For example, it was declared that
the realisation of the second Peace Bridge between Canada and USA facilitated $29 billion in
trade and contributed to the construction of an international trade complex in the adjoining
area. On the other hand, the growth in the local economy could lead to increase and change in
demography which has tremendous implications (increase) on demand for the usage of the
subject facility.
3.5 Land Use Changes
The study by Jarv et al. (2012) revealed that urban sprawl in turn results in varying land use
changes which influence traffic demand. This study explored the relationship between
suburban land use (in terms of road usage for different purposes such as work, leisure,
shopping, etcetera), and transportation. The authors determined that land use changes due to
suburbanization and urban sprawl influence traffic demand. The authors further observed that
societal structures and dynamics including growth in prosperity, shift in labour market,
globalization (constant increase in movement of people, goods and information, adoption of
information and telecommunication technologies and growing social networks influence travel
behaviour in the long run.
3.6 Willingness to Pay
The studies by Alasad et al. (2012; 2013) demonstrated the influence of willingness to pay for
transport services on travel demand. The willingness to pay is in turn motivated by the quality
of service, historical experience of paying for similar service, benefits from using the facility,
182
income and user wealth. On the other hand, the level of fee charged for the use of the service
(toll charges) negatively affects user’s willingness to pay, which reduces the demand.
4 Findings and Discussion
Summarily, the factors influencing travel demand could be classified into environmental or
project-specific factors (including road capacity improvement, new developments, alternative
land uses, traffic congestion) (Alasad et al., 2012; Nӕss et al., 2012); economic and financial
factors (consisting of policies, population, level of economic activity, fuel price changes,
vehicle price and operating costs and time value (Wardman, 2006; Musso et al., 2012;
Holmgren, 2013); and socio-cultural factors (encompassing living conditions/quality of life,
leisure time, car ownership, business time, walk distance from station, competition with other
modes of transport (travel time, park and ride possibilities, and waiting time for
rides/frequency) and security (Zou et al. 2011; Holmgren, 2013; Panou, 2014). However, these
factors interact with one another and cannot be considered in isolation. Factors such as level of
income, lifestyles, car ownership, living conditions/quality of life, and employment levels are
influenced by the level of economic activity with resultant positive effects on travel demand
(Khoo, 2012; Musso et al., 2012; Holmgren, 2013). As people become wealthier, the
proportion of income devoted to transport increases, implying an increased demand (Musso et
al., 2013).
Although literature noted that these factors are inter-dependent and do not influence traffic
demand in isolation (Wardman, 2006; Jarv et al., 2012) and further acknowledged that
elasticity values of traffic and the magnitude of influence are mainly determined by economic,
financial conditions, and geographical frameworks (Musso et al., 2013), the factors considered
to be most influential on travel demand were not indicated. In an attempt to fill this gap, the
current paper attempts to rank the factors according to their frequency of occurrence in the
literature selected and reviewed. The results are shown in table 1. Associated effects and their
impact (positive or negative) on travel demand are highlighted, as suggested in both studies by
Alasad et al. (2012; 2013).
From the table, it can be seen that the level of economic activity ranked highest with a
percentage occurrence of 44% (R=1); followed by introduction of new developments (roads)
with a percentage occurrence of 38% (R=2). Alternative and competing land uses, socio-
economic status and socio-cultural factors ranked third with a percentage occurrence of 31%,
respectively. This suggests that the level of economic activity which influence the level of
income, quality of life and car ownership capabilities of citizens or users of the road, influences
the demand for that project’s service (Alasad et al., 2012; 2013). On the other hand,
improvement in capacity (R=6) seemed to be the least influential factor considered in the
reviewed literature as evinced by its percentage occurrence (25%) and ranking. These findings
seemingly suggest that with regard to traffic demand, the expansion or rehabilitation of
dilapidated roads would not have as much influence on the demand for the subject route as
much as the level of economic activity and development of new roads would have on the travel
demand in an area. These findings would inform transport infrastructure planners and investors
on factors that could potentially cause the most variations in demand and make proper
allowances for them in order to arrive at more accurate transport performance forecasts (with
regard to traffic demand). Therefore, attention to these identified factors will reduce
uncertainties regarding traffic demand in pre-project planning and result in greater accuracy in
the estimation of travel demand.
5 Conclusion
183
The study sought to identify critical factors which moderate traffic demand in the short and
long term, and which should ideally be included in transport demand forecasts. The objective
has been met. The most influential factors identified as gathered from the modal investigation,
which include level of economic activity and introduction of new developments, should be
given priority in traffic demand considerations during pre-project planning in order to ease
decision-making regarding investment and development of proposed infrastructure. This is
because policy makers and investors usually base their decisions to invest or prioritise among
different competing projects and with limited availability of resources based on the potential
or envisaged outcomes of the projects. More accuracy in forecasting during transport
infrastructure planning will achieved if all potentially demand-related determinants are
included. Since forecasting is a vital input for broader policy-making in land use decisions,
economic growth and environmental impact assessments and cost-benefit analysis, the findings
of this study would influence transport policy and investment decisions. The current study has
one obvious limitation, being a review paper. Therefore, future studies could explore the
relationship between and amongst the identified factors and traffic demand variations as well
as prediction accuracy, using alternative research techniques.
6 Acknowledgement
The present paper is part of an on-going doctoral research project being funded by the
University of Johannesburg through its Global Excellence and Stature Scholarship.
7 References Alasad, R., Motawa, I. and Ogunlana, S. (2012). A system dynamics-based method for demand
forecasting in infrastructure projects - A case of PPP projects. In: Smith, S.D (Ed) Procs
28th Annual ARCOM Conference, 3-5 September 2012, Edinburgh, UK, Association of
Researchers in Construction Management, 327-336. Alasad, R., Motawa, I. and Ogunlana, S. (2013). A system dynamics-based model for demand
forecasting in PPP infrastructure projects - A case of toll roads. Organization, Technology
and Management in Construction, 6(2):791-798.
Bhatta, B. (2010). Causes and Consequences of Urban Growth and Sprawl. Ch. 2 in Analysis
of Urban Growth and Sprawl from Remote Sensing Data pp. 17-36. Springer.
Brown-Luthango, M. (2011). Capturing land value increment to finance infrastructure
investment: Possibilities for South Africa. Urban Forum, 22:37-52.
Doll, C., Durango-Cohen, P. L. and Ueda, T. (2009). Transportation infrastructure planning,
management and finance. Journal of Infrastructure Systems, 15(4):261-262.
Feng, Z., Zhang, S. and Gao, Y. (2015). Modeling the impact of government guarantees on toll
charge, road quality and capacity for BOT road projects. Transportation Research Part A,
78: 54-67.
Flyvbjerg, B., Holm, M. K. S. and Buhl, S. L. (2006). Inaccuracy in traffic forecasts. Transport
Reviews, 26(1):1-24.
Havenga, J. H. and van Eeden, J. (2011). Forecasting South African containers for international
trade. Journal of Transport and Supply Chain Management, 170-185.
Holmgren, J. (2013). An analysis of the determinants of local public transport demand focusing
the effects of income changes. Eur. Transp. Res. Rev., 5:101-107.
Jarv, O., Ahas, R., Saluveer, E., Derudder, B. and Witlox, F. (2012) Mobile phones in atraffic
flow: A geographical perspective to evening rush hour traffic analysis using call detail
records, 7(11):e49171.
Jeerangsuwan, T., Said, H., Kandil, A. and Ukkusuri, S. (2014). Financial evaluation for toll
road projects considering traffic volume and serviceability interactions. Journal of
Infrastructure Systems, 20(3): 1-9.
184
Khoo, H. L., Ong, G. P. and Khoo, W. C. (2012). Short-term impact analysis of fuel price
policy change on travel demand in Malaysian cities. Transportation Planning and
Technology.
Litman, T. (2016). Generated Traffic and Induced Travel: Implications for Transport Planning.
Victoria Transport Policy Institute.
Liu, M., Balali, V., Wei H. and Peña-Mora, F. A. (2015). Scenario-based multi-criteria
prioritization framework for urban transportation projects. American Journal of Civil
Engineering and Architecture, 2015, Vol. 3, No. 6, 193-199.
Locateli, G. and Mancini, M. (2010). Risk management in a mega-project: The universal EXPO
2015 case. International Journal of Project Organisation and Management, 2(3): 236-253.
Matsiliza, N. S. (2016). Critical factors in respect of managing the e-toll road project in
Gauteng, South Africa. African Journal of Hospitality, Tourism and Leisure, 5(1): 21-38.
Musso, A. Piccioni, C. Tozzi, M. Godard, G., Lapeyre, A. and Papandreou, K. (2012). Road
transport elasticity: How fuel price changes can affect traffic demand on a toll motorway.
Procedia: Social and Behavioural Sciences, 87: 85-102.
Musso, A., Godard, G., Lapeyre, A., Papandreou, K., Piccioni, C. and Tozzi, M. (2013). The
impact of fuel price changes on traffic demand: The case of a Greek motorway corridor.
13th World Conference on Transport Research, 15-18 July, Rio de Janeiro, Brazil.
Ngowi, A. B., Pienaar, E. and Akindele, O. (2006). Globalisation of the construction industry:
Preview of infrastructure planning. Journal of Financial Management of Property and
Construction, 11(1): 45-57.
Nicolaides, G. (2016). Gautrain needs 48 more carriages to keep up with current demand.
Eyewitness News, 12 January.
Nicolaisen, M. S., Ambrasaite, I. and Salling, K. M. (2012). Forecasts: Uncertain, inaccurate
and biased? Proceedings of the Annual Transport Conference. Aalborg University.
Nӕss, P. Nicolaisen, M. S. and Strand, A. (2012). Traffic forecasts ignoring induced demand:
A shaky fundament for cost-benefit analysis, EJTIR, 12(3): 291-309.
Paaswell, R. E. (2013). Infrastructure investment decision-making: The emerging roles of
planning and sustainability. Urban Public Transportation Systems, 395-404.
Panou, K. (2014). Factors influencing car user propensity to to shift to other modes and their
impacts on demand for airport parking facilities. Journal of Airline and Airport
Management, 4(1): 26-47.
Parthasarathi, P. and Levinson, D. (2009). Post construction evaluation of forecast accuracy.
Minnesota: Department of Transport.
Robins, G. (2015). The Dube Trade Port-King Shaka international airport mega-project:
Exploring impacts in the context of multi-scalar governance processes.
Salet, W. Bertolini, L. and Giezen, M. (2013). Complexity and uncertainty: Problem or asset
in decision making of mega infrastructure projects. International Journal of Urban and
Regional Research, 37(6):1984-2000.
Taylor, M. A. P. (2008). Critical transport infrastructure in urban areas: Impacts of traffic
incidents assessed using accessibility-based network vulnerability analysis. Growth and
Change, 39(4): 593-616.
Van der Westhuizen, J. (2007). Glitz, glamour and the Gautrain: Megaprojects as political
symbols. Politikon, 34(3): 333-351. Wardman, M. (2006). Demand for rail travel and the effects of external factors. Transportation
Research Part E: Logistics and Transportation Review, 42(3): 129-148.
Welde, M. and Odeck, J. (2011). Do planners get it right? The accuracy of travel demand
forecasting in Norway, EJTIR, 11(1): 80-95.
185
Zou, S., Peng, Y., and Mei, Z. (2011). Research on the new methgod of forecasting model of
urban passenger traffic. pp. 2673-2680. 11th International Conference of Chinese
Transportation Professionals, 14-17 August, Beijing, China.
Table 1. Summary of factors influencing travel demand
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Influence of Administrative and Political Authorities’
Decisions on the Construction of Community Development
Projects in India Dillip Kumar Das
Central University of Technology, Free State, South Africa
Email: ddas@cut.ac.za
Abstract:
Construction of community development projects, particularly in rural areas of India is a
challenge. Administrative and political authority decisions play a major role on the construction
of these projects. Therefore, the objectives of the investigation are (1) to explore how and to
what extent the administrative and political decisions influence the executive agencies at the
local level, and (2) to examine the various project parameters that get influenced by such
decisions. The investigation was conducted by using the case study of two Community
Development Blocks in Odisha State of India and by employing a survey research method.
Findings suggest that the decisions influence the construction of projects both positively and
negatively. The decisions are found to facilitate funding of projects, administrative and
technical approval of projects and build confidence among the contractors and beneficiaries;
however concurrently some of the decisions negatively influence the local executive agencies
like Block and Village panchayat authorities, technical personnel, design of projects and
quality of work, and also engender conflict among the stakeholders, thus influencing the
execution of the projects adversely. Besides, the major implications of the negative influences
of the administrative and political decisions are setting up of unrealistic target for completion
of projects, pressure on spending of funds within unrealistic period of time, poor quality of
work, delay in project execution, delay in delivery of projects, poor design of projects,
unrealistic estimated project duration, unrealistic project estimate, and conflict in project
planning and allocation.
Keywords:
Administrative decisions, Community Development Projects, Construction, Execution,
Quality of work, Stakeholders
1 Introduction
In recent years Community Development Programmes have been initiated by the governments
both at national level and state (provincial) level of India to undertake different socio-economic
welfare and reconstruction programmes. Particularly, their importance in the rural areas has
been emphasized. For, example, according to the Planning Commission of India, community
development is an attempt to bring about a social and economic transformation of village life
through the efforts of the people themselves (Mondal, 2015). Under this community
development programmes, a number of construction projects particularly in rural areas of India
have been taken up over the years under different schemes. Some of the schemes are Prime
Minister’s Gramya Sadak Yojna ((PMGSY) (Prime Minister’s Rural Road Plan), Jawahar
Rojgar Yojna (JRY) (Jawahar Employment Scheme), Members of Parliament Local Area
Development Scheme (MPLAD), Members of Legislative Assembly Local Area Development
Scheme (MLALAD), Indira Awas Yojna (IAY), etc. These schemes/programmes are usually
187
used to create social infrastructure in rural areas of the country. A number of community
development construction projects such as road construction in rural areas, building of
community centres, and schools, construction of low cost houses, construction of minor
irrigation projects, etc., are being taken up under these programs. These programmes/schemes
are generally sponsored and financed by the Central Government, and State Governments
separately or by both jointly. The implementation and execution of these projects are usually
done by the executive agencies such as District Rural Development Agencies (DRDA) and
Community Development Blocks or Gramya (village) Panchayats (councils at village level) at
the local level.
However, the local governments at the Block level and District level remain pivotal in the
decision making regarding the planning, sanctioning and execution of these projects. The local
political leaders at the District level, Block level and Village panchayat level play a major role
in the planning, construction and delivery of the projects. Similarly, the onus of the
management, execution and administration of these projects remain with the administrative
officers both at the District, and Block level, who essentially work under the policy and advices
of the Central Government and State Governments. So, decisions regarding the administrative
sanctioning, implementation, execution and completion of the projects rest largely with the
administrative authorities and political leaders (executives) at the local, District and State level.
Many times it is observed that the fate of a programme or scheme and consequent development
construction works depends of the decisions and actions of these administrative authorities and
political leaders. For example, according to World Bank (2004), public projects are often found
to be of poor quality and remain uncompleted or undelivered undermining the welfare of the
people (Banerjee et al., 2007; World Bank, 2007).
Similarly, political leader and bureaucrats are often found to be the two important agents who
are responsible for the execution, and delivery of these projects (Rogers, 2014). Besides,
according to stakeholders and community, the administrative and political decisions and
implementation actions are often taken in isolation without much consultation and concurrence
with the stakeholders such as technical personnel and community beneficiaries who have direct
stake in these projects, which cause challenges in the execution and completion of the projects
in time within the limited resources (Chapman, 2015; Lucas and Pangbourne, 2012). Although,
this is one of the critical aspects with regards to the success of construction of community
development projects, studies on it are found to be scarce. So, the objectives of the investigation
are (1) to explore how and to what extent the administrative and political decisions influence
the executive agencies at the local level, and (2) to examine the various project parameters that
get influenced by- and implications of such decisions. The study was conducted by using the
case study of two Community Development Blocks in Odisha State of India. A survey research
method was followed for this purpose. Findings suggest that the important decisions that are
usually taken by the administrative and political authorities at the district and local level on
priority include decisions relating to project allocation, fund allocation to projects, selection of
beneficiaries, and administrative approval of the projects for execution.
However, decisions relating to the use of construction methods and technology, review and
renewal of projects, staff allocation and deployment, and completion and delivery of projects
receive lower priorities. The decisions influence the construction of projects both positively
and negatively. The decisions are found to facilitate funding of projects, administrative and
technical approval of projects and build confidence among the contractors and beneficiaries;
however concurrently they negatively influence the local executive agencies like Block and
Village panchayat authorities, technical personnel, design of projects and quality of work and
188
also engender conflict among the stakeholders, thus influencing the execution of the projects
negatively. Besides, the major implications of the negative influences of the administrative and
political decisions are setting up of unrealistic target for completion of projects, pressure on
spending of funds, poor quality of work, delay in project execution, delay in delivery of
projects, poor design of projects, unrealistic estimated project duration, unrealistic project
estimate, and conflict in project planning and allocation.
The paper contributes to understand the implications of political and administrative decisions
on the technical personnel, local executive agencies and stakeholders on the construction of
community development projects based on which remedial measures can be taken to improve
the construction process and alleviate the impediments in the construction of community
development projects.
2 Research Methodology
2.1 Case Study and Profile of Projects
Two community development blocks such as Balipatna (Block 1) and Balianta (Block 2) of
Khurda district of Odisha state of India were taken as the case study areas. The investigation
was conducted by considering three types of community development projects, such as primary
schools, roads and minor irrigation projects in the two mentioned Community Development
Blocks of. Table 1 presents the profile of projects in the study areas. The projects constitute
construction and repair of 26 primary schools, 18 rural roads, and 11 minor irrigation projects.
The estimated duration of the projects varies between 6 and18 months although projects are
usually expected to be completed within one financial year. The projects were mostly funded
by either State Government or Central Government. The District Rural Development Agency
(DRDA) headed by a project director under the district collector is the nodal implementing and
supervising authority at the district level and Block Development Offices are the executive
agencies at the local level. However, the Zillaprishad (Elected District council) at District level
and Panchayat Samiti (elected council at the Community Development Block level) at the local
level are the decision making agencies with regards to the planning, implementation and
execution of the projects. Also, Gramya Panchyats (elected village level councils) are
implementation and executive agencies at the Village panchayat level.
Table 1. Profile of projects
Source: Researcher
2.2 Survey, Data and Analysis
Project characteristics Total Estimated
project
cost (USD)
range
Estimated
project
duration
(months)
Executive agency
Type of
projects
Block 1 Block 2
Schools
projects
15 11 26 3500-5000 12-18 Community
Development Blocks
Roads 11 7 18 3000-4000 6-12 Community
Development Blocks
Minor
irrigation
projects
11 6 5 2500-3500 6-12 Community
Development Blocks
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Project profiles and status of the projects were collected from archival records of the
executive agencies located at the block level and through physical survey. A stakeholders’
survey was conducted to collect primary data by using pre-tested questionnaires to find out
to what extent and how administrative decisions influence the construction projects as well
as to explore the parameters that get influenced by such decisions. The survey was
administered by employing random sampling process. The stakeholders surveyed include
administrative personnel, local leaders, contractors, engineers, school authorities/teachers,
NGOs officials, and common citizens of the villages and direct and indirect beneficiaries.
The questionnaire include type of administrative and policy decisions, parameters and
challenges with respect to project implementation and execution, project parameters
influenced by these decisions, roles and responsibilities of various stakeholders, parameters
relating to finance availability, cost of projects, contractor selection process, beneficiary
selection, duration of projects, issues relating to materials, equipment, execution and
project management issues, reviewing process, and general challenges encountered in the
projects. A sample size of totalling to 160 (90 from Block 1, 70 from Block 2) was used.
Besides, informal meetings were conducted by inviting stakeholders and engaging them in
discussions to understand the powers, roles and responsibilities of the administrative and
political leaders in the projects and their influence thereof on the success or failure of the
projects. The stakeholders’ discussion and engagement was conducted through semi-
structured interviews and informal group discussions.
Quantitative descriptive statistics analysis and Cronbach’s alpha test of the data collected
were conducted to observe the reliability of the data. An index based on average index
method and significance test (t test for α ≤ 0.05) for 95% confidence level were conducted
to observe the relationship among the variables. The index was calculated by considering
the weighted average of the perceptions of stakeholders assigned by the respondents on a
particular variable in a five-point scale ranging between -2 and +2 (-2 indicating highly
negative influence, 0 indicating neutral and +2 indicating highly positive influence) was
used to evaluate the perceptive level of influence. The formula used for calculating
perception index is given in Equation (Eq.1).
Perception index= PI= ∑Wi*Ni/ ∑Ni ..............................................................Eq. (1)
Ni= number f respondents assigning a particular index value
wi= index values assigned by respondents.
Followed by descriptive statistics analysis and significance tests were conducted to examine
the influence of administrative and political decisions on various project parameters.
3 Findings and Discussion
The results were analysed under three aspects to understand the influence of the administrative
and political decisions on community development construction projects. The three aspects on
which the analyses were made are (1) the important decisions that are taken by administrative
and political authorities with regards to community development projects, (2) influence of the
decisions on different project parameters and (3) implication of the negative influence of the
decisions on various project attributes. Before analysing the data reliability test was conducted
by using Chronbach α and the high Chronbach α (0.84) indicates that the data is reliable and
suitable for analysis.
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Table 2 presents the various important decisions that are generally taken by the administrative
and political authorities and their relative priorities with regards to community development
projects at the District and local Block level. There are about 12 types of decisions that are
usually taken. The most important and prioritise decisions are related to project allocation
(86.3%), fund allocation to projects (82.0%), selection of beneficiaries (81.4%) and
administrative approval of the projects for execution (77.0%). The next set of important
decisions are implementation of Government policies (74.2%), selection of contractors
(72.3%), use of labour intensive methods of construction (71.2%), and modes of execution of
projects (67.1%). However, decisions which receive lower priorities with respect to projects
include use of construction methods and technology (64.1%), review and renewal of projects
(62.5%), staff allocation and deployment (59.0%), and completion and delivery of projects
(57.3%). Thus, it is found that while the authorities are more concerned about taking decisions
with regards project allocation, fund allocation and selection of beneficiaries, review and
renewal of projects, staff allocation and deployment and completion and delivery of projects
are highly undermined.
Table 2. Important decisions taken by administrative and political authorities
Decision N Agreed by
% of
stakeholders
Priority of
the
decisions
Project allocation 160 86.3 1
Administrative approval of the projects 148 77.0 4
Fund allocation 144 82.0 2
Staff allocation and deployment 151 59.0 11
Implementation of Government policies 155 74.2 5
Completion and delivery of projects 157 57.3 12
Modes of execution 143 67.1 8
Use of construction methods and technology 145 64.1 9
Use of labour intensive methods of
construction
146 71.2 7
Selection of beneficiaries 156 81.4 3
Selection of contractors 148 72.3 6
Review and renewal of projects 152 62.5 10
Source: Researcher
Table 3 presents the relative influence of administrative and political decisions on different
project parameters. Findings suggest that the decisions have highly positive influence on
funding of projects (PI= 1.40), administrate approval (PI= 1.25), and technical approval of
projects (PI=1.10). Similarly, estimated cost of projects, estimated duration of projects,
beneficiaries and contractors are fairly positively influenced by the decisions However, on the
contrary, the decisions have very high negative influence on local executive agencies (PI= -
1.30) and technical personnel (PI= -1.05). Similarly, the decisions also cause conflict among
stakeholders (-0.95), fairly negatively influence design (PI=-0.90), quality of work (PI=-0.82)
and completion of the projects (PI=-0.75). Thus, it is evident that the administrative and
political decisions have both positive and negative influences on important project parameters.
In other words, while the decisions facilitate funding of projects, administrative and technical
approval of projects and build confidence among the contractors and beneficiaries, they have
highly negative influence on the local executive agencies like Block and Village panchayat
authorities, technical personnel, design of projects and quality of work. The decisions also
engender conflict among the stakeholders, thus influencing the execution of the projects
negatively.
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Table 3 Relative influence of administrative and political decisions on different project parameters
Parameter N Perceptive level of
influence (PI)
Standard
deviation (SD)
Administrative approval 160 1.25 0.19
Technical approval 155 1.10 0.12
Funding of projects 160 1.40 0.22
Estimated cost 145 0.55 0.06
Estimated duration 155 0.45 0.08
Influence of local executive agencies 154 -1.30 0.24
Influence on contractors 148 0.25 0.05
Influence of beneficiaries 156 0.35 0.04
Influence of completion of projects 156 -0.75 0.26
Design of projects 148 -0.90 0.15
Quality of work 155 -0.82 0.12
Conflict among stakeholders 158 -0.95 0.08
Influence on Technical personnel 152 -1.05 0.05
(Note: Chronbach α= 0.84, p*<0.05 for α <0.05; p**<0.05 for α <0.05;
*: one tailed, **: two tailed)
Furthermore, an assessment on the implications of the three most important negative influences
revealed that the negative influence on local executive agencies cause unrealistic target for
completion of the projects, and pressure on spending the funds allotted within a unrealistic
specified period of time (p*<0.05 for α <0.05; p**<0.05 for α <0.05) (Table 4). This happens
in order to comply with the targets set by the State Government and Central Government
authorities. Similarly, Table 4 also suggests that the negative influence on technical personnel
leads to poor quality of work, delay in delivery of projects, unrealistic estimated project
duration, unrealistic project estimate, and poor design of the projects. Such scenarios occur
because of the pressure on the technical personnel to comply to the administrate and political
decisions, completion of the activities within unrealistic time frame as well as poor
communication and coordination among administrative and technical personnel, and moreover,
the technical personnel are not adequately consulted while taking decisions with regards to the
projects (p*<0.05 for α <0.05; p**<0.05 for α <0.05). Furthermore, the other negative
influence- conflict among stakeholders’ cause delay in project execution and conflict in project
allocation and project planning, which also usually adversely influence the project execution
(p*<0.05 for α <0.05; p**<0.05 for α <0.05). Thus, the major implications of negative
influence of administrative and political decisions include setting up of unrealistic target for
completion of projects, pressure on spending of funds within unrealistic period of time, poor
quality of work, delay in project execution, delay in delivery of projects, poor design of
projects, unrealistic estimated project duration, unrealistic project estimate, and conflict in
project planning and allocation.
Table 4. Implications of negative influence of the decisions on project attributes
Cause Implication T values P* P**
Influence of
local
executive
agencies
Unrealistic target for
completion of projects
2.7 0.0035 0.007
Pressure on spending
of funds
3.8 0.000095 0.00019
Influence of
technical
personnel
Poor quality of work 3.1 0.0011 0.0022
Delay in delivery of
projects
4.3 0.0000013 0.0000027
Poor design of projects 5.6 0.00000005 0.0000001
Unrealistic estimated
project duration
3.9 0.00014 0.00029
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Unrealistic project
estimate
2.8 0.0036 0.0073
Conflict
among
stakeholders
Delay in project
execution
5.9 1.77E-08 3.44E-08
Conflict in project
planning and allocation
7.6 3.61E-12 7.23E-12
Source: Researcher
4 Conclusion and Further Research
Decision-making is an important aspect in the construction of community development
projects in India. Usually the major decisions regarding to the policy, planning and execution
of projects are taken up by the administrative and political authorities at different level such as
at the Central Government, State Government, District and Block levels. The decisions have
profound impact on the local executive agency level, which influence the construction of the
projects. Although, understandably this forms a significant aspect of community development
and construction management of community development projects, much study has not been
conducted to understand the various challenges, parameters influenced by the decisions and
implication of the decisions on different project attributes. Therefore, the objectives of the
paper were to explore how and to what extent the administrative and political decisions
influence the executive agencies at the local level, and to examine the various project
parameters that get influenced by such decisions. A survey research method and case study
approach were resorted to realise the aims of the study. The study revealed that of the 12 types
of decisions are usually taken by the administrative and political authorities at the district and
local level decisions relating to project allocation, fund allocation to projects, selection of
beneficiaries, and administrative approval of the projects for execution are the prioritised ones.
However, decisions relating to the use of construction methods and technology, review and
renewal of projects, staff allocation and deployment, and completion and delivery of projects
receive lower priorities.
The administrative and political decisions have both positive and negative influences on the
project parameters. Findings suggest that decisions facilitate funding of projects, administrative
and technical approval of projects and build confidence among the contractors and
beneficiaries; however concurrently they have highly negative influence on the local executive
agencies like Block and Village panchayat authorities, technical personnel, design of projects
and quality of work and also engender conflict among the stakeholders, thus influencing the
execution of the projects negatively. Besides, it is also found that the negative influences have
profound implication on various project attributes. The major implications of negative
influence of the administrative and political decisions are setting up of unrealistic target for
completion of projects, pressure on spending of funds, poor quality of work, delay in project
execution, delay in delivery of projects, poor design of projects, unrealistic estimated project
duration, unrealistic project estimate, and conflict in project planning and allocation.
The paper contributes to understand the implications of political and administrative decisions
on the technical personnel, local executive agencies and stakeholders on the construction of
community development projects. The outcomes of the study are relevant to understand the
challenges and issues that are caused by the administrative and political decisions and their
impact on the construction projects so that remedial measures can be taken up by the concerned
authorities to improve the process of construction- and delivery of the community development
projects in India.
193
5 Acknowledgement
The author offers his sincere thanks and gratitude to the organisations and stakeholders who
participated in the survey and people who assisted in the survey and data collection process.
6 References
Banerjee, A., Iyer, L., Somanthan, R. (2007). ‘Public action for Public Goods’, In: T.P Schultz
and J. Strauss, Handbook of Development Economics, Vol (4), Amsterdam: Elsevier.
Chapman, Lee. (2015). ‘Weather and climate risks to road transport’, Infrastructure, Asset
Management, Vol. 2(2), pp. 58–68. http://dx.doi.org/10.1680/iasma.14.00032
Lucas, K. and Pangbourne, K. (2012.) ‘Transport and climate change policy in the United
Kingdom: a social justice perspective’, In: Ryley TR and Chapman L, Transport and
Climate Change (Transport and Sustainability, Volume 2), Bingley: Emerald Group, UK,
pp. 287–312.
Mondal, P. (2015). The Community Development Programme of India
(http://www.yourarticlelibrary.com/india-2/the-community-development-programme-
of-india-2405-words/4866/, Retrieved on 08.07.2016
Rogers, D. (2014). ‘The causes and consequences of political interference in Bureaucratic
decision making: evidence from Nigeria’, Job Market paper, pp. 1-43.
World Bank. (2004). World development report, 2004, Making Services work for the poor,
Washington DC: World Bank publications.
World Bank, (2007). Stolen Asset Recovery Initiative, Challenge, Opportunities and Action
Plan, Washington DC: World Bank publications.
194
Valuation of Sugarcane Farmland for Construction
Projects in Durban, South Africa S.H.P. Chikafalimani and K. Ramphal
Department of Construction Management and Quantity Surveying
Durban University of Technology, South Africa
Email: ramphalk@dut.ac.za
Abstract:
This paper is practical and describes the valuation process and challenges encountered by
property valuers and estate agents in the valuation of sugarcane farmland earmarked for
construction projects in Durban, South Africa. The study identified: receiving valuation
instruction, property inspection and collection of valuation information, analysis and
adjustment of valuation data, and valuation report writing as key steps in the valuation process
of sugarcane farmland. Challenges include: determination of acceptable comparable market
evidence to be applied in the valuation exercise, more especially for sugarcane farmland
located near to existing prime infrastructure and property development projects; and property
market speculation on the part of sugarcane farmland owners. The intention of the study is to
make construction and property practitioners, owners and other investors aware of current
challenges and factors which will assist them in the decision making processes linked to the
acquisition and determination of market values of sugarcane farmland which are significant
components in the processes of construction projects and property development.
