Embed Size (px)
Citation preview
COMPLIANCE AND REGULATORY FRAMEWORK IN PUBLIC
PROCUREMENT OF PUBLIC ROAD CONSTRUCTION PROJECTS IN UGANDA
By
NOAH MWELU
(3245346)
Msc.PSCM, Bsc.PSCM & SPLM (MAKERERE UNIVERSITY)
A thesis submitted to University of Newcastle, Faculty of Engineering and Built Environment, School of Architecture and Built Environment in fulfilment of the requirement for the award of the Degree of Philosophy in Building.
Supervisors:
Professor Peter Davis and Dr Yongjian Ke
October 2019
i
Doctorial Confirmation Committee
Prof: Thayaparan Gajedran Chair Person
Prof: Willy Sher Member Member
Dr Marcus Jefferies Member
Prof: Peter Davis Principal Supervisor
Dr Yongjian Ke Co-Supervisor
ii
Certification
The undersigned certify that they have read and recommend for acceptance by the University of Newcastle as a dissertation titled Compliance and Regulatory Framework in Public Procurement of Public Road Construction Projects in Uganda. In fulfilment for the award of the Degree of Philosophy (Building) of the University of Newcastle Australia.
……………………………………………
Dr Yongjian Ke
(Supervisor)
Date: 30th October 2019
……………………………………………
Professor. Peter Davis
(Supervisor)
Date: 30th October 2019
iii
Statement of Originality
I Noah Mwelu, hereby certify that the work embodied this thesis is my own original work, conducted under normal supervision. The thesis contains no material which has been accepted, or is being examined, for the award of any other degree or diploma in any other university or other tertiary institution and, to the best of my knowledge and belief, contains no material previously published or written by another person, except where due reference has been made. I give consent to the final version of my thesis being made available worldwide when deposited in the University’s Digital Repository, subject to the provisions of the copyright Act 1968 and any approved embargo.
……………………………………….
Signature
Date: 30th October 2019
iv
Acknowledgment of Authorship
I hereby certify that the work embodied in this thesis contains published paper/s/scholarly work of which I am a joint author. I have included as part of the thesis a written declaration endorsed in writing by my supervisor, attesting to my contribution to the joint publication/s/scholarly work.
By signing below, I confirm that Noah Mwelu contributed by extracting three papers from this thesis as detailed below. As a process of peer reviewed paper for publication, Noah as a lead and corresponding author together with co-authors listed below participated in revising the manuscripts throughout the entire process until these articles were accepted and published. In addition, Noah as a lead author had extra workload through coordination with the respective journal editorials.
No Title Journal Authors
1 Compliance within a Regulatory Framework in Implementing Public Road Construction Projects.
Construction Economics and Building.
DOI: https://doi.org/10.5130/AJCEB.v18i4.6362
Name Sig
Noah Mwelu
Prof Peter Davis
Dr Yongjian Ke
Dr Susan Watundu
2 Success Factors for Implementing Uganda’s Public Road Construction Projects
International Journal of Construction Management.
DOI:10.1080/15623599.2019.1573481
Noah Mwelu
Prof Peter Davis
Dr Yongjian Ke
Dr Susan Watundu
Dr Marcus Jefferies
3 Compliance Mediating Role within Road Construction Regulatory Framework
Journal of Public Procurement Noah Mwelu
Prof Peter Davis
Dr Yongjian Ke
Dr Susan Watundu
[Professor Peter Davis]
v
Abstract
Public road construction projects are a key to economic development of many Nations
including Uganda being the focus of this dissertation. However, persistent lack of compliance
in public sector procurement and increasingly unsuccessful public road construction projects
were observed in Uganda. This thesis considered compliance with a public procurement
regulatory framework and the successful implementation of public road construction projects
as key components to boost Uganda’s economic development. Consequently, the dissertation
examined six factors influencing compliance with a regulatory framework and seven factors
influencing successful implementation of public road construction projects using agency and
institutional theories. The theories guided in the selection of study variables that were
explored in a comprehensive literature review. The thesis adopted a cross-sectional research
design using a self-administered questionnaire to collect data from five organizations
involved in public road construction projects. Considering a sample size of 299 participants,
a response rate of 64.9% was achieved.
Structural Equation Modelling based on Partial Least Squares (PLS-SEM) was used
for data analysis and model estimation. Additionally, Med-Graph excel programme and Sobel
test were used to determine mediation and examine interactive effects among factors that lead
to the successful implementation of public road construction projects. Three validated models
named compliance; project success and mediation are established to guide management in
implementing road construction projects. Under the compliance model, results show that staff
sanctions, perceived inefficiency of a regulatory framework and contractors’ resistance to
non-compliance significantly enhanced compliance with the public procurement regulatory
framework. While under the project success model, compliance with regulatory framework,
familiarity with regulatory framework, monitoring activities, professionalism of staff and
perceived inefficiency of regulatory framework significantly enhanced the successful
implementation of public road construction projects. Finally, the mediation Med-Graph Sobel
test results show that compliance with a public procurement regulatory framework
significantly mediated the relationship between familiarity with the regulatory framework,
monitoring activities, sanctions on staff, and contractors’ resistance and project success.
The compliance model was developed to support governmental efforts to initiate and
ensure compliance in public procurement, while the project success model would guide
governments through respective bodies on how to successfully implement public road
vi
construction projects. Given the complexity of construction projects, the interplay of factors
is inevitable to reinforce successful construction sector. Hence, mediation effects would
enhance stakeholders’ understanding on the mediating role of compliance with a regulatory
framework in successful implementation of public road construction projects. Consequently,
management should consider an interactive effect rather than singularly applying success
factors whilst implementing construction projects. Finally, management should pay attention
to respective indicators of compliance and project success factors (Study variables) when
implementing validated models. This would save the Ugandan government significant funds
that could be channelled to other priority sectors, increase paved road networks and boost
economic development in Uganda.
vii
Dedication
This dissertation is dedicated to my beloved wife Dr Susan Watundu Mwelu and my
daughters Lucky Mercy Mwelu, Peace Joy Mwelu, Talituleka Hope Mwelu, Blessed
Malyamu Mwelu and Mariza Susan Mwelu.
viii
Preamble
My quest for public procurement started back in 1990 when I was in senior three.
During that time, I was studying commerce as one of the ten subjects at Ordinary level in
Moroto High School. In Commerce, under the topic departmental stores, I became impressed
with the economic advantages of a purchasing officer. My impression increased with the
wellbeing and lifestyle of a few purchasing officers that I had encountered. However, at that
time and as a student of a remote up-country school, I did not know that there was a bachelor’s
degree or a PhD in public procurement. Having stayed out of school for long because of
tuition, in 2006, I embarked on my dream by doing a Certificate in Strategic Procurement
and Logistics Management from Makerere University under the guidance and encouragement
from my uncle Geoffrey Wepondi. This certificate secured me a job as a stores officer. Later
in 2007, I started a Bachelor’s degree in Procurement and Supply Chain Management that
culminated into my promotion to stores manager. During my Bachelor’s study, the quest of
public procurement increased with the motivation from my lecturer Professor Moses
Muhwezi who by then was holding a PhD with vast experience in public procurement. This
motivation saw me in 2010 enrolling for a Master’s degree in Procurement and Supply Chain
Management that I completed in 2012.
From 2007 onwards, I gained experience in public procurement with some most
memorable times when I participated in two projects for procurement of secondary schools’
textbooks respectively funded by World Bank and African Development Bank through
Ministry of Education and Sports. During this time, I learnt of many challenges facing public
procurement especially procurement irregularities accounting for some of the greatest
percentage of the National budget of Uganda. These challenges particularly surrounding
heavily funded construction projects motivated my quest to do a PhD and conduct an
empirical study to determine factors enhancing compliance with a public procurement
regulatory framework and successful implementation of public construction projects. The
procurement knowledge gained from certificate to PhD level coupled with experience has
enabled my understanding of how public procurement can transform economic development
of any Nation if effectively managed.
ix
Acknowledgement
This PhD was fully funded by the Commonwealth Government of Australia through the
University of Newcastle, Australia. Successful completion of this PhD study is attributed to
a number of factors and personalities. In this regard, I would like to extend my sincere
gratitude and heartfelt feelings to the following;
I start by thanking the Almighty God through the name of our Lord Isa Masiya for
enabling me to reach all this far. I know perfectly well that without God’s grace and Mercy I
would be nowhere. Recalling my humble background, gambling with tuition fees and life
etcetera, thank you very much my Almighty God. It is from this point that I would like to
thank my late grandmother Efulasi Nakhumitsa for sowing an education seed into me as a
key to bright future. “Mum” as I used to call you, thanks very much Grandmother for being
my earthly God. May the Almighty God be with you wherever you are.