Keywords:
Construction projects, property development and valuation
1 Introduction
The first step which most of the property developers and practitioners undertake to implement
construction projects is to acquire or buy land where the construction projects will be built.
Acquisition of land for construction projects, more especially in the cities, can present different
challenges to property owners, developers and investors which include need for proper
valuation of land which is to be purchased to ensure that a market related or reasonable price
is paid for the land. Other common challenges faced are: scarcity and expensive good urban
land for construction, rezoning of land, township establishment, subdivision of land,
consolidation of land parcels where construction will take place, and registration of land in the
deeds office. The result of shortage of land and other urban related problems being experienced
in the commercial business districts (CBD’s) in most of South African cities has been
increasing decentralisation of residential and commercial real estate developments as well as
other infrastructure developments since the election of a democratic government in 1994
(Ghyoot, 2002). Traffic congestion, high crime levels and decreasing property values are some
of the popular examples of urban problems in the CBD’s. Following from these challenges,
Durban City, just like other big cities in South Africa is equally experiencing accelerated
relocation of residential and commercial real estate developments and other major
infrastructure developments to the North of Durban. King Shaka International Airport is one
of the major infrastructure projects which was recently relocated to this area (Chikafalimani &
Ramphal, 2016). However, most of the land in this area is still under sugarcane farms. This
study specifically focuses on the valuation process of sugarcane farmland in the North of
Durban and highlights challenges encountered by property developers, owners and
195
practitioners in the acquisition or buying of sugarcane farm land in the area identified for
construction projects in the area.
2 Literature Review
Few authors and researchers have written and conducted studies on: the concept of property
value, value-forming factors of agricultural property, and valuation of sugarcane farmland.
Syagga (1994) argued that the concept of property value can be defined using two main
classifications: utility value and market value. Utility value is the value to the owner-user,
which includes the value of the amenities attached to the property, as in the case of the owner-
occupier. He adds that market value is the value in exchange, the amount of money at which
the property can be sold or exchanged at a given time or place. When one refers to the value of
a property, one generally means its market value, the price in terms of money for which a
property would sell or be rented-out in the open market. Syagga (1994) concluded that the
general value of a property is a function of its physical characteristics, location, and
government policies in the form of legislation, fiscal or monetary policies.
Physical characteristics which affect property value include among others: age, condition of
repair, quality of architectural design and finishes. With regard to main physical factors which
determine use and value of agricultural property, Cloete (1997) identified the following four
major factors as critical: type of soil; topography and slope; water source, and climatic
conditions. Soil type determines the type of crop which can be grown on the farm. Slope of the
farm plays an important role in determining the agricultural potential of the farm. Some of the
factors directly affected by the steepness of land are: soil erosion susceptibility of lands, the
potential for mechanisation of field operations and the degree of enterprise intensification.
Rainfall is the farm’s major source of water.
It provides run-off which when stored, can enhance productivity. Seasonality of streams and
rivers as well as the legalities pertaining to water rights are important facets to consider when
assessing this resource. Cloete (1997) further observed that dams and boreholes are also
important in that they increase the potential volume of water able to be utilised for farm
activities. He concludes by noting that climate is probably the single most important natural
resource governing the potential viability of a farm since it is from this resource that all other
natural resources are derived. Syagga (1994) emphasised that in general location is the main
factor contributing to property value. Location is concerned with relationships external to the
property and determines whether or not there will be demand for the services which the
property is capable of providing. The concept of location is a dynamic one and comprises of
two main components (Maritz and Ghyoot, 1990). The first component is the convenience
network which a specific property maintains with human functions that are of vital importance
to it. The second component is the exposure network of the property to the other properties in
its vicinity.
3 A Brief on Sugarcane Crop and Valuation Approach
Sugarcane Crop
Total land area under sugarcane farming in South Africa stays relatively stable at around
430,000 ha (Mulder, 2005). The sugarcane production areas extend from Eastern Cape through
KwaZulu-Natal to Mpumalanga Provinces. KwaZulu-Natal is a major producer of sugarcane
in South Africa which produced on 88.9% of all sugarcane land in South Africa (SA Cane
196
Growers, 2006). Photograph 1 of sugarcane crop in the field is given below. Sugarcane crop
prefers tropical climate which basically has warm and humid weather. Cold winters and frost
can cause damage to the crop and influence production negatively. As a consequence,
commercial sugarcane production is more limited to the sub-tropical and tropical climates of
the eastern board of KwaZulu-Natal and the lowveld of Mpumalanga Provinces (Pienaar,
2013). In addition, sugarcane grows well at low altitudes.
Duke (1983) describes seven types of soil for growing sugarcane, namely: (i) Red soils, rich in
iron and phosphorous (ii) Black soils with a clay subsoil, and poorly drained (iii) Black soils,
with a calcareous subsoil, and highly productive (iv) Brown clay loams with a stiff top soil, but
responding well to fertilisation (v) Alluvial soils of enduring fertility and easy to cultivate (vi)
Sands and sandy loams of low fertility, well drained and easy to cultivate and (vii) Soils of
organic origin. For the best results the soil should have a pH level ranging from 5.5 to 6.5.
Ranges from 4.3 to 8.4 are possible for sugarcane growth. However, Krontal (2013) noted that
too much variation of pH from the optimum range can stress sugarcane and cause reduced
growth. Importantly, prior to planting, the soil should be cultivated deeply to subsoil level and
prepared thoroughly. This gives the sugarcane extensive root system room to grow.
Furthermore, the soil should be tested to determine the proper type and amount of fertiliser to
be applied for optimum growth and production.
According to Pienaar (2013), sugarcane is propagated in South Africa by stem cuttings (10 tons
per hectare); 40,000 two-bud or 30,000 three-bud setts per hectare, aiming for a millable stalk
population target of 130,000 per hectare. He further noted that harvesting of sugarcane
commences depending on the cultivar and climate. In the irrigated areas of Mpumalanga and
KwaZulu-Natal the first crop is harvested at 14 months and thereafter every 12 months. In the
dryland areas of the KwaZulu-Natal coast the cycle is 12 months from the first ratoon crop, but
in the inland areas towards Midlands the growing cycle is 24 months. The canes become tough
and turn pale and yellow when ready for cutting. The cane is cut as close as possible to the
ground because the root end of the cane is the part richest in sugar. The rhizomes will continue
to crop for at least 3 to 4 years. Hand harvested sugar cane is usually replanted after 10 years
while machine harvested cane lands are replaced every 3 to 4 years due to compaction of the
soil and declining yields (Pienaar, 2013). A ratoon is the cane that grows from buds remaining
in the stubble left in ground after a sugarcane crop has been harvested. It is also important to
note that realistic sugarcane crop yield norms are 120 tons per hectare for sugarcane under
centre-pivot production while dryland yields on 12-month cycles are 25 tons per hectare and
40 tons per hectare on 24-month cyles (Pienaar, 2013).
197
Figure 1: Photograph 1: Sugarcane crop (Source: Researcher)
Valuation Approach of Sugarcane Farmland
Pienaar (2013) indicated that the value of sugarcane land includes the land, water entitlement
(right) and the sugarcane roots. He further added that the establishment cost forms roughly
30% of the value of a sugarcane plantation; and the value of the roots is roughly 25% of the
total value. Sugarcane crop is normally replanted after the plant crop plus the 10th ratoon crop.
The roots decline in value due to their declining productive life, as in the case of other
permanent crops. This means that the value of established sugarcane farmlands should decline
in value with age as illustrated in Table 1 below. The distance from a mill also influences the
value of sugarcane farm land and likewise the presence of tollgates between the sugarcane farm
and the mill. Sugarcane is bulky and expensive to transport. Pienaar (2013) argued that in
general the farm should preferably not be farther than 50km, or at most 70 km from the mill.
Based on the assessment of land transfer figures in the northern irrigated areas, Chadwick
(1998) observed that on an index of 100 for established irrigated sugarcane farmland, the value
of dryland sugarcane is 50% of that of the irrigated sugarcane farmland. The equivalent value
in Zululand in KwaZulu-Natal is 70%, on the North Coast 46%, on the South Coast 30% and
the value for sugarcane farmland in the Midlands is 28% of the value of irrigated sugarcane
farmland.
Table 1: Value of sugarcane farm land in relation to age
(Source: Pienaar, 2013)
3 Research Methodology
Two main research approaches were used to collect data for the study. Firstly, a literature
survey was conducted to collect data from publications focusing on the concept of property
value, valuation of agricultural property and more specifically for sugarcane farms. Secondly,
a survey of property valuers and estate agents located and practicing in the North of Durban
was conducted to determine challenges encountered and methods followed in the valuation of
sugarcane farmland for construction projects in the area. A questionnaire was designed and
sent to 25 property valuers and estate agents practicing in the selected area that were possible
to trace. To obtain quick responses, respondents were asked two open ended questions. The
first question was to mention important steps followed in the valuation of sugarcane farmland.
Secondly, respondents were asked to list challenges encountered in the valuation of sugarcane
farmland earmarked for construction projects located near to existing prime construction
projects and property developments in the North of Durban. Out of 25 questionnaires sent out,
20 questionnaires were returned representing a response rate of 80%.
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4 Findings and Discussion
Results of the survey of property valuers and estate agents which was undertaken to determine
challenges encountered and approach followed in the valuation of sugarcane farmland for
construction projects in Durban, South Africa are contained in Tables 2 and 3 below. Map 1
below shows the selected residential and commercial areas identified in the North of Durban
connected with the study. The selected areas include: King Shaka International Airport (KSIA)
and Dube Trade Port (DTP), Umhlanga, Gateway, Umdloti, La Mercy, Zimbali, Ballito,
Compensation, Tongaat and Verulam. These areas are special in the sense that they were
originally sugarcane growing areas and over the past years due to partially the decentralisation
process of real estate and infrastructure developments from Durban CBD, they were rezoned
and developed into residential and commercial areas. Some of these areas which include KSIA
and DTP, Umhlanga, Gateway, Zimbali and Ballito are currently some of the most upmarket
residential and commercial areas in Durban. However, abundant sugarcane farmland still exists
in and around these areas for construction projects. This study specifically intends to highlight
challenges encountered and the approach followed in the valuation of this sugarcane farmland
earmarked for new construction projects in an area now considered to be very prime and
upmarket in the City of Durban because to its closeness to newly built prime property and
infrastructure developments in the area.
In Table 2, all respondents (100%) mentioned that four main steps are involved in the valuation
of sugarcane farmland. According to the respondents, the first step which is undertaken by all
property valuers and estate agents in the valuation of sugarcane farmland is ‘to receive the
valuation instruction’. The respondents commented that an ‘instruction’ from the sugarcane
farm owner (client) gave the property valuers and estate agents the authority to assess the
sugarcane farm and advise the property owner its estimated market value. A well written
‘instruction’ should include legal description of the farm, street or location address, and
purpose of valuation. In Table 2, it is noted that the second step in the valuation process of a
sugarcane farm is ‘property inspection and collection of valuation information’. Property
inspection is one of the most important steps in the valuation of sugarcane farmland. At this
critical step the property valuers and estate agents collect some of the following relevant
information of the farm: location, farm size, soil type, topography, climate, sugarcane crop age
and land split, and farm improvements. During farm inspection, property valuers and estate
agents also assess the surrounding properties and services in the locality.
Property valuers and estate agents also collect property market information and evidence they
may notice during the trip in the vicinity of the farm including market prices of sugarcane farm
land in the area. ‘Analysis and adjustment of valuation data’ is the third step property valuers
and estate agents undertake in the valuation of sugarcane farmland. Valuation information
collected during farm inspection is analysed and adjusted accordingly to be in line with the
specifications of the sugarcane farm under valuation, also popularly described by the property
valuers and estate agents as the ‘subject farm’. Results of the study in Table 2 also show that
all respondents reported ‘valuation report writing’ as the final step in the valuation of sugarcane
farmland. All respondents indicated that generally a valuation report will contain some of the
following subheadings about the subject farm: Instruction, general information, title deed
information, local government information, farm description, market research, method of
valuation, and recommended value (certificate of value). Under the method of valuation, all
respondents mentioned that two main methods of valuation are combined to determine the
market value of the sugarcane farm. Firstly, depreciated replacement building cost method is
used to estimate market value of the improvements which comprise of buildings and other
199
related structures on the farm. Secondly, direct comparable sales method is used to estimate
market value of land and sugarcane crop together. Estimated values derived from the two
methods of valuation are added to arrive at the market value of the subject sugarcane farm. It
is important to note that the prices applied to estimate market value of sugarcane crop land
depend on the age of the sugarcane crop in the specific area.
Results of the survey summarising the main challenges encountered by property valuers and
estate agents in the valuation of sugarcane farmland in the North of Durban are contained in
Table 3. Unsurprisingly, it is observed that all respondents (100%) agree that determination of
acceptable comparable market sugarcane farmland prices is a challenge in the area because of
the existence of prime infrastructure and property development projects in the area. This
problem is commonly faced by government departments and financial institutions who intend
to compensate or finance infrastructure and property development projects in the area. The
matter specifically connected to this challenge is that the property owners ask for land prices
which are normally very high and are not in line with recent registered sugarcane farmland
prices in the area.
Under these circumstances it becomes a problem for property valuers and estate agents to
justify and motivate to government and financial institutions payments and funding of land to
be bought for construction projects based on sugarcane farmland prices that are not well
supported by market related registered sugarcane farmland sales in the area. This possesses a
challenge and disputes for prices to be paid for land earmarked for development at the stage of
construction investment decision-making because government and financial institutions always
want to pay and conclude land transactions based on market related evidence. It is also noted
in Table 3 that 90% of the respondents consider ‘market speculation’ as a major challenge in
the valuation of sugarcane farmland in the North of Durban. Property valuers and estate agents
believe that most of the property owners selling land in the area are asking exorbitant prices
for their land based on market speculation. This problem is due to the fact that North of Durban
is now considered by many property investors as an upmarket area and most of the available
sugarcane farmland for sale is located close to existing prime infrastructure and real estate
developments. This market perception has influenced the sugarcane farmland sellers to
speculate and sometimes demand ridiculously high prices for the land they own in comparison
to land prices already paid in the area.
Table 2: Property valuers’ and estate agents’ responses on the valuation approach of
Sugarcane farmland in the North of Durban
Response Frequency Percent (%)
1 Receiving valuation instruction 20 100
2 Property inspection and collection of valuation information 20 100
3 Analysis and adjustment of valuation data 20 100
4 Writing valuation report 20 100
Table 3: Challenges encountered by property valuers and estate agents in the North of Durban
Response Frequency Percent (%)
1 Determination of acceptable comparable market sugarcane
farm land prices
20 100
2 Market speculation (opinion without firm market evidence) 18 90
Source: Researcher
Map 2: Selected residential and commercial areas in the North of Durban
200
(Source: www.kingshakaairport.co.za, 2016-08-30)
5 Conclusion and Further Research
The aim of the study was to describe the valuation process and highlight challenges
encountered by property valuers and estate agents in the valuation of sugarcane farmland
earmarked for construction projects in the North of Durban. This was achieved by conducting
a survey of property valuers and estate agents that are practicing and were possible to trace in
the selected areas which have sugarcane farmland in the vicinity. The selected areas include:
KSIA and DTP, Umhlanga, Gateway, Umdloti, La Mercy, Zimbali, Ballito, Compensation,
Tongaat, and Verulam. These areas are special because they were originally sugarcane growing
areas and over the years they have been developed due to massive decentralisation of major
infrastructure and real estate developments from Durban CBD. In addition, these areas have
some of the most upmarket infrastructure, residential and commercial property developments
in the City of Durban.
Results of the study reveal that four main steps are undertaken by all property valuers and estate
agents in the valuation of sugarcane farmland in the area and are as follows: (i) receiving
valuation instruction from the client, (ii) property inspection and collection of valuation
information, (iii) analysis and adjustment of valuation data and (iv) writing the valuation report.
Pienaar (2013) observed that in practice the value of sugarcane farmland includes the land and
sugarcane roots. The roots decline in value due to their declining productive life, just like other
permanent crops. This means that the value of established sugarcane farm declines in value as
the age of the sugarcane crop increases. In addition, this study found interesting challenges
which are faced by property valuers and estate agents operating in the North of Durban. The
main challenge is the determination of acceptable and comparable market related sugarcane
farmland prices. This is due to the fact that sugarcane farmland owners in the area are asking
for very high prices for their land which are difficult to support since they are not in line with
registered market land sales in the area.
Property valuers and estate agents believe this trend is linked to market speculation which relies
on the fact that the available sugarcane farmland in the area is located close to existing prime
infrastructure and popular property developments, for example, KSIA and Gateway Shopping
201
Centre. These challenges have presented enormous problems on interested government
departments, financial institutions and other investors with regard to property investment
decision making on land, construction, infrastructure and property development transactions
they are handling in the area in order to make sound decisions for sugarcane farmland to be
compensated or acquired for proposed construction projects. This study recommends further
research to be undertaken on land in the area in the future since valuation plays a critical role
in the fair acquisition and compensation of land for construction projects and in the assessment
of viability of construction and property development projects.
6 References
Chadwick, J. (1998), Land Values, Valuations and New Freehold Growers. Grower Services-
SA Cane Growers
Chikafalimani, S.H.P. & Ramphal, K. (2016), Impact of King Shaka International Airport on
the Property Market in Durban, South Africa, paper presented at Infrastructure
Conference, University of Johannesburg, July 2016, Johannesburg, South Africa.
Cloete, C.E. (1997), Valuation of Special Properties Marketing. Sandton: South African
Property Education Trust.
Ghyoot, V. (2002), Real Estate Education in Africa, in monograph of Real Estate
EducationThroughout the World: Past, Present and Future, Schulte, K.-W. (editor)
(2002). Kluwer Academic Publishers.
Maritz, N.G. & Ghyoot, V.G. (1990), The Estate Agency Business. Cape Town: Juta.
Mulder, D. (2005), Sugar Industry Outlook South Africa. South Africa: ABSA AgriBusiness
Pienaar, P. (2013), Farm Valuations Practice. South Africa: Agri Land Price Index.
SA Cane Growers (2006), Areas under sugarcane (ha). Retrieved from SA Cane Growers:
www.sacanegrowers.co.za.
Syagga, P.M. (1994), Real Estate Valuation Handbook. Nairobi: Nairobi University Press.
www.kingshakaairport.co.za (2016/08/30).
202
Predicting Academic Success of Undergraduate
Architecture Students: Using K Nearest Neighbour
Algorithm Ralph Aluko1, Clinton Aigbavboa2 and Olalekan Shamsideen Oshodi3
1Department of Architecture,
Olabisi Onabanjo University, Nigeria,
Email: finioloro@yahoo.com 2 Department of Construction Management and Quantity Surveying,
University of Johannesburg, South Africa,
Email: calgbavboa@uj.ac.za 3 Department of Architecture and Civil Engineering,
City University of Hong Kong, Hong Kong
Email: oshodilekan2002@yahoo.com
Abstract:
The number of applicants considered during the admission selection process for universities
has increased exponentially. This has led to development and improvement of the admission
criteria so as to ensure that new intakes that possess the potential to achieve academic success
are selected. The aim of the present study is to examine the relationship between academic
success of architecture student and prior academic performance using K-nearest neighbour
algorithm (k-NN). Data on prior academic performance, which is considered during admission
process, and academic success was collected on four cohorts of architecture students. Then the
data is divided into two parts: training set (70%) and test set (30%). Finally, the k-NN was
developed using the training sets and the predictive performance was evaluated using the test
set. The experimental results shows that the overall accuracy of the k-NN model is 73.33%. It
is anticipated that the developed model could provide useful information that can be used to
identify new intakes whom possess adequate intellectual capabilities to succeed in
undergraduate architecture programs in Nigeria.
Keywords:
Academic success, Architecture students, Classification, Modelling
1 Introduction
In recent years, there has been a drastic increase in the number of applicants seeking admission
into universities in Nigeria. This creates difficulties for admission committees each year in
identifying, selecting and admitting exceptionally good students. The committees will screen
applicants based on several criteria which have been defined for different programs at each
university. A robust selection process will ensure that ‘best’ students that fit each program are
selected (Young, 1989). One type of information which is typically used during admission
selection process is prior academic performance of the applicants. The sources of information
on prior academic performance include: grades obtained in secondary school terminal
examinations, unified tertiary matriculation examination (UTME) and post-UTME test scores
(post-UTME test is conducted by each university). Information gleaned from these different
sources are important in selecting good and capable student into the architecture undergraduate
program.
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Admission policies are designed to select applicants with high prior performance. In some case,
subjective applicant information (such as age, letter of recommendation, personal interviews
with selection committee, etc.) are also considered. This is to ensure that the selected applicants
possess intellectual capacity to succeed academically in an academic programme. This is based
on the assumption that there is a strong relationship between academic ability (measured by
prior academic achievement) and success in architecture undergraduate programs at tertiary
education level. Selecting applicants that are well suited for the undergraduate architecture
program is important for several reasons which include: reduction in student attrition and
decrease in resources spent on remedying struggling students (McManus & Richards, 1986).
Increasing complexity, competition and dynamics of the construction industry has resulted in
the need for well trained (Ling et al., 2011) and academically successful construction
professionals. Also, it must be noted that government-owned university have policies targeted
at selecting applicants from diverse backgrounds. For example, admission policies are designed
to attract and select applicants from educationally disadvantaged areas so as to meet the needs
of their communities.
This study aims to examine the relationship between prior academic performance and academic
success in an architecture undergraduate program. With this aim, the specific objectives are to:
(1) examine the relationship between prior academic performance and academic success of
architecture students using k-NN algorithm (2) analyse the importance of various information
considered during the admission process. The outcome of the current study will provide
admission committees and other relevant stakeholders with valuable information on the impact
of prior academic performance on academic success of undergraduate architecture students. In
addition, the outcome may result in a re-evaluation of the criteria used in the decision process
for selecting new intakes into the architecture program. This is because it is a generally held
believe that high prior academic performance may be suggest high likelihood of academic
success.
2 The concept of 'academic success' and its determinants
2.1 Academic Success
Research into academic success has a long history. One of the seminal studies in this area was
reported by Sohn in 1977. The term ‘academic success’ refers to a phenomenon that
incorporates academic achievement, attainment of learning objectives, acquisition of desired
skills and competencies, satisfaction, persistence and post college performance (May, 1923;
Strong et al., 2005). Academic success has also been viewed as completion of academic
activities which improves the academic achievement of the student concerned. It is evident that
academic success is vital to achieving main objectives of education (acquiring necessary skills
and knowledge). Hence, it is important to understand factors that affect student academic
success at universities.
Several studies have investigated factors affecting academic success of undergraduate students
(e.g. Abisuga et al., 2015). However, it is imperative to note that the terms ‘academic
achievement’ and ‘academic successes are used interchangeably in literature. Herminio (2005)
classified factors affecting academic success into two classes namely: internal and external
factors. The internal factors are class schedule, class size, classroom environment, role of the
lecturers, technology and nature of examination while the external factors include
extracurricular activities, family and work activities. Herminio (2005) showed that internal
factors are much more significant than the external factors. Ling et al. (2011) examined
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teaching and learning approaches that resulted in improved academic performance. It was
found that growing teaching approach and achieving motive learning approach are related to
improved academic success. Also, empirical evidence has shown that prior academic
performance has significant impact on academic success of first year of university students
(McKenzie & Schweitzer, 2001). Although Bone & Reid (2011) argue that numerical
assessment scores/grades obtained in a subject may not be a true reflection of the knowledge
gained by a student on a topic/subject, it is evident that the numerical score/grade remains the
most available proxy for measuring academic success.
2.2 Prior academic performance and success at undergraduate programs
A large and growing body of literature has investigated the relationship between prior academic
achievement and academic success of undergraduate students at different universities (see
Abisuga et al., 2015; Curtis et al., 2007). Marcus & Chertes (2007) investigated the effect of
student's demographic characteristics and prior academic performance (entry criteria) on
academic success in two core courses in an undergraduate real estate program. The findings of
the study showed that prior academic performance has a positive relationship with grades of
the students in those two core courses. Others studies showed that academic entry criteria and
maturity (in terms of age) are the best predictors of academic success in nursing (Whyte et al.,
2011; van Rooyen et al., 2006) and paramedic undergraduate programs (Whyte et al., 2011).
In a study conducted by Ting (2001), it was found that a combination of prior academic
achievement and psychological variable are significant predictors of academic success in
undergraduate engineering programs. Taken together, it is evident that the findings of these
studies demonstrate that the prior academic performance and academic success in
undergraduate programs are positively related. However, the strength of this relationship varies
from strongly to weakly and no relationship.
The strength of the relationship between prior academic performance and academic success
has been a controversial and much disputed issue within education data mining research.
Findings from Curtis et al. (2007) suggest that admission criteria are weak predictors of
academic performance for first year and graduating students in an undergraduate dental
program. Also, Abisuga et al. (2015) found a weak relationship exist between admission
criteria and academic success of building technology students. Poole et al. (2007) showed that
admission criteria are significant predictors of academic performance in the first two years of
study for undergraduate students in dentistry program. However, the level of significance
waned in later years. In contrast, some studies have reported that no relationship exist between
prior academic achievement and academic success in undergraduate programs in medicine
(Guraya & Zolaly, 2012) and biology (Bone & Reid, 2011). Similarly, Kirby and Demster
(2014) found that provision of accommodation and financial support are better predictors of
academic success in a foundation program at a university in South Africa. Based on the
foregoing, it is evident that the result of studies on the relationship between prior academic
achievement and academic success are contrasting. In addition, very little is known about this
relationship in the context of built environment education. Except for few studies focused on
undergraduate programs in building technology (Abisuga et al., 2015) and real estate (Allen &
Carter, 2007). Hence, the present study investigates the relationship between prior academic
performance and student’s academic success in an undergraduate architecture program using a
machine learning technique.
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3 Research Methodology
Different authors have examined determinant of academic success in built environment
education research using various methods. The research methods used in those built
environment education studies include: questionnaire survey (Ling et al., 2010); simulation
(Long et al., 2009) and so on. Review of published conference papers showed that survey,
experiment, literature survey, case-study, modelling, archival research and grounded theory are
prevalent methods used by built environment researcher in West Africa (Laryea & Leiringer,
2012). It is important to note that suitability of research approach is important in the process of
achieving research objectives. Modelling techniques have been proven to be adequate and
suitable for investigating relationship between dependent and independent (Fellows & Liu,
2015). The underlying pattern which is uncovered can be used for prediction (testing of
competing theories). Thus, the k-NN algorithm is used to predict academic success of
undergraduate students in an architecture program in a Nigerian university. The predictive
accuracy (i.e. generalizability) of the developed model is also investigated.
3.1 Student data
The developed model was trained using data collected from Department of Architecture,
Olabisi Onabanjo University, Ogun State, Nigeria. Data relating to prior academic
performance, which is the criteria used during the admission decision process, were collected
for all the 102 students that have completed the undergraduate program between 2011 and
2014. Due to missing information; the data for 101 students was used during the model
development phase of the current study.
The collected data includes 13 input (independent) variables, which are measures of prior
academic performance, and one output (dependent) variable. The input variables are the grades
obtained in ordinary (‘O’) level examination, total score in university matriculation
examination (also referred to as JAMB or UTME), and mode of entry (which is a dummy
variable 1= direct Entry and 0 = JAMB). The collected data is similar to those used in an earlier
study (see Young, 1989). The grades in O’ level examination are transformed into 9 classes
(i.e., A1=9; B2=8; B3=7; C4=6; C5=5; C6=4; D7=3; D8=2; F9=1 and no grade= 0). For the
output variable, the cumulative grade point average (CGPA) obtained by each student upon
completion of the architecture undergraduate program is used as a measure of academic
success. The numerical values of CGPA were transformed into categorical classes. The
classification places each student into one of the two classes namely: 'Pass' or 'Fail'. CGPA
which range between 5.0 and 2.4 were classified as ‘pass’; while, those between 2.39 and 0.00
were categorized as ‘fail’. It is important to note that achieving a minimum CGPA of 2.4 is a
criterion used in selecting students that will proceed to the Master of Science (MSc)
Architecture program. Therefore, this criterion is used as a measure of academic success. The
details of the input variables and output variables used in the developing the models are
presented in Table 1.
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Table 1. The pre-processed input and output variables
Attribute Type Description
Mathematics (MATH) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
English (ENG) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Physics (PHY) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Biology (BIO) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Chemistry (CHEM) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Local language (e.g. Yourba- YOR) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Geography (GEO) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Technical drawing/Fine arts (TD) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Economics (ECON) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Further mathematics (FM) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Agricultural science (AGRIC) O’ level result student's grade (numeric: from 9 - A1 to 0 - no grade)
Total UTME scorea (JAMB) UTME Total score (numeric: from 1 to 0)
Direct entry (DE) mode of entry Mode of entry (binary: yes-1 or no)
Academic Success CGPA CGPA at graduation (Binary: 1- Pass or 0-Fail)
Total UTME score = student’s UTME score divided by 400
3.2 k-NN algorithm
The k-NN was implemented in R programming software (R Core Team, 2015) using the
Rminer R-package (Cortez, 2010). Classic linear regression models are used to examine the
relationship between a set of independent variables and dependent variable. It is imperative to
note that linear regression model is not suitable for predicting categorical dependent variable
(i.e. classification problem). Hence, the k-NN algorithm is applied in the present study.
K-nearest neighbour (k-NN) is a machine learning technique that has been applied to
classification and regression task. In this research, k-NN is used for a classification. According
to Parsian (2015), the underlying principle behind the k-NN algorithm is that no prior
assumption is made about the function f:
nxxxfy ...21 (1)
Where y is dependent variable and xi are the independent variables. The function f is non-
parametric because no parameter is estimated. Given new data set (i.e. test data), the algorithm
dynamically identifies k observations in the training data that are similar to p (the k nearest
neighbour). The neighbours are determined by a similarity measure that is computed between
the observations based on independent variables. The Euclidean distance between the
independent variables in the training set and test set can be expressed as:
22
22
2
11 ... nn pxpxpx (2)
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For detailed explanation of the k-NN, interested readers are referred to Parsian (2015). To
validate the developed model, the collected data is divided into two: training set (70%) and test
set (30%). The training data-set were initially fitted to the model. Subsequently, the trained
model is used to predict previously unseen data, i.e., test data set. This is done to evaluate the
predictive performance of the model (generalization capability). The percentage of correctly
classified (degree of accuracy) and Cohen's kappa coefficient (Kappa) are computed as
measures of predictive performance. In addition, sensitivity analysis as explained in Cortex
(2010) was applied to evaluate the relative importance of the input variable in the developed
model.
4 Findings and Discussion
The processes carried out prior to fitting the model are described in the preceding section. The
training datasets were fitted to the k-nearest neighbour model. Also, the predictive accuracy of
all the models are presented in this section.