I would like to thank the Commonwealth Government of Australia and the University
of Newcastle Australia for the generous and particularly financial support that enabled me to
achieve this spectacular dream and academic status. May the Almighty God bless you all.
Furthermore, special thanks go to the Government of the Republic of Uganda and
management of Makerere University Business School for granting me a study leave and
supporting me throughout this academic journey. I will live to remember all your
contributions and support in various capacities.
I would like to extend my sincere and heartfelt thanks to my committed supervisors
Professor Peter Davis and Dr Yongjian Ke for their tireless supervision and guidance that has
resulted into this tremendous achievement. Besides your academic mandate, you showed me
parental love that I will remember forever. May the Almighty God bless you and be with you
always. I equally thank the Doctorial confirmation committee Professor Thayaparan
Gajedran, Professor Willy Sher and Dr Marcus Jefferies. This achievement would be just a
dream without you.
I would like to thank the School of Architecture and Built Environment, University
of Newcastle for academic, material and social support and facilitation that greatly enhanced
my success. I will always remember Professor Sue Anne Ware Head of School and her
professional team for equal treatment of PhD students in sharing resources including partying
and provision of meals among others. Special thanks go to Professor Suzanne Ryan of the
x
Business School, University of Newcastle for her tremendous research methods’ class and
facilitation that I will live to remember. In the same vein, I thank Ms Lisa Ogle senior
researcher and librarian Faculty of Engineering and Built Environment for her EndNote
classes and guidance. May the Almighty God bless you all abundantly.
I am extremely thankful to my beloved wife Dr Susan Watundu Mwelu and our lovely
daughters Lucky Mercy, Peace Joy, Talituleka Hope, Blessed Malyamu and Mariza Susan
for your prayers, encouragement and tireless support that has seen me all this far. Dr Super
girl Susan Watundu, thank you very much for looking after our daughters and home. I am
equally indebted to tell you that you have contributed greatly towards my life and
achievements. May the Almighty God bless you and our daughters generously in the name
of our Lord Isa Masiya. Special gratitude goes to Evangelist Christopher Besweri Kaswabuli
and the entire church of Isa Masiya for your heartfelt prayers and support. I am equally
grateful to my mother Naome Namono, Uncle Richard Mabonga; Uncle Geoffrey Wepondi,
Uncle Perez Matanda, Uncle Dyson Maswere, Uncle Richard Wambi, Uncle Francis Waluya,
Uncle Peter Khaukha, Aunties: Joy Namasaba, Deborah Wanyenya, Lorna Watela, Maris
Wanyerah, Connie Mlay, Sister Loy Lunyolo, Mother in-law Malyamu Wambi and brother
in-law Simon Sakwa among others for your support.
I would like to express my sincere appreciation to the staff of Makerere University
Business School for your generosity and support in various capacities that have enabled me
to reach this far. Special recognition of the Principal and Professor Waswa Balunywa,
Professor Moses Muhwezi, Professor Moya Musa, Dr Lubogoyi Bomali, Dr Nkutu Geoffrey,
Mr. Gad Mutaremwa, Ms Irene Namutebi and my fellow colleagues. In the same vein, I am
equally thankful to my Australian/Ugandan mentors and seniors including Dr Matthew
Kalubanga, Dr Sarah Eyaa, Dr Patrick Kakwezi, Dr Sheila Namagembe, Dr Friday Derick,
Dr Mathias Mulumba and Mr. Julius Bulamu, all my lecturers at various levels and my
teachers of primary and secondary schools. I will never forget your support and contribution
both academically and socially that has made me what I am.
Furthermore, I thank my PhD colleagues Dr Tanvi Nwaz, Dr Josephine Vaughan, Dr
Michael Dawes, Dr Olabode Ogunmakinde, Dr Matthew Abunyewah, Owi Toinpre, Meney
Brendan, Tania Papasotiriou, Georgia Kissa, Ali Yousefi, Ali Papzan, Simon Laura, Salah
Alghamdi, Mahmoud Ershadi, Adane Molla, Abhinav Walia, Reza Forghani, Bernard
Tuffour, Udara Ranasinghe, Shumnk Deep, Sulala Zaki, Rumana Asad, Nurul Along and
xi
Mina Tehrani. Finally, and in a special way, I thank my Australian Landlord/lady (Stephen
and Nina) for your passion, all my relatives, friends and neighbours in various places for your
support and contribution in my life from such a humble background. May the Almighty God
bless and reward you all in the name of our Lord Isa Masiya. Amen.
xii
Table of Contents
CHAPTER ONE ............................................................................................................... 1
INTRODUCTION ............................................................................................................ 1
1.1 Background to the Study ................................................................................................................ 2 1.1.1 Importance of public procurement and construction industry .................................................. 5 1.1.2 Importance and challenges of Uganda’s public road construction projects .............................. 7
1.2 Sample road construction projects under investigation for procurement irregularities ............... 8
1.3 Statement of the Problem ............................................................................................................. 10
1.4 Research Aim ................................................................................................................................ 12
1.5 Research objectives ....................................................................................................................... 12
1.6 Significance of the Study .............................................................................................................. 12
1.7 Study scope ................................................................................................................................... 13
1.8 Structure of the thesis ................................................................................................................... 14
CHAPTER TWO ............................................................................................................ 15
THEORETICAL FOUNDATION ................................................................................. 15
2.1 Introduction .................................................................................................................................. 16
2.2 Agency theory, Compliance in public procurement and Project success .................................... 16
2.3 Institutional theory, Compliance in public procurement and Project success ............................ 22
CHAPTER THREE........................................................................................................ 28
LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT ........................... 28
3.1 Introduction` ................................................................................................................................. 29
3.2 Research Model ............................................................................................................................ 29
3.3 Implications of Compliance with Public Procurement Regulatory Framework ......................... 33 3.3.1 Familiarity with regulatory framework and compliance ......................................................... 37 3.3.2 Monitoring activities and compliance ...................................................................................... 40 3.3.3 Professionalism of staff and compliance .................................................................................. 42 3.3.4 Sanctions on staff and compliance............................................................................................ 46 3.3.5 Perceived Inefficiency of public procurement regulatory framework and compliance .......... 49 3.3.6 Contractors’ resistance and compliance .................................................................................. 51
xiii
3.4 Implications of Construction Project success ............................................................................... 52 3.4.1 Compliance with public procurement regulatory framework and Project success ................. 53 3.4.2 Familiarity with public procurement regulatory framework and Project success .................. 55 3.4.3 Monitoring activities and project success ................................................................................. 57 3.4.4 Professionalism of staff and project success ............................................................................. 58 3.4.5 Perceived inefficiency of public procurement regulatory framework and project success ..... 60 3.4.6 Contractors’ resistance and project success ............................................................................. 61 3.4.7 Sanctions on staff and project success ...................................................................................... 62
3.5 Mediation effects and Hypotheses ................................................................................................ 64
3.6 Selection of study variables .......................................................................................................... 68
3.7 Justification for used study variables ........................................................................................... 70
CHAPTER FOUR .......................................................................................................... 74
METHODOLOGY ......................................................................................................... 74
4.1 Introduction .................................................................................................................................. 75
4.2 Research Question ........................................................................................................................ 75
4.3 Literature Review Approach ........................................................................................................ 75
4.4 Research Framework and Approach ........................................................................................... 76 4.4.1 Research Approach .................................................................................................................. 79 4.4.2 Research Design and Justification ............................................................................................ 79
4.5 Measurement Development .......................................................................................................... 80 4.5.1 Questionnaire Design, Justification and Variables .................................................................. 80 4.5.2 Questionnaire Validity and Reliability ..................................................................................... 85
4.5.2.1 Internal Validity .............................................................................................................. 86 4.5.2.2 Face Validity.................................................................................................................... 86 4.5.2.3 Content Validity .............................................................................................................. 86 4.5.2.4 External Validity ............................................................................................................. 86 4.5.2.5 Stability ........................................................................................................................... 87
4.6 Data Collection ............................................................................................................................. 87 4.6.1 Data Collection Method and Questionnaire Justification ........................................................ 87 4.6.2 Data Type and Sources ............................................................................................................. 88 4.6.3 Study Population and Sample .................................................................................................. 88 4.6.4 Study Participants .................................................................................................................... 91 4.6.5 Sample ...................................................................................................................................... 93
4.6.5.1 Sample Size Determination .............................................................................................. 93 4.6.6 Sampling Technique ................................................................................................................. 93
4.7 Ethical Consideration ................................................................................................................... 94
CHAPTER FIVE ............................................................................................................ 96
xiv
DATA ANALYSIS ......................................................................................................... 96
5.1 Introduction .................................................................................................................................. 97
5.2 Data Processing and Analysis ....................................................................................................... 97 5.2.1 Data Preparation ...................................................................................................................... 97
5.3 Adoption and Justification for Using PLS-SEM ........................................................................ 101
5.4 Measurement Model Evaluation ................................................................................................ 103 5.4.1 Validity and Reliability........................................................................................................... 104
5.4.1.1 Reliability ....................................................................................................................... 104 5.4.1.2 Convergent and Discriminant Validity .......................................................................... 105
5.5 Structural Model Evaluation ...................................................................................................... 106 5.5.1 Collinearity Assessment .......................................................................................................... 107 5.5.2 Significance and Relevance of Structural Model Relationships............................................. 108 5.5.3 Coefficient of Determination (R²) ........................................................................................... 108 5.5.4 Effect Size (ƒ²) ......................................................................................................................... 109 5.5.5 Model Fitting .......................................................................................................................... 110
5.6 Mediational Effect ...................................................................................................................... 110
CHAPTER SIX ............................................................................................................. 112
RESULTS INTERPRETATION ................................................................................. 112
6.1 Introduction ................................................................................................................................ 113
6.2 Profile of Respondents and their Organisations ........................................................................ 113
6.3 Composite Reliability.................................................................................................................. 117
6.4 Factor Loadings .......................................................................................................................... 119
6.5 Average Variance Extracted (AVE) ........................................................................................... 120
6.6 Discriminant Validity ................................................................................................................. 122
6.7. Diagnostic Tests ................................................................................................................................ 123 6.7.1 Collinearity Test ..................................................................................................................... 123 6.7.2 Normality Test ........................................................................................................................ 125 6.7.3 Linearity Test ......................................................................................................................... 126 6.7.4 Homogeneity Tests .................................................................................................................. 127
6.8 Analysis of Variance (ANOVA) of Study Variables ................................................................... 128
6.9 Relationship between Study Variables ....................................................................................... 130 6.9.1 Path Coefficients and Significance Level ............................................................................... 130 6.9.2 Mediational Effect Analyses ................................................................................................... 133
6.10 Coefficient of Determination (R2), Effect size (f2) and Model Fit............................................... 147
xv
6.11 Validation of Results ................................................................................................................... 151
6.12 Final Validated Models ............................................................................................................... 152
CHAPTER SEVEN ...................................................................................................... 155
DISCUSSIONS ............................................................................................................. 155
7.1 Introduction ................................................................................................................................ 156
7.2 Compliance Relationships .......................................................................................................... 156 7.2.1 The Relationship between Familiarity with Public Procurement Regulatory Framework and Compliance with Public Procurement Regulatory Framework. ........................................................ 156 7.2.2 The Relationship between Monitoring Activities and Compliance with Public Procurement Regulatory ........................................................................................................................................... 158 7.2.3 The Relationship between Professionalism and Compliance with Public Procurement Regulatory Framework ....................................................................................................................... 159 7.2.4 The Relationship between Sanctions and Compliance with Public Procurement Regulatory Framework .......................................................................................................................................... 161 7.2.5 The Relationship between Perceived Inefficiency of Public Procurement Regulatory Framework and Compliance with Public Procurement Regulatory Framework .............................. 162 7.2.6 The Relationship between Contractors’ Resistance and Compliance with Public Procurement Regulatory Framework ....................................................................................................................... 163
7.3 Project Success Relationships ..................................................................................................... 164 7.3.1 The Relationship between Compliance with Public Procurement Regulatory Framework and Project Success .................................................................................................................................... 164 7.3.2 The Relationship between Familiarity with Public Procurement Regulatory Framework and Project Success .................................................................................................................................... 166 7.3.3 The Relationship between Monitoring Activities and Project Success .................................. 167 7.3.4 The Relationship between Professionalism and Project Success ........................................... 168 7.3.5 The Relationship between Perceived Inefficiency of Public Procurement Regulatory Framework and Project Success ......................................................................................................... 169 7.3.6 The Relationship between Contractors’ Resistance and Project Success .............................. 170 7.3.7 The Relationship between Sanctions and Project Success ..................................................... 171
7.4 Mediation Relationships ............................................................................................................. 172
7.4.1 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Familiarity with Public Procurement Regulatory Framework and Project Success. .............. 172
7.4.2 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Monitoring Activities in Public Road Construction and Project Success ............................ 174 7.4.3 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Professionalism of Staff in Public Road Construction Projects and Project Success .......... 175 7.4.4 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Sanctions in Public Road Construction Projects and Project Success ................................. 176 7.4.5 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Perceived Inefficiency of Public Procurement Regulatory Framework and Project Success. 178 7.4.6 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Contractor’s Resistance to Non-Compliance and Project Success....................................... 178
7.5 Hypotheses Summary ................................................................................................................. 180
xvi
CHAPTER EIGHT ...................................................................................................... 181
STUDY IMPLICATIONS AND CONTRIBUTIONS ................................................. 181
8.1 Introduction ................................................................................................................................ 182
8.2 Theoretical Implication and Contributions ................................................................................ 182
8.3 Managerial Implications and Contributions .............................................................................. 184
8.4 Methodological Contribution ..................................................................................................... 187
8.5 Knowledge Contribution ............................................................................................................ 187
8.6 Practical Contribution ................................................................................................................ 189
CHAPTER NINE ......................................................................................................... 192
CONCLUSIONS AND RECOMMENDATIONS ....................................................... 192
9.1 Introduction ................................................................................................................................ 193
9.2 Compliance with Public Procurement Regulatory Framework ................................................ 193
9.3 Public Road Construction Project Success................................................................................. 195
9.4 Mediational effects ...................................................................................................................... 198
9.5 Recommendations ....................................................................................................................... 200
9.6 Limitations .................................................................................................................................. 204
9.7 Further Research ........................................................................................................................ 206
9.8 Conclusion .................................................................................................................................. 206
REFERENCES ............................................................................................................. 209
APPENDICES .............................................................................................................. 235
xvii
List of tables Table 1.1 Showing Public Sector Procurement Expenditure and Contribution ............................. 6
Table 1.2: Showing stock of paved national roads .................................................................... 8
Table 1.3: Showing sample road construction projects marred by lack of compliance ............... 9
Table 2.1 Theoretical tenets and application of Agency theory .................................................. 21
Table 2.2: Three dimensions of institutional theory. ............................................................... 25
Table: 4.1. Research framework.................................................................................................... 76
Table 4.2 Variable measurement and Questionnaire design ....................................................... 82
Table 4.3 Completed and On-going National Road Construction Projects .................................. 89
Table 4.4 Participants................................................................................................................ 92
Table 4.5: Response rate ........................................................................................................ 94
Table 6.1: Organisations ...................................................................................................... 113