4.1 K-nearest neighbour (k-NN)
The k parameter in the k-NN algorithm is a user defined parameter. In this study, an initial
experiment was carried out by setting k at values of 1, 3, 4, 5, 6, 7 and 9. Subsequently, k is set
at 1. This is because no significant improvement in the accuracy of the k-NN model was
observed due to changes in the value of k. The results of out-of-sample prediction (i.e. the test
set) for the k-NN model is presented in Table 2. On the overall, 73.33% of the instances (cases)
were correctly classified. Also, kappa statistic is calculated as 0.318.
Table 2. The pre-processed input and output variables
Observed
Predicted
Fail Pass
Fail 4 4
Pass 4 18
Overall accuracy = 73.33%
Kappa = 0.318
Source: Researcher
4.2 Sensitivity analysis
Compared to k-NN, linear models (such as regression) are easy to interpret. This is the reason
why machine learning techniques are termed as ‘black box’ models. After using the developed
k-NN model for prediction; sensitivity analysis is carried out. Sensitivity analysis is a technique
used to extract additional information on the importance of each independent variable in
predicting the dependent variable in machine learning models (see Cortez et al., 2009; Tinoco
et al., 2011). Figure 1 shows the importance attributed by k-NN to each input variable (i.e.
prior academic performance) based on sensitivity analysis. As can be seen from the figure, it
is evident that the most influential input variables are MATH, PHY, and CHEM.
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Figure 1 Importance of each input variable in the k-NN model
4.3 Discussion of findings
The present study was designed to investigate the effect of admission criteria (used as a proxy
for prior academic achievement) on student’s academic success in an undergraduate
architecture program. In addition, the significance of the outcome of this study has been
described in the opening section of this paper. The results of the study prove that the k-NN
model can reliably predict architecture student’s academic success using prior academic
performance as predictors. The overall accuracy of the developed k-NN model is 73.33%. It
was found that student’s grades in mathematics, physics and chemistry in O’level examinations
are significant predictors of academic success for architecture students. One unanticipated
finding was that grades obtained in local language (such as Yoruba) has significant impact on
academic success of architecture students. A possible explanation for this might be that
lecturers explain complex architecture terms in the local language of the region where the case
university is located.
The findings emanating from the current study are in agreement with those obtained in previous
studies (Whyte et al., 2011; Abisuga et al., 2015). However, it is imperative to note that the
strength of the relationship found in Abisuga et al. (2015) is weak. Contrastingly, it has been
found that no relationship exists between admission criteria and academic performance of
undergraduate students (Guraya and Zolaly, 2012; Bone and Reid, 2011). This differs from the
findings presented in the current study. Also, there seems to be some agreement with those.
These differences can be partly explained by non-linearity in the collected data and problem in
distinguishing between 'prediction' and 'relationship' - see Shmueli (2010) for a detailed
explanation on the distinction between the two. Since the purpose of the present study is to
investigate the predictability of student’s academic success using admission criteria as
predictors, it is evident that the developed k-NN model can provide a reliable forecast. This
information would be particularly useful for stakeholder involved in making decision on
admitting new architecture students into undergraduate programs at universities.
5 Conclusion
The purpose of the current study was to investigate the predictive ability of using prior
academic performance as a predictor of academic success in an undergraduate architecture
program. In addition, the impact of each admission criteria on academic success was examined.
209
The collected data was subjected to the k-NN algorithm and the predictive performance (in
terms of accuracy) of the developed model was evaluated.
The present research has shown that the developed k-NN model is an accurate and reliable tool
for modelling and predicting academic success of undergraduate architecture students. Also, it
is evident that grades obtained in mathematics, physics, chemistry and Yoruba at ‘O’ level
examination has significant impact on academic success of architecture students. Overall, this
study strengthens the idea that machine learning techniques (such as k-NN) are particularly
useful for predicting academic success. This has been confirmed by a review of previous
studies presented in Shahiri and Husain (2015). The current findings add to the growing
literature on academic success, built environment and application of machine learning
techniques to education related problems. Hence, it can be concluded that k-NN model is valid
for application as a tool by stakeholders for admitting new intakes into undergraduate
architecture programs at universities. However, these findings must be interpreted with caution
because there are other factors that could influence student’s academic performance. A well-
known example of such factors is teaching method.
6 References
Abisuga, A.O., Olanrewaju D.O., & Oyekanmi O.O. (2015), ‘Pre-Qualification Academic
Requirement as a Predictor of Academic Performance in a Building Technology
Programme: A Case of Lagos State Polytechnic’, Covenant Journal of Research in the Built
Environment, 3(1), pp. 44-53.
Allen, M., & Carter, C. (2007), ‘Academic success determinants for undergraduate real estate
students’, Journal of Real Estate Practice and Education, 10(1), pp. 149-160.
Bone, E. K., & Reid, R. J. (2011), ‘Prior learning in biology at high school does not predict
performance in the first year at university’, Higher Education Research & Development,
30(6), pp.709-724.
Cortez, P. (2010), ‘Data Mining with Neural Networks and Support Vector Machines using the
R/rminer Tool’, In: Perner, P., Advances in Data Mining Applications and Theoretical
Aspects, Berlin, Germany, Springer, pp. 572-583.
Cortez, P., Cerdeira, A., Almeida, F., Matos, T., & Reis, J. (2009), ‘Modeling wine preferences
by data mining from physicochemical properties’, Decision Support Systems, 47(4), pp. 547-
553.
Curtis, D. A., Lind, S. L., Plesh, O., & Finzen, F. C. (2007), ‘Correlation of admissions criteria
with academic performance in dental students’, Journal of Dental Education, 71(10), pp.
1314-1321.
Fellows, R. F., & Liu, A. M. (2015), Research methods for construction. 4th Edition, United
Kingdom: John Wiley & Sons.
Guraya, S. Y. & Zolaly, M. A. (2012), ‘High School Grades are not Reliable Predictors of
Academic Performance in Undergraduate Medical School: A Study from a Saudi Medical
School’, Biomedical & Pharmacology Journal, 5(2), pp. 219-225.
Herminio, R.P. (2005), Factors Influencing Students’ Academic Performance in the First
Accounting Course: A Comparative Study between Public and Private Universities in
Puerto Rico, Florida. PhD Thesis, Argosy University.
Kirby, N. F., & Dempster, E. R. (2014), ‘Using decision tree analysis to understand foundation
science student performance. Insight gained at one South African university’, International
Journal of Science Education, 36(17), pp. 2825-2847.
Laryea, S., & Leiringer, R. (2012), ‘Built environment research in West Africa: current trends
and future directions’, In: Laryea, S., Agyepong SA, Leiringer, R. Hughes W. (Eds),
210
Proceedings 4th West Africa Built Environment Research (WABER) Conference, 24-26 July
2012, Abuja, Nigeria, WABER, pp. 797-804.
Ling, Y. Y., Khai Ng, P., & Leung, M. Y. (2010), ‘Predicting the academic performance of
construction engineering students by teaching and learning approaches: Case study’,
Journal of Professional Issues in Engineering Education & Practice, 137(4), pp. 277-284.
Long, G., Mawdesley, M. J., & Scott, D. (2009), ‘Teaching construction management through
games alone: a detailed investigation’, On the Horizon, 17(4), pp. 330-344.
Marcus, T. A & Charles, C.C. (2007), ‘Academic success determinants for undergraduate real
estate students’, Journal of Real Estate Practice and Education. 10(2), pp. 149-160.
May, M. A. (1923), 'Predicting Academic Success', Journal of educational psychology, 14(7),
pp. 429-440.
McKenzie, K., & Schweitzer, R. (2001), ‘Who succeeds at university? Factors predicting
academic performance in first year Australian university students’, Higher Education
Research & Development, 20(1), pp. 21–33.
McManus, I. C., & Richards, P. (1986), ‘Prospective survey of performance of medical
students during preclinical years’, British Medical Journal, 293, pp. 124-127.
Parsian, M. (2015). Data Algorithms: Recipes for Scaling Up with Hadoop and Spark.
Sebastopol: O'Reilly Media, Inc.
Poole, A., Catano, V. M., & Cunningham, D. P. (2007), ‘Predicting performance in Canadian
dental schools: the new CDA structured interview, a new personality assessment, and the
DAT’, Journal of Dental Education, 71(5), pp. 664-676.
R Core Team. (2015). R: A language and environment for statistical computing. R Foundation
for Statistical Computing, Vienna, Austria.
Shahiri, A. M., & Husain, W. (2015), ‘A Review on Predicting Student's Performance Using
Data Mining Techniques’, Procedia Computer Science, 72, 414-422.
Shmueli, G. (2010), ‘To explain or to predict?’, Statistical science, 23(5), pp. 289-310.
Sohn, D. (1977), ‘Affect-generating powers of effort and ability self-attributions of academic
success and failure’, Journal of Educational Psychology, 69(5), pp. 500-505.
Strong, W. B., Malina, R. M., Blimkie, C. J., et al. (2005), 'Evidence based physical activity
for school-age youth', The Journal of paediatrics, 146(6), pp. 732-737.
Ting, S-M. R. (2001), ‘Predicting academic success of first-year engineering students from
standardized test scores and psychosocial variables’, International Journal of Engineering
Education, 17(1), pp. 75-80.
Tinoco, J., Correia, A. G., & Cortez, P. (2011), ‘Application of data mining techniques in the
estimation of the uniaxial compressive strength of jet grouting columns over time’,
Construction and Building Materials, 25(3), pp. 1257-1262.
van Rooyen, P., Dixon, A., Dixon, G., & Wells, C. (2006), ‘Entry criteria as predictor of
performance in an undergraduate nursing degree programme’, Nurse education today, 26(7),
pp. 593-600.
Whyte, D. G., Madigan, V., & Drinkwater, E. J. (2011), ‘Predictors of academic performance
of nursing and paramedic students in first year bioscience’, Nurse education today, 31(8),
pp. 849-854.
Young, A. S. (1989), ‘Pre-enrollment factors and academic performance of first-year science
students at a Nigerian university: a multivariate analysis’, Higher Education, 18(3), pp. 321-
339.
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Critical Review of Ethical Considerations in the Teaching
Approach of Construction Professionals Mart Mari Els
Department of Quantity Surveying and Construction Management,
University of the Free State, South Africa
Email: archerm@ufs.ac.za
Abstract:
The purpose of this paper is to emphasize the importance of ethical behaviour in the
construction industry therefore the inclusion of ethics in the education of young construction
professionals. This paper demonstrates the importance of the example set by the
lecturer/mentor and his/her approach towards the teaching and learning experience of future
professionals in the construction industry. This paper is a result of critical review of the
importance of ethics in the construction industry and the influence of the teaching and learning
experience of construction graduates. A qualitative research method was followed supported
by a quantitative approach which includes a questionnaire sent to undergraduate and
postgraduate students and to academics in the built environment in the Free State province of
South Africa. The findings of this study indicate the importance of the inclusion of ethics in
education but more so the critical role of the lecturer/mentor in the teaching and learning
experience of the students. The value of this review reflects the importance of the lecturers’
approach in the education of young professionals in the construction industry.
Keywords:
Ethics, Education, teaching and learning, lecturer, construction industry.
1 Introduction
The impact and significance of the construction industry can be seen everywhere in society.
Modern society relies on the construction industry for producing commercial and industrial
facilities for business, civil infrastructure for public and private needs and housing residents
(Russel, Hanna, Bank & Shapira, 2007).
Public often has great expectations of professionals in the industry and expect value for money,
professionalism and competence. Professionals have to act lawfully and ethically. They have
to fulfil their responsibility to their profession, colleagues, employers, clients and the public,
an act which requires maturity of judgement (Fan & Fox, 2009).
2 Literature Review
Ethics is the study and understanding of morality, moral principles, and the moral decision-
making process (Fan, Ho & Ng, 2001). Business ethics as an applied version of ethics typically
involves two tasks: the normative task of providing justification for abstract standards of
behaviour and the practical task of applying these standards to business conduct. Business
ethics is the application of our understanding of what is good and right to that assortment of
institutions, technologies, transactions, activities and pursuits which we call business
(Velasquez in Fan, Ho & Ng, 2001).
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Ethics can be thought of as a person’s ability to act in a socially acceptable manner and to make
decisions based upon one’s morals and belief structure (Lecher, 2002). Professional ethics
concerns the study of the morality of the behaviour of professionals in their day-to-day practice.
Professionals are primarily held responsible to the general public, but the morality of their
behaviour is not only assessed in ordinary moral terms but also in terms of special professional
norms (Ho & Ng, 2003). Maxwell (2003) refers to the Golden Rule as to treat others the same
way you would like to be treated.
The Royal Institute of Chartered Surveyors (RICS) has five ethical and professional standards
which their members must adhere to. Act with integrity, always provide a high standard of
service, act in a way that promotes trust in the profession, treat others with respect and take
responsibility (RICS, 2015). Even when professionals are inherently ethical, the pressure of
the working environment may complicate and obscures their ethical course of action
(Helgadottir, 2008). Some construction professionals have been involved unethical behaviour
and found guilty of dishonourable conduct. A difficult economic climate adds to the stress of
making ethical decisions. Professional ethical behaviour or lack thereof has subsequently come
under the attention of the public who expect high ethical standards.
This expectation has complicated and widened the study of professional ethics (Fan, Ho & Ng,
2001). According to Bowen et al. (2007) unethical behaviour in the construction includes:
unfair conduct, professional negligence, conflict of interest, fraud and bribery. Construction
professionals face a number of ethical dilemmas specific to the construction industry. The
conduct and practices of the professionals engaged in the South African construction industry
are governed by the guidelines provided by the respective professional bodies and the South
African Council for the Built Environment. Construction professionals are bound by the
professional code of ethics to have a responsibility to society (Fan & Fox. 2009). According
to Donaldson (in Bowen et al., 2007) ethical practices should promote economic efficiency by
respecting others, avoiding negative practices such as nepotism and bribery, and to conduct
business professionally.
The factors that make the construction sector prone to unethical behaviour include competition
for contracts, bureaucracy for obtaining official approvals and permits, project uniqueness
which makes price comparison difficult, opportunities for delays and overruns, and that most
work is concealed by concrete, plaster and cladding (Transparency International, 2005 in
Bowen et al., 2007). The cause of organizational ethical failure can be traced to the culture
and the failure of leaders to actively promote ethical practice (Bowen et al., 2007). It is
therefore important for young professionals in the construction industry to develop ethics,
moral values and professionalism at an early stage in their careers.
According to Guillaud and Garnier (2001), education refers to all the ways in which students
train and develop to fulfil their potential, realised as a result of acquiring skills, attitudes and
values that not only reflect the needs of industry but also the social, cultural and physical
environment in which students live. According to (Carrol, 2009), business ethics can be taught.
College students sometimes say that their values are set by the time they reach college and that
nothing that they learn will change their view.
In business ethics education, the aim is not to change students’ feelings, but to sharpen their
thinking. Dulaimi (2005) mentions that education may be a narrow learning process of a fixed
syllabus to pass an examination, or it can be the individual’s exposure to varied experiences.
The question however is: Does current education providing students with optimal knowledge
on ethics, if not, what are the consequences and what can be done to avoid this?
213
Professional education and training is the main concern of academics, associations and society.
Construction professionals should learn professional values, integrity and competence during
their university education. There are certain basic and important skills that are expected in each
profession, which are best learned at universities (Chan, Chan, Scott & Chan, 2002).
Construction education institutions should plan their curricula carefully to encompass the
appropriate training and professionals should undertake lifelong learning throughout their
career (Chan, Chan, Scott & Chan, 2002). Therefore, education should not stop once the
student leaves the classroom but must be continued throughout one’s career in the form of
continuous professional development (CPD).
The teaching approach with specific reference to ethics can include the following but are not
limited: a) traditional lecture format, b) seminars, c) case discussions and d) cooperative
education programs. The case study approach might be seen as an effective way to develop
awareness of the ethical pressures faced by professional (King, Duan, Chen & Pan, 2008).
Formal education is also where the most people develop their understanding of ethical
standards in their profession (Russel & Stouffer, 2003). Students should not only acquire
knowledge but should be prepared for the practicalities of the construction industry (King,
Duan, Chen & Pan, 2008). Although formal education does not solely determine the level of
professional preparation, it provides the background and understanding for the challenges,
problems and joys of professional practice (Russel & Stouffer, 2003). The role that universities
and teachers play to ensure that graduates entering the economy understand the environment
can function effectively within society.
The education and development of students regarding ethics and leadership may effectively
enhance the quality of leadership in the built environment as “a strong moral education
empowers a person to make good ethical choices.” (Maxwell, 2003)
According to Russel et al. (2007), educators, mentors and advisors involved in professional
practices must help prepare the future generation of professionals. Practices such as critical
thinking, understanding globalisation and expanding social awareness should be applied and
integrated in the learning experience of students.
Ethics can be defined as “a set of moral principles, governing the conduct for an individual. It
comprises a study of thought, language, reasoning, processes and judgement that informs the
choices people make in their daily lives that affect their own well-being and that of others”
Bowen et al., 2007).
Therefore, the example set by the lecturer can be seen as vital in the approach of the teaching
and learning experience of students.
The judgement of the lecturer can be seen as a true reflection of his/her beliefs and values
(Bowen et al., 2007).
Therefore, it is important for the lecturer to be professional, honest, not engage in unfair
conduct towards students and not be negligent in his/her duties as educator and to apply the
Golden Rule, which states that one should treat other as he/she would like to be treated.
214
3 Research Methodology
Both quantitative and qualitative research methods were used during this study. It includes a
literature study, followed by an investigation by means of a structured questionnaire distributed
to undergraduate and postgraduate students as well as academics in the property industry in the
Free State province in South Africa. The questionnaire was developed and constructed based
on the literature review.
3.1 Questionnaire construction
The purpose of the questions included in the questionnaire are the following:
• to identify various important contribution elements of a lecturer;
• to determine important outcomes/abilities education should provide, and
• to determine the importance of certain attributes for preparedness of graduates for a long-
term career and to evaluate certain outcomes and abilities of formal education.
3.2 Sample size
The sample size that took part in the research comprised the following respondents: 62
undergraduate students in their third and final year of study, 39 postgraduate students in their
honours year of study, and 13 lecturers in the property industry. Ethical considerations included
that the respondents participated voluntarily and personal information were not to be disclosed.
A 100% response rate was achieved.
3.3 Data analysis
The data were summarised descriptively, using Microsoft Office Excel® 2007 to generate
spreadsheets, tables and figures. The results were statistically analysed by a professional
statistician and then interpreted by the author.
4 Findings and Discussion
4.1 Contribution of lecturer
The importance of the lecturer in terms of contributing towards the preparedness of graduates
should not be underestimated. Elements such as passion and motivation of the lecturer, the
lecturer being an expert or specialist, the availability of the lecturer, organisational,
communication and presentation skills, as well as presentability and self-confidence of the
lecturer were tested. The top three elements, according to the respondents, are:
Explaining, communication and presentation skills;
Specialist, expert and knowledgeable, and
Passion, motivation and an inspiration to the students.
In terms of teaching and learning at higher education institutions, it is important to get the
information across to the student as effectively and efficiently as possible. If the lecturer has
215
good communication, explaining and presentation skills, and if he/she is knowledgeable and
an expert in the related subject matter, the students’ learning experience of will be enhanced.
This will ultimately lead to the preparedness of graduates not only to enter the profession, but
also to have the ability to realise and anticipate future trends and to stay responsive to industry
and society needs. If the lecturer is passionate, motivated and set a good example in terms of
ethical behaviour it will inspire the students.
4.2 Most important attributes for a professional career
Table 1 shows the mean score of the most important attributes on a scale of 1 to 5, according
to the respondents, to be prepared for a professional career, where 1 is the least important and
5 the most important. The attributes that were to be evaluated include: Application of
knowledge, analysis of problems, evaluation ability and creativity.
Table 1: Attributes to be prepared for a future career
The above-mentioned four attributes were ranked according to the average score by the
respondents. Table 1 indicates that the students’ most important attribute should be the ability
to analyse problems. There was also consensus among the three groups of respondents, as each
ranked the above-mentioned required attributes in the same order. Table 1 also reveals that,
apart from the importance of analysing problems, the students’ ability to apply knowledge and
to evaluate are regarded as extremely important attributes necessary to prepare them for a long-
term career.
Ethical decision making is very important to apply when analysing problems.
4.3 Provided outcomes and abilities by education
The outcomes and abilities that the education system should provide to students for a
professional career in the built environment are depicted in Table 2. The most important
attributes selected relate to the students' own abilities.
Table 2: Outcomes and abilities provided by education
216
According to the respondents’ education should enable students to compare alternatives and
evaluate issues, as perceived by both students and lecturers, as the most vital element.
Education should also teach students to report and provide them with the ability to clarify and
illustrate comprehension. Lecturers place a higher emphasis on the importance of these
outcomes and abilities than undergraduate and postgraduate students do.
5 Conclusion and Further Research
The literature revealed that preparedness of students in addition to the necessary knowledge,
skills and understanding should be aligned with a teaching experience that focuses on the total
development of a person. This development cannot aim at specific professional skills but a
broader approach to development and student-teacher relationships is necessary. In terms of
ethics, the lecturer plays an integral role. The lecturer must stress the importance of ethics.
The lecturer also has an important role to play not only in terms of teaching students, but also
by setting the example. If the lecturer is innovative, knowledgeable, passionate, and has good
communication skills, the students will soon want to follow in his/her footsteps as a
professional. Setting a good example will contribute to the enhancement of preparedness of
graduates for a long-term career in the property industry.
To reach effective solutions to the problems students may encounter in their future work
environment may require ethical decision making and -approach in the ability to analyse and
evaluate.
It is suggested that education and training are the strongest support determinants of the
development of ethics within the industry and should therefore be the main driver of this
development. Education, training and development in the property industry are very important
in terms of a lifelong career as a professional. Being creative and innovative in terms of
education will enhance the preparedness of graduates not only to enter the profession
successfully but also to stay responsive to industry and society needs for at least four decades.
Construction professionals face the supreme challenge of building a better tomorrow. As
educators, mentors and advisors we have the supreme challenge of helping them to get ready
for this task and cementing an ethical future.
6 References
Bowen, P., Akintoye, A., Pearl, R. & Edwards, P.J. (2007) Ethical behavior in the South
African construction industry. Construction Management and Economic. Vol 25, No 6,
pp 631 – 648.
217
Carrol, A.B. (2009) Business Ethics: Brief readings on vital topics. New York.
Routledge.
Chan, E.H.W., Chan, M.W., Scott, D. & Chan, A.T.S. (2002). Educating the 21st century
construction professionals. Journal of Professional Issues in Engineering Education and
Practice, 128(1), 44–51.
Christabel, Ho Man-Fong. & Vincent, Ng Chi-Wai. (2003) Quantity Surveyors’ background
and training, and their ethical concepts, conceptions and interests’ considerations.
Construction Management and Economics. Vol 21, No 1, pp 43 – 67.
Dulaimi, M.F. (2005) The influence of academic education and formal training on the project
manager’s behavior. Journal of Construction Research. Vol 6, No 1, pp 179 – 193.
Fan, L.C.N, Ho, C.M.F. & Ng, V. (2001) A study of quantity surveyors’ ethical behaviour.
Construction Management and Economics. Vol 19, No 1, pp 19 – 36.
Fan, L.C.N. & Fox, P.W. (2009) Exploring factors for ethical decision making:
Views from construction professionals. Journal of Professional Issues in Engineering
Education and Practice. Vol 135, No 2, pp 60 – 69.
Helgadottir, H (2008) The ethical dimension of project management. International
Journal of Project Management. Vol 26, No 1, pp 743 – 748.
King, W.S., Duan, L., Chen, W.F. & Pan, C.L. (2008) Education improvement in construction
ethics. Journal of Professional Issues in Engineering Education and Practice. Vol 134, No
1, pp 12 – 19.
Lecher, S. (2002) Ethical procedures for a global economy. Journal of Professional Issues in
Engineering Education and Practice. Vol 128, No 3, pp 109 – 110.
Maxwell, J.C. 2003. Ethics 101. New York: Center Street, Hachette Book Group.
Russel, J.S. & Stouffer, W.B. (2003) Some ethical dimensions of additional education
for the 21st century. Journal of Professional Issues in Engineering Education and Practice,
129(4), 225–231.
Russel, J.S.; Hanna, A.; Bank, L.C. & Shapira, A. (2007). Education in construction
engineering and management on tradition: Blueprint for tomorrow. Journal of Construction
Engineering and Management, 133(9), pp. 661–668.
Velasquez, M.G., In: Fan, L.C.N., Ho, C.M.F. & Ng, V. (2001) A study of quantity
surveyors’ ethical behaviour. Construction Management and Economics. 19(1), pp. 19
– 36.
218
Evaluation of Barriers to University - Industry
Collaboration (UIC) in the Nigerian Construction
Industry G Odawn, S Muhammad and MZ Muhammad
Building Department,
Ahmadu Bello University Zaria, Nigeria.
Email: odawn.godwin@yahoo.com
Abstract:
The purpose of this paper is to develop an understanding of the major barriers to University-
Industry Collaboration in Nigeria and provide the findings of the study to date alongside early
recommendations for advancing the practice in Nigeria. Universities-Industry Collaboration
(UIC) refers to the interaction between any parts of the higher educational system and industry
aiming mainly to encourage knowledge and technology exchange. Hence, it is a ‘win-win’
relationship meant to advance the operations of the parties. This however, has not been the case
in Nigeria. The study adopted quantitative methods with the distribution of 193 questionnaires
to the built environment professionals and academics receiving a response rate of 63%. The
instrument listed 26 common barriers under 7 categories that impedes the practice of UIC from
relevant literatures for the respondents to rate. Analysis of the data shows that Poor
Leadership/Top management commitment and support towards the partnership is the major
barrier to University-Industry Collaboration in Nigeria with mean score standard deviation and
RII of 3.98, 5.42 and 0.80 respectively. The research was of an exploratory nature and thus
limited. However, it shows that further study including the government is required for a better
cover. The finding suggest that policy makers should encouraging UIC by making policies that
reduces the barriers to the partnership. Key barriers to the partnership typical to Nigeria are
reviewed in the paper. These findings should encourage a mutually beneficial relationship that
promotes research and technology transfer between the researchers and the practitioners.
Keywords:
Barriers, Collaboration, Industry, Nigeria, University
1 Introduction
Partnership between the research community and the professionals is essential in contributing
to the technological development and innovations in the industrial sector and enhancing its
global competitive capability. The industry should be responsible in collaborating with
university for adoption and practice of the new technological ideas generated by the University
researchers. It should also be responsible in providing funds for and in most cases initiating
these research operations.
However, according to Salter et al., (2009), Collaboration between industry and universities
faces significant challenges including the fact that these organizations are driven by different
incentive systems. Universities are driven primarily to create new knowledge, publish and
educate, whereas private organizations are focused on capturing valuable knowledge that can
be leveraged for competitive advantage, Dasgupta and David, (1994). Practitioners claim that
academics are becoming increasingly proactive managers of their collaborations with industry,
seeking to create valuable Intellectual Property (IP) for themselves. Whereas, in many
developed countries, more and more interactions between universities and industry are
219
becoming subject to measurement and management, leading to more formal, contractual
exchanges based on codified rules and regulations. This is significantly altering the nature of
the interactions between universities and industry, which in the past has relied largely on
informal relations. Although both of these aspects have been acknowledged in literatures on
university-industry (U-I) linkages.
Private firms often conflict with university researchers over the topic of research, timing and
form of disclosure of research results. While researchers may be keen to disclose information
to gain priority, firms may wish to keep secret or appropriate the information. Brown and
Duguid (2000) asserted that academics wish to create ‘leaky’ knowledge so that their ideas will
be acknowledged by their peers while firms want the knowledge to be ‘sticky’ so that they can
control a resource that is not accessible to their competitors. University researchers are also
likely to select research topics that are perceived by their peers to be interesting and valuable,
while firms are likely to select topics and problems that are perceived as being valuable for the
development of new products and services for their customers (Nelson, 2004). However,
against this background of frequent fall back on the age-old norms and roles of these two
entities in developing nations, there is presently an increasing international competition and
rapid technological changes. Governments becoming more actively involved in encouraging
collaborations as a means of improving innovation efficiency and consequently enhancing
increasing creation of wealth.
2 Literature Review
2.1 Historical Development of University-Industry Collaboration.
Historically, University Researchers in developed countries have collaborated with industrial
scientists on marketable projects. UIC have had a long history (Bower, 1993; Oliver, 2004) as
one means of building organizations’ knowledge stock (Cricelli and Grimaldi, 2010). Of late,
there has been a substantial increase in these collaborations in several developed nations
including: Japan (Woolgar, 2007); Singapore (Lee and Win, 2004), and European Union
Countries (Gertner et al., 2011; Powers, 2003). This increase has been attributed to a
combination of pressures on both industry and universities. News coverage at the turn of the
twenty-first century might lead one to believe that this is a current phenomenon. However,
science historians have traced collaborations between European companies and university
researchers back to the 1800s (Jan et al., 2010).
Traditionally, industry sought partnerships with universities as a means to identify and train
future employees. As global economies shifted, companies wanted access to faculty who
created the cutting edge knowledge and technology central to university research. Knowledge
creation and technology development require considerable capital investments, historically
provided by Governments (Dorota, 2009). The interdependent research relationships between
universities and companies enable both entities to sustain growth in their areas. While
companies rely on university researchers for product innovations, faculty gain prestige through
increased external research funds. Just as industry needs innovative ideas to ensure profits,
researchers need additional research dollars to sustain faculty productivity (Mieczyslaw and
Przemyslaw, 2009).
In Nigeria, this interaction between university research and industry is at a generally low level,
and policies are hardly derived from the results of research conducted in our universities
(Ibidapo-Obe, 2014). There is a growing need for collaborative research that addresses the
complex questions that matter most to the nation. This partnership is considered as one of the
220
main factors contributing to successful innovation and growth in the past two decades (Izaidin
and Ismail, 2009). High quality innovative research has the potential to transform the
Construction industry in Nigeria completely and give us breakthroughs in several areas such
as Graduate Employments, Power and Energy, Water, Infrastructure such as Roads, Rails and
even Water transportation, agricultural improvements, and sustainable national development.
According to (Ibidapo-Obe, 2014), one of the key reasons why this collaboration is important
is that no one sector is a repository of all knowledge and skills. Modern research is increasingly
complex and demands a wide range of expertise and experience. Thus, it is necessary to form
research collaboration across the three sectors. Further, it is clear that the academia does not
have the necessary financial muscle to fund high impact research efforts alone. The rising
financial costs of conducting high quality research suggest the need to pool resources across
sectors. This therefore calls for partnerships between the academia, the industry and even the
government. Such collaborative efforts would help in increasing the number, frequency and
diversity of research endeavours to cater for the various segments of the society.
2.2 Barriers to the Operation of University-Industry Collaboration.
Several factors that either facilitate or inhibit the operation of UICs are found in most of the
literatures on University-Industry Collaboration (UIC) (Samuel and Omar, 2015) which
confirmed the finding by many researchers that the literature on the factors that facilitate or
inhibit UIC is indeed abundant (Salter et al., 2009; Cricelli and Grimaldi, 2010). The factors
were found, if correctly managed, to have a positive effect on the perceived success of
knowledge and technology exchange. On the other hand, where the same factors were
neglected or mismanaged, there tended to be a corresponding negative impact on the perceived
success of knowledge and technology exchange. These factors are summarized under the
following seven categories or sub-headings: Capacity and Resources; Legal Issues,
Institutional Polices and Contractual Mechanisms; Management and Organizational Issues;
Issues relating to the Technology; Political Issues; Social Issues, and Other Issues.