Table 6.2: Education ............................................................................................................ 113
Table 6.3: Professional Training ........................................................................................... 114
Table 6.4: Age ..................................................................................................................... 114
Table 6.5: Title .................................................................................................................... 115
Table 6.6: Gender ................................................................................................................ 115
Table 6.7: Registration with any professional body ............................................................... 116
Table 6.8: Name of registered professional body .................................................................. 116
Table 6.9: Descriptive Statistics for Years in Current Position in the organization and number of employees 117
Table 6.10: Reliability test results .......................................................................................... 118
Table 6.11: Outer Loadings .................................................................................................... 119
Table 6.12: Average Variance Extracted (AVE) ..................................................................... 122
Table 6.13 a: Fornell-Larker Criterion ................................................................................... 122
Table 6.13 b: Cross Loadings ................................................................................................ 122
Table 6.13 c: Heterotrait-Monotrait Ratio (HTMT) ............................................................... 123
Table 6.14 a: Smart-PLS Inner VIF Values ........................................................................... 124
Table 6.14 b: Smart-PLS Outer VIF Values ........................................................................... 124
Table 6.15 a: SPSS Compliance model Coefficientsa results .................................................. 124
Table 6.15 b: SPSS Project success model Coefficientsa results ............................................. 125
xviii
Table 6.16: Statistics for skewness and Kurtosis results .......................................................... 126
Table 6.17 a: Compliance model Regression linearity results ................................................ 127
Table 6.17 b: Project success model Regression linearity results. ........................................... 127
Table 6.18: Levene test of Homogeneity of Variance results................................................... 127
Table 6.19: One-Way ANOVA results ................................................................................... 129
Table 6.20: Path Coefficients ................................................................................................. 133
Table 6.21: Coefficient results for the three steps above ......................................................... 134
Table 6.22: Hierarchical regression results for familiarity, compliance and project success ..... 135
Table 6.23: Compliance Mediating Familiarity and Project Success ....................................... 135
Table 6.24: Coefficient results for the three steps above ......................................................... 136
Table 6.25: Hierarchical regression results for monitoring activities, compliance and project success 137
Table 6.26: Compliance Mediating Monitoring activities and Project Success ........................ 138
Table 6.27: Coefficient results for the three steps above ......................................................... 139
Table 6.28: Hierarchical regression results for professionalism, compliance and project success 139
Table 6.29: Compliance Mediating Professionalism and Project Success ................................ 140
Table 6.30: Coefficient results for the three steps above ......................................................... 141
Table 6.31: Hierarchical regression results for sanctions, compliance and project success ....... 141
Table 6.32: Compliance Mediating Sanctions and Project Success.......................................... 142
Table 6.33: Coefficient results for the three steps above ......................................................... 143
Table 6.34: Coefficient results for the three steps above ......................................................... 144
Table 6.35: Hierarchical regression results for contractors’ resistance to non-compliance, compliance and project success ................................................................................................... 145
Table 6.36: Compliance Mediating Contractors’ Resistance and Project Success .................... 145
Table 6.37: R2, Adjusted R2 and Standardized Root Mean square Residual (SRMR) ............... 148
Table 6.38: Effect size (f2) results........................................................................................... 148
Table 6.39: Total effect .......................................................................................................... 149
Table 6.40: Summary of hypotheses results ............................................................................ 151
xix
List of figures
Figure 2.1: Summarised theoretical foundation linked to literature review................................ 26
Figure 3.1(a) Broad conceptual model linking compliance factors with regulatory framework and project success ....................................................................................................................... 31
Figure 3.1(b) Conceptual model showing selected compliance and project success factors....... 31
Figure 3.1(c) Final conceptual model of compliance and Project Success with Respective Measurement Indicators ................................................................................................................ 32
Figure 3.2: Mediation illustration ................................................................................................. 65
Figure 5.1: Types of construct measurement .......................................................................... 104
Figure 6.1: Compliance Mediating Familiarity and Project Success ............................................. 136
Figure 6.2: Compliance Mediating Monitoring activities and Project Success ........................ 138
Figure 6.3: Compliance Mediating Professionalism and Project Success ................................ 140
Figure 6.4: Compliance Mediating Sanctions and Project Success.......................................... 143
Figure 6.5: Compliance Mediating Contractors’ Resistance and Project Success .................... 146
Figure 6.6: Final Structural and Measurement model (PLS-Algorithms) ................................ 150
Figure 6.7: Final validated Structural model (Bootstrapping output)....................................... 151
Figure 6.8: Combined Validated Model ................................................................................ 153
Figure 6.8.1 Compliance Validated Model............................................................................... 154
Figure 6.8.2 Project Success Validated Model ......................................................................... 154
xx
List of Abbreviations ACCU Anti-corruption coalition Uganda
AG Auditor General
AVE Average Variance Extracted
APRM African Peer Review Mechanism
ARB Architecture Registration Board
AU$ Australian Dollar
ERB Engineering Registration Board
ERP Enterprise Resource Planning
EU European Union
Fig Figure
GDP Gross Domestic Product
HREC Human Resource Ethics Committee
HTMT Heterotrait-Monotrait Ratio
IPPU Institute of Procurement Professional Uganda
IGG Inspector General of Government
KSH Kenyan Shillings
MoWT Ministry of Works and Transport
MoFEP&D Ministry of Finance Economic Planning and Development
NDP National Development Plan
OECD Organization for Economic Cooperation and Development
PPDA Public Procurement and Disposal of Public Assents Authority
PPDA Act Public Procurement and Disposal of Public Assents Act 2003
PDEs Procuring and Disposal Entities
PLS-SEM Partial Least Square-Structural Equation Modelling
PSRRC Public Service Review and Reorganization Commission
RDC Resident District Commissioner
SPSS24 Statistical Package for Social Scientist version 24
SRB Surveyor’s Registration Board
SRMR Standardized Root Mean Square Residual
xxi
TSH Tanzanian Shillings
UACE Uganda Association of Consulting Engineers
UGX Uganda Shillings
UIPE Uganda Institute of Professional Engineers
UNABCEC Uganda National Association of Building and Civil Engineering Contractors
UNRA Uganda National Roads Authority
URF Uganda Road Fund
USA United States of America
US$ United States Dollar
UK Unites Kingdom
VIF Variance Inflation Factor
1
CHAPTER ONE INTRODUCTION
2
1.1 Background to the Study The introduction chapter identifies the study background, problem statement with the
research question, research aim, objectives, study scope, significance and the study structure.
For purposes of this thesis, the public procurement regulatory framework is a collective term
for regulations, laws, rules, policies, procedures, directives and formal instructions governing
public road construction projects.
For decades, Uganda’s public entities have been known for poor performance and
lack of compliance with the public procurement regulatory framework. This has caused poor
utilisation of resources and personnel management etc. Because of these inefficiencies, in
1989 the Ugandan government initiated a public service review and reorganisation
commission (PSRRC) to examine and suggest recommendations for improving service
delivery, transparency, efficiency and effectiveness in the whole framework (Kakwezi and
Nyeko, 2010). The review subsequently established public agencies for example; Public
Procurement and Disposal of Public Asset Authority (PPDA), Uganda Revenue Authority
(URA), National Agricultural Research Organization (NARO) among others aimed at
improving service delivery. Improving service delivery requires complying with regulatory
framework and since government on behalf of the public spends public funds, accountability
and transparency are important (Basheka and Bisangabasaija, 2010, Wittig, 1999).
Complying with regulatory framework is important because it plays a vital role in delivering
construction projects successfully (Zadawa et al., 2018a, Signor et al., 2016b). The current
Ugandan public procurement regulatory framework came into existence on February 23,
2003 (Tukamuhabwa, 2012, PPDA Authority, 2003). The Ugandan government and
International Development Partners have worked together since 2000 to reform public
procurement system resulting into PPDA Act 2003, aiming at strengthening public
procurement. The Act established Public Procurement and Disposal of Public Asset
Authority (PPDA) to regulate and oversee public procurement (PPDA Authority, 2003). Prior
to PPDA Act 2003, public procurement was conducted under 1990 Statute where
procurement was undertaken by the government central purchasing corporation with parallel
police and military tender boards being responsible for their respective procurement
activities. The government central purchasing corporation replaced Central Purchasing
Organisation (CPO) established in 1977 that was inefficient and unprofessional (Agaba and
Shipman, 2007).
3
Public procurement is a contractual arrangement between government and private
sector to deliver infrastructure, goods and services (Frøystad et al., 2010). It is the purchasing,
hiring or obtaining by any other contractual means of goods, works and services by public
sector (Appelt and Galindo-Rueda, 2016). Public procurement is different from private
procurement because public procurement economic results are measured against complex
and long-term criteria including economy, accountability, non-discrimination and respect for
international obligation. It is subjected to all countries and requires enacting regulation to
protect public interest unlike private procurement (Odhiambo and Kamau, 2003).
Accordingly, public procurement in Uganda’s construction sectors is governed and regulated
by PPDA Act No 1 of 2003, Regulations 70 of 2003, Local Government (Amendment) Act
No 2 of 2006 (February 2006) and Regulations S1 No 39 of 2006 (August 2006), Standard
Biding Documents (SBD) and PPDA guidelines (PPDA Authority, 2008). However, public
procurement in the construction sector is vulnerable to procurement irregularities affecting
both developed and developing economies (Chan and Owusu, 2017). These irregularities, in
the form of fraudulent practices account for failed public construction projects (Shan et al.,
2020a, Zadawa et al., 2018a, Gambo et al., 2016, Signor et al., 2016b). Interestingly,
construction sectors have a significant impact on the development of these economies (Shan
et al., 2020b, Love et al., 2019, Darko et al., 2017, Shan et al., 2017). This is why a strong
and effective regulatory framework is important to govern public procurement and meet
government objectives especially for complex construction sector including road
construction projects.