The variety of factors confirmed (Barnes et al., 2002)’s view that the success of a collaborative
project is governed by a complex interaction of factors as well as the cumulative result of
negative and positive impacts from those factors. In addition, of the total number of the factors
identified, there are more factors in the management and organizational category than in any
one of the other categories, which correlates with Siegel et al. (2003) that organizational and
managerial issues were critical factors that facilitate or inhibit such relationships between
universities and industry.
3 Research Methodology
3.1 Research Design
This paper is based on a single methodological approach of data collection: quantitative
procedures. With the application of the quantitative data collection, a survey questionnaire was
designed and administered to the built environment academics in three of the Nigeria’s oldest
and leading Universities and construction professionals in four major cities having high
construction activities and are around the universities selected.
3.2 Data Collection
The sample size for this work was determined using the sample size determination table
published by Yamane (1967) in Glenn (1999). In all, 193 questionnaires were distributed and
221
121 (65%) were retrieved as depicted in table 2 below. All questionnaires were administered
personally to the respondent during which advantage was taken to interview some top and
middle level management staff. Respondents were given three weeks to fill the questionnaires
after which the questionnaires were personally collected for analysis.
Table1. Breakdown of responses
Source: Researcher
3.2.1 Questionnaire Design and Data Collection
A structured questionnaire consisting of closed ended questions was developed for the study.
The questions in the questionnaire were adopted from relevant literatures to the study. A five
point Likert Scale was used for ranking of the items in which 1 stands for “not a factor”, 2
stands for “of low effect”, 3 stands for “of moderate effect”, 4 stands for “of high effect, 5
stands for “of extreme effect”. They were administered to Lecturers in the Universities and
Managers of the construction companies.
3.3 Data Analysis
The data generated in the study are presented using tables and charts showing frequencies and
mean and standard deviation where necessary to enable the result to be properly understood
and evaluated. The data analysis was carried out using descriptive analysis with the aid of
Statistical Package and Service Solution (SPSS) and Microsoft Excel.
4 Findings and Discussion
4.1 Barriers to UIC in Nigerian Construction Industry
Universities
Departments
Number of
Questionnaire
Distributed
Total Number of
Questionnaires Properly
Filled and Returned
“ABU Zaria” Building 7
Architecture 13
Quantity Surveying 8
Civil Engineering 8
Sub Total 36 29
“Unilag” Lagos Building/Quantity
Surveying
9
Architecture 11
Civil Engineering 8
Sub Total 28 20
“UNN” Nsukka Architecture 12
Civil Engineering 9
Sub Total 21 13
Total for University 85 62
INDUSTRY
(Construction Firms)
Locations (Cities)
Number of
Questionnaire
Distributed
Total Number of
Questionnaires Properly
Filled and Returned
Lagos 57 27
Abuja 32 17
Port-Harcourt 13 9
Enugu 6 6
Total for Industry 108 59
GRAND TOTAL 193 121
222
The common barriers to University-Industry Collaboration identified from literatures were
subjected to the opinion of the respondents in the Industry and in the University via the
questionnaire to indicate their level of agreement or disagreement. Based on their opinion, the
ranking of the items identified is shown in table 2. The entire table is split into three parts the
first part is the ranking based on the opinion of the top management of firms (industry), the
second part is the ranking based on the opinion of the academics, while the third part is the
overall ranking based on the combined opinion of the professionals and the academics.
Table 2; Barriers to University-Industry Collaboration
223
As shown by Table 2, the practitioners ranked “Inadequate resources (funding, human and
facilities)” as the first barrier to UIC with mean score of 4.03. To the academics, it is not but
the second ranked barrier with a mean score of 3.69. Based on the overall (combined) ranking,
it was ranked 2nd with mean score of 3.86. The academics ranked “Poor Leadership/Top
management commitment and support” as first with mean score of 3.98, but to the practitioners,
it is ranked second with mean score of 3.98. However, in the overall ranking it has a mean
score of 3.98 and thereby ranked 1st. To the practitioners in the industry “Use of intermediary
(third party)” is the least item on the ranking with the mean score of 3.22 but to the academics,
it was ranked 23rd with mean score of 3.62. In the overall ranking, it was ranked as 25th with a
mean score of 3.23. The least ranked item according to the academics is “risk of research”
having a mean score of 3.24, however, it was ranked as the twentieth by the practitioners with
mean score of 3.37 and ranked 24th in the overall ranking with mean score of 3.23. Based on
the overall ranking, the least ranked barrier (26th) is Lack of Project Management Skills with
mean score of 3.22 and ranked 25th by both the academics and practitioners with mean scores
of 3.15 and 3.31 respectively. The other barriers as according to the overall ranking are as
follows in a descending order starting from the third rank; Poor Incentive structures for
university researchers - 3.72, Capacity constraints of Small & Medium Enterprises (SMEs) –
3.63, Lack of Teamwork and flexibility to adapt - 3.59, Nature of the technology/knowledge
to be transferred - 3.60, Lack of Collaboration champion – 3.60, Low level of awareness of
university research capabilities – 3.55, Policy/legislation/regulations on UIC – 3.53, Lack of
mutual trust, commitment and personal relationships – 3.54, The issue of recruitment and
training for technology transfer staff – 3.55, Inflexible university policies including – 3.48,
Organization structure (university administrative structure and firm structure) – 3.50,
Geographic proximity – 3.43, Poor absorptive capacity – 3.45, Poor Communication Skills –
3.42, Treatment of confidential and privately owned information, moral responsibility versus
legal restrictions – 3.41, Ability of the collaboration to enhance – 3.40, Firm size (size of
organization) – 3.36, Organization culture differences – 3.36, Lack of Skill and the role of both
university and industry boundary spanners – 3.34, Conflict over intellectual property – 3.36,
224
And Human capital movement/personnel exchange – 3.34
Their importance index and standard deviations were also considered in the ranking process
where-in the item with lower standard deviation is ranked higher than the one with a higher
standard deviation
5 Conclusion and Further Research
In summary, the multi-national construction companies usually engage their home country’s
researchers in research collaborations and innovative ventures rather than the Nigerian
Universities. Poor Leadership and top management commitment and support is the major
barrier to partnership between the University and the construction industry having the highest
mean score of 3.98. In other words, Management systems and policies do not offer significant
support for UIC as poor management and leadership issues constitute the highest barrier to
UIC. Other major barriers include issues relating to, policies, capacity and technology,
availability of equipment as well as enlightenment issues. Further study should include the
government since policies plays a key role in collaboration success.
6 References
Bower, D. J. (1993). Successful joint ventures in science parks. Long Range Planning, 6.
Brown, J. S., and P. Duguid. (2000). The Social Life of Information. Boston, Massachusetts:
Harvard Business School Press.
Cricelli, L., and Grimaldi, M. (2010). Knowledge-based interorganizational collaboration.
Journal of Knowledge Management, 14: 348-358.
Dasgupta, P., and David, P. (1994). Towards a New Economics of Science. Research Policy,
(23) 487-522.
Dorota, M. (2009) Commercialisation of research results – step by step. Cracow University of
Technology
Gertner, D., Roberts, J., and Charles, D. (2011). University-industry Collaboration: A CoPs
approach to KTPs. Journal of Knowledge Management, 05: 625-647.
Glenn, D. I. (1999). Determining Sample Size. Tallahassee: University of Florida IFAS
Extension.
Ibidapo-Obe, O. (2014). Enhancing Research Collaboration Between the Academia,
Government and Industry. Ife: Computer Science/Information Technology Research and
Development Workshop.
Izaidin, A. M., and Ismail, K. (2009). Entrepreneurial Management and Technology-based
Firms. Koln. Germany.: Lambert Academic Publisher.
Jan, S., Blazej, S., and Ewa, M. (2010). Collaboration between Universities and Industry Based
on Experience of the Silesian University of Technology. International Conference on
Engineering Education (pp. 1-10). Gliwice, Poland: Science and Industrial Cooperation.
Lee, J., and Win, H. N. (2004). Technology transfer between university Research Centers and
Industry in Singapore. Technovation, 24: 433-442.
Mieczyslaw, B., and Przemyslaw, K. (. (2009). " Institute for Private Enterprise and
Democracy . Warsaw: Entrepreneurial University.
Nelson, R. R. (2004). The market economy, and the scientific commons. Research Policy,
(33) 455-471.
225
Oliver, A. L. (2004). On the duality of competition and collaboration: Network-based
knowledge relations in the biotechnology industry. Scandinavian Journal of Management,
20: 151-171.
Powers, J. B. (2003). Com mercialising academic research: Resource effects on
performance of university technology transfer. Journal of Higher Education, Columbus,
74: 26-47.
Salter, A., Bruneel, J. and D'Este, P. (2009, June 17-19). Investigating The Factors That
Diminish The Barriers To University-Industry Collaboration. Druid, pp. 02-42.
Samuel, A., and Omar, A.-T. (2015). University-Industry collaboration: A systemic review.
Scandavian Journal of Management, 928-950.
Woolgar, L. (2007). New institutional policies for university—industry Link in Japan.
Research Policy, 36: 1261-1274.
226
Contribution of Value Management to Construction
Projects in South Africa Clinton Aigbavboa, Ayodeji Oke and Sponono Mojele
Department of Quantity Surveying and Construction Management,
University of Johannesburg, South Africa
Email: caigbavboa@uj.ac.za, emayok@gmail.com, mojelespon@gmail.com
Abstract:
For clients, owners and financiers of construction projects, construction process signify a huge
capital investment which translate into substantial fixed costs for their organizations. Value
Management (VM) is a business strategy tool to ascertain whether construction of a facility
will provide best function at the lowest possible cost. This study examines the contribution of
value management to construction projects with a view to assessing challenges and measures
to improve adoption and application of the discipline. Primary data were collected through
well-structured questionnaires administered on construction professionals within the study area
and Mean Item Score was used for data analysis. The major contributions of VM to the South
African construction industry include optimize value for money, creates a clearer focus on the
project objectives and works towards arriving at a more effective design. However, poor
communication, lack of interaction and unwillingness of clients to pay for VM service, were
the challenges affecting the adoption of VM. In order to improve construction project
performance using the process of value management, orientation meetings should be duly
organised, team structure should be finalised and team members must be appropriately selected
for construction projects. Built environment professionals - including construction and project
managers, should familiarize themselves with VM and strive for its full adoption and
implementation for construction projects in order to achieve best value at the lowest complete
life cycle project cost for construction clients.
Keywords:
Construction, Project, Teamwork, Value Management
1 Introduction
Value Management (VM) is a concept that has been used in construction projects for several
years in United States of America and United Kingdom (Bowen et al., 2010). There are other
terms that are synonymous with VM, these include Value Planning (VP, Value Engineering
(VE) and Value Analysis (VA). However, some authors claim that VP takes place at the
planning stage of a project, VE takes place during working drawing and production stage while
VA is practiced at the construction, occupation and post-occupation stage. The three terms are
summarized as VM and this has been accepted and adopted as a construction management tool
in the construction industries in South Africa and most other countries around the world. In
South Africa, Value Management was introduced in 1968 by Union Carbide (Sigle et al.,
1999). However, Coetzee (2009) stated that Value Management in South Africa is not yet a
process well known and it is also a concept not yet fully practiced in the South African
construction industry by relevant parties. Manoliadis (2013) also noted that the use of VM to
assimilate sustainability into construction has not been taken into consideration in the country.
According to Ellis et al. (2007), VM became more widely spread in the 1990s after VE has
evolved. However, Kelly (2007) noted that VM began within manufacturing industry of the
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United States of America (USA) in 1947 and has been referred to as VA, then it was later
renamed VE. Lin and Shen (2007) together with Afshar and Rezaei (2013) emphasizes that
VM was referred to as VE and was first introduced by Lawrence Miles in the 1940s as an
organized approach to provide necessary functions at the lowest cost. This implies that VM
came into existence in the 1940s and it has become a useful tool in every sector of the economy
including the construction industry. Norton and McEllligott (1995) concluded that VM has
become a blanket term that covers all the value techniques, whether they are called VP, VA or
VE. VM is a systematic, multi-disciplinary and structured methodology that improve the value
and whole life cost of a facility through detecting opportunities to remove unnecessary costs
while ensuring that quality, performance and other critical factors will meet or exceed
expectations of customers (Shen and Liu, 2004). The main objective of the discipline is to
ensure that projects are delivered to the best function at the lowest possible whole life cost.
Clients’ satisfaction is a major determinant of construction project performance. However,
there has been change in clients demands and this has lead to innovative and modern approach
to achieve their demand. Value Management seeks to address challenges such as budget
constraints or restrictions by seeking to reduce unnecessary costs towards the project without
affecting quality and reliability. This study therefore evaluates construction professionals’
perspective of the contributions of VM to the South African construction industry in South
Africa with a view to improving the utilization of the discipline in the industry.
2 Literature Review
Value management is not a cost-cutting exercise as perceived by many but the major focus of
the exercise in on function of an element or project. This implies that project is procured at the
lowest possible cost by employing various cost control mechanism without jeopardizing the
value and function of the project.
2.1 Value Management and the Construction Industry
VM plays an important role in the construction industry. It is a cost management tool because
it highlights all the ideas that would ensure that projects are delivered at the least possible cost
while maintaining value and function. Coetzee (2009) noted that VM services should be
combined with the total project economics service to achieve the best results from the VM
process. For many organizations construction represents a huge capital investment which
translates into significant fixed costs and may represent a constraint upon an organization’s
flexibility. Therefore, VM are applied in the construction industry to address the business
strategy issue of whether the construction of a facility represents the best manner in which to
meet the organization needs (Norton and McElligott, 1995). It should never be seen as a quick
fix or cost cutting exercise for projects in trouble (Srinath and Hayles, 2011).
VM ensures that all project participants have a clear understanding of the project brief and
work towards requirements of their clients (Coetzee, 2009). Manoliadis (2013) concluded that
the purpose of VM is to increase performance of the construction projects and to address
resources other than cost. VM process ensures that all project participants have a clear
understanding of the project brief and work towards the client’s requirements. It also offers the
means for project stakeholders to contribute to a better built environment and ultimately the
opportunity to accelerate development.
Originating from other industries, VM is as an essential part of project, construction, lean, risk,
and knowledge management system in the construction industry. It can be undertaken by a
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range of construction professionals but need the involvement of experienced facilitators. VM
is an activity based on systematic processes and utilise multidisciplinary teams in creative
workshops. VM is a means of defining project the objectives at uncertain events and it needs
creativity in order to generate options which meet required functions (Hiley and Paliokostas,
2001). A common technique used for the exercise is brainstorming which an important tool for
enhancing value of any project. VM enhances value by clarifying objectives, establishing good
communication and preventing conflicts. VE promotes the elimination of unnecessary cost and
as a consequence adds value to the project. Both techniques improve decision making
2.2 Barriers to Adopting VM in construction
The level of awareness, adoption and utilization of VM in South Africa is still very low as
observed by Coetzee (2009) and this has contributed to low value of construction projects.
Norton and McElligott (1995) stated that the basic reason to adopt VM is that there are always
elements or factors involved in a project which contribute to poor value. According to O’Farrell
(2010), VP, VE, VA and VM are often misunderstood by participants as devalue which may
contribute to the level of adaptation of VM to construction projects.
Another issue is the process involved in VM workshop. The important aspect of VM is that the
structure usually contains a five-phase process known as the job plan conducted during the VM
study or workshop to ensure improvement of project performance (Ashworth et al., 2013). In
decision making, the VM framework offers an auditable process for decisions for both parties
to review and contribute information. This method which enables the team members and
stakeholders to tackle each approach one step at the time in order to make decisions is called a
VM job plan which differs rendering to the timing within the project and scope of the study.
The purpose of the job plan is to identify and establish a balance of the objectives between
stakeholders, then throughout the project it is concentrated on the choices evaluation and the
design process with the activity to achieve the best value for the stakeholders (Srinath and
Hayles, 2011). O’Farrell (2010) illustrated the job plan approach into 6 stages that are
interwoven. These stages are information, function analysis, creative, evaluation, development
and presentation. The problem is that the decision to proceed or revert to an early stage depend
solely on the team members and this may not provide the best solution as expected of the
exercise. For instance, if the team perceived that the result is not satisfactorily after the
evaluation phase, they can revert to creative phase to seek better solution.
There also some risks associated with VM and these can jeopardize the objectives of the
exercise. These risks according to Seeley (1996); and Chhabra and Tripathi (2014) have direct
impact on the exercise and can only influence the entire project negatively. Poor representation
of the project stakeholders in the VM workshop that can result in them influencing the exercise.
More so, incorrect assumptions can also occur during the exercise due to insufficient and poor
quality information that is distributed. Another issue is insufficient allocation of time that can
affect the expected outcomes from the VM study. The exercise can also disrupt project team
and affect their activities, incur extra fees for the clients/sponsors and can extend design period
if not properly managed.
3 Research Methodology
In order to examine the contributions of VM to the South African construction industry,
determine the challenges affecting the its adaptation and establish measures that can be taken
to improve construction project performance using the concept of VM, quantitative research
approach was employed because it is more accurate and seeks to control for errors and bias in
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design. Survey design was therefore adopted through the administration of close-ended
questionnaires on target population comprising of Architects, Builders, and Quantity
Surveyors, Construction Managers, Project Managers and Civil Engineers who are registered
with their various professional bodies in Gauteng province, South Africa.
The study ensure that the professionals are currently working on on-going or have worked on
completed construction projects in the last one year. List of these professionals were obtained
from their professional bodies in order to ensure accuracy of information and ensure that quack
is not contacted for the study. Convenient method was employed in the sampling of respondents
due to time and cost constraints of sampling the whole population. Gauteng was also selected
because of high level of construction activities going on in the area that has attracted
construction professionals from other provinces of the country.
Questionnaire was adopted to ensure flexibility in data obtained from the respondents, provide
clear implications and ensure higher response rate. These were structured in English language
which is the official language for education and trading the respondents went through before
becoming professionals. The first part of the instrument address general information about the
respondents while other parts were structured based on the three main objectives of the study.
A covering letter was also provided detailing the purpose of the study, average duration it will
take to complete a questionnaire and other information relating to confidentiality of the data
provided. 60 questionnaires were administered personally and through email out of which 47
were retrieved.
5-point Likert scale was used as the basis of obtaining data with 5=Strongly Agree, 4=Agree,
3= Neutral, 2=Disagree and 1=Strongly disagree. The 5-point scale was converted to Mean
Item Score (MIS) for each of the identified variables for the purpose of determining relative
importance of the items, and thereby ranking them in descending order.
4 Findings and Discussion
4.1 Background information of respondents
On the average, the respondents are currently involved in about 2 projects. 53% of them are
males while 47% are females. Respondents were spread across the four ethnic groups in that
81% are Africans, 11% are White, 6% are Coloured and 2% are either Indian or Asian with an
average experience of about 9 years. On the profession of respondents, 33% are quantity
surveyors, 24% are architects, 11% are engineers, 11% are project managers, 9% are builders,
6% are construction managers while 6% are site agents.
4.2 Benefits of Value Management to Construction Industry
On the level of adoption of VM to construction projects, it could be observed that the practice
is mostly used for renovations and housing estates projects. It is also common in hospitals,
schools and government offices construction while it is rarely used in civil and heavy
engineering construction works.
The major advantage of VM to South African construction industry as revealed in table 1 are
optimization of value, clearer focus on the project objectives and more effective design. It also
identifies of unnecessary costs associated with project, enhances client involvement, provides
the structure for project team to collaborate, advances design decisions and highlights various
design options for selection. The least benefits are improving design efficiency, provides an
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authoritative review of the project, enhances consensus between stakeholders affords an
independent functional review of construction project.
Table 1: Contributions of Value Management
MIS=Mean Item Score; σX= Standard deviation; R=Rank
4.3 Barriers to Adoption of VM in the Construction Industry
The major challenges affecting the adaptation of value management in the industry are poor
communication and lack of interaction among construction team members coupled with the
fact that clients are unwilling to pay for the service of VM. Equally important factors are
insufficient time to do the job, VM session not properly facilitated, VM can easily be
misunderstood by the participants, incorrect assumptions by stakeholders, lack of needed
information, lack of experts in VM exercise and VM incur extra fees. Others are outdated
standards or specifications, difficulty in conducting evaluation and resistance from design
consultants.
Table 2: Challenges of VM adaptation
Benefits of VM MIS σX R
Optimize value for money 4.36 10.12 1
Creates a clearer focus on the project objectives 4.30 7.57 2
Works towards arriving at a more effective design 4.21 8.08 3
Identifies unnecessary costs associated with the project 4.19 9.36 4
Improve ways to comply with the project brief 4.15 11.53 5
Seeks to obtain maximum efficiency ratios. 4.13 3.21 6
Mutual understanding between the stakeholders is enhanced 4.13 9.98 7
Provide clear definitions of responsibilities 4.09 6.66 8
Value Management discovers project issues, constraints and risks involved 4.09 8.26 9
Supports information of the project brief 4.09 13.43 10
Client involvement is enhanced 4.09 8.92 11
Highlights design options for selection 4.06 7.93 12
Advance design decisions 4.06 8.46 13
Provides the structure for the team to collaborate 4.06 10.11 14
Provides the structure for the team to gain the benefits of partnering. 4.00 6.85 15
Provides clear definition of roles 3.98 6.90 16
Provides management with authoritative evaluations 3.94 9.11 17
Reduce project costs 3.94 9.14 18
Provides an authoritative review of the project 3.91 8.33 19
Improve design efficiency 3.91 9.46 20
Consensus between stakeholders is enhanced 3.89 9.11 21
Value Management can afford an independent functional review 3.70 9.91 22
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Challenges MIS σX R
Poor communication 4.34 10.53 1
Clients are unwilling to pay for the service 4.06 8.26 2
Lack of interaction 4.06 11.73 3
Not enough time to do the job 4.04 7.50 4
Value Management session is not properly facilitated 4.02 8.50 5
Can easily be misunderstood by the participants 4.02 9.78 6
Poor representation of the project stakeholders in the Value Management
study
4.00 9.14 7
Lack of coordination between the designers 4.00 10.74 8
Value Management session is not properly guided 3.96 8.32 9
Incorrect assumptions 3.94 6.13 10
Lack of participation 3.94 8.53 11
Lack of needed expects 3.89 4.79 12
Lack of needed information 3.89 5.91 13
Incur extra fees 3.89 9.81 14
Deficiency of coordination between operations’ personnel 3.87 6.29 15
Clients do not request the service 3.87 8.06 16
Extra work for existing project team 3.85 6.55 17
Difficulty in conducting analysis 3.81 5.50 18
Not adequately supported by senior management 3.79 6.11 19
Extend design period 3.79 8.79 20
Outdated standards or specifications 3.77 5.91 21
Value management skills are unavailable 3.77 6.11 22
Scope of changes for missing items 3.74 6.40 23
Difficulty in conducting evaluation 3.74 6.45 24
There is resistance from design consultants 3.66 2.50 25
MIS=Mean Item Score; σX= Standard deviation; R= Rank
4.4 Measures to Improve Project Performance through VM
Table 3 indicate factors to be considered in order to improve project performance using value
management principles in the construction industry. There is a need for innovative ideas and
solution, orientation meeting for team members to familiarise with the project and process, cost
estimate verification during the exercise and excellent communication skills. More so, positive
environment must have created for members, a visit to the site should be arranged for team
members, proper introduction of value management facilitator should be ensured and a
knowledge management system should be developed for the discipline.
Table 3: Measures to improve construction project performance using VM
Measures MIS σX R
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Innovative ideas and solution 4.47 11.37 1
Excellent communication skills 4.38 9.45 2
Orientation meeting 4.38 12.10 3
Cost estimate verification 4.38 13.32 4
Selection of the value management team members 4.36 11.30 5
Function Analysis 4.34 10.21 6
Finalizing the team structure 4.32 8.39 7
Evaluation criteria 4.32 11.68 8
Developing a performance measurement framework for value management
studies
4.30 9.45 9
Record all the ideas shared in the value management sessions 4.28 9.71 10
Information gathering 4.28 10.24 11
Positive environment 4.26 6.66 12
A visit to the site 4.21 9.50 13
Structuring the process 4.19 8.50 14
Introduce the value management facilitator 4.17 11.18 15
Creative thinking techniques 4.15 9.61 16
Deciding on the duration of the value management session 4.11 8.96 17
Establishing a group support system 4.11 11.30 18
Determining study location and conditions 4.09 11.18 19
Preparation of models 4.09 11.73 20
Using value added/based strategies 4.06 7.37 21
Preparation of efficiency data 3.96 9.64 22
Developing a knowledge management system 3.96 10.40 23
MIS=Mean Item Score; σX= Standard deviation; R= Rank
4.5 Discussion of Findings
VM has contributed to the performance of construction industry in no small measure. In support
of May (1994), Norton and McElligott (1995), Seeley (1996), and Oke et al. (2015) argue that
VM enhances project value, improves design efficiency, optimizes value for money and
advances design decisions. It also creates clear focus on the project objectives, discovers
project issues, constraints, and risks involved, and provides an authoritative review of the
project. In addition, Coetzee (2009) notes that VM will not only provide clear definitions of
responsibilities but will also ensure mutual understanding between the stakeholders and
provides clear definitions of roles if fully adopted.
The major challenges of VM adoption in the construction industry are concerned with
stakeholders' issues and wrong perception of the discipline due to lack of training, orientation
and proper awareness of stakeholders. Chhabra and Tripathi (2014) identified lack of needed
information as well as difficulty in conducting evaluation and analysis as major challenges
while Seeley (1996) identified extra work for the existing team as the major challenge.
Ashworth et al. (2013); and Aghimien and Oke (2015) also stated that lack of enough time to
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do the job, unwillingness of client to request and pay for the service are the major factors.
Norton and McElligott (1995) noted that the major variable is poor communication and it could
be noted that these challenge would have encountered where the earlier stated challenges are
prevalent. Adopting modern method and effective commutation will enhance and improve
adoption and utilization of VM in the construction industry. In agreement, Ashworth et al.
(2013) identified function analysis as one of the most effective measures while Norton and
McElligott (1995) and Coetzee (2009) concluded that selection of value management team
members, finalising the team structure and duration of the study were the most effective
measures to be taken to improve project performance using the process of VM in the
construction industry.
5 Conclusion and Further Research
Value management has contributed to performance of construction projects as evidenced in
studies and findings from various countries where it has been fully implemented. In South
Africa, the discipline has not fully adopted and utilized for construction projects due to lack of
awareness, insufficient information about the discipline, wrong perception of the discipline,
unwillingness on the part of clients to adopt and pay for the exercise as well as lack of
motivation from other concerned stakeholders. However, the fact that it has been introduced
and used mostly for renovation and school projects has contributed to the goal of construction
projects, which is to provide value for money for construction clients and enhance better project
performance. It has serve as a viable management tool to optimize value for money, create
clearer focus of project objectives, works towards more effective design and identifies
unnecessary costs through unnecessary design, material, labour and machine.
In order to improve the use of VM for better performance of construction projects, there is a
need to adopt innovative ideas and solutions that will work for South African construction
industry considering the culture and state of mind of the general citizen. There is also a need
for excellent communication skills of construction professions since they are all potential VM
team member and more information gathering to understand effective ways of applying the
discipline. Appropriate and relevant guidelines as well as legislations to adopt, enforce and
monitor the application of the discipline is also an important prerequisite.
6 References
Afshar, A. and Rezaei, A. (2013). Value management in building construction industry of
northern Cyprus: Addressing a theory and practice gap. USA, American Society of Civil
Engineers.
Aghimien, D. O. and Oke, A. E. (2015). Application of value management to selected
construction projects in Nigeria, Developing Country Studies, 5(17), pp. 8-14.
Ashworth, A., Hogg, K. and Higgs, C. (2013). Practice and Procedure for Quantity Surveyors.
USA, John Wiley & Sons Ltd.
Bowen, P., Cattell, K., Edwards, P. and Jay, I. (2010). Value management practice by South
African quantity surveyors. Facilities, 28(1/2): pp. 46–63
Chhabra, J. and Tripathi, B. (2014). Value Engineering: A Vital Tool for Improving Cost &
Productivity. International Journal Industrial Engineering & Technology, 4(6): pp. 1-10.
Coetzee, C.E. (2009). Value Management In The Construction Industry: What Does It Entails
And Is It a Worth While Practice? BSc thesis submitted to Department of Quantity
Surveying, University of Pretoria, South Africa.
234
Ellis, R.C.T., Wood, G.D. and Keel, D.A. (2007). Value management practices of leading UK
cost consultants. Construction Management and Economics, 23(5): pp. 483-493.
Hiley, A. and Paliokostas, P.P. (2001). Value Management and Risk Management: An
Examination of the Potential for their Integration and Acceptance as a Combined
Management Tool in the UK Construction Industry. In RICS (edn.) Construction and Built
Research Conference, 3 - 5 September, Glasgow, Royal Institution of Chartered Surveyors,
pp. 49-57
Kelly, J. (2007). Making client values explicit in value management workshops. Construction
Management and Economics, 25 (4): pp. 435-442.
Lin, G. and Shen, Q. (2007). Measuring the Performance of Value Management Studies in
Construction: Critical Review, Journal of Management in Engineering, 23(1), pp. 2-9.
Manoliadis, O. (2013). Sustainability Issues as Applied to the Value Management Practices in
Construction Projects. A publication of American Society of Civil Engineers, USA.
May, S.C. (1994). Value engineering and value management. The College Of Estate
Management: United Kingdom.
Norton, B.R. and McElligott, W.C. (1995). Value Management in Construction: A Practical
Guide. MacMillan Press Ltd: London.
O’Farrell, P.K. (2010). Value Engineering: An Opportinity for Consulting Engineers to
Redefine Their Role. MSc Thesis in Construction Project Management: Waterford Institute
of Technology, Ireland.
Oke, A. E, Aghimien, D. O. and Olatunji, S. O. (2015). Implementation of value management
as an economic sustainability tool for building construction in Nigeria, International
Journal of Managing Value and Supply Chains, 6(4), pp. 55-64.
Seeley, I.H. (1996). Building Economics (4th edn.), Palgrave MacMillan: London.
Shen, Q. and Liu, G. (2004). Applications of Value Management in the Construction Industry
in China. Engineering, Construction and Architectural Management, 11(1), pp. 9-19.
Sigle, H.M., Klopper, C.H. and Visser, R.N. (1999). Value Management in the South African
Construction Industry, Acta Structilia, 6(1/2), pp. 41-50.
Srinath, P.C.S. and Hayles, S.K. (2011). An Analysis of Value Management in Practice: The
Case of Northern Ireland’s Construction Industry. Journal of Financial Management of
Property and Construction, 16(2), pp. 94-110.
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Perceptions of Skilled Labour Attributes on Delays in
Construction Projects in India Dillip Kumar Das
Department of Civil Engineering,
Central University of Technology, Free state, South Africa
Email: ddas@cut.ac.za
Abstract
Evidence from the literature suggests that the causes of delays in construction are well
researched. Client, contractor, consultant, design, equipment and material related aspects have
varied influence on the occurrence of delay. However, the perception of various labour
attributes on the occurrence of delay have been least investigated. Thus, the objective of the
paper is to identify the various labour attributes that cause delay and examine how these
attributes influence the occurrence of delay. A survey was conducted among various
stakeholders that include engineers, contractors, clients, project managers, architects,
supervisors, labour contractors and skilled labourers to collect the data on the perception of
labour attributes that cause delay. To conduct the survey a questionnaire was distributed among
75 individual stakeholders selected through random sampling process from 3 construction
projects in Bhubaneswar city of India. A perception index was developed based on weighted
average method to examine the relative influence of the labour attributes on delay followed by
descriptive statistics analysis and significance tests to establish the interlinkage between labour
attributes and their consequences that cause delay. Findings revealed that lack of appropriate
skill, lack of adequate remuneration, poor commitment by the labours to the project work are
the major labour attributes which engender delay in construction projects. It is also found that
lack of skill and competency lead to poor quality of work and consequently rework and delay.