The construction sector plays a crucial role in accelerating economic development of
nations worldwide (Sinesilassie et al., 2019, Munyasya and Chileshe, 2018, Zadawa et al.,
2018a, Love et al., 2018b, Shaban, 2008). However, the sector is dynamic with increasing
uncertainties revolving around technology, budgets and process that complicates successful
implementation of construction projects (Sinesilassie et al., 2019, Jari and Bhangale, 2013).
Particularly, delivering transport construction projects within estimated budget is still a
challenge among governments worldwide (Love et al., 2019). The success of construction
projects is tagged on a number of factors that need careful attention in order to meet intended
goals. For example, these projects can only be successful if they meet construction
stakeholders’ expectations as well as achieving intended goals (Jari and Bhangale, 2013).
The common expectations and goals determining successful construction sector include but
are not limited to cost, time and quality (Hussain et al., 2019, Zadawa et al., 2018a, Kog and
4
Loh, 2011). Considering a regulatory framework in the construction industry is important.
Interestingly, a regulatory framework is a significant factor for the successful construction
sector (Tabish and Jha, 2011). Despite its significance, a public procurement regulatory
framework in construction industry is complex because it involves human resource,
equipment, materials, environment, political factors and many stakeholders requiring careful
attention to enhance compliance and successful implementation. Particularly, construction
projects are complex since they involve various participants with varying interests that affect
their successful implementation (Hussain et al., 2019, Sinesilassie et al., 2019, Lapidus and
Yves, 2018, Shaban, 2008). Furthermore, the construction industry is complicated and
requires highly skilled and competent staff to encounter growing challenges (Hussain et al.,
2019, Love et al., 2002). With dynamism and complexity of construction projects,
establishing and understanding success factors suitable for implementing these projects
would ensure an effective construction sector by eradicating impeding challenges (Jari and
Bhangale, 2013).
A lack of compliance pose serious challenges in the procurement of construction
projects (Zadawa et al., 2018a, Abdullahi et al., 2017). According to a 2008 PPDA
consultative workshop with stakeholders in public construction sector, major challenges
identified include lack of clear national construction standards and regulations (PPDA
Authority, 2008). These challenges create uncertainty in regulatory frameworks governing
the construction sector causing, lack of compliance in project implementation. Specifically,
weaknesses challenging public procurement include; poor contract management, record
keeping, tender evaluation, confidentiality, rational use of prequalification lists and dispute
resolution mechanism (PPDA Authority, 2009b). Such inefficient and ineffective structures
promote lack of compliance with the procurement regulatory framework, costing
government million dollars and poor service delivery (Zadawa et al., 2018b, Ntayi and Eyaa,
2009). The construction industry globally loses significant funds annually. For example
US$340 billion (AU$ 462.4B) is lost worldwide through fraudulent practices (Sohail and
Cavill, 2008). These are compliance and projects implementation challenges equally
affecting Uganda’s public road construction projects causing late project delivery,
substandard works and over budget. Convincingly, a construction project is successful if it is
completed within time, budget and according to specifications (White and Fortune, 2002).
Noteworthy, according to His Excellency the President of Uganda, road construction projects
are failing to meet these key success indicators (Red Pepper, 2018).
5
Uganda’s road network consists of four groups namely; national roads, district roads,
urban roads and community access roads. The research scope of this thesis was limited to
the implementation stage of national roads. The national roads are grouped into completed,
on-going and future construction projects. This dissertation was further limited to completed
and on-going road construction projects rather than those that are under pre-planning stages.
Furthermore, Uganda’s national roads are managed and supervised between other public
bodies including; Ministry of Works and Transport (MoWT), Uganda National Roads
Authority (UNRA), Uganda Road Fund (URF) and Public Procurement and Disposal of
Public Assets Authority (PPDA). Basing on the public service review and reorganization
commission, these bodies were established under different Public Acts with respective
mandates. For example; supervising, monitoring, developing and maintain national roads in
addition to managing ferries linking the national road network and axle control. All of these
aimed at strengthening efficiency in service delivery (Ministry of Works and Transport,
2014). However, balancing between transport sector importance and its challenges requires
a sound and effective regulatory framework to achieve government goals. Achieving
government goals would guarantee justification for increased budget allocation and public
confidence in government expenditure. A lack of compliance with a public procurement
regulatory framework and unsuccessful public road construction projects impairs achieving
government goals. The following section outlines importance of public procurement and
construction industry.
1.1.1 Importance of public procurement and construction industry
Public procurement is a macro-economic tool relied upon by most governments as a
backbone for economic development (Davis et al., 2016, Peprah, 2015). Particularly,
procurement of construction projects is key in the construction industry (Sinesilassie et al.,
2019, Zadawa et al., 2018b, Zadawa et al., 2018a). This is because large funds are committed
to public procurement especially in works (Czarnitzki et al., 2018, Chan and Owusu, 2017,
Appelt and Galindo-Rueda, 2016, Signor et al., 2016b). Interestingly, for public procurement
to achieve economic development, effective and efficient management is paramount Obicci
(2015), Mahmood (2010) because an ailing economy can use public procurement for
economic development and stabilisation (Thai, 2001, Arrowsmith, 1998). Of note, public
procurement is increasingly promoting innovative activities (Czarnitzki et al., 2018).
However, if public procurement is mishandled, its contribution may be catastrophic to
economic development because public procurement is a powerful driver in sustaining
6
economies (Cheng et al., 2018, Abdullahi et al., 2017). Table 1.1 presents information on
public procurement across sectors based on contribution and expenditure in terms of Gross
Domestic Product (GDP). This shows how governments globally spend more funds in public
procurement.
Table 1.1 Showing Public Sector Procurement Expenditure and Contribution
Item/procurement Expenditure (%GDP) Contribution (GDP) Source
World procurement 15-18.42 Mahmood (2010), (Decarolis
et al., 2018)
Global average 12-20 Frøystad et al. (2010)
Global construction AU$ 74.352b Sohail and Cavill (2008)
Australia building &
construction
7.9 AU$ 99.4b Australian Procurement &
Construction Council (2013)
Developed countries 5-7 (Sohail and Cavill, 2008,
Kenny, 2007, Rizk et al., 2018)
Developing countries 2-3 (9-13)% Sohail and Cavill (2008),
Oluka and Basheka (2014)
Industrialized countries 5-8 10% (Navon, 2005, Trionfetti,
2000, Shaban, 2008)
OECD countries 12 (Czarnitzki et al., 2018, Appelt
and Galindo-Rueda, 2016)
European Union 17 (Turley and Perera, 2014,
Wittig, 1999)
South Africa 29 (Turley and Perera, 2014,
Wittig, 1999)
Middle East & Africa 9-13 Odhiambo and Kamau (2003)
USA Federal AU$ 272b Pegnato (2003)
Russia Federal 40 Fradkov (2004)
Uganda 70 Akech (2004)
Uganda construction
industry
50.2 13.7% Ministry of Finance (2013)
Road sector 2-3.5 Estache (2006)
Kenya 60 Akech (2004)
7
Tanzania 70 Mwakibinga and Buvik (2013)
Nigeria 1.4% Abdullahi et al. (2017)
The next section explains importance and challenges in Uganda’s road construction subsector.
1.1.2 Importance and challenges of Uganda’s public road construction projects
Having reviewed procurement expenditure in relationship to GDP, this section
investigates Uganda’s transport subsector in particular. The transport sector plays a crucial
role in Uganda’s economic development and it is prioritised in the National Development
Plan (NDP) (Ministry of Works and Transport, 2014). The notion of criticality is supported
by reports attaching the transport sector’s importance to economic development (Love et al.,
2019, Munyasya and Chileshe, 2018, Love et al., 2018b, Shan et al., 2017, Amann et al.,
2016). An efficient transport system enables lower production costs, timely service delivery,
access to markets, boosting tourism, promoting imports and exports. Indeed, efficient
transport infrastructure is a hallmark for a well-functioning economy (Love et al., 2017). The
road sector is a core mode of transport with 90% of cargo freight and passengers (Ministry
of Works and Transport, 2014). Despite its core importance, Uganda’s road subsector is
facing underfunding and increasing construction and maintenance costs (Uganda National
Road Authority, 2018). For example, in 2012/13 cost increased by 25% and in 2013/14 by
41%. Sharply rising road construction costs in Uganda are worsened by restrictions of
companies outside African Caribbean & Pacific (ACP) region to bid for European Union
(EU) funded projects (Ministry of Works & Transport, 2013).
The transport and communication subsector contributed 5.3% to total GDP in
2013/2014 and 5.1% in 2012/2013 and its budget allocation increased by 16% 2014/2015 and
17% in 2015/2016 (Ministry of Works and Transport, 2015). Further, in budgetary terms, the
road sector absorbs substantial capital compared to other sectors. For example in 2008/2009,
budget was increased from UGX (400million-1.6trillion) (AU$ 0.152M-608M) (Cornish and
Mugova, 2014, Ministry of works and Transport, 2012). While road maintenance budget
increased from UGX (158.577-181.87) billion (AU$60.259-69.111M) in financial Year (FY)
2007/2008 and FY2012/2013 (Uganda National Roads Authority, 2013, Ministry of Works
& Transport, 2013). Before data collection in Uganda, the national road network was
21,000km consisting of 3,981km (19%) paved and 17,019km (81%) unpaved roads as at June
2015 (Ministry of Works and Transport, 2015). However, according to financial year (FY)
2017/2018, the stock of national roads is 20,544Km (4,551 paved and 15,993 unpaved). This
8
represents a 22.2% paved against 77.8% un paved roads (Uganda National Road Authority,
2018). Accordingly, Table 1.2 shows accumulating paved roads from FY2007/2008 to
2017/2018.
Table 1.2: Showing stock of paved national roads
Financial year Paved roads
Annual increase (KM) Stock (KM)
2007/08 2,875.6
2008/09 159.0 3,034.6
2009/10 165.4 3,200.0
2010/11 64.1 3,264.1
2011/12 53.0 3,317.1
2012/13 172.5 3,489.6
2013/14 305.2 3,795
2014/15 186 3,981
2015/16 238 4,157
2016/17 100 4,257
2017/18 294 4,551
Source: (Uganda National Road Authority, 2018, Ministry of Works and Transport, 2015)
1.2 Sample road construction projects under investigation for procurement
irregularities
Procurement irregularities are a consequence of unprofessional behaviours by public
procurement stakeholders (Basheka and Mugabira, 2008). They depict a lack of compliance
with their respective public procurement regulatory framework (Kingsford Owusu and Chan,
2018, Chan and Owusu, 2017, PPDA Authority, 2009b, Kling, 2008). Media reports show
increasing cases of public procurement irregularities (New Vision, 4th August 2017, Red
Pepper, 3rd November 2016, Daily Monitor, 24th October 2016). These irregularities cause
public road construction projects to incur significant losses (New Vision, 28th July 2016).
9
Despite appeals by Uganda National Roads Authority’s (UNRA) executive director for
timely and quality road construction projects, UNRA is accused of failing to meet its
obligations. For example, irregularities have led to unsuccessful implementation of public
road construction projects (Red Pepper, 2018, New Vision, 4th August 2017). This has
attracted public attention with the Ugandan parliament commencing investigations on 28 on-
going road construction projects (Red Pepper, 21st October 2016). Examples of public road
construction projects reportedly facing procurement irregularities are shown in Table 1.3.
Table 1.3: Showing sample road construction projects marred by lack of compliance
Road Construction
Project
Amount Problem Reference
Hima-Katunguru
(58KM) and Kanoni-
Ssembabule-Villa
Maria (110KM
UGX22 billion
(AU$ 122.36M)
Queried and being
investigated on lack of
compliance.
(New Vision, 20th
October 2016).
Mukono-Katosi-
Nyenga (74KM)
UGX24.7 billion
(AU$9.386M)
Funds lost and project
delayed.
(New Vision, 28th
July 2016, New
Vision, 4th August
2017).
Kampala-Entebbe
Expressway (51KM
UGX55 billion
(AU$20.9M)
Inflated cost due to lack
of compliance with road
specifications and
delayed completion.
(Daily Monitor, 5th
November 2016,
New Vision, 4th
August 2017).
Musita-Lumino-
Busia-Majanji
(105KM)
Not specified Delayed completion. (Daily Monitor,
29th August 2016)
Busega-Masaka
(51Km)
Not specified Over 52% contract cost
variation and delayed
completion by three
years.
(Uganda National
Road Authority,
2014)
10
Kanungu–Kihiihi–
Ishasha–Rukungiri
road (78.5Km).
Not specified Delayed completion (Red Pepper,
2018)
These examples show lack of compliance with the public procurement regulatory
framework affecting successful implementation of public road construction projects. They
are costing taxpayers significant funds and with schedule overruns, altogether failing
government goals, inconveniencing business communities and affecting economic
development. Hence, this leads to problem statement.
1.3 Statement of the Problem
A lack of compliance is persistently reported in public sector procurement and
particularly in the construction sector, leading to extra cost and time wastage (Kingsford
Owusu and Chan, 2018, Zadawa et al., 2018a, Abdul-Rahman, 1995). Surprisingly, a lack of
compliance costs the construction sector US$340B (AU$ 462.4B) (Shan et al., 2020b, Rizk
et al., 2018, Shan et al., 2017). A lack of compliance include; poor implementation plans,
substandard work, high contract price variations and schedule overruns. These factors have
cost Uganda US$258.6 million (AU$ 351.696M) annually (Agaba and Shipman, 2007).
These compliance issues affect successful implementation of public road construction
projects (Red Pepper, 2018, Love et al., 2016a, Kakitahi et al., 2013). For example, deviating
from regulatory frameworks affects implementation of construction projects (Stansbury,
2003). Convincingly, Golden and Picci (2006) highlighted that an increasing lack of
compliance in the construction industry has resulted in significant loss of funds and failed
construction projects. In Uganda, reports show that compliance with the regulatory
framework in public procurement is reducing despite efforts to enforce improvement
strategies through capacity building (PPDA Authority, 2012, Tukamuhabwa, 2012).
Particularly, a lack of compliance occurs frequently under contract award, contract
implementation and record keeping (Bowen et al., 2012). This is equally affecting Uganda’s
public road subsector that is heavily donor funded. Reports arising from Public Procurement
and Disposal of Public Assets Authority, Inspector General of Government, Attorney General
and the Media provided the catalyst for this research project as they identified a lack of
compliance with a regulatory framework, they suggested a significant funds loss and pointed
to unsuccessful construction projects.
11
Whenever a lack of compliance is mentioned, people think of unethical procurement
officials Ntayi et al. (2013) but attach less importance to explaining why this occurs (Ntayi
et al., 2010b). Recent reports by the PPDA authority document a lack of compliance with
public procurement regulatory frameworks amongst Procuring and Disposal Entities (PDEs)
hampering successful implementation of many projects (PPDA Authority, 2007). Since the
PPDA Act 2003 was enacted, several reforms have taken place with the current PPDA
amendments 2014 all aiming at strengthening public procurement regulatory framework to
achieve value for money. Despite these, procurement officials still do what they find
convenient. This action affects successful implementation of public road construction
projects in Uganda. For example, cost variations and delayed completion in road construction
projects affected successful implementation of these projects that in turn affect performance
of public sector (Odeck, 2004). Specific examples listed in Table 1.3 underpin Uganda’s
unsuccessful road construction projects depicting lack of compliance (Red Pepper, 2018,
New Vision, 20th October 2016).
Despite efforts by the Ugandan government and development partners to improve
public procurement performance, a lack of compliance, substandard works and contract cost
variations persist, leading to unsuccessful implementation of public road construction
projects (New Vision, 4th August 2017, Daily Monitor, 5th November 2016). Noteworthy,
pertinent reports show that over UGX22 billion (AU$8.36M) was paid to Chinese ghost
contractors Red Pepper (3rd November 2016). In addition, UGX577 billion (AU$219.26M)
was paid to suspected ghost claimants in dubious transactions on land acquisition for various
road projects where UGX49 billion (AU$18.62M) was lost and another UGX562 billion
(AU$213.56M) funds was paid without a satisfying reason (Daily Monitor, 24th October
2016). A Report by African Peer Review Mechanism Country review (APRM) in 2009,
identified a lack of compliance costs Uganda over US$184 billion (AU$ 250.24B) annually,
while Anti-Corruption Coalition Uganda (ACCU) put the figure at UGX200 billion (AU$
76M) annually (Eyaa and Oluka, 2011). Similarly, a lack of compliance accounts for
unsuccessful large construction projects in Uganda. For example, the World Bank funded
Bujagali hydroelectricity project worthy US$550 million (AU$ 748M) was suspended for
wrongly awarding a contract (Prayas Energy group, 2002).