Poor remuneration prompts poor commitment to the projects. Poor commitment slows down
the speed of work, and regular availability to the project and consequently influence the level
of output, thus contributing to the delay of the projects. The findings contribute to the discourse
of delay in construction from the labour attribute point of view.
Keywords:
Construction projects; Commitment; Delay, Labour attribute; Remuneration; Skill
1 Introduction
Availability of skilled labour is among the most essential requirements for successful and
timely completion of the construction projects. The actual construction work, quality of
construction, handling and use of materials, plants and machinery, preparation of site for
construction, efficiency of supply chain in the project site and the completion and delivery of
the project to name a few are the major activities that are carried out by the skilled labour. In
other words, they carry the actual burden of construction and quality of work. It is thus
imperative that there is a need to comprehend the skilled labour attributes so that skilled labour
should not become impediments to construction and cause delay of projects.
Delay is apparently a major cause of concern in many construction projects. The sources of
delays are varied and multi-fold. The essential reasons of delays in construction projects which
have been evidenced from the literature include the performance and involvement of
stakeholders, resource availability, environmental conditions, contractual relations, and so on
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(Alaghbari, Razali, Kadir and Ernawat 2007; Bon-Gang, Xianbo, Lene Lay 2015; Bon-
Gang, Shimin, 2014; Bon Gang & Lay Peng, 2013; Kaming, Olomolaiye, Stumpf, 2000; Odeh
and Battaineh, 2002). The important causes of delays which have been intensively investigated
are contractor related factors, client related aspects, and consultant design linked attributes
(Alwi, and Hampson, 2003; Aiyetan and Das, 2015; Bon-Gang, Xianbo, Lene Lay, 2015;
Bon-Gang, Shimin, 2014; Bon Gang & Lay Peng, 2013; Das, 2015; Sweis, Sweis, Hammad,
Abu, 2008). Furthermore, improper and inadequate material supply that impedes on the speed
of construction of a project relative to on time delivery is also a factor that causes significant
delay. Poor quality of the material, poor material handling on site, poorly scheduled delivery
of material to site, inappropriateness/misuse of material, poor storage, etc., which are
performed by the labour force both on and off the project site influence the other activities and
stakeholders to keep the project on schedule (Alwi and Hampson, 2003). Lack of trades’ skills,
poor distribution of labour, inadequate number of supervisors / foremen, inexperienced
inspectors, and shortage of manpower (skilled, semi-skilled, unskilled labour) are also the
factors that adversely influence the delivery of projects on time (Alwi and Hampson 2003;
Odeh and Battaineh 2002; Sambasivan and Soon 2007; Satyanarayana and Iyer 1996; Sweis et
al., 2008). More importantly, lack of skill and competency of human resources - particularly
the labour in the construction project are the major factors that adversely affect project delivery
time (Alwi and Hampson 2003; Odeh and Battaineh, 2002; Sambasivan and Soon, 2007;
Satyanarayana and Iyer, 1996; Sweis et al., 2008). So, the role of skilled labourers in the
completion of projects has been highly significant although largely undermined. Besides,
although a plethora of researches have been evidenced on various issues causing delay in
construction of projects, investigations on the challenges of skilled labourers and their
attributes with regards to delay are scarce.
Therefore, the objective of the paper is to identify the various labour attributes that cause delay
and examine how these attributes influence the occurrence of delay. For this purpose, a survey
research method was followed and a perception survey was conducted among various
stakeholders that include engineers, contractors, clients, project managers, architects,
supervisors, labour contractors and skilled labourers to collect the data on the perception of
labour attributes that cause delay. Findings suggest that lack of appropriate skill, lack of
adequate remuneration, poor commitment by the labours to the project work are the major
labour attributes which engender delay in construction projects. It is also found that lack of
skill and competency lead to poor quality of work and consequently rework and delay. Poor
remuneration prompts poor commitment to the projects. Poor commitment slows down the
speed of work, and regular availability to the project and consequently influence the level of
output, thus contributing to the delay of the projects. The findings contribute to the discourse
of delay in construction from the labour attribute point of view.
2 Research Methodology
2.1 Case study area and profile of projects
Three construction projects in Bhubaneswar city of India were used as case studies for data
collection from stakeholders. Bhubaneswar is the provincial capital of Odisha state located on
the eastern part of the country. It is one of fastest growing cities of the country having a
population of about 0.88 million and area of 422 sq. km (Census, India, 2011). Currently the
city is being considered as one of the top most cities to be developed as a smart city in India.
Although started as the administrative capital of the Odisha state (province), large scale
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industrial activities particularly in the areas of knowledge industry and education sector
become integral part of the city functions. Consequently, a spurt in the real estate development
and construction activities have been seen particularly in the last one and half decade. Like
many other parts of the country, construction activities in the city are also being suffered
because of various challenges such as availability of finance, budget constraints, conflict
among the stakeholders like promotors, contractors and consumers (buyers) and more
importantly labour related issues. Therefore, to comprehend the labour related challenges and
labour attributes linked to delay in construction three different projects have been chosen as
case studies for data collection from various stakeholders engaged in the construction of the
projects. The three projects include two building projects – a housing apartment project, one
university building project in the private sector and a road project commissioned by the
Government but executed by a private contractor. Table 1 presents the profile of projects. The
estimated duration of the projects varies between 18-30 months for building projects and 12
months for the road project. The approximate estimated cost of projects is 3.0 million USD for
housing projects, 0.75 million for university building and 0.5 million USD for the road projects
(estimated from the information obtained from the stakeholders in the absence of actual and
reliable estimate, which could not be obtained directly from the promotors/owners). The
building projects were owned by private promoters/ developers and the contractors were
appointed by the owners directly. The owners have direct authority over the contractors. The
road project was owned by the Government (Municipal Corporation) and the contractor was
appointed through competitive biddings. However, the labourers were the direct responsibility
of the appointed contractors, who have appointed skilled labourers directly and employed
semiskilled/unskilled labours through labour contractors/subcontractors
Table 1 Profile of projects
Source: Researcher
2.2 Survey, data and analysis
A stakeholder’s perception survey was conducted to collect primary data by using pretested
questionnaires. To conduct the survey a questionnaire was distributed among 75 individual
stakeholders selected through random sampling process from the 3 mentioned construction
No Type Ownership Estimated
project cost
(USD)
Estimated
project
duration
(months)
Contractor
1 Housing
projects
Private
sector
(Real estate
developer)
3.0
Million
30 Multiple contractors from
private sector engaged in
different activities under
the promoters direct
authority
2 University
Building
Self-
financed
University
authorities
0.75
Million
18 A main contractor working
directly under the
promoters direct authority
but has employed several
sub- contractors
3 Road Governme
nt
0.50
Million
12 Contractor selected
through tendering process.
238
projects. The survey was conducted among various stakeholders that include engineers
(12%), contractors (8%), clients (4%), consultant (8%) project managers (4%), architects
(5.3%), supervisors (12%), labour contractors (8%), and skilled labourers (38.7%) to collect
the data on the perception of labour attributes that cause delay (Table 2).
Quantitative descriptive statistics analysis and Cronbach’s alpha test of the data collected
were conducted to observe the reliability of the data. A perception index was developed
based on weighted average method to examine the relative influence of the labour attributes
on delay followed by descriptive statistics analysis and significance tests (t test for α ≤ 0.05)
at 95% confidence level were conducted to establish the interlinkage between labour
attributes and their consequences that cause delay. Perception index was calculated by
considering the weighted average of the perceptions of stakeholders assigned by the
respondents on a particular variable in a scale ranging between 0 and 1. The formula used
for calculating perception index is given in Equation (Eq.1).
Perception Delay index= PDI= ∑wxi/ ∑xi ..............................................................Eq. (1)
xi= number of respondents assigning a particular index value
wi= index values assigned by respondents.
A perception index was developed based on weighted average method to examine the
relative influence of the labour attributes on delay followed by descriptive statistics analysis
and significance tests to establish the interlinkage between labour attributes and their
consequences that cause delay.
Table 2: Profile of respondents in survey
Stakeholders Number
surveyed
Response (%)
Engineer 9 12.0
Architect 4 5.3
contractor 6 8.0
Client 3 4.0
Consultant 6 8.0
Project manager 3 4.0
Supervisor 9 12.0
Labour contractors 6 8.0
skilled labourer 29 38.7
Total (N) 75 100.0
Source: Researcher
3 Findings and Discussions
The relative influences of the attributes were evaluated based on the share of respondent
stakeholders agreed to a particular attribute as a challenge and the average perception index
obtained from the responses assigned by them. However, before each attribute’s influence is
measured the data and responses were checked for reliability and consistency of the responses.
The high Chronbach α of the attributes (ranging between 0.81 and 0.89) suggest for reliability
of the data set used for evaluation (see Table 3). Furthermore, the very low Standard Deviation
(SD) values for each attribute (values range between 0.10 and 0.18) indicate the consistency of
the responses (see Table 3). Therefore, the responses and data set was considered reliable and
suitable for evaluation of the influences of skilled labour attributes on delay. Table 3 presents
the relative influence of the various skilled labour attributes on construction delay. It is found
239
that majority of the respondents agree that lack of appropriate skill and competency among
labourers (89.0%), inadequate remuneration (94.4%), poor commitment to the project (83.1%),
lack of belongingness (81.3%) and lack of availability of labourers to project (76.1%) are the
major skilled labour attribute challenges. However, relatively less number of respondents opine
that lack of appropriate technical knowledge (62.1%), lack of training (60.7%), poor
communication skill of labourers (57.1%), coordination and communication between
supervisors and labourers (63.1%), motivation to complete a task in time (58.3%), and conflict
with other stakeholders (34.8%) are relatively lesser skilled labour attribute challenges.
Consequently, based on the perception indices, inadequate remuneration (PDI= 0.84), lack of
appropriate skill and competency (PDI=0.82), poor commitment (PDI=0.79), lack of
belongingness to the project (PDI=0.76), lack of availability of skilled labourers to the project
on account of poor remuneration and commitment (PDI= 0.72) are the major skilled labour
attributes which contribute to the construction delay.
Table 3 Relative influence of skilled labour attributes on construction delay
Skilled labour attributes N Response (%) PDI SD Chronbach
α
Lack of appropriate skill
and competency
73 89.0 0.82 0.16 0.87
Lack of appropriate
technical knowledge
58 62.1 0.61 0.14 0.84
Inadequate Remuneration 72 94.4 0.84 0.18 0.86
Lack of training 56 60.7 0.62 0.14 0.83
Poor communication skill 63 57.1 0.52 0.14 0.85
Coordination and
communication between
supervisors and labourers
65 63.1 0.68 0.16 0.86
Poor commitment 59 83.1 0.79 0.17 0.89
Motivation for completion
of the given task
48 58.3 0.68 0.11 0.81
Lack of belongingness to
the project
64 81.3 0.76 0.18 0.82
Lack of availability due to
poor remuneration and
commitment
67 76.1 0.72 0.12 0.81
Rework because of lack of
skill and competency
62 77.4 0.77 0.15 0.84
Conflict with other
stakeholders
69 34.8 0.42 0.10 0.84
(Significance test p values < 0.05 for α<0.05)
Furthermore, an interlinkage among the various major labour attributes and their causal effects
that influence delay were established by significance t tests and p values for 95% confidence
level (for α<0.05). Table 4 presents the interlinkage between labour attributes and causal
effects. The significance test results revealed that lack of skill and competency cause poor
quality of work that lead to rework (p values < 0.05 for α<0.05), which contributes to the delay
of the projects. Poor remuneration lead to poor commitment, lack of belongingness and lack of
availability of skilled labourers to the project (p values < 0.05 for α<0.05), which essentially
lead to delay form the skilled labourers point of view. Similarly, poor commitment leads to
lack of speed in work and adherence to schedule which also cause delay in construction (p
values < 0.05 for α<0.05). However, analyses with regards to motivation to complete a task in
time by the labourers indicate that while inadequate remuneration do not motivate the labourers
to complete a task in time (p values < 0.05 for α<0.05). However, lack of appropriate skill and
competency do not have any real bearing for lack of motivation to complete a task in time (p
240
values > 0.05 for α<0.05). Thus, the causal effects of lack of skill and competency and poor
quality of work and consequent rework; inadequate remuneration leading to poor commitment,
lack of availability of skilled labourers, lack of belongingness and lack of motivation to
complete as task in time; and poor commitment leading to lack of speed in work and adherence
to schedule influence construction delay from the skilled labourer attributes point of view.
Table 4 Interlinkage between skilled labour attributes and their causal effects influencing
delay (based on significance t- test results and p values)
Labour attribute Causal effect for
delay
df T values p* p** Significance
Lack of
appropriate
skill and
competency
Poor quality of
work and
rework
122 4.23 0.000022 0.000045 Significant
Inadequate
remuneration
Poor
commitment
116 3.79 0.00012 0.00024 Significant
Inadequate
remuneration
Lack of
availability
126 2.84 0.0026 0.0052 Significant
Inadequate
remuneration
Lack of
belongingness
126 3.58 0.00024 0.00048 Significant
Poor
commitment
Lack of speed
in work and
adherence to
schedule
116 4.16 0.00003 0.00006 Significant
Lack of
appropriate
skill and
competency
Lack of
motivation to
complete task
in time
94 1.59 0.057 0.115 Insignificant
Inadequate
remuneration
Lack of
motivation to
complete task
in time
94 1.79 0.016 0.033 Significant
Source: Researcher
4 Conclusions
Delays are a major challenge in construction projects in India. Skilled labourers are an integral
part of construction projects and influence the timely completion of construction work.
However, the skilled labour attributes component of the construction projects and their
influence on delay in construction projects have been largely undermined. Moreover, studies
on this aspect, particularly in the Indian construction industry sector are found to be scarce. So
using the case study of three construction projects in Bhubaneswar city in India, and conducting
a survey among the various stakeholders including skilled labours in the three mentioned
projects, the study identified the various labour attributes that cause delay and examined how
these attributes influence the occurrence of delay. The study revealed that inadequate
remuneration, lack of appropriate skill and competency, poor commitment by the labours to
the project work, lack of belongingness of labourers to the project and lack of availability of
skilled labourers due to poor remuneration are the major labour attributes which engender delay
in construction projects. It is also found that lack of skill and competency lead to poor quality
of work and consequently rework and delay. Poor remuneration also prompts poor
commitment, lack of belongingness, lack of availability to the projects and lack of motivation
to complete a task in time. Poor commitment slows down the speed of work, and do not allow
the labourers to adhere to the schedule and consequently influence the level of output, thus
contributing to the delay of the projects. However, it is also found that lack of appropriate skill
241
and competency does not lead to lack of motivation to complete a task in schedule conclusively.
Thus, the study indicates that major labour attributes such as poor skill and competency,
inadequate remuneration, poor commitment, lack of belongingness of the labourers to projects
are the significant challenges and their causal effects which need to be taken care of in order to
mitigate or reduce delay in construction from the skilled labourers’ point of view.
The paper has certain limitations such as the investigation is conducted based on primary data
and perception of the stakeholders because of unavailability of structured statistical data.
However, availability and analysis of statically data would have provided further insight to the
skilled labour related attributes and their influence on construction delay. However, in its
current state the findings contribute to the discourse of delay in construction from the labour
attribute point of view, which has not seen intensive research so far. Besides, the study is
relevant to the owners of the projects, project team including project managers, and supervisors
as it will provide them the requisite insights to comprehend the skilled labour attribute related
challenges and their causal effects that lead to delay so that corrective measures can be taken
to overcome the challenges and reduce delay.
5 References
Alaghbari, W., Razali, M., Kadir, S., Ernawat, G. (2007). ‘The significant factors causing delay
of building construction projects in Malaysia, EngConstr Arch Manage, 14(2), pp. 192–
206.
Alwi, S. and Hampson, K., Identifying the important causes of delays in building construction
projects. In Proceedings The9th East Asia-Pacific Conference on Structural Engineering
and Construction, Bali, Indonesia, 2003.
Aiyetan OA., Das, D. (2015). Using system dynamics modelling principles to resolve problems
of rework in construction projects in Nigeria, Journal of Construction Project
Management and Innovation, Vol. 5(2), 1266-1295.
Bon Gang, Hwang. & Lay Peng, Leong. (2013). Comparison of schedule delay and causal
factors between traditional and green construction projects, Technological and Economic
Development of Economy, 19(2) pp. 310-330, DOI: 10.3846/20294913.2013.798596
Bon-Gang, Hwang., Shimin, Yang. (2014). Rework and schedule performance: A profile of
incidence, impact, causes and solutions, Engineering, Construction and Architectural
Management, 21 (2), pp.190 – 205.http://dx.doi.org/10.1108/ECAM-10-2012-0101
Bon-Gang, Hwang., Xianbo Zhao, Lene Lay Ghim, Tan. (2015). Green building projects:
schedule performance, influential factors and solutions’, Engineering, Construction and
Architectural Management, 22 (3), pp. 327 – 346.
Census, India (2011). Odisha State, India
Das, D., Development of Mechanisms by Using Conceptual System Dynamics Models to
Resolve Delay in Construction Projects, International Construction Specialty Conference
2015, June 7-10, Vancouver, Canada, 2015.
Kaming, P., Olomolaiye, P., Holt, G., Harris, F. (1997). Factors influencing construction time
and cost overruns on high-rise projects in Indonesia. Construction Management
Economics, 15(1), 83–94.
Odeh A. M., Battaineh H. T., 2002. Causes of construction delay: traditional contracts.
International Journal of Project Management, 20(1), 67–73.
Sambasivan, Murali., Soon, Yau Wen., Causes and effects of delays in Malaysian construction
industry. International Journal of Project Management, Elsevier, 25, 517–526, 2007.
Satyanarayana, K.N., and Iyer, K.C., Evaluation of delays in Indian construction contracts.
Journal of the Institution of Engineers (India), Springer, 77, 14–22, 1996
242
Sweis G., Sweis R., Hammad A. Abu, Shboul A., Delays in construction projects: The case of
Jordan. International Journal of Project Management, Elsevier, 26, 665–674, 2008.
243
Determinants of Small and Medium Contractor Business
Failure Christopher Collins and Gerrit Crafford
Department of Quantity Surveying,
Nelson Mandela Metropolitan University,
Email: gerrit.crafford@nmmu.ac.za
Abstract:
The study aimed to determine the most prevalent/predominant external (macro) and internal
(micro) factors contributing to small and medium contractor business failure within Port
Elizabeth, South Africa. A literature review was conducted of the relevant literature relating to
small and medium enterprises and factors leading to small and medium contractor business
failure. The information obtained was used to develop a questionnaire which was distributed
to a sample of small and medium contractors operating within Port Elizabeth. The data obtained
from the questionnaires was analysed and interpreted in terms of the objectives of the research.
The research established that factors contributing to small and medium contractor business
failure, and the extent thereof, vary from business to business. It is not one factor, but rather a
combination of factors that interacts, causing company performance to spiral towards
inevitable bankruptcy. However, the majority of small and medium contractors operating in
Port Elizabeth perceived access to finance as being the most prevalent/predominant external
(macro) factor contributing to business failure. Ironically, too much debt (debt financing) was
perceived the most prevalent/predominant internal (micro) factor contributing to company
collapse. Research will be delimited to owners and/or managers of small and medium
construction enterprises operating within Port Elizabeth, South Africa. The study is of
importance to both current and future entrepreneurs, in various small business sectors, notably
construction. South African entrepreneurs need to be informed of the challenges faced by small
and medium enterprises. Factors contributing to small and medium contractor business failure
are revealed here. The study could provide entrepreneurs with the knowledge and guidance to
avoid business failure, aid in the development and sustainability of small and medium
enterprises, and ultimately provide our nation with the ammunition to defeat the triple
challenges of poverty, unemployment and inequality.
Keywords:
Construction industry, Failure factors, Small and medium enterprises,
1 Introduction “For big companies, the SMEs represent the world from which they came and wherefrom their
future competitors will come. For individuals, SMEs often represent their first job, the first step
in their career or the first step into the world of entrepreneurs. For the economy in whole, the
SMEs are regarded as an essential element in a successful formula for achieving economic
growth” (Savlovschi & Robu, 2011).
Malhembe (2011:14) noted that: “One of the most significant characteristics of a flourishing
and growing economy is a vibrant and blooming SME sector.” A healthy SME sector is of
great importance to the economy, irrespective of the country’s developmental stage, through
job creation, economic growth and social progress. Two thirds of the newly created jobs are
owed to the small and medium sector (Savlovschi & Robu, 2011). Not only are they a main
driver for generating employment, they also promote innovation, foster regional economic
244
integration, eradicate poverty and improve standards of living (Malhembe, 2011). Therefore,
SMEs are of vital importance to the economic prosperity of any country.
SMEs particularly play a vital role in developing countries, with major employment and
income distribution challenges, such as South Africa (Cant & Wiid, 2013). It was estimated
that 91 percent of total businesses in South Africa are SMEs and that these SMEs contribute
between 52 to 57 percent to GDP and account for roughly 61 percent of employment (Cant &
Wiid, 2013). According to these statistics, SMEs have, at least in theory, the potential to
generate employment and upgrade human capital (Berry, von Blottnitz, Cassim, Kesper,
Rajaratnam & van Seventer, 2002).
Despite the acknowledged importance of SMEs; SMEs are still facing a number of difficulties
and impediments that are hindering and complicating their operations and growth (Mahembe,
2011). SMEs are criticised for their high rate of bankruptcy. It is a fact that SA has one of the
lowest SME survival rates in the world (Mahembe, 2011). While they create many jobs, they
also destroy a lot of jobs. Construction SMEs face the same challenges as their counterparts in
other sectors of the economy (Apples, 2010). Therefore, the fact that failing SMEs hold the
greatest potential to inflict damage on society; certainly holds true within construction.
Moilwa (2013) stated that 70 to 80 percent of small and medium-sized contractors in South
Africa fail within the first five years. Given that such a large percentage of SME is
unsuccessful, it is meaningful to investigate the causes of poor performance and failure faced
by these firms. Much research has been done on the success and growth factors of new firms.
In contrast, little has been done to examine factors of poor performance and failure of
established SMEs. This study aims to fill the abovementioned theoretical gap. This is supported
by Franco & Haase (2009), who stated that the failure of SMEs is a vitally important area for
research and he rightly stated that no policy can be formulated for SMEs without a central
understanding of business malfunctions.
Consequently, the objective of this research was to identify the factors leading to the failure of
construction SMEs within Port Elizabeth. The factors identified were grouped in order to
establish the most prevalent/predominant external (macro) and internal (micro) contributors to
SME contractor business failure.
This will provide current and future entrepreneurs, in various small business sectors, with the
knowledge and guidance to prepare for and avoid business failure. It will also aid in the
development and sustainability of SMEs; ensure the production of high quality infrastructure;
and ultimately provide our nation with the ammunition to defeat the triple challenges of
poverty, unemployment and inequality.
2 Literature Review
2.1 Defining an SME
2.1.1 International overview
While the importance of the SME sector and the informal sector is acknowledged globally,
defining an SME is an extremely challenging task, as every country has its own definition. The
existence of numerous definitions is a consequence of the fact that there is a multitude of
criteria that could be considered when defining an SME. Nonetheless, some criteria are used
245
more predominantly in defining SMEs. These criteria include number of employees, turnover
and total balance sheet (Buculescu, 2013).
2.1.2 Defining an SME in South Africa
In order to define an SME from a South African perspective, various sources may be utilised.
However, for the sake of this research, the definition supplied by the National Small Business
Act of 1996 was used in determining whether respondents and the business they represent can
be classified as being a small to medium enterprise.
A ‘small business’ is defined as follows: “A separate and distinct business entity, including co-
operative enterprises and nongovernmental organisations, managed by one owner or more
which, including its branches or subsidiaries, if any, is predominantly carried on in any sector
or sub sector of the economy mentioned in column I of the Schedule.” (RSA, 1996)
Small businesses can be classified as micro, very small, small or medium enterprises, following
a complex set of thresholds (RSA, 1996). The National Small Business Act defines the
thresholds per sectors and sub-sectors.
Also, small and medium-sized enterprises were focused on, not SMMEs. A small enterprise
includes both very small and small organisations. If one of the thresholds, according to Act 102
of 1996, categorises the construction firm as being a small to medium enterprise, the
organisation was more than likely included in the research.
2.1.3 Defining a construction SME in South Africa
The National Small Business Act of 1996 defines a construction SMME according to certain
thresholds, namely: number of full time employees, total annual turnover and total gross asset
value. According to these thresholds, very small contractors are defined as firms that employ
between 5-20 full-time employees, earn a total annual turnover between R200 000-R3 million,
and have a total gross asset value between R100 000-R500 000. Small contractors can be
defined as firms that employ between 20–50 full-time employees, earn a total annual turnover
between R3 million-R6 million, and have a total gross asset value between R500 000-R1
million. Medium contractors employ between 50–200 full-time employees, earn a total annual
turnover between R6 million-R26 million, and have a total gross asset value between R1
million-R5 million (RSA, 1996).
2.2 Economic importance of SMEs
2.2.1 Importance of SMEs to the South African economy
SMEs are renowned for the vital role they play in almost all economies, but particularly in
developing countries with major employment and income distribution challenges, such as
South Africa. The creation and sustainability of new SMEs are essential to the economic
prosperity of a country or else it risks an economic stagnation (Cant & Wiid, 2013). A study
conducted by Mahembe (2011) estimated that SMEs account for roughly 91 percent of the
formal business entities, contributing between 51 and 57 percent to the GDP and they account
for 60 percent of employment in South Africa. SMEs have the potential to assist countries to
emerge from poverty and unemployment and to face a more prosperous future (Apples, 2010).
Figure 2.1 illustrates the economic contribution of SMEs in South Africa from 1997 to 2012.
246
As South African SMEs have a huge impact on the South African economy it is critical that
the SMEs are successful in order to grow and stimulate the South African economy. With the
South African unemployment rate reaching 24.3 percent in the fourth quarter of 2014 (Trading
Economics, 2015), and the fact that SMEs contribute 60 percent of employment in South
Africa, it is fundamental that South African SMEs are successful. An increase in the success
rate of SMEs will result in an increase in the gross domestic product and a decrease in
unemployment.
Year Contribution
for
GDP
Job creation Representation
of total
businesses (%)
(%)
1997 32-42 62 99.3
2001 36 56 97.65
2006 40%-50 More than 50 91
2012 57 61 91
Figure 2.1: SME economic contribution in South Africa, Source: Wiese (2014)
2.3 The construction industry
The construction industry has a major contribution to economic growth, development and
economic activities on a global scale (Claase, 2010). This is supported by Behm (2008) who
stated that construction is a large, dynamic and complex industry that plays an important role
in many economies. The South African Government regards the construction industry highly,
and views the construction industry as a national asset that should be developed, maintained
and transformed. The construction industry makes up about ten percent of the world economy.
Approximately 70 percent of the global construction investment is attributable to the United
States of America, Western Europe and Japan; whereas Africa only accounts for approximately
only one percent (Apples, 2010).
2.3.1 Construction SMEs in South Africa
Construction SMEs perform the activities assigned to the construction team [main contractor(s)
and sub-contractor(s)]. In other words, they are the contractors who perform the on-site
construction activities (Constrinnonet, 2004).
Construction business encompasses a number of small and medium-sized contractors which
form a major part of the industry (Benjaoran, 2009). This is supported by a study conducted by
Moloi (2013), which stated that 78.5 percent of companies in the construction industry are
small and medium. Hence, these companies are vital in job creation and the well-being of the
South African economy. The need to develop small and medium construction enterprises has
to be related back to the South African government’s important policy of providing
infrastructure in underdeveloped areas in order to improve the standard of living. According
to the Republic of South Africa (1999), the development of SMEs is directly linked to the
department’s policy on job creation, innovation and long-term growth. Moilwa (2013) supports
this statement by further expressing that small and medium-sized construction enterprises are
vital for the economic growth of South Africa.
2.4 Construction firm failure
247
According to Mbonyane (2006), many new businesses are started every year, but an increasing
number of businesses are failing annually. Adding to this statement, Theng and Boon (1996)
stated that SMEs tend to have a high mortality rate, with a large percentage of SMEs failing
within the first five years of operation. Apples (2010) supported the latter statistic by stating
that between 70 to 80 percent of small businesses fail within the first five years in South Africa.
It is fact that South Africa has one of the lowest SME survival rates in the world (Mahembe,
2011).
Failure of any organisation, particularly in the construction industry, may have a negative
impact on the economy. Construction firms are more likely to experience financial distress due
to the nature of the industry as each project is unique and there is heightened competition and
extensive instabilities in the market regarding construction activity (Moloi, 2013). Ropega
(2011) supported this by stating that although business failure is common among businesses of
all sizes, small businesses are exposed to greater threats as they lack the support of resources
and extra finance that larger companies typically possess.
Given the fact that such a large percentage of SMEs are unsuccessful, it is meaningful to
investigate the causes of poor performance and failure faced by these firms. According to a
study conducted by Monks (2010), access to the necessary financial reserves has been
determined as a critical factor in determining the success or failure of SMEs both in developing
and developed countries. The lack of management skills and formal financial planning systems
on the part of the small business owner are, according to Apples (2010), the most often cited
reasons for the failure of small enterprises. Franco and Haase (2009) obtained the following
results, namely that the most often cited external factor leading to firm failure was limited
access to finance, as opposed to lack of co-operation and networking, being the most often
cited internal factor leading to firm failure. According to Ropega (2011), the global financial
crisis (2007-2009) was viewed as the most important macro factor leading to business failure,
and the inability to obtain public funding was seen as the major internal factor leading to
company collapse. It must be noted that it is usually not one factor, but rather a combination of
factors that interact, causing company performance to spiral towards inevitable bankruptcy
(Rice & Heimbach, 2007).
The factors contributing to contractor failure are extremely vast, in the sense that there is no
study, book, journal, etc. that lists and accounts for all of these factors. Reasons for failure vary
from business to business, and the severity of a failure factors’ contribution to business failure
is ever-changing.
The researcher divided the ‘failure factors’ into two groups, namely the external environment
and the internal environment. Within the external environment, failure factors were grouped
according to a political, economic, social, technological, environmental and legal (PESTEL)
analysis. The business functions were used to group failure factors within the internal
environment.
2.5 The external environment
The external environment is made up of two components, namely the macro environment and
the industry environment (Hellriegel, Slocum, Jackson, Louw, Staude, Amos, Klopper, Louw,
Oosthuizen, Perks & Zindiye, 2012).
248
According to Moloi (2013), the macro environment deals with all the aspects that organisations
and entrepreneurs have no control over, for example changes in law, government regulations
and economic issues.
The industry environment, also known as the market environment, is one in which the
organisation can influence with no control over the variables, for example the business can
influence the potential customer through marketing and advertising, but has no control over
what the customer decides to do (Moloi, 2013).
Within the external environment, this study has placed greater emphasis on the macro
environment, although certain variables within the industry environment have been dealt with.
2.5.1 PESTEL analysis
There is a variety of strategic analysis tools that a firm can utilise. The PESTEL analysis is the
most widely-used detailed analysis of the macro environment or the environment as a whole.
Managers and strategy builders use this analysis to find where their market currently stands. It
also helps foresee where the organisation will be in the future (Makos, 2015). This research
utilised the PESTEL analysis to group ‘failure factors’ under each letter of the acronym.
PESTEL analysis consists of various factors that directly or indirectly influence the business
environment. Each letter in the acronym denotes a set of factors. The letters in PESTEL, stand
for the following:
Political factors;
Economic factors;
Social factors;
Technological factors;
Environmental factors, and
Legal factors.
For the purpose of this research an additional factor was investigated and included to the
PESTEL acronym, namely the nature of the construction industry.
The political environment is that part of the macro environment that is directly controlled by
the government or the state. Governments tend to have control over the following political
factors: tax laws; labour laws; government policies; tariffs; and government stability and
support (Hellriegel et al., 2012). All of these factors impact, to a greater or lesser degree, on
the survival of a firm.
Economic factors include all the determinants of an economy and its condition. The economic
factors include: rate of economic growth (gross domestic product); interest rates; exchange
rates; inflation rate; monitory or fiscal policies; levels of income; levels of unemployment;
national and international economic conditions (recession); access to finance and load-
shedding (Hellriegel et al., 2012).
249
An analysis of the social environment is concerned with determining and understanding the
impact of a society as well as the changes in that society on an organisation, its industry and
markets (Hellriegel et al., 2012). The social factors include: culture (values, attitudes and
beliefs); demographics and changes in demographics; social structure (age, gender, level of
education, etc.); population size; social lifestyles; HIV/Aids and crime.
Technology is continuously advancing at a rapid pace. This advancement greatly influences
businesses and therefore performing environmental analysis on these factors will help firms
keep up to date with these changes. Technological factors used to a firm’s benefit and in some
cases detriment include: technological change, technological trends, and new discoveries
(Makos, 2015).
South African companies are being required to comply with environmental best practice. No
longer are environmental issues addressed on a voluntary basis, and no longer is simply
protecting the environment sufficient. The real concern is sustainable development –
“development that meets the needs of the present without compromising the ability of future
generations to meet their own needs”. The environmental factors include: geographical
location; weather; climate; climate change; and environmental laws and regulations. These
factors may particularly affect industries such as tourism, farming and insurance (Hellriegel et
al., 2012).
The legal environment is part of the macro environment that is either under direct or indirect
control of the government or the state. Governments tend to have control to a greater or lesser
degree over the following legal factors: legislative changes; employment laws; health and
safety law; competitive regulations and trade union regulations (Hellriegel et al., 2012).
Many characteristics that are unique to the construction industry are also key contributors to a
contractors’ financial difficulties. The nature of the construction industry includes factors such
as: high labour cost; low labour productivity; delays (weather, strikes, etc.); shortage of
skilled/qualified labourers; fluctuating demand; strong domestic competition; project
uniqueness and unfamiliar types of construction; customer relations and supplier relations.
2.6 The internal environment
The internal environment, also known as the micro environment, is an environment in which
the business carries out its activities. It deals with all the aspects inside the business such as
people, structures, resources, capabilities and the business culture. The business has full control
over the variables or factors of this environment, wherefrom numerous opportunities and
threats emerge. This environment determines the ability of the business to operate successfully
(Moloi, 2013).
2.6.1 The business functions
Businesses, regardless of size, perform a large number of activities. From these activities eight
business functions are established. In order for a business to attain its strategic intentions
(vision, mission, key values, goals and objectives), as well as improving business longevity, it
is imperative that these eight business functions and associated tasks are managed in a
coordinated fashion. The eight business functions are: general and strategic management,
purchasing management, human resource management, marketing management, financial
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management, production/operations management, administration or information management,
and business (corporate) communication (Bosch, Tait & Venter, 2011).
This study utilised all eight business functions; however, tasks relating to the administration or
information management function as well as the business (corporate) communication function
were included under the general and strategic management function. Under each of the business
functions accounted for, relevant tasks contributing to the success or failure of a business were
listed.
The general and strategic management function embraces all the other business functions. In
other words, managers need to incorporate this function in all the business functions. The
strategic intentions and general policy of a business are established through the general and
strategic management function (Bosch, Tait & Venter, 2011). Tasks listed under general and
strategic management include: leadership style; business knowledge and general management
skills and experience; strategic (long-term) planning and thinking; planning, organising,
leading and controlling; communication competencies; planning and administrative
competencies; teamwork competencies; flexibility and innovativeness; building learning
organizations; strategic action competencies; global awareness competencies; emotional
intelligence and self-management competencies; formal education/qualification and
succession planning (Bosch, Tait & Venter, 2011).
The purchasing management function links the operations of the organisation and its suppliers,
as well as the providers of various types of inputs for the operations. The tasks of the purchasing
function include: decisions about quality and quantity of materials; supplier selection; price of
materials; storage of materials and materials arriving on time (Bosch, Tait & Venter, 2011).
Human resource management (HRM) deals with the firm’s attempt to attract and retain
sufficient numbers of employees of the right quality and quantity. A contented and productive
workforce is a prerequisite for customer satisfaction and a financially stable business (Bosch,
Tait & Venter, 2011). The HRM tasks include: appropriate training and development for
owners and employees; inability to retain employees; human resource planning and labour
relations (Bosch, Tait & Venter, 2011).
The survival and future growth of any organisation depends on satisfying the needs and wants
of customers. The marketing function is concerned with studying consumer needs and wants,
product development, the determination of selling prices, the choice of distribution channels,
physical distribution, marketing communication, and many others (Bosch, Tait & Venter,
2011). The firm’s marketing strategy, which includes the above-mentioned activities, is listed
as the task of the marketing management function.
The financial management function focuses on the efficient management of all aspects of
finance in an organisation (Hellriegel et al., 2012). The financial management tasks
contributing to contractor firm failure include: insufficient financial knowledge and skill; lack
of proper record keeping; absence of a trained accountant; cash flow not properly managed;
high operating expenses; too much debt; inaccurate budgeting and forecasting; lack of adequate
capital reserves; financial analysis, planning and control; and late payment by client and main
contractor (Bosch, Tait & Venter, 2011).
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The production and operating management function concerns the technical and economic
production processes, that is, the physical production of products and services. Production and
operating management tasks affecting business survival include: poor business location and
selecting unfamiliar areas of operation; poor project selection; growing the company too
quickly; numb to risk and absence of risk management; afraid of layoffs; inability to tender
accurately; suicide tendering; and total quality management (Bosch, Tait & Venter, 2011).
3 Methodology This study made use of the quantitative research method in order to achieve the objectives of
the study. A major downfall of quantitative studies is that it fails to allow the respondent to
effectively express their view and opinion on the topic, and the potential findings are then
limited to the design of the questionnaire (Thomas, 2003). The population comprised of owners
or employees in managerial positions, of small and medium construction enterprises operating
within Port Elizabeth.
A pilot study was conducted, in order to identify any potential problems with the questionnaire,
as well as to ensure the questionnaire was understandable and of appropriate length. The
recommendations that were made during the pilot study were subsequently recorded, and the
various amendments were made to the questionnaire.
The questionnaire together with a covering letter, was physically handed out on site to the
respondents, and thereafter contact details were exchanged. Questionnaires were collected on
receiving notification of completion. The data contained in completed questionnaires was
converted to Excel for analysis. An email reminder was sent to outstanding respondents after
one week of receiving the questionnaire.
4 Findings
4.1 The response rate
The questionnaire was physically handed out on site to 23 potential participants. From the 23
questionnaires that were handed out, 20 questionnaires were successfully returned. However,
of the 20 questionnaires returned, 2 did not qualify and were thus discarded. The remaining 3
questionnaires have not yet been returned.
Therefore, to date, a total of 18 questionnaires have been utilised and form part of this study.
This means a response rate of 78.3 percent has been achieved.
4.1 Demographic information summary
The average participant in this study can be summarised as being a male, aged 25-34 years
old. The average participant is a Junior Manager with a quantity surveying profession, having
5-9 years of experience and holding an Honours Degree.
4.2 The organisation
Three specific quantitative questions were asked with the intention of determining whether the
organisation could be categorised as being a small to medium enterprise. The three questions
pertained to the total number of full-time employees, total annual turnover and total gross asset
value. As mentioned before, if one of the questions categorised the construction firm as being
a small to medium enterprise, the organisation was more than likely included in the research.
252
With this being said, two respondents returned questionnaires that did not meet the stipulated
requirements of the study, and were therefore discarded from further participation in the
research.
4.3 The external environment
In the third section of the questionnaire the respondents were asked to rank, according to their
knowledge and expertise, to what extent various external (macro) variables contributed to small
and medium contractor business failure. The objective being to determine the most
prevalent/predominant external (macro) factor contributing to small and medium contractor
business failure within Port Elizabeth. The failure factors were derived from the theoretical
framework in “The external environment” and were grouped according to the PESTEL
analysis. The ten most prevalent/predominant external (macro) failure factors cited by the SME
owner/managers, according to their respective means, are shown in figure 4.1.
External Failure Factor PESTEL Category Mean Rank
Access to finance Economic factor 5.33 1
Low labour productivity Nature of the construction industry 5.28 2
High labour cost Nature of the construction industry 5.11 3
Fluctuating demand (too much
work or no work)
Nature of the construction industry 4.83 4
Strong domestic competition Nature of the construction industry 4.72 5
Shortage of skilled/qualified
labourers
Nature of the construction industry 4.67 6
Government policies Political factor 4.61 7
National and international
economic conditions
(recession)
Economic factor 4.59 8
Delays (weather, strikes, etc.) Nature of the construction industry 4.56 9
Crime Social factor 4.53 10
Figure 4.1: Most prevalent/predominant external (macro) failure factors
The economic factor, access to finance was rated to be the most prevalent/predominant external
factor contributing to SME contractor failure. The result here was consistent with that found
by Monks (2010), Franco and Haase (2009) and Ropega (2011). Having a mean of 5.33
indicated that respondents viewed access to finance as having a ‘high contribution’ to
contractor business failure. With a standard deviation of 0.77 it can be deduced that the
respondents were in agreement with access to finance as being the most prevalent/predominant
external (macro) factor contributing to contractor business failure. In addition, with a mean of
4.54 the nature of the construction industry was viewed as the PESTEL category having the
greatest contribution to contractor business failure (see Figure 4.2).
PESTEL Category Mean Rank
Nature of the construction industry 4.54 1
Economic factors 4.33 2
Political factors 3.97 3
Legal factors 3.94 4
Technological factors 3.70 5
Social factors 3.66 6
Social factors 3.60 7
Figure 4.2: PESTEL contribution to SME contractor failure
4.4 The internal environment
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In the fourth section of the questionnaire the respondents were asked to rank, according to their
knowledge and expertise, to what extent various internal (micro) variables contributed to small
and medium contractor business failure. The objective being to determine the most
prevalent/predominant internal (micro) factor contributing to small and medium contractor
business failure within Port Elizabeth. The failure factors were derived from the theoretical
framework in “The internal environment” and were grouped according to the business
functions. The ten most prevalent/predominant internal (micro) failure factors cited by the SME
owner/managers, according to their respective means, are shown in figure 4.3.
Internal Failure Factor Business Function Mean Rank
Too much debt (debt financing) Financial management 5.47 1
Inaccurate budgeting and
forecasting
Financial management 5.41 2
Financial analysis, planning
and control
Financial management 5.35 3
High operating expenses Financial management 5.33 4
Cash flow not properly
managed
Financial management 5.33 5
Lack of adequate capital
reserves
Financial management 5.19 6
Tender winning prices
unrealistically low (suicide
tendering)
Production and operating management 5.18 7
Inability to tender accurately Production and operating management 5.17 8
Late payment by client and
main contractor
Financial management 5.17 9
Planning, organising, leading
and controlling
General and strategic management 5.11 10
Figure 4.3: Most prevalent/predominant internal (micro) failure factors
Under the business function financial management, too much debt (debt financing) was rated
to be the most prevalent/predominant internal factor contributing to SME contractor failure. A
mean of 5.47 indicated that respondents viewed too much debt (debt financing) as having a
‘high contribution’ to contractor business failure. With a standard deviation of 0.80 it can be
deduced that the respondents were in agreement with too much debt (debt financing) as being
the most prevalent/predominant internal (micro) factor contributing to contractor business
failure. In addition, with a mean of 5.18 financial management was viewed as the business
function having the greatest contribution to contractor business failure (see Figure 4.4).
Business Function Mean Rank
Financial management 5.18 1
General and strategic management 4.71 2
Production and operating management 4.51 3
Human resource management 4.43 4
Marketing management 4.41 5
Purchasing management 4.33 6
Figure 4.4: Business function’s contribution to SME contractor failure
5 Conclusion Despite the acknowledged importance of SMEs; SMEs are still facing a number of difficulties
and impediments that are hindering and complicating their operations and growth (Mahembe,
2011). SMEs are criticised for their high rate of bankruptcy. It is a fact that SA has one of the
lowest SME survival rates in the world (Mahembe, 2011). While they create many jobs, they
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also destroy a lot of jobs. Construction SMEs face the same challenges as their counterparts in
other sectors of the economy (Apples, 2010). Therefore, the fact that failing SMEs hold the
greatest potential to inflict damage on society; certainly holds true within construction.
Given that such a large percentage of SME is unsuccessful, it is meaningful to investigate the
causes of poor performance and failure faced by these firms. Consequently, the objective of
this research was to identify the factors leading to the failure of construction SMEs within Port
Elizabeth. The factors identified were grouped in order to establish the most
prevalent/predominant external (macro) and internal (micro) contributors to SME contractor
business failure.
The economic factor, access to finance was rated to be the most prevalent/predominant external
factor contributing to SME contractor failure. The result here was consistent with that found
by Monks (2010), Franco and Haase (2009) and Ropega (2011), who stated that access to the
necessary financial reserves can be viewed as the most critical factor leading SME failure.
Ironically, under the business function financial management, too much debt (debt financing)
was rated to be the most prevalent/predominant internal factor contributing to SME contractor
failure. According to literature, the lack of management skills (Monks, 2010), as well as the
lack of operating and networking (Franco & Haase, 2009) was the most often cited internal
factor leading to company collapse. This supported the literature, which stated that the factors
contributing to contractor failure are extremely vast; the reasons for failure vary from business
to business; and the severity of a failure factors’ contribution to business failure is ever-
changing.
Highlighting the most prevalent/predominant SME failure factors within Port Elizabeth, may
provide entrepreneurs with the knowledge and guidance to avoid business failure, aid in the
development and sustainability of small and medium enterprises, and ultimately provide our
nation with the ammunition to defeat the triple challenges of poverty, unemployment and
inequality.
6 Recommendations
SMEs play a vital role in almost all economies, particularly in developing countries with major
employment and income distribution challenges, such as South Africa (Cant & Wiid, 2013).
Not only are SMEs a main driver for generating employment, they also promote innovation,
foster regional economic integration, eradicate poverty and improve standards of living
(Malhembe, 2011). Despite this acknowledged importance of SMEs, between 70 to 80 percent
of small businesses fail within the first five years in South Africa (Apples, 2010). It is a fact
that SA has one of the lowest SME survival rates in the world (Mahembe, 2011).
Being aware of, and understanding the factors contributing to contractor business failure is the
first, and most important step in overcoming the challenges faced by many SMEs. The
entrepreneurs of today, possessing such knowledge, will be the successful small business
owners of tomorrow (Maye, 2014). Early identification of possible failure factors will lead to
the implementation of a prompt action plan and possible business failure prevention.
Addressing the issue of SME survival should be viewed as a national and governmental
priority. Although South Africa has made many efforts to assist SMMEs; the current
atmosphere is one in which running a small business is difficult and risky (Maye, 2014). The
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South African government should provide SMEs with increased support, with reference to the
factors contributing to SME failure. An example of such support would be to provide SMEs
with improved access to finance.
The factors contributing to contractor business failure are extremely vast; reasons for failure
vary from business to business; and the severity of a failure factors’ contribution to business
failure is ever-changing. It is thus recommended that further research regarding business failure
will prove invaluable. Regardless whether research be conducted elsewhere in South Africa,
within other sectors of the economy, or internationally; it will allow the opportunity for current
and future entrepreneurs and small business owners to be up-to-date with current failure factors
and possibly prevent business failure.
7 References
Apples, G. 2010. Strategic management guidelines for construction SMEs in the Eastern Cape.
Published M.B.A.-thesis. Port Elizabeth: Nelson Mandela Metropolitan University.
Behm, M. 2008. Rapporteur’s report: Construction sector. Journal of Safety and Research,
39(1), 175-178.
Benjaoran, V. 2009. A cost control system development: A collaborative approach for small
and medium-sized contractors. International Journal of Project Management, 27(3), 270-
277.
Berry, A., von Blottnitz, M., Cassim, R., Kesper, A., Rajaratnam, B. & van Seventer, D.E.
2002. The economics of SMMEs in South Africa. [Online] Available:
http://www.tips.org.za/files/506.pdf [Accessed: 27 April 2015].
Bosch, J., Tait, M. & Venter, E. 2011. Business management: An entrepreneurial perspective.
2nd edition. Port Elizabeth: Lectern Publications.
Buculescu, M.M. 2013. Harmonization process in defining small and medium-sized
enterprises. Journal of Theoretical and Applied Economics, 9(586), 103-114.
Cant, M.C. & Wiid, J.A. 2013. Establishing the challenges affecting South African SMEs.
Journal of International Business & Economics Research, 12(6), 707-716.
Claase, J. 2010. Achieving alignment of the objectives of the role players in a typical
construction industry. Unpublished M.B.A.-thesis. Potchefstroom: North-West University.
Constrinnonet. 2004. Innovation issues, successful practice and improvements. [Online]
Available:
http://constrinnonet.vtt.fi/material/final%20report/innovation%20issues%20succesful%20pr
actice%20and%20improvements.pdf [Accessed: 28 April 2015].
Construction Industry Development Board. 2008. Construction Industry Development
Regulations, 2004. [Online]. Available:
http://www.cidb.org.za/documents/kc/cidb_publications/leg_regs/other_leg_regs/leg_regs_r
egulation_amended_14nov08.pdf [Accessed 28 April 2015].
Franco, M. & Haase, H. 2009. Failure factors in small and medium-sized enterprises:
Qualitative study from an attributional perspective. Journal of International
Entrepreneurship and Management, 6(1), 503-521.
Hellriegel, D., Slocum, J., Jackson, S.E., Louw, L., Staude, G., Amos, T., Klopper, H.B., Louw,
M., Oosthuizen, T., Perks, S. & Zindiye, S. 2012. Management. 4th edition. Pretoria: Oxford
University Press.
256
Mahembe, E. 2011. Literature review on small and medium enterprises’ access to credit and
support in South Africa. Unpublished literature review. Pretoria: Underhill Corporate
Solutions.
Makos, J. 2015. What is environmental analysis? [Online] Available:
http://pestleanalysis.com/what-is-environmental-analysis/ [Accessed: 8 September 2015].
Maye, M. 2014. Small Business in South Africa: What the Department of Small Business
Development Can Do to Stimulate Growth [Online]. Available:
http://www.cplo.org.za/?wpdmdl=71&&ind=0 [Accessed 19 October 2015].
Mbonyane, B.L. 2006. An exploration of factors that lead to failure of small businesses in the
Kagiso Township. Unpublished M.B.A.-thesis. Johannesburg: University of South Africa,
College of Economic and Management Sciences.
Moilwa, S. 2013. Factors constraining the development of professional project managers in
small and medium sized construction enterprises in South Africa. Published M.S.E.-thesis.
Johannesburg: University of the Witwatersrand.
Moloi, N. 2013. The sustainability of construction Small-Medium Enterprises (SMEs) in South
Africa. Published M.B.A.-thesis. Johannesburg: University of the Witwatersrand.
Monks, P.G.S. 2010. Sustainable growth of SMEs. Published M.B.A.-thesis. Port Elizabeth:
Nelson Mandela Metropolitan University.
Republic of South Africa (RSA). 1999. White paper on creating an enabling environment for
reconstruction growth and development in the construction industry. Pretoria: Department
of Public Works. [Online] Available:
http://www.publicworks.gov.za/PDFs/documents/White-
Papers/White%20PaperReconstruction_Growth_and_Development_in_the_Construction_I
ndustry.pdf [Accessed: 27 April 2015].
Republic of South Africa (RSA). 1996. National Small Business Act, no. 102 of 1996. Pretoria:
Government Printer.
Rice, H. & Heimbach, A. 2007. Why contractors fail: A casual analysis of large contractor
bankruptcies. FMI Quarterly Journal of Business, 2.
Ropega, J. 2011. The reasons and symptoms of failure in SME. Journal of the International
Atlantic Economic Society, 17(1), 476-483.
Savlovschi, L.I. & Robu, N.R. 2011. The Role of SMEs in Modern Economy. Journal of
Economia Seria Management, volume 14, 1, pp. 277-281.
Theng, L.G. & Boon, J.L.W. 1996. An exploratory study of factors affecting the failure of local
small and medium enterprises. Asia Pacific Journal of Management, 13(2), 47-61.
Thomas, R.M. 2004. Blending qualitative & quantitative research methods in theses and
dissertations. Thousand Oaks, CA: Sage Publications.
Trading Economics. 2015. South Africa unemployment rate. [Online] Available:
http://www.tradingeconomics.com/south-africa/unemployment-rate [Accessed: 26 April
2015].
Wiese, J.S. 2014. Factors determining the sustainability of selected small and medium-sized
enterprises. Unpublished M.B.A.-thesis. Potchefstroom: North-West University.
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Critical Success Factors of Labour-Intensive
Subcontractors in South Africa: An Eastern Cape study Dylan Massyn and Gerrit Crafford
Department of Quantity Surveying,
Nelson Mandela Metropolitan University,
Email: gerrit.crafford@nmmu.ac.za
Abstract:
The purpose of this paper is to identify the critical success factors (CSFs) of labour-intensive
subcontractors in South Africa and to establish why these types of subcontractors do not
implement the CSFs in their operations. Implementation can assist in improving performance
on construction projects. A questionnaire was administered to site foremen and supervisors in
the Eastern Cape to gain the insights of those involved with labour-intensive construction
projects. The results identify timely completion of projects, programme/planning, safety
performance and profit as the most important CSFs for labour-intensive subcontractors. The
most significant factor contributing to the non-implementation of CSFs is a greater focus on
short-term profits than on the long-term establishment of firms. The research is limited to site
foremen and supervisors who have been involved with labour-intensive construction projects
in the Eastern Cape. The study will inform labour-intensive subcontractors of the CSFs they
can implement to improve performance. Their success can aid job creation. The CSFs labour-
intensive subcontractors can implement to be successful and reasons for failure to implement
them are identified.
Keywords:
Critical Success Factors, Labour Intensive, Subcontractors
1 Introduction
International Labour Organisation (ILO, 2015) projections indicate that South Africa will have
the eighth-highest unemployment rate globally in 2015 and that the situation is not expected to
change over the next five years. The current unemployment rate in South Africa is 25 per cent,
which amounts to 5.23 million people. When using the broad definition of unemployment, this
rate increases to 35 per cent (Statistics South Africa, 2015).
Labour-intensive construction is one of the methods the South African Government is
implementing to address the high levels of unemployment the country is currently
experiencing. Public work infrastructure programmes and projects are seen as a major
economic development tool for transforming the lives of people throughout the developing
world. The character of development, its direction and pace, and the way people share in its
benefits are largely determined by how a country manages its development projects and
programmes (Thwala, 2007).
Government initiatives such as the Expanded Public Works Programme (EPWP), the Emerging
Contractor Development Programme (ECDP), Construction Industry Development Board
(CIDB) and the Construction Education and Training Authority (CETA) aim to alleviate
poverty, create jobs and develop skills for the unemployed. The objective of the EPWP is to
create employment by promoting the use of labour-intensive construction methods in
infrastructure development (McCutcheon & Parkins, 2009).
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Per unit of expenditure, labour-intensive methods generate significantly more productive
employment opportunities than conventional capital-intensive methods without compromising
time, cost or quality (McCutcheon, 2008). Moreover, labour-intensive programmes generate
more direct and indirect local employment opportunities and income by using locally available
materials, simple tools and local labour than high-technology programmes do (Thwala, 2007).
The support of these programmes by key players in the construction industry is crucial to their
success. However, there tends to be a negative perception regarding the use of emerging
subcontractors on construction projects. This perception has been created by the poor
performance of this type of subcontractor on previous projects, and the lack of initiative and
finance from the private sector further supports this negative perception (Ngebulana, 2006).
To improve this perception, it is vital to improve the performance of emerging subcontractors
on projects that fall under programmes such as the EPWP. To do this, it essential to identify a
list of critical success factors (CSFs) applicable to these subcontractors, specifically those
labour intensive in nature. Furthermore, it is important to ensure the implementation of these
CSFs into subcontractors’ practices.
Thus, the objectives of the research are identifying the CSFs pertinent to labour-intensive
subcontractors, establishing whether there is a negative perception regarding the use of labour-
intensive subcontractors and identifying the reasons for this perception (not discussed in this
paper), and identifying the reasons for labour-intensive subcontractors’ failure to implement
the CSFs into their operations.
2 Literature Review
2.1 Labour-intensive subcontractors
Labour intensive, from an economics perspective, describes the degree to which labour is
employed in an operation when compared to other resources (Ng & Tang, 2010). McCutcheon
(2008) defines labour-intensive construction as the economically efficient employment of as
great a proportion of labour as is technically feasible, ideally throughout the construction
process including in the production of materials, to produce as high a standard of construction
as demanded by the specification and allowed by the funding available. Labour intensive
should not be confused with labour extensive. Labour extensive involves the use of large
numbers of people on relatively unplanned emergency or relief projects to construct something
of ill-defined quality and value (McCutcheon, 2008).
Labour-intensive subcontractors, in the context of this paper, are those who assign a significant
proportion of expenditure to employing manual labour to accomplish a trade-specific
construction operation. Subcontracting is used by main contractors to reduce the risk of hiring
an excessive number of direct labourers as well as to capitalise on the skills and specialisation
of labour-intensive subcontractors (Ng & Tang, 2010).
In their 2010 study, Ng and Tang identify excavation works, foundation works and demolition
works as being the most labour-intensive trades. Excavation and foundation works are the
earthworks activities relating to construction works. More specifically, the activities of
excavation, loading, hauling, unloading and spreading are classified as being labour intensive.
(LIC Guidelines, 2011).
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Rubble masonry concrete (RMC) dam construction is another form of construction work that
can be carried out labour intensively. The construction of RMC dams has been utilized in areas
where there is a desperate need for employment. The benefits of RMC dams are low
construction cost, employment generation and skill development. This is a perfect example of
a labour-intensive technology (CIDB, 2005).
Other labour-intensive technologies include storm-water drainage channels, RMC arch bridge
construction, the construction of low-volume roads and the construction of cast in-situ block
pavements (CIDB, 2005).
2.2 Critical success factors
Traditionally, the aspects of time, cost and quality compliances have been used to measure the
success or failure of a project (Msani, 2011). More recently, researchers have proposed specific
variables for measuring project success. Ng and Tang (2010) propose several project success
criteria and success factors identified by various researchers, as illustrated in Table 1.
Table 1. Project success criteria and success factors
Success factors
Adoption of new technologies
Cash flow
Company history
Company’s management system
Employee growth
Environmental performance
Growth in revenue
Insurance terms
Interest rates
Management-level leadership
Market conditions
Number of projects completed
Payment method
Profit
Programme/planning
Project procurement
Quality system
Relationship with stakeholders
Reputation
Safety performance
Scale of projects completed
Staff morale
Staff performance
Staff training
Timely completion of project
(Source: Ng and Tang, 2010)
Ng and Tang (2010) identify nine of these factors as CSFs for labour-intensive subcontractors
and rank them according to their importance. They subsequently group the CSFs into three
components, namely managerial performance, financial performance and labour-intensive
specific factors. The managerial performance component consists of timely completion of
projects, programme/planning and management-level leadership. Profit, cash flow and growth
of revenue make up the financial performance component, while labour-intensive specific
factors comprise the relationship with the main contractor/client/consultants, employee morale
and employee skills. Table 2 shows ranking according to importance and the component
grouping of each CSF.
Table 2. CSF ranking according to importance and component classification
Rank Critical success factor Component
1 Timely completion of project Managerial
2 Profit Financial
3 Programme/planning Managerial
4 Cash flow Financial
5 Management-level leadership Managerial
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6 Relationship with main
contractor/client/consultant Labour-intensive specific
7 Staff team spirit/morale Labour-intensive specific
8 Staff qualification/skill Labour-intensive specific
9 Growth in revenue Financial
(Source: Ng and Tang, 2010)
2.3 Unemployment and labour-intensive construction
South Africa’s rising unemployment rate is a challenge the government has been attempting to
address for many years. The growth of an economy is reliant on a country’s infrastructure and
industrial development from construction activities, and it is of vital importance that projects
are executed as per the stipulated objectives (Tabish & Jha, 2012). Economic growth and
employment opportunities are two of the major advantages of the successful completion of
projects. Other benefits include reliable and widespread access to electricity, expanded health
facilities, port development, proper roads and improved water and sanitation facilities (Orr &
Kennedy, 2008).
The EPWP is a current South African Government initiative aimed at creating employment by
promoting the use of labour-intensive construction methods in infrastructure development
(McCutcheon & Parkins, 2009). The first phase of the EPWP was launched in 2004 with the
objective of alleviating unemployment for at least one million people (at least 40 per cent of
women, 30 per cent of the youth and 2 per cent of disabled people). Significant conclusions
drawn from the first phase of the EPWP include: (1) The direct and indirect beneficiaries of
the EPWP welcomed the short-term job opportunities—those who had worked on the
programme wanted further employment opportunities. (2) There was little enforcement of
labour-intensive construction methods and training. In the infrastructure sector, labour intensity
fell from 26 per cent in 2004 to 9 per cent in 2008/2009, which indicates that these projects
were executed using conventional capital/machine-intensive construction. (3) The budget for
infrastructure spending during the first five years of the EPWP was R15 billion in 2004, but
actual expenditure amounted to R33.8 billion (McCutcheon & Parkins, 2009). In May 2008,
the Minister of Public Works announced that the goal of creating one million employment
opportunities had been achieved one year ahead of schedule. Because of the budget overrun,
no additional employment was generated per unit of expenditure.
3 Research Methodology
A quantitative research approach was utilised to conduct the survey to obtain the information
required, as this allowed the researchers to objectively measure the information required using
the identified variables relevant to each topic investigated. The population consisted of site
foremen and supervisors who have been involved with labour-intensive construction projects.
The survey was conducted in the Eastern Cape and the population randomly sampled. Random
sampling allows each member of the population the same likelihood of being included in the
sample (Dane, 2011).
The questionnaire consists of four sections of closed-ended questions as well as an open-ended
question in the final section. Closed-ended questions offer respondents a range of answers to
choose from, while open-ended questions allow respondents to formulate their own responses
(Welman, Kruger & Mitchell, 2005). The first section was utilised to gather the respondents’
demographic information. In the subsequent sections, the researchers attempted to obtain the
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insights of the respondents on the following issues: the critical success factors (CSFs) of
labour-intensive subcontractors, the perception of labour-intensive construction within the
construction industry (not discussed in this paper), and the reasons for labour-intensive
subcontractors’ failure to implement the CSFs.