Previous studies such as those by Mwakibinga and Buvik (2013), Eyaa and Oluka
(2011) attempted to determine compliance factors in public procurement, other studies
12
considered project success factors for the construction industry (Hussain et al., 2019, Tayeh
et al., 2018, Love et al., 2015b, Langston, 2014, Shaban, 2008). However, less attention has
been placed on the economically dependable public road construction subsector (Amann et
al., 2016). Additionally, few of the studies focusing on the public road construction subsector,
when they did they hinged on only a few indicators (Ameyaw et al., 2017, Love et al., 2016a,
White and Fortune, 2002). However, with the uniqueness and complexity in operations of
road construction, this subsector requires a more elaborate study involving expected
compliance and success factors from different perspectives. Hence, with literature evidence
on anomalies facing public road project implementation, there exists a call for research to
establish factors affecting compliance with public procurement regulatory framework and
successful implementation of Uganda’s public road construction projects (Eyaa and Oluka,
2011). The Research Question enhanced the study: What factors affect compliance in
performance of public road construction projects? This leads to the research aim and
objectives of this dissertation.
1.4 Research Aim
This dissertation aims to establish factors responsible for compliance with the public
procurement regulatory framework and successful implementation of public road
construction projects in Uganda.
1.5 Research objectives
To achieve this aim, three specific research objectives are;
I. To investigate what compliance factors are and how these factors influence
compliance with the public procurement regulatory framework.
II. To ascertain how compliance with the public procurement regulatory framework and
compliance factors influence successful implementation of public road construction
projects.
III. To evaluate the mediating role of compliance with the public procurement regulatory framework in successful implementation of public road construction projects.
1.6 Significance of the Study
The public road subsector is the backbone for economic development of a nation as it
accounts for movement of all business forms. Failure in road construction projects implies
economic decline. This dissertation establishes significant compliance and success factors in
13
implementing public road construction projects. Established significant factors are the
cornerstone for successful implementation of future public road construction projects.
Complying with public procurement regulatory framework is important in successful
implementation of public road construction projects. Significant compliance and project
success factors would ensure meeting government objectives, achieving value for money and
steering economic development. This is possible when these projects are implemented within
time, budget and according to project specifications.
The study in this thesis is important because it establishes significant factors
enhancing compliance with the public procurement regulatory framework and
successful implementation of public road construction projects.
The research findings offer the opportunity for government to identify areas for
performance improvements and choose appropriate factors from recommendations
herein.
This research enables Procuring and Disposal Entities (PDEs) to implement public
road construction projects successfully in a transparent manner by learning from study
results.
This research contributes to existing body of knowledge and forms a basis for further
research especially exploring compliance and project success factors as well as
mediational effects in the construction industry.
The researcher gained from the study by acquiring research knowledge, skills and
accomplishing a PhD.
1.7 Study scope
Public procurement in construction projects is broad and given the PhD time
constraints coupled with complexity of public road construction projects Tayeh et al. (2018),
Chan and Owusu (2017), this thesis was limited to the implementation stage of national
public road construction projects in Uganda including completed and on-going road
construction projects. Particularly, the study was limited to investigating which factors were
significant in ensuring compliance with the public procurement regulatory framework and
successful implementation of public road construction projects in Uganda (Gelderman et al.,
2017, He et al., 2015). This research further investigates the mediating role of compliance
with the public procurement regulatory framework in successful implementation of public
road construction projects. Uganda was considered since its public road construction projects
14
are majorly donor funded and there are persistent procurement irregularities reported (Red
Pepper, 2018, PPDA Authority, 2014). The finding would be equally important globally
given similarities in public sector procurement (Kling, 2008, Verdeaux, 2003).
1.8 Structure of the thesis Chapter one explains the public procurement regulatory framework background, the
road construction sector, the importance of the construction sector and public road
construction sub-sector, challenges facing Uganda’s road subsector with sample cases under
investigations. The chapter further provides the problem statement, research aim, objectives,
study scope, significance, and structure of the thesis. Chapter two explains the theoretical
foundation supporting research study linked to study variables. Agency and institution
theories are discussed to extract and support the study variables. Chapter three details the
literature review from peer reviewed journals and public documents, hypotheses
development, research model, selection and justification of using study variables. Chapter
four presents the research methodology that addresses the research question including;
research question and hypotheses, literature review approach, research framework, research
approach, research design and justification, measurement development, data collection and
ethics consideration.
Chapter five presents detailed data analysis including data processing and analysis,
adoption and justification for using Partial Least Square Structural Equation Modeling (PLS-
SEM), measurement model evaluation, and structural model evaluation and mediation effects
determination. Chapter six presents results interpretation including descriptive statistics,
composite reliability, factor loadings, Average Variance Extracted (AVE), discriminant
validity, diagnostic tests, Analysis of Variance (ANOVA), relationship between study
variable, model estimation and fitting, validation of results and final validated model. Chapter
seven provides discussion of results that includes; compliance relationships, project success
relationships, mediation effects and summary of hypotheses. The discussions of results are
in line with nineteen hypotheses developed in chapter three. Chapter eight presents study
implications and contributions including; theoretical and managerial implications,
methodological, knowledge and practical contributions. Chapter nine presents conclusions
and recommendations including limitations and areas for further research. The following
chapter discusses theories underpinning study factors.
15
CHAPTER TWO THEORETICAL FOUNDATION
16
2.1 Introduction
Chapter two explains the thesis’s theoretical foundation that supports the study
variables. Theory drives a research problem from causal factors and explores possible
governance mechanism to solve the problem. The move to use a theoretical approach was
inevitable since sound and relevant research is built from theoretical foundation (Mentzer et
al., 2008). Likewise, a theory is good in grounding knowledge (Boer et al., 2014). The
research focus was to formulate knowledge and test relationships Pitariu and Ployhart (2010),
agency and institutional theories were selected to enhance the research and expose several
study variables described below. These theories were selected because previous studies had
used them to underpin compliance with regulatory framework (Zadawa et al., 2018b). In
addition, public road construction projects are the government’s mandate. This mandate
controls the implementation process through institutions informed by regulatory framework.
Hence, institutional theory is paramount in legitimacy of stakeholders’ management given an
existing phenomenon to instill value and shaping the organisations (Brammer et al., 2012,
Zsidisin* et al., 2005). In addition, these projects are implemented by a team acting on behalf
of government that clearly mimic Principal-Agent relationship. Finally, these theories are
consistently and widely applied to enhance research across different fields (Scaraboto and
Fischer, 2012, Brammer et al., 2012, Hillebrand et al., 2011, Bruton et al., 2010, Zsidisin and
Ellram, 2003, Reichelstein, 1992).
Notably, public road construction projects in Uganda are implemented according to
the Public Procurement Act 2003 since these are procurement of works. Hence, the three
isomorphism of institutional theory (Regulatory, Normative and Cultural-Cognitive) and
principal-agency theory are deemed fit to enhance compliance and successful implementation
of public road construction projects. A theory approach was used to establish study variables
as a guiding foundation in literature review as demonstrated in section 2.2 and 2.3.
2.2 Agency theory, Compliance in public procurement and Project success
The background to agency theory is linked to information economics emphasising
risk sharing between contractual parties for efficient contracts in different environment
(Zsidisin and Ellram, 2003). Principal-Agent theory is a contract theory used to evaluate
public procurement contracts (Zadawa et al., 2018b). For example, in this dissertation,
implementing public road construction projects is a contract between the Ugandan
government and a project implementation team. Ideally, agency theory specifies the
17
relationship between the principal and the agent through a contract whereby the agent is
delegated to accomplish the principal’s tasks (Saam, 2007). Convincingly, agency theory
offers insights into information systems, outcome uncertainty, incentives, risk and power
asymmetry (Saam, 2007, Eisenhardt, 1989). In public procurement of construction projects,
information asymmetry arises due to a principal’s failure to monitor an agent’s competences
(Saam, 2007, Zsidisin and Ellram, 2003). In addition, information asymmetry results in a lack
of professionalism in the administration of a principal-agent contract referred to as
opportunistic behaviour (Um and Kim, 2018, Müller, 2009). The attitude jeopardises
compliance and project implementation (Um and Kim, 2018). A lack of information and
knowledge during public road implementation incapacitates a government’s ability to
monitor and assess staff performance. Such monitoring inability permits opportunistic
behavior in combination with organizational complexity and presents a failing to meet targets
(Worsham et al., 1997). This identifies that staff knowledge and monitoring are vital during
public road implementation since it influences compliance with project requirements.
Relatedly, staff use their own unprofessional behavior to maximize benefits for themselves;
this costs the government consequently affecting successful project implementation. This
unprofessional behavior has been attributed to goal conflict and differing risk perception
(Wright et al., 2001). Wright and colleagues suggest that a team’s expertise through
professionalism in executing duties can influence compliance and promote successful
implementation of public road construction projects (Wright et al., 2001).
When the principal delegates authority to its agent and because of self-seeking
behaviour, problems arise in meeting goals especially when the principal lacks information
in verifying the agent’s actual performance (Um and Kim, 2018). Differing attitudes of the
principal and agent in risk sharing associated with meeting contractual goals complicates
matters. It is the basis of agency theory that advocates for the principal to invest in
information systems, monitoring agent activities and countering opportunistic behaviour
(Saam, 2007, Eisenhardt, 1989). The principal is encouraged to invest in agent capabilities
through training to seal any incompetence gap during project implementation. Hence, the
government is encouraged to equip road construction team with necessary skills through
training workshops. These training workshops enable an understanding and compliance with
public procurement regulatory framework governing different procurement contacts. This
includes the implementation of public road construction projects (Agaba and Shipman, 2007).
18
Such investment would promote staff professionalism and familiarity underpinned in agency
theory.
The government undertakes public road construction projects on the public’s behalf
and different players in respective entities implement these projects. This process calls on the
government’s legal authority to influence road construction team to comply with its interest
(Heath and Norman, 2004). Such influence is enforced through sanctioning stakeholders to
ensure compliance with a public procurement regulatory framework and successful
implementation of public road construction projects. Uganda’s public procurement legal
power is derived from the PPDA Act 2003, Local government Act 2006 and Public Finance
Act 2003 on performing different procurement contracts. Accordingly, agency theory is
widely applied to influence management strategies by eradicating unprofessional behavior
(Um and Kim, 2018, Donaldson and Davis, 1991). Enforcing sanctions to influence road
construction staff is inevitable because humans being are rational, self-seeking and risk
averse (Mwakibinga and Buvik, 2013, Saam, 2007, Zsidisin and Ellram, 2003, Wright et al.,
2001). These human elements challenge successful implementation of public road
construction projects and government’s goals.
Self-seeking attitude is a major cause of teamwork failures because the attitude
undermines staff professionalism in contract implementation. This attitude has caused many
projects and their concomitant objectives to fail (Um and Kim, 2018). Since public road
construction projects bring different stakeholders together to accomplish common goal, such
attitude hampers government goals by failing to implement these projects. Furthermore,
information asymmetry causes project implementation problems because the government
contracts the road implementation team without knowing their potential capabilities. This
arises from moral hazard and adverse selection of staff due to hidden information or
misrepresentation because the government lacks complete information on staff
professionalism and familiarity embedded in qualifications, skills and competencies (Saam,
2007). Similarly, goal conflict increases cost in agency theory when the principal strives to
bring order in attaining goals. Accordingly, government incurs costs for ensuring compliance
and successful implementation of public road construction projects. For example, the
government may increase governance mechanism, pursuing court cases, retendering, and
compensations and rectifying substandard works with the aim of meeting goals.
19
Evidence shows that agency theory aims to minimise cost in the principal-agent
relationship (Hillier et al., 2011, Zsidisin and Ellram, 2003, Wright et al., 2001).
Convincingly, agency theory is well known for managing risks across purchasing
organisations when implementing various projects (Zsidisin and Ellram, 2003). The theory
is equally vibrant to guide government in implementing public road construction projects
through minimum costs because the theory helps in leveraging risks (Leland, 1998). In
addition, agency theory is prominent in successful designing of outsourcing transport
contracts by reducing relationship risks (Logan, 2000). Ideally, a road implementation team’s
compliance with a public procurement regulatory framework would ensure the projects are
implemented according to set requirements and in line with government goals. This is crucial
because the implementation team plays a relationship role to successfully implement public
road construction projects and meet government’s objectives (Donahue, 1989). However,
through delegation of authority a gap between the government and the road implementation
team is created because of conflicting interest and opportunistic behaviour that hampers
compliance and successful implementation of projects. Such a gap and attitude can be
rectified through controlling, monitoring and sanctioning staff (Mwakibinga and Buvik,
2013, Tracey and Johannesson, 2008, Saam, 2007).
Furthermore, the theory is predominant in establishing governance models driven by
goal conflict and interest divergence between the principal and the agent who are viewed as
utility maximisers (Davis et al., 1997). This is attributed to individual interest where each
strives to maximise gains at the expense of the other. Lack of compliance would arises when
there is a conflict of interest between the government and public road implementation team
in achieving goals. To ensure compliance in project implementation and goal achievement,
sanctions are inevitable (Obanda, 2010). Convincingly, compliance with a regulatory
framework is based on certainty and severity of sanctions (Gelderman et al., 2010, Sutinen
and Kuperan, 1999). Furthermore, Sutinen and Kuperan (1999) contends that compliance is
affected by illegal behaviour imbedded in professionalism and measured through unethical
conduct of staff charged with implementation of public road projects. Sutinen and Kuperan
(1999) adds that the agent is controlled through monitoring, surveillance and enforcement
mechanisms. These control mechanisms would equally enable the government to
successfully implement public road construction projects as supported by various scholars
(Mwakibinga and Buvik, 2013, Davis et al., 1997, Donaldson and Davis, 1991). In addition,
the government should monitors staff compliance with project requirements aimed at value
20
for money through cost reduction (Robinson and Scott, 2009). This is worthy emphasising
since road implementation team manipulate government and pursue individual interests that
cost the government (Saam, 2007, Brown and Potoski, 2003, Ross, 1973).
Reviewing agency theory from a supply chain management perspective, information
sharing, incentive alignment and trust are important (Fayezi et al., 2012). These aspects are
equally important in implementing complex public road construction projects involving
multiple stakeholders, allowing a government to meet project goals. A lack of compliance
manifested through a conflict of interest in public road construction projects is costs both the
primary stakeholders, the government and its taxpayer (New Vision, 20th October 2016, New
Vision, 28th July 2016). Accordingly, to enforce compliance, Kauppi and van Raaij (2015)
suggested monitoring, training and sanctioning an agent to achieve the principal’s objectives.
Monitoring enables a government to measure and control staff behaviour to enhance
compliance and successfully implement road construction projects. This is propelled through
punishment, performance evaluations and audits (Davis et al., 1997). Additionally, training
promotes staff professionalism and familiarity that in turn would promote compliance and
successful implementation of public road construction projects. Professionalism and
familiarity encompass staff competence in public road construction projects. Success is
boosted if the regulatory framework governing these projects is clear to reduce lack of
compliance (Gelderman et al., 2010). Interestingly, successful contract performance is
achieved if the government objectives are clear and the staff are competent (Chiappori and
Salanié, 2002). This notion introduces the need for an efficient regulatory framework to
enforce compliance and successful public road construction projects. This is inevitable
because an efficient regulatory framework can effectively bond contracts that influence
compliance with project requirements (Wright et al., 2001). Conversely, this is linked to a
perceived inefficiency of the regulatory framework in determining compliance and successful
implementation of public road construction projects (Gelderman et al., 2006).
According to Rokkan and Buvik (2009), agency theory explains the use of sanction
by the principal to influence the agent’s actions in meeting expectations. Rokkan and Buvik
emphasises compliance through power influence by the principal that is in line with
government’s legal powers of controlling public road construction team. The use of sanctions
in implementing public road construction projects is equally important to ensure compliance
and successful implementation of these projects. Similarly, agency theory suggests a use of
21
effective monitoring and sanctions mechanisms to improve compliance, this outcome is
inconsistent with the empirical findings of Mwakibinga and Buvik (2013) showing that
increasing monitoring and sanctions simultaneously fail to enhance compliance with a
regulatory framework. However, when monitoring and sanctions are applied sequentially,
they effectively enhance compliance. When increasing monitoring, it is proposed that
sanctions should be reduced otherwise staff may retaliate by not complying due to a
perception of mistrust from management (Mwakibinga and Buvik, 2013). Other authors have
shown that monitoring mechanisms are vital in solving principal-agent problems that arise in
the course of achieving organisational goals (Rutherford et al., 2007, Ross, 1973).
In summary, agency theory was considered suitable for this study because it is an
inspiring theory widely applied in different research areas to manage contracts between the
agent and the principal including; procurement, manufacturing and supply chain management
(Fayezi et al., 2012, Saam, 2007, Zsidisin and Ellram, 2003). Additionally, agency theory is
universally applied in many contractual relationships including buyer-supplier relationship,
employer- employee relationships within organisations and supplier-retailer among
organisations (Norrman, 2008, Zsidisin and Smith, 2005, Ross, 1973). By mimicking
government and road implementation team, agency theory clearly explains