To identify the CSFs pertinent to labour-intensive subcontractors, respondents were asked to
indicate whether each of the identified success factors has no importance (represented by 1 on
a five-point Likert scale) or is extremely important (represented by 5 on the scale) to a labour-
intensive subcontractor’s operations. The perception section measured how often the identified
variables are negatively affected using a five-point Likert scale, with 1 representing never and
5 representing always. The same five-point Likert scale was utilised to measure the reasons
labour-intensive subcontractors fail to implement the CSFs in their operations. An ‘unsure’
option was included for each variable. These sections of the questionnaire were utilised to
achieve the objectives of the study.
A pilot study was conducted with four construction professionals to assist in identifying any
shortcomings or misunderstandings in the questionnaire. The pilot testers’ feedback was
recorded and the various recommendations implemented to optimise the questionnaire.
Subsequently, hard copies of the revised questionnaire were hand delivered to the respondents
on various construction sites, and each questionnaire was accompanied by a cover letter. The
respondents completed the questionnaire in the presence of the researcher, who provided
assistance with any problems that arose, such as language barriers and the respondents being
unable to comprehend the questions asked.
After the respondents had completed the questionnaires, the data was manually captured and
analysed in Excel. The frequency of each response and the descriptive statistics for each
variable were calculated. The descriptive statistics calculated include the mode, mean, standard
deviation and skewness for each variable. The variables were then ranked in descending order
according to the mean of each variable. Any ‘unsure’ choices were excluded when calculating
the descriptive tactics to avoid affecting the validity of the data.
4 Findings and Discussion
Responses
Thirty-two questionnaires were completed after being hand delivered to various sites in the
Eastern Cape.
Critical success factors
Twenty-five success factors were identified through the literature review and these success
factors formed part of the questionnaire used to identify the CSFs of labour-intensive
subcontractors. A success factor with a mean rating of more than or equal to four was
recognised as a CSF. Where two or more factors had the same mean scores, the one with the
lower standard deviation was deemed more important. Timely completion of projects was
identified as being the most important CSF for labour-intensive subcontractors. Twenty-two
respondents (68.8%; n=32) classified this factor as being extremely important, while the
remaining ten respondents (31.3%; n=32) classified timely completion of projects as being
important. The mean score for this factor was 4.69, thus suggesting that timely completion of
projects is an extremely important CSF for labour-intensive subcontractors.
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Programme/planning was classified as being the second most important CSF for labour-
intensive subcontractors, and it could be said that this factor has a direct influence on the timely
completion of projects. The mean score for this factor was 4.59, with 19 respondents (59.4%;
n=32) indicating that it is extremely important and the remaining respondents (f=13; 40.6%;
n=32) identifying programme/planning as being important. The least important success factor
identified was employee growth, although the majority of respondents (f=12; 37.5%; n=32)
suggested that this factor is important. Table 3 illustrates the identified CSFs for labour-
intensive subcontractors.
Table 3. Critical success factors for labour-intensive subcontractors.
Critical success factor Rank Mean Std. dev.
Timely completion of projects 1 4.69 0.47
Programme/planning 2 4.59 0.5
Safety performance 3 4.41 0.61
Profit 4 4.38 0.55
Quality system 5 4.34 0.6
Staff performance 6 4.31 0.64
Management-level leadership 7 4.28 0.77
Relationship with main contractor/client/consultant 8 4.19 0.59
Cash flow 9 4.16 0.63
Reputation 10 4.03 0.69
Growth in revenue 11 4.03 0.81
Number of projects completed 12 4.00 0.72
Seven of the CSFs identified during the survey are identical to the CSFs identified by Ng and
Tang (2010). An additional five success factors were classified as being CSFs after evaluating
the mean scores of the variables. These CSFs are safety performance, quality system, staff
performance, reputation and number of projects completed. The identification of additional
CSFs could be due to the respondents’ opinions regarding the variables. For example,
construction health and safety has increasingly been the focus of numerous industry
stakeholders and role players in South Africa (MBA, 2012). This could be the reason why the
respondents view safety performance as important and hence a CSF. Experience is another
important factor utilised to measure a subcontractor’s efficiency, and this explains why the
respondents regard reputation and the number of projects completed as important success
factors. Staff performance and quality system are important aspects of labour-intensive
construction, as these influence the quality of work produced by employees. The identified
CSFs are grouped into managerial, financial and labour-intensive specific components in Table
4.
Table 4. CSF classification according to component
Component Critical success factor
Managerial performance
Timely completion
Programme/planning
Management-level leadership
Safety performance
Financial performance Profit
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Cash flow
Growth in revenue
Labour-intensive specific factors
Quality system
Staff performance
Relationship with main
contractor/client/consultant
Reputation
Number of projects completed
Implementation of the critical success factors
Nine reasons for the non-implementation of the critical success factors were identified through
the literature review and pilot testing of the questionnaire. These reasons were utilised to
establish why labour-intensive subcontractors do not implement the critical success factors
(CSFs) in their operations. The greatest cause is that they are more focussed on short-term
profits than the long-term establishment of their firms. This is illustrated by 37.5% of the
respondents (f=12; n=32) suggesting that this is always the reason for the non-implementation
of the CSFs and 53.1% of the respondents (f=17; n=32) suggesting that this is often the reason
for non-implementation. The mean score for this variable was 4.28. Cash flow (mean=3.91)
and time constraints (mean=3.66) complete the list for the top three reasons for the non-
implementation of the CSFs.
The variable contributing the least to the non-implementation of the CSFs was established as
being lack of resources. Only one respondent (3.1%; n=32) suggested that lack of resources is
always the reason for the non-implementation of the CSFs, and nine of the respondents (28.1%;
n=32) believed that it is often the reason. The majority of the respondents (f=17; 56.3%; n=32)
indicated that this is sometimes the cause for non-implementation of the CSFs. Alternative
reasons identified by the respondents include that these types of subcontractors are purely
production focused, do not utilise forecast plans for company growth, lack proper
supervision/management, misuse or poorly manage company funds and utilise unqualified
workers. Table 5 provides the full results.
Table 5. Reasons for the non-implementation of the critical success factors into labour-intensive subcontractors’
operations.
Reason Rank Mean Standard
deviation
Focused on short-term profits 1 4.28 0.63
Cash flow 2 3.91 0.69
Time constraints 3 3.66 0.83
Experience 4 3.5 1.02
Disregard long-term establishment of firm 5 3.47 0.76
Training 6 3.44 0.95
Education 7 3.41 0.8
Awareness of CSFs 8 3.29 1.01
Lack of resources 9 3.22 0.71
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There is growing consensus that focusing on short-term shareholder value is not only bad for
society but also leads to poor business results (Denning, 2013). For labour-intensive
subcontractors to achieve business sustainability, it is essential that they forego short-term
profits and concentrate on the long-term establishment of their firms. Having insufficient
operating funds (that is, cash flow) is another fatal mistake that can be made by this type of
subcontractor. Business owners underestimate how much funds they require and are forced to
close their businesses before having had a fair chance to succeed (Schaefer, 2011).
Subcontractors struggling with operating cash flow may find it difficult to implement CSFs.
Moreover, time constraints could be a result of over-committing themselves to work and
therefore having insufficient time to assess and implement the CSFs pertinent to their
operations, and inadequate experience, training and education could affect their ability to
implement the CSFs due to unawareness of or not having the required
knowledge/understanding of the CSFs.
5 Conclusion and Further Research
The researchers first attempted to identify the critical success factors (CSFs) pertinent to
labour-intensive subcontractors by ranking each success factor according to importance.
Twelve CSFs were found during the investigation. Timely completion of projects was
determined to be the most important CSF for labour-intensive subcontractors. The literature
review confirmed this finding. This CSF is classified as a managerial function; hence,
management is ultimately responsible for the timely completion of projects. The second most
important CSF is programme/planning, which is another managerial function that has a direct
influence on completing projects on time. This emphasis on timely completion of projects
could potentially be due to the heavy penalties incurred when time overruns occur.
Furthermore, the researchers attempted to determine reasons for labour-intensive
subcontractors’ failure to implement the CSFs in their operations. The findings suggest that
non-implementation results from this type of subcontractor’s focus on short-term profits and
frequent disregard of the long-term establishment of the firm. It was also found that
subcontractors experiencing cash flow difficulties often do not implement the CSFs.
The identification of CSFs for labour-intensive subcontractors can assist in improving the
performance of this type of subcontractor. Moreover, establishing the reasons for these
subcontractors not implementing the CSFs in their operations provides a basis for overcoming
the problem. Ultimately, the success of labour-intensive subcontractors can assist in creating
employment opportunities in South Africa.
6 Recommendations
This paper identified the CSFs for labour-intensive subcontractors and allowed the researchers
to classify these factors into three components, namely managerial, financial and labour-
specific factors. It is advisable that these subcontractors attempt to implement the CSFs in their
operations to improve performance. Where appropriate knowledge of the three identified
components is lacking, it is essential for owners and managers to close this gap through training
and education or by employing knowledgeable persons who can assist in providing insights.
Government initiatives promoting the development of contractors must create awareness of the
CSFs pertinent to labour-intensive construction projects. The methods utilised and the
processes to be followed to implement these CSFs should be essential elements of contractor
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development. In addition, it is extremely important for government to monitor and maintain
the level of labour intensity on construction projects where this method of construction has
been specified. Identifying a set of principles to be followed during labour-intensive projects
can assist in achieving this objective.
The construction industry as a whole should attempt to support labour-intensive programmes
initiated by the government. The support of these programmes by key stakeholders in the
industry is essential to their success. The support offered by the construction industry could
include the training and development of subcontractors on government projects.
Further research:
An investigation to identify methods of improving the managerial, financial and labour-
specific components identified as part of labour-intensive sub-contractors’ operations;
A case study evaluating the level of labour-intensity over the duration of a construction
project, to identify potential reasons for declining labour-intensity as a project progresses;
Confirmatory research with a greater sample size in the future, and
The establishment of key performance indicators for labour-intensive subcontractors based
on the identified CSFs.
7 References
Construction Industry Development Board, (2005), ‘Labour-based methods and technologies
for employment intensive construction works’, Available from:
<http://www.cidb.org.za/Documents/KC/cidb_Publications/Prac_Docs/other_prac_docs/p
rac_docs_labour_based_methods.pdf>. [25 March 2015].
Dane, F.C. (2011), Evaluating Research. California: Sage.
Denning, S. (2013), ‘How modern economics is built on ‘the world's dumbest idea’’. Available
from: <http://www.forbes.com/sites/stevedenning/2013/07/22/how-modern-economics-is-
built-on-the-worlds-dumbest-idea/>. [16 July 2015].
Department of Public Works, (2011), Labour Intensive Construction Guidelines for Water
Provision, Sanitation, Solid Waste and Building Works. Pretoria: International Labour
Organisation.
International Labour Organisation, (2015), World employment and social outlook: Trends
2015. Geneva: International Labour Organisation.
Master Builders Association, (2012), ‘Health and safety’, Available from:
<http://www.masterbuilders.co.za/members_services/health_safety.htm>. [16 August
2015].
McCutcheon, R.T. (1995), ‘Employment creation in public works: Labour-intensive
construction in Sub-Saharan Africa: The implications for South Africa’, Habitat
International, 19(3), pp. 331–355.
McCutcheon, R.T. (2008), ‘The generation of productive employment opportunities for the
unskilled: Principles, potential and pitfalls of labour-intensive construction’, Keynote
Address: Keynote Address:10th Path to Full Employment Conference / 15th National
Unemployment Conference, 4-5 December 2008, Centre of Full Employment and Equity
(CofFEE), University of Newcastle, Australia; 12pp.
McCutcheon, R.T. & Parkins, F.T. (2009), ‘South Africa’s Expanded Public Works
Programme: A case study in government sponsored employment creation and poverty
alleviation focusing upon the infrastructure component’, Rhetoric, reality and opportunities
foregone. Labour Underutilisation, Unemployment and Underemployment, incorporating
266
the 11th Path to Full Employment Conference and 16th National Conference on
Unemployment, pp. 196–212.
McCutcheon, R.T. & Parkins, F.T. (2012), ‘The Expanded Public Works Programme: Policy,
rhetoric, reality and opportunities foregone during the expenditure of over R40 billion on
infrastructure’. Civil Engineering, 20(6), pp. 34–46.
Msani, T.A. (2011), ‘Critical Success Factors Influencing Project Success in the Durban
Construction Industry’, MA Unpublished thesis, Durban University of Technology.
Ng S. T. & Tang Z. (2010), ‘Labour-intensive construction sub-contractors: Their critical
success factors’, International Journal of Project Management, 23(7), pp. 732–740.
Ngebulana, M.R. (2006). ‘Evaluation of Labour - Intensive Construction Projects in Madibeng
Municipality, North-west Province, South Africa’, Unpublished Masters thesis, University
of Witwatersrand, Johannesburg.
Orr, R. & Kennedy, J. (2008), ‘Highlights of recent trends in global infrastructure: New players
and game rules’, Transnational Corporation, 17(1), pp. 95–130.
Schaeffer, P. (2011), ‘The seven pitfalls of business failure and how to avoid them’, Available
from: <http://www.businessknowhow.com/startup/business-failure.htm>. [7 August
2015].
Sorensen, L. (2011), ‘Labour Intensive Construction in the South African Infrastructure
Sector’, BSc Hons thesis, Nelson Mandela Metropolitan University.
Statistics South Africa, (2015), Quarterly labour force survey—Quarter 2: 2015. Pretoria:
Statistics South Africa.
Tabish, S.Z.S. & Jha, K.N. (2012), ‘Success traits for a construction project’, Journal of
Construction Engineering & Management, 138(10), pp. 1131–1138.
Thwala, W.D. (2007), ‘Challenges facing labour-intensive public works programmes and
projects in South Africa’, International Journal of Construction Management, 7(2), pp. 1–
9.
Thwala, W.D. (2006), ‘Urban renewal through labour-intensive construction technology in
South Africa: Problems and potentials’, Available from:
<http://asq.africa.ufl.edu/files/Thwala-Vol8Issue4.pdf>. [17 April 2015].
Welman, C., Kruger, F. & Mitchell, B. (2005), Research methodology, 3rd ed., Cape Town:
Oxford University Press Southern Africa.
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Factors for Selecting Joint Venture Partner for
Construction Project in South Africa Bekale Mba and Justus Agumba
1 Department of Construction Management & Quantity Surveying
University of Johannesburg, South Africa
Email: mariefrancoisebm@gmail.com, jagumba@uj.ac.za
Abstract:
The construction industry plays a vital role in South Africa’s economic and social development
where this industry provides the physical infrastructure and backbone for economic activity
while providing a large-scale provider of employment. In a world of rapidly increasing global
competition, enterprises partake in joint ventures in order to stay competitive and strategically
flexible. Even though, one of the most prevalent types of business arrangements that are being
used by South Africans, in the tender environment, is Joint Venture, risks are innate in JV
construction projects and lead to at least 40% to 70% of JVs failure. As a result, the success
of a joint venture evidently depends on the synergy created by the individual contributions of
each partner, and thus, a good joint venture management lies not only in the implementation of
the project, but also a proper partner selection. Therefore, the purpose of this study is to identify
the factors to select JV partner. A quantitative research methodology was adopted and the data
was collected through the use of questionnaires. Key findings reveal that the selection criteria
of JV partner(s) include the commitment between the partners, complementary technical skills,
compatible management teams, complementary resources, commitment to joint venture
objectives as well as trust between partners. Other selection criteria which appear to be neutral
to respondents relate to mutual dependency and relative company size. As the study reveals
these findings, interested and concerned parties (contractors, consultants, owners of
construction companies) are able to improve by far the performance of JV construction projects
in South Africa before signing contracts agreement.
Keywords:
Construction Industry, Joint Venture, Partners, Projects, Selection Criteria
1 Introduction
Despite the fact that international construction firms have extensively used joint ventures as a
vehicle to enter new construction markets in South Africa, the failure rate of such ventures has
been quite alarming through delays and disruptions, poor site management (Govindan, 1995).
Indeed, according to Farrel (2014), It is estimated that at least 40 percent and up to 70 percent
of joint ventures fail. Issues related to the formation and operation of joint ventures for
construction projects have been the subject of considerable commentary. As innovative
opportunities are constantly developing as a result of globalization which allows local firms to
enter into international construction markets to compete worldwide (Misbah et al., 2008),
majority of multinational enterprises (MNEs) will have to participate in international joint
ventures in order to remain competitive and strategically flexible. In order to get benefit in
global competition, construction firms should have to plan for their survival and development
by entering into joint ventures (Gunhan & Arditi, 2005). Even though, one of the most
prevalent types of business arrangements that are being used by South Africans, in the tender
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environment, is Joint Ventures according to Rooyen (2014), risks are innate in joint venture
construction projects such as agreement of the contract, partner selection, potential financial
distress, improper project feasibility study, project delay, inadequate forecast about market
demand, loss due to bureaucracy for late approvals and design changes (Kwok et al., 2006 &
Shen et al., 2001). Thus, the researcher has found interest to research on this specific area on
partner selection to revaluate joint venture formation.
2 Partner selection criteria for successful joint venture
Before enumerating and explaining all the relevant selection criteria for JV partners involved
in construction projects, it is important to first gain knowledge of what a joint venture entails.
Indeed, a joint venture is the most common form of organizational structure where the partners
wish to establish and operate a jointly owned business (Kale et al., 2013). Unlike a partnership,
a JV has a distinct legal entity and also has a certain time limit. Kolbehdari & Sobhiyah (2014)
further highlight that joint venture remains a specific type of long-term alliance among the
partners which creates an exceptional opportunity for combining distinct merits and
complementary resources. However, according to Hyun & Ahn (2013), the selection of a
potential partner determines the configuration of the patented resources and technology to
which a firm has access and ominously affects the success of its deliberate investment
objectives. Therefore, it becomes crucial to identify the potential selection criteria which
pertain to the success of a JV operation.
2.1 Complementary technical skills and resources
The primary selection criterion should be a partner's ability to provide the technical skills and
resources which supplement those of a firm seeking the partner (Kottolli, 2002; Minja et al.,
2012). Moreover, Hyun & Ahn (2013) suggest that favourable cooperative relations, resource
compatibility, as well as, the location of the partner are acute among the factors affecting the
joint venture process. Hence, if prospective partners cannot offer these capabilities, then
formation of a joint venture is a questionable proposition. Therefore, as argued by Kottolli
(2002) and Govindan (1995), technical complementarily should be viewed as a minimum
qualification for selecting a partner as it builds a stable relationship based on mutual
dependency.
2.2 Mutual dependency
Adnan et al. (2011) and Kottolli (2002) made the observation that mutual dependency involves
seeking a partner with complementary technical skills and resources which can allow each
partner to concentrate their resources in those areas where it possesses the greater relative
competence while diversifying into attractive but unfamiliar business areas. Rather than
intensifying weaknesses, in that sense, joint ventures can thus be a means of creating strengths.
There should be some identifiable mutual need, with each partner delivering exceptional
capabilities or resources critical to the joint venture success (Rumpunen, 2011). When one
partner is strong in areas where the other is weak and vice versa, mutual respect is nurtured and
second guessing as well as conflict are mitigated (Kottolli, 2002; Adnan et al., 2011). Thus,
Rumpunen (2011) emphasized that, the apprehension of the potential benefits to a firm from
entering into a joint venture (JV) depends on finding a partner who can provide balancing
capabilities or resources that match its own in order for the joint venture to meet the firm's
considered objectives.
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2.3 Relative company size
Joint ventures often have the best chance of long term success if both partners are equal in size,
preferably large as well as the reputation of the partner (Kottolli, 2002; Govindan, 1995;
Rumpunen, 2011). In fact, according to Kottolli (2002), if a small firm decides to enter into a
JV with a similarly sized partner, the firms may expand each other's weakness. It is then
expected that two large firms which have similar values and control systems, similar
forbearances for losses, and similar appetites for risk will increase those assets. Moreover,
crises are less present in large firms, particularly concerning short-term cash flow (Kottolli,
2002). Hyun & Ahn (2013) suggest that the commensurate size of the partner firm is the most
important criterion for partner selection in order to secure impartial cooperation between
partner firms and this criterion may facilitate complementarity in their cooperation in
customized marketing, technology, human resources, and financial resources.
2.4 Commitment to joint venture objectives
According to Kottolli (2002) and Minja et al. (2012), having different objectives in forming
the joint venture, including the timing and level of profits on their investments, frequently
produce conflicts of interests between partners. Moreover, Govindan (1995) suggest that the
success of a joint venture primarily depends on compatibility of the partners' objectives. In
Govindan`s opinion (1995), JVs are primarily formed to maximize the partners' joint
objectives, which include and are not limited to, conflict of interest between the joint objectives
as well as partners' distinct objectives which often affect the operation of the JV. Thus, as
partners' objectives differ, there is an increasing risk of frustration and associated problems.
The risk may be heightened when the joint venture's environment is characterized by a high
level of uncertainty, since, under the circumstances; changes on a joint venture's operations are
most likely (Kottolli, 2002). Although determining a prospective partner's objectives is often
difficult task, it is essential as failure to do so may increase the forecasts for later problems.
2.5 Compatible management teams
Management team at the helm of the joint venture plays a major role in its accomplishment. In
making this comment, Kottolli (2002) and Govindan (1995) write that personal rapport
between main decision makers is habitually important as it helps nurture the level of
understanding necessary for a successful joint venture. In other words, Adnan et al. (2011) and
Minja et al. (2012) believed that, managerial compatibility can enhance the partners' ability to
attain consensus on critical policy decisions and to overcome roadblocks faced during the
operation of the joint venture formation. For instance, Kottolli (2002) highlights that, joint
ventures with firms in Mexico, Brazil, other Latin American countries, Japan, China, and Asia
establishment of close personal rapport is customarily prerequisite to concluding business
negotiations.
2.6 Trust and commitment between partners
According to both Kottolli (2002) and Minja et al. (2012), forming and operating a joint venture
requires more than cordial relations between partner's management teams. The partner's
perceived trustworthiness and commitment are also essential considerations, especially if the
proposed JV involves firm's core technologies or other proprietorial skills which are eventually
the essence of the firm's competitive advantage (Kottolli, 2002 & Adnan et al., 2011). That is
why Hyun & Ahn (2013) examined joint ventures in the construction industry and found that
commitment and trust occasioned positive effects in terms of the project efficiency and
deliberate benefits. Thus, it must be remembered that today's partners could be tomorrow's
competitors and managers have to respond with some initial distrust regarding hidden partners'
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motives. As can be expected, Kottolli`s point is that (2002), habitually, a partner will have
access to your trade secrets and might attempt to complete a few projects, learn what the other
partner does, then exclude that partner from future contracts. Thus, exposing the other`s
technological core without proper legal protection can eventually threaten its partnership's
competitiveness. Therefore, without essential trust and commitment by each party, there is little
hope for a successful joint venture as those precipitate desirable behaviours and this
significantly reduce the risks of alliances, according to Hyun & Ahn (2013).
3 Research Methodology
According to Creswell (2008), research designs are the detailed procedures involved in the
research process: data collection, data analysis, and report writing. As the main aim of this
study is to identify selection criteria of joint venture partners, this study is therefore deductive
in nature. Moreover, in the attempt to answer the research question, set prior to this study, a
quantitative method was preferred in this research because it is often used in a wide range of
natural and social sciences, including physics, biology, psychology, sociology and geology.
Therefore, the analytical survey method was preferred for this research since it uses scientific
sampling and a questionnaire design to measure features of the population with statistical
precision (Sukamolson, 2012). The research work started with a literature review for the
compilation of a list of the selection criteria for joint venture partners, and then the
questionnaire was developed in order to conduct the survey.
3.1 Sampling method
A non-probability sampling method and more specifically the convenience method was
adopted which, according to Mbokane (2009), this sampling method implies that not every
element of the population has a chance for being included in the sample. Thus, any participant
which happens to cross the researcher’s path, and meets the inclusive criteria set (being
involved in joint venture construction project and registered with the SACPCMP juristic body)
gets included in a convenience sample.
3.2 Sample size
Determining the sample size can be a strenuous exercise, according to Singh & Masuku,
(2013) and Israel`s table (1992) which can provide a useful guide for determining the sample
size, one may need to calculate the required sample size for a different combination of levels
of precision, confidence, and variability or the degree of freedom (P). However, a simplified
formula to calculate sample size with a 95% confidence level and P (level of precision) = 0
.5:
n = N / (1 + N (e)2 )
n = 5000 / (1 + 5000 (0.5)2)
n = 399.68 ≈ 400
Where: n = sample size;
N = population size, and
e = level of precision.
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3.3 Sample selection
As database concerning professionals involved in joint venture construction projects registered
with the SACPCMP was unavailable, the researcher reached out the 400 respondents via email
before sending out questionnaires to ensure their involvement into JV construction projects.
Even though simple convenience sampling method was applied, it was necessary for the
researcher to ensure that those respondents were involved in joint ventures.
3.4 Data collection
After determining the sample size of the study (400), the process of data collection took
approximately two months starting in beginning February 2016 to April 2016. 100% of the
questionnaires were handed out via emails and on sites for the respondents to fill in on their
own time so that they give their true point of views. After intensive efforts were made, by April
2016 a total of 115 responses which were all usable (28.8 %) were received specifically from
the provinces of Gauteng (Johannesburg, Pretoria, Sandton), Western Cape (Cape Town) and
Limpopo (Polokwane). Based on literature review, the response rates for mailed questionnaires
are usually not encouraging and low, thus, a response rate of 15% to 25% is still being
considered appropriate and acceptable (Wahab et al., 2010) whilst a response rate of 10% to
15% is still considered appropriate according to Fryrear (2015).
3.5 Data analysis
The data analysis procedure started with data compilation, screening and finally using
descriptive statistics to analyse the proposed background information and selection criteria of
JV partners where all the statistical techniques in this study was performed using Statistical
Package for Social Sciences (SPSS) software version 23.0 and in relation with the current study
research objective, the researcher considered the mean item core and standard deviation
statistical techniques.
In fact, for all the sections of the questionnaire, the data analysis involved the following steps:
coding the responses, screening and cleaning of data to identify any missing values, as well as
the selection of appropriate statistical analysis technique whereby the research problem and
objective and characteristics of data were considered. Thus, to meet the purpose of this study,
descriptive analyses were used. First, Mean Item Scores (MIS) and Standard Deviations (Std)
have been calculated in order to identify selection criteria. In order to determine the Mean Item
Scores (MIS) and Standard Deviations (Std), the five point Likert- scale was used: 1 = Strongly
disagree (SA), 2 = Disagree (D), 3 = Neutral (N), 4 = Agree (A), and 5 = Strongly agree (SA).
4 Findings and Discussion
4.1 Respondents’ Profile
Table1 indicates that out of the 115 (100%) respondents, 74.8% of the respondents are male
while 25.2% of the respondents are female. Moreover, 35.7% of respondents were between the
age of 31 and 40. In terms of professional status construction project manager were 19.1 %
while construction managers and civil engineers each accounted for 16.5 %. Moreover, within
the provinces of Gauteng, Western Cape and Limpopo in South Africa 33.9% had been
involved in JV projects for a period of less than 5 years, and only 32.2% participants had been
involved for a period of 5 to 10 years. Moreover, the preferred type of JV in South Africa is
combined JV with 39.1% compared to the integrated JV at 36.5% and the non-integrated
method at 24.3%.
272
Table 1. Background information of respondents
Classification Frequency
(No)
Percentage
(%)
Male 86 74.8
Female 29 25.2
Younger than 21 1 0.9
21-30 23 20.0
31-40 41 35.7
41-50 29 25.2
51-60 16 13.9
Older than 60 5 4.3
Architect 13 11.3
Chemical engineer 4 3.5
Civil engineer 19 16.5
Construction Manager 19 16.5
Construction Project Manager 22 19.1
Electrical engineer 3 2.6
Quantity surveyor 18 15.7
Mechanical engineer 5 4.3
Other 12 10.4
Less than 5 years 39 33.9
5-10 years 37 32.2
10-15 years 25 21.7
15-20 years 7 6.1
More than 20 years 7 6.1
Integrated 42 36.5
Non-integrated 28 24.3
Combined 45 39.1
Source: Field data 2016
4.2 Factors for selecting a JV partner
Table 2 reveals that in undertaking a JV operation in South Africa, the parameters that one
needs to consider the most in selecting a partner in order to be successful in JV operations are
commitment between partners (∂=4.27, μ=0.88), complementary technical skills (∂=4.24,
μ=0.99), and compatible management teams (∂=4.19, μ=0.94). This result is in line with the
work of Hyun & Ahn (2013) who agreed that commitment between partners occasioned
positive effects in terms of the project efficiency and also deliberate benefits as it must be
remembered that today's partners could be tomorrow's competitors. Moreover, authors such as
Kottolli (2002) & Minja et al. (2012) supported favourable cooperative relations, resource
compatibility (in terms of complementary in technical skills), as well as, the location of the
partner are acute among the factors affecting the joint venture process. Similarly, Adnan et al.
(2011) and Minja et al. (2012) agreed on managerial compatibility as being essential because
it can enhance the partner’s ability to attain consensus on critical policy decisions and to
overcome roadblocks faced during the operation of the joint venture formation.
Moreover, complementary resources (∂=4.13, μ=0.97), commitment to joint venture objectives
(∂=4.13, μ=0.98) as well as trust between partners (∂=4.10, μ=1.04) play a major role in the
selection criteria of JV partners as respondents mutually agreed on them. Indeed, these findings
are in line with authors Kottolli (2002); Minja et al. (2012) and Hyun & Ahn (2013) who
believe that the primary selection criterion should be a partner's ability to provide resources
which should supplement those of a firm seeking the partner. Moreover, Kottolli (2002) and
Minja et al. (2012) agreed on commitment to joint venture objectives as a crucial selection
273
factor as the opposite including timing and level of profits on their investments, frequently
produce conflicts of interests between partners. Kottolli (2002) further agreed that, since, a
partner will have access to each other’s trade secrets and might attempt to complete a few
projects, learn what the other partner does, then exclude that partner from future contracts, it is
vital to have trust between partners as a criterion of selection when involved into JVs.
Yet, respondents are neutral on factors such as mutual dependency (∂=3.90, μ=1.12) and
relative company size (∂=3.67, μ=1.23) as they seem not to be as relevant as the other factors
of the selection criteria of JV. These findings are contested by Rumpunen (2011) who
emphasized that, the apprehension of the potential benefits to a firm from entering into a joint
venture (JV) depends on finding a partner who can provide balancing capabilities or resources
that match its own and this enable the joint venture to meet the firm's considered objectives.
Similarly, Kottolli (2002) agreed on these findings as he believes that company sizes aspect is
arguable as an important selection criterion since a small firm can decide to enter into a joint
venture with a similarly sized partner which may have consequences of expanding firms’
weaknesses.
Table 2. Factors for selecting JV Partner
Parameter
Response in Count and Percentages (%) Mean
(∂)
Std.
Deviation
(μ)
Rank Strongly
Disagree Disagree Neutral Agree
Strongly
Agree
Commitment between
partners
4 4 12 48 47 4.27 0.88 1
3.5 3.5 10.4 41.7 40.9
Complementary
technical skills and
resources
5 5 0 52 5 4.24 0.99 2
4.3 4.3 0.0 45.2 4.3
Compatible management
teams
3 4 11 47 50 4.19 0.94 3
2.6 3.5 9.6 40.9 43.5
Complementary
resources
3 6 11 47 48 4.14 0.97 4
2.6 5.2 9.6 40.9 41.7
Commitment to joint
venture objectives
4 4 12 48 47 4.13 0.98 5
3.5 3.5 10.4 41.7 40.9
Trust between partners 5 5 11 46 48
4.10 1.04 6 4.3 4.3 9.6 40.0 41.7
Mutual dependency 6 7 21 39 42
3.90 1.12 7 5.2 6.1 18.3 33.9 36.5
Relative company size 9 11 23 37 35
3.68 1.23 8 7.8 9.6 20.0 32.2 30.4
Source: Researcher
5 Conclusion and Further Research
The formation of joint ventures between construction organizations has been an important
attempt in overcoming problems facing local contractors such as delays and disruptions, poor
site management, time and cost variations, skills and competence issues as well as lack of
worker participation. These problems can be addressed by forming joint ventures between
companies/partners. The common purpose of joint venture is to spread a risk inherent in large
projects and to pool resources with the intention to gain more profits and enhance expertise.
274
Thus the formation of joint venture companies in South Africa needs to take into consideration
the selection criteria of partners prior to the execution of the project. In preparation of a joint
venture arrangement, it is important to consider all important selection criteria in order to have
a project delivered effectively. Selection criteria that guide joint venture partner when entering
joint venture formation in South Africa are commitment between partners, complementary
technical skills, compatible management teams as well as complementary resources,
commitment to joint venture objectives and finally trust between partners.
6 Acknowledgement
It is important to acknowledge that this article is a part of the researcher main project on the
development of a joint venture model for successful delivery of construction projects in South
Africa.
7 References
Adnan, H., Chong, H. & Morledge, R. (2011), Success criteria for international joint ventures:
The experience of Malaysian contractors in the Middle East. African Journal of Business
Management, 5(13), 5254-5260.
Creswell, J.W. (2008), Research Design: Qualitative, Quantitative, and Mixed Methods
Approaches, United States of America, SAGE Publications,16-24.
Cumberbatch (2004), Research methods: Data analysis. Available from:
http://www.smartpsych.co.uk/wp-content/uploads/2012/02/psych_methods1.pdf
(Accessed 27 September 2014)
Farkas,F., & Avny, G. (2005), Cross-Cultural Issues of International Joint Ventures: A
Viewpoint from Israel. Unpublished doctoral thesis, Budapest, Óbuda University.
Farrell, E.P. (2014), The 7 Deadly Sins of Joint Ventures. Available from:
http://www.entrepreneur.com/article/236987 (Accessed 27 January 2015).
Fryrear, A. (2015), Survey Response Rates. Available from:
https://www.surveygizmo.com/survey-blog/survey-response-rates/ (Accessed 13 April
2016).
Govindan, S. (1995), Determinants of joint venture performance in the construction industry:
Cases from the mass rapid transit project in Singapore. PhD. London: University College
London.
Gunhan, S., & Arditi, D. (2005), “Factors affecting international construction”, Journal of
Construction Engineering and Management, 131 (3), 273-282.
Hyun, J.H. & Ahn, S.Y. (2013), Host Country Perspectives on Partner Selection Criteria for
the Success of International Joint Ventures: An Empirical Survey of Korean Firms, In:
Planet Hollywood, conference proceedings of the 24th International Business Research,
Las Vegas, USA, December 12-13 2, Korea: Hankuk University of Foreign Studies, 1-17.
Israel, G. D. (1992), Sampling the Evidence of Extension Program Impact: Determining
Sample Size. Available from: http://edis.ifas.ufl.edu/pdffiles/pd/pd00600.pdf (Accessed 04
April 2015)
Kale, V.V., Patil, S.S., Hiravennavar, A.R., & Kamane, S.K. (2013), Joint Venture in
Construction Industry. Journal of Mechanical & Civil Engineering, 3, 60-65.
Kolbehdari, S., & Sobhiyah, M. H. (2014), Effects of Negotiations about the Formation of
Construction Consortium on Consortium Successful Performance in Iran’s Construction
Industry, International Journal of Management, Accounting and Economics, 1(5), 371-388.
275
Kottolli, A. (2002), Partner Selection criteria for International Joint Ventures. Available at:
http://www.geocities.ws/akottolli/partner_selection_criteria_for_IJV.html (Accessed 9
March 2015).
Kwok, H.C.A., Then, D. & Skitmore, M. (2006), Risk Management in Singapore Construction
Joint Ventures, Journal of Construction Research, 1(2), 139-149.
Mbokane, A. (2009), The Utilization of Contraceptives by Women who requested termination
of pregnancy services in the Gert Sibande District (Mpumalanga). Magister Thechnologiea
thesis, Pretoria, University of South Africa.
Minja, S.J., Kikwasi, G.J., & Thwala, W.D. (2012), A study of joint venture formation between
construction organizations in Tanzania, Australasian Journal of Construction Economics
and Building, 1 (2), 32-42.
Misbah J., Muftiet, N.A., & Khan, A.H. (2008), Risk Identification for International Joint
Venture Construction Projects, In: Advancing and Integrating Construction Education,
Research & Practice, conference proceedings of the First international conference held in
Karachi, Pakistan, August 4-5, Punjab, University of Engineering and Technology, 291-
301.
Rooyen, W.V. (2014), 8 things you must know about Joint Ventures. Available from:
http://www.sa-tenders.co.za/docs.php?id=2877 (Accessed 29 May 2015)
Rumpunen, S. (2011), Partner Selection for International Joint Venture Operations, PhD,
Vaasa, University of Vaasa.
Shen, L. Y., Wu, G. W. C., and Catherine, S. K. N. (2001), Risk assessment for construction
joint ventures in china, Journal of Construction Engineering and Management, 127 (1),
76-81.
Singh, A., & Masuku, M.B. (2013), Fundamentals of applied research and sampling
techniques, International journal of medical and applied sciences, 2 (4), 124-132.
Sukamolson, S. (2010), Fundamentals of quantitative research. Available from:
http://isites.harvard.edu/fs/docs/icb.topic1463827.files/2007_Sukamolson_Fundamentals
%20of%20Quantitative%20Research.pdf (Accessed 04 April 2015)
Wahab, S.A., Abdullah, H., Uli, J. & Rose, R.C. (2010), Inter-Firm Technology Transfer and
Performance in International Joint Venture Firms, International Journal of Business and
Management, 5 (4), 93-103.
Young, J. (2012), Gauteng’s engineering firms are driving the provincial economy. Available
from: http://www.matchdeck.com/article/681-gauteng-s-engineering-firms-are-driving-
the-provincial-economy (Accessed 27 January 2015).
276
Factors Affecting Cost and Time Control in Construction
Projects Olajide Faremi and Olabode Ogunsanmi
Department of Building,
University of Lagos, Nigeria
Email: juliusfaremi@gmail.com, olabodeogunsanmi@gmail.com
Abstract:
This study examines factors affecting cost and time control of construction projects with a view
to proposing recommendations that could assist stakeholders to achieve enhanced cost and time
performance of construction projects. Consequently, a survey of professionals managing
construction projects in Lagos, Nigeria was conducted. Structured questionnaire was developed
and administered to eighty (80) managers of construction projects who were randomly selected
from a sample frame of One-hundred (100) construction project contractors. A total of fifty-
two (52) questionnaires were retrieved representing 62% response rate. Using Statistical
Package for Social Sciences, version 20.0, descriptive and inferential statistical tools including,
bar chart, mean, minimum and maximum values, frequency tables, T-test and Analysis of
Variance (ANOVA) were employed to analyze collected data. The results of the analysis
revealed that the top three significant factors affecting cost and time control of construction
projects are; design and documentation issues, poor labour productivity and financial resource
management. This study recommends the avoidance of poor work quality in construction
activities. Also, project and construction managers should focus on project tripod constraints
of cost, quality and time while workers hired and deployed on construction projects should be
adequately skilled in order to achieve desired cost and time performance.
Keywords:
Construction, Control, Cost, Time
1 Introduction
Cost and time control is the process or activity of controlling costs and time associated with an
activity or process. It involves the process of managing and controlling factors that change or
affect the budget and time of a given activity or sets of activities (Owens & Krynovich, 2007).
Reading and Muir (2005) posit that construction projects represent a unique set of activities
that must take place to produce a unique product. Construction projects comprise of new
buildings and structures, additions, alterations, conversions, expansions, reconstruction,
renovations, major replacements, mechanical and electrical installations among others. The
need to control cost and time in construction industry is essentially to ensure that projects are
completed within budget and on time or as scheduled (Rahman, Memon, Nagapan, Latif, &
Azis, 2012).
Globally, the success of a construction project is determined by the ability of the project to
meet the criteria of cost, time, safety, resource allocation, and quality as determined by the
client. Kagioglou, Cooper, & Aouad (2001) affirm that a successful project is the project which
has accomplished its technical performance, maintained its schedule, and remained within
budgetary costs. Rahman et al. (2012) buttress the position that time and cost performance is
the fundamental criteria for success in any construction project.
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Despite the establishment of these performance metrics, ever reoccurring is the challenge of
completing construction projects within the scheduled time and budgeted cost. Olawale and
Sun (2010) argue that the generality of construction industry has been regarded as industry
facing poor performance leading to failure in achieving effective time and cost performance.
Consequently, most construction projects face huge amount of time and cost overrun. Ameh,
Soyingbe, and Odusami (2010) concur that the history of the construction industry worldwide
is full of projects that were completed with significant time and cost overruns. The authors
recount that of 8,000 construction projects surveyed in 1994, only 16% could satisfy the three
famous performance criteria of been completed within scheduled time, within the budgeted
cost and maintaining a high standard of quality.
The inability of construction project managers to keep cost and time of construction projects
within scheduled limits often results in grave consequences. Azis, Memon, Rahman, & Karim,
(2013) opine that construction project cost which is out of control adds to investment pressure,
increases construction cost, and affects investment decision-making. Shanmugapriya &
Subramanian (2013) add that from the national economic perspective, time and cost overruns
reduce the productivity of available economic resources, edge the development potential and
diminish the effectiveness of the economy.
Studies existing in literature (Olawale & Sun, 2010; Ameh & Osegbo, 2011; Memon, Rahman,
Asmi, & Azis, 2011; Ibrahim, 2012; Azis et al., 2013; Hashim, 2013; Juliet & Ruth, 2014;
Muhwezi, Acai, & Otim, 2014; Shanmugapriya & Subramanian, 2013; Ballhysa & Blloku,
2014; Idiake, Shittu, & Oke, 2015) are limited to the identification of the influencing factors,
but did not progress onto finding ways of mitigating the identified challenges. These
observations underlie the rationale for this study as it aims to identify the factors affecting cost
and time control of construction projects with a view to recommend mitigating measures to
assist construction project managers achieve improved control of cost and time on construction
projects.
This study aimed at evaluating factors affecting time and cost control on construction projects
in Lagos State with a view to making recommendations that could assist construction project
managers achieve improved control of time and cost of construction projects.
In order to achieve the aim of this study, the following objectives are defined:
To assess the factors affecting cost and time control of construction projects in Lagos State,
Nigeria, and
To examine measures for achieving improved cost and time control of construction projects
in Lagos State.
The study also seeks to test the null hypothesis that:
HO: There is no significant difference in the perception of construction professionals on
factors influencing cost and time control of construction projects in Lagos State.
2 Literature Review
Cost and time control is defined as a process by which construction cost and time of a project
is managed through best methods and techniques (Otim, Nakacwa, & Kyakula, 2012) so that
project stakeholder(s) do not suffer losses as the activities of the project are carried out. Koh
(2005) concurs that project cost and time control refers to the process by which the cost of a
278
project is kept within the agreed cost limits and the duration kept within agreed schedule limits
respectively.
Furthermore, Raut, Pimplikar and Sawant (2013) opine that construction cost and time control
consists of simply monitoring actual cost and time performance of a project against the cost
and time estimates earlier designed or stipulated for the project and identifying variances. The
authors explain that the aim of cost and time control process is to monitor actual cost and time
performance of projects and identify improvement opportunities, which must be dealt with by
corrective actions.
Idiake et al. (2015) buttress that time, cost and quality are three major variables that are of
primary concern to the main parties involved in procurement of building projects. The
management of these variables is usually a complex task for project managers in practice.
Ameh and Osegbo (2011) opine that the challenge of controlling project schedule is of global
concern. Ineffective control of time in line with project schedule usually result in the extension
of time beyond planned completion dates. Similarly, ineffective control of construction project
cost would usually result in a difference between actual cost of a project and its Cost limit
(Ballhysa & Blloku, 2014). When this differences occur it is referred to as cost overrun. Cost
overrun on projects thus occurs when the resultant cost target of a project exceeds its cost limits
where Cost limit of a project refers to the maximum expenditure that the client is prepared to
incur on a completed building project while cost target refers to the recommended expenditure
for each element of a project.
Construction cost which is out of control adds to investment pressure, increases construction
cost, affects investment decision making and wastes the national finance might result in
corruption or offence (Rahman et al., 2012). Most construction project are being completed at
costs much higher than initial estimate which indicate that initial cost estimates on construction
projects can hardly be relies upon by clients (Olawale & Sun, 2010). The problem of poor cost
and time management and its respective overruns in project cost and time are serious issues in
both developed and developing countries. This needs serious attention for improving the
construction cost and time performance as rarely projects are completed within budget and
schedule. This study would survey opinions of its sample on the challenges of cost and time
control of construction projects within the study area by adopting articulated challenges
discussed in this section of the study.
Rahman et al. (2012) opine that time and cost performance of construction projects are affected
by factors such as design and documentation issues, financial resource management, project
management and contract administration, contractors’ site management, information and
communication technology, material and machinery resource, labour (human) resource and
external factors.
Furthermore, Memon et al. (2010) present twenty-four factors that influence the effective
control of costs on construction projects. The authors opine that the factors include the practice
of assigning contract to lowest bidder, contractor's poor site management and supervision, cash
flow and financial difficulties faced by contractors, incorrect planning and scheduling by
contractors, inadequate contractor experience, shortage of site workers, delay in Material
procurement, incompetent project team (designers and contractors), fluctuation in prices of
materials, underestimate project duration resulting schedule delay, shortages of materials,
mistakes during construction, lack of communication among parties, labor productivity, low
speed of decisions making, change in the scope of the project, poor technical performance,
279
frequent design changes, slow payment of completed works, unforeseen ground conditions,
equipment availability and failure, necessary variations of works, owner interference and social
and cultural impacts. All identified factors in literature cited in this study were adopted for use
in the course of collecting data for this study.
3 Research Methodology
This study was geographically delimited to Lagos State, the economic nerve center of Nigeria.
A total sample frame of 100 construction companies having operations in Lagos state was
developed for this study. The sample frame comprises of eighty-eight (88) construction
companies that are registered with Lagos state tender board and twelve construction companies
scooped from the list of construction companies on Vconnet data base. Adopting the Taro
Yamane (1967) equation for determining sample size as explained by Israel (2013) that:
………………… equation 1
Where:
n is the sample size
N is the population size
e is the level of precision
A sample size of eighty (80) was obtained. Consequently, eighty (80) data collection instrument
was designed and administered. Out of the administered questionnaires, a total of fifty-two
questionnaires were retrieved representing 65% response rate.
4 Results and Discussion of Findings
4.1 Demographic Data of Respondents
The statistics of the characteristics of the respondents for this study was analysed and the results
presented in Figure 1 below:
Figure 1: Respondents’ demographic data
280
Figure 1 above shows the characteristics of respondents for this study across four areas of
respondents’ designation, academic qualification, academic background and the years of
experience on construction projects of those that responded to the survey. The analysis revealed
that the designation of majority of the respondents were project managers and construction
managers account for about 70% and 29% of the responses respectively. This implies that the
respondents are core professionals equipped to handle building construction projects, thus their
responses would be of immense value to this study. Also about 47% of the respondents have
Higher National Diploma certificates or Bachelor of Science certificate while about 51%
possessed post graduate qualifications. It implies the generality of the respondents have
acquired significant level of formal education and would therefore be able to provide
appropriate responses to the various formulated research questions.
4.2 Factors Affecting Cost and Time Control of Construction Projects
Based on extensive review of literature as discussed in previous chapter of this study, prevailing
factors affecting cost and time control of construction projects were presented to surveyed
respondents and they were asked to assess the level of significance of each of the articulated
factors on a 5 point Likert scale ranging from not significance to highly significance. A total
of forty-nine (49) factors were assessed, the resulting analyses are shown in table 1 below:
Table 1: Factors affecting cost and time control of construction projects
Factors N Minimum Maximum Mean Rank
Design and Documentation issues 47 3 5 4.57 1
Poor labor productivity 49 3 5 4.53 2
Financial Resources Management 51 3 5 4.51 3
Change in the scope of the project 48 4 5 4.48 4
The practice of assigning contract to
lowest bidder
49 3 5 4.45 5
Poor technical performance 50 3 5 4.44 6
Shortage of site workers 51 2 5 4.43 7
Unforeseen ground conditions 48 2 5 4.42 8
Incompetent project team (designers and
contractors)
51 3 5 4.41 9
Human Resources 49 3 5 4.41 10
Project Management and Contract
Administration
50 2 5 4.40 11
Inadequate contractor experience 48 2 5 4.40 12
Delay in Material procurement 51 3 5 4.39 13
Frequent design changes 49 3 5 4.39 14
Owner interference and social and cultural
impacts
49 4 5 4.39 15
Lack of communication among parties 48 3 5 4.38 16
Material and Machinery Resource 51 2 5 4.37 17
Necessary variations of works 49 4 5 4.37 18
Incorrect planning and scheduling by
contractors
49 2 5 4.37 19
Shortages of materials 50 3 5 4.36 20
281
Factors N Minimum Maximum Mean Rank
Low speed of decisions making 48 3 5 4.35 21
Inadequate fund for the project 50 3 5 4.34 22
Contractors Site Management Techniques 50 3 5 4.34 23
Obtaining building permits and approvals 49 2 5 4.33 24
Slow payment of completed works 50 3 5 4.32 25
Mistakes during construction 50 2 5 4.30 26
Contractor's poor site management and
supervision
49 2 5 4.29 27
Fluctuation in prices of materials 51 2 5 4.27 28
Cash flow and financial difficulties faced
by contractors
51 2 5 4.27 29
Equipment availability and failure 49 3 5 4.27 30
Design changes during project execution 50 2 5 4.26 31
Subcontractor incompetency 51 2 5 4.25 32
Information and Communication
Technology
50 3 5 4.24 33
Delay in delivery of materials 51 1 5 4.24 34
Underestimate project duration resulting
schedule delay
48 2 5 4.23 35
Incompleteness of technical
documentation
51 2 5 4.16 36
Inadequate planning of project before
commencement
51 1 5 4.16 37
Variations 50 2 5 4.14 38
External Factors 47 2 5 4.13 39
Unexpected subsoil/ground condition 48 2 5 4.10 40
Inadequate tools and equipment 51 1 5 4.08 41
Accidents 48 1 5 4.02 42
Political instability or change in
government policies
48 1 5 4.02 43
Delay in response to decision taking 50 1 5 4.02 44
Labour dispute in form of strike or lock-
out
48 2 5 3.98 45
Delay in inspection and testing of
completed work
50 1 5 3.96 46
Temporary work stoppages due to adverse
weather
46 1 5 3.96 47
Unclear or inadequate instructions to
operators
48 1 5 3.90 48
Community issues 49 2 5 3.86 49
The results in table 1 reveal that design and documentation issues ranked first among factors
affecting cost and time control of control projects. This is followed by the productivity level of
282
labour resources on construction projects, financial resource management, change in the scope
of projects and the practice of assigning contracts to lowest bidders respectively. This result
implies that significant time is spent on resolving request for changes in design by key project
stakeholders. Also cost and time spent on obtaining required development permits for building
construction projects from relevant government agencies within the study area are relatively
difficult to estimate because in most cases such approval periods are prolonged due to the
bureaucratic nature of obtaining such permits and approvals, this consequently alters project
managers and construction managers cost and time schedule.
This result concurs with the findings of Memon, Rahman, and Azis (2012) that design and
documentation issues are very dominant in construction, they opine that design and
documentation issues have significant impact on cost and time performance of construction
projects as frequent design changes are common practice on construction projects. Factors
ranked to be least significance include; strike actions as a result of labour dispute, delay in
inspection and testing of completed work, temporary work stoppages due to adverse weather,
unclear or inadequate instructions to operators and community issues. Unlike this study that
ranked labour productivity as the second most significant factor affecting cost and time control
of construction projects, Rahman et al. (2012) in their study titled “Time and cost performance
of construction projects in southern and central regions of peninsular Malaysia” ranked
financial resource management as the second most significant factor affecting cost and time
control of construction projects. They explained that delay in payment to the contractor for
completed works by the client results in cash flow challenges which usually slow down the
pace of contractors.
4.3 Measures for Achieving Improved Cost and Time Control of Construction
Projects
This study seeks to assess measures for achieving improved cost and time control of
construction projects hence respondents were presented with hypothesized measures that could
improve control of cost and time of construction projects as elicited from literature. The
respondents were asked to rate their level of agreement or otherwise with each of the potential
measures using a 5 point Likert scale ranging from strongly disagree to strongly agree. Table
2 below shows the resulting analysis:
Table 2: Measures for improved cost and time control of construction projects
Measures for improved cost and time control N Mean Std. Deviation
Avoid poor quality of work 48 4.65 .526
focus on the quality cost and delivery of the
project
50 4.62 .490
hire skilled workers to achieve good progress 49 4.59 .497
committed leadership and management 48 4.56 .542
proper work planning 48 4.56 .542
training and development of all participant to
support delivery process
50 4.54 .646
more rectification and double handling, close
monitoring
50 4.54 .613
283
Measures for improved cost and time control N Mean Std. Deviation
adoption of tools and techniques i.e.: value
management, lean thinking, total quality
management, etc
50 4.52 .580
effective site management and supervision 50 4.50 .580
use new construction technologies (IBS-
Industrialize Building System)
50 4.48 .677
effective strategic planning 50 4.46 .542
send a clear and complete message to worker to
ensure effective communication
50 4.46 .579
proper project planning and scheduling 50 4.44 .644
fully utilize the construction team 49 4.43 .707
use of appropriate construction methods 48 4.40 .765
measure performance against other projects 48 4.35 .699
provide knowledge/training to unskilled workers
based on their scope of work
50 4.30 .839
clear information and communication channels 47 4.30 .720
frequent progress meeting 49 4.29 .764
focus on client’s need 50 4.28 .640
use of experienced subcontractors and suppliers 52 4.27 .660
frequent coordination between the parties 47 4.23 .729
perform a preconstruction planning of project
tasks and resources needs
48 4.23 .692
systematic control mechanism 47 4.19 .680
comprehensive contract administration 47 4.17 .732
use up to date technology utilization 47 4.15 .908
improving contract award procedure by giving
less weight to prices and more weight to the
capabilities and past performance of contractors
46 4.09 .812
proper emphasis on past experience 50 4.08 .752
developing human resources in the construction
industry
46 4.04 .815
Source: Researcher
The analysis in Table 5 shows that respondents strongly agree that avoidance of poor quality
of work with a mean of 4.65 is the most significant measure for achieving improved cost and
time control of construction work. The second most significant measure agreed by the
respondents is that construction project managers should focus on project quality, project cost
and project delivery as inseparable entity. The results infers that quality work orientation and
avoidance of poor quality of work would reduce defective work and rework in the course of
construction activities which would in turn impact cost and time performance of construction
projects positively.
4.4 Research Hypotheses
Ho: There is no significant difference in the perception of construction professionals on factors
affecting cost and time control of construction projects within the study area.
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H1: There is significant difference in the perception of construction professionals on factors
affecting cost and time control of construction projects within the study area.
To test the hypotheses, the Analysis of Variance (ANOVA) method was used. The ANOVA is
a statistical method for making simultaneous comparisons between two or more means and
since there were five (5) groups of construction professionals as respondents to this survey
(Architects, Quantity Surveyors, Builders, Civil Engineers and Mechanical Engineer) the
ANOVA method was most appropriate.
From the computation for the hypothesis, the overall average significance value for the
Analysis of Variance test was found to be 0.437 at a significant level of 0.05. Although a case
by case significance test as revealed in table 6 shows that there are significant differences in
the perception of the respondents on four (4) of the factors therefore the individual null
hypotheses for them were rejected. The affected factors include mistakes during construction
(p=0.033, p<0.05), lack of communication among parties (p=0.030, p<0.05), low speed of
decision making (p=0.016, p<0.05) and frequent design changes (p=0.024, p<0.05). The
average statistics value (p=0.437, p>0.05) however supports the null hypothesis that there is
no significant difference in the perception of construction professionals on factors affecting
cost and time control of construction projects.
5 Conclusion
This research concludes that that out the forty-nine hypothesized factors examined in the course
of this study, the five top predominant factors affecting cost and time control of construction
projects in Lagos state, Nigeria include design and documentation issues, labour productivity,
financial resources management, changes in the scope of the project and the practice of
awarding contracts to the lowest bidder. This findings supports the position of Rahman et al.
(2012) that design and documentation as well as financial resource management are the two
most important factors for improving cost performance of construction projects. The authors
argue that design and documentation issues are highly correlated with project management and
contract administration and thus impact significantly on project management and contract
administration activities. Azis et al. (2013) further emphasize that design is the road map and
systematic guide in leading to the objective of any project while documentation plays an
important role in tracking and monitoring the progress of the project.
In addition, other top factors that project stakeholders should give attention in the quest for
effective cost and time control in construction projects include labour productivity issues (i.e.
poor productivity of workers on construction projects). Shanmugapriya and Subramanian
(2013) affirm that poor labour productivity is one of the seven (7) most significant factors
affecting cost performance of construction projects in Indonesia. Others factors affecting cost
and time control of construction projects in Lagos state are incessant changes in the scope of
construction projects and the practice of assigning the contracts of construction projects to
lowest bidders. These set of factors complement design and documentation issues and financial
resources management as the top five (5) most significant factors affecting cost and time
control of construction projects.
Furthermore, despite the availability of computer software applications that could assist project
and construction site managers in controlling cost and time of construction projects, the level
of proficiency of those managing construction projects as revealed by this survey mere average.
This implies that most of the project and construction managers within the study area are likely
285
to be reactive rather than been proactive on issues and challenges bothering on cost and time
control because of the mere average appreciation of modern tools to appraise cost and time
performance of projects and anticipate potential challenges with attendant implications of poor
cost and time performance of construction projects.
Further to the findings, this study recommends that construction project stakeholders especially
project and construction managers should ensure that poor workmanship are avoided when
carrying out construction activities. This would minimize the need for rework and consequently
enhance the optimization of both financial and time resources. Also, project and construction
managers should constantly and consistently focus on construction project tripod of cost,
quality and time. Such focus should encompass the development of skills and competence that
would enhance their ability to effectively discharge duties in this regard. Construction project
stakeholders should make effort at hiring only workers that are adequately skilled as the project
or work/activity demands. This would result in accelerated progress of work and consequently
good construction project time performance.
6 References
Ameh, O. J., & Osegbo, E. E. (2011). Study of Relationship Between Time Overrun and
Productivity on Costruction Sites. International Journal of Construction Supply Chain
Management, 1(1), 56–67.
Ameh, O. J., Soyingbe, A. A., & Odusami, K. T. (2010). Significant Factors Causing Cost
Overruns in Telecommunication Projects in Nigeria. Journal of Construction in
Developing Countries, 15(2), 49–67.
Azis, A. A. A., Memon, A. H., Rahman, I. A., & Karim, A. T. A. (2013). Controlling Cost
Overrun Factors in Construction Projects in Malaysia. Research Journal of Applied
Sciences, Engineering and Technology, 5(8), 2621–2629.
Ballhysa, V., & Blloku, M. (2014). Critical Factors Affecting Construction Cost In Albania.
International Journal of Engineering Research and Technology, 3(2), 3014–3022.
Baloyi, L., & Bekker, M. (2010). Causes of Construction Cost and Time Overruns : The 2010
FIFA World Cup stadia in South Africa. Acta Structilia, 18(1), 51–67.
Enshassi, A., Mohamed, S., & Abushaban, S. (2009). Factors Affecting the Performance of
Construction Projects in the Gaza Strip. Journal of Civil Engineering and Management,
15(3), 269–280.
Hashim, M. (2013). Assessing the Challenges of Cost Control Practices in Nigerian
Construction Industry. Interdisciplinary Journal of Contemporary Research in Business,
366–374.
Ibrahim, M. O. (2012). Analysis and Prediction of Cost and Time Overrun of Millennium
Development Goals ( MDGS ) Construction Projects in Nigeria. Developing Country
Studies, 2(10), 140–147.
Idiake, J. E., Shittu, A. A., & Oke, A. A. (2015). A Study of Time and Cost Relationship of
Private Building Projects in Abuja, International Journal of Construction Engineering
and Management, 4(1), 26–34.
Israel, G. D. (2013). Determining Sample Size. University of Florida, IFAS Extension,
PE0D6(April 2013), 1–5.
Kagioglou, M., Cooper, R., & Aouad, G. (2001). Performance management in construction: a
conceptual framework. Construction Management & Economics, 19(1), 85–95.
Kasimu, A., M., & Usman, M. D. (2013). Delay in Nigerian Construction Industry. Journal of
Environmental Sciences and Resources Management, 5(2), 120–129.
Koh, W. L. (2005). Cost Control in Construction Project of the Site. Universiti Teknologi
Malaysia.
286
Memon, A. H., Rahman, I. A., Asmi, A., & Azis, A. (2011). Preliminary Study on Causative
Factors Leading to Construction Cost Overrun. Interbational Journal of Sustainable
Construction Engineering and Technology, 2(1), 57–71.
Muhwezi, L., Acai, J., & Otim, G. (2014). An Assessment of the Factors Causing Delays on
Building Construction Projects in Uganda. International Journal of Construction
Engineering and Management, 3(1), 13–23.
Olawale, Y., & Sun, M. (2010). Cost and Time Control of Construction Projects: Inhibiting
Factors and Mitigating Measures in Practice. Construction Management & Economics,
28(5), 509–526.
Otim, G., Nakacwa, F., & Kyakula, M. (2012). Cost Control Techniques Used On Building
Construction Sites in Uganda. In Second International Conference on Advances in
Engineering and Technology (pp. 367–373).
Rahman, I. A., Memon, A. H., Nagapan, S., Latif, Q. B. A. I., & Azis, A. A. A. (2012). Time
and Cost Performance of Costruction Projects in Southern and Cenrtal Regions of
Penisular Malaysia. CHUSER 2012 - 2012 IEEE Colloquium on Humanities, Science and
Engineering Research, 1(1), 52–57.
Raut, S., Pimplikar, S. S., & Sawant, K. (2013). Effect of Project Cost and Time Monitoring
on Progress of Construction Projct. International Journal of Research in Engineering and
Technology, 02(12), 796–800.
Shanmugapriya, S., & Subramanian, K. (2013). Investigation of Significant Factors
Influencing Time and Cost Overruns in Indian Construction Projects. International
Journal of Engineering Technology and Adcanced Engineering, 3(10), 734–740.
Sweis, G. J., Sweis, R., Rumman, M. A., Hussein, R. A., & Dahiya, S. E. (2013). Cost Overruns
in Public Construction Projects: The Case of Jordan. Journal of American Science, 9(7),
134–141.
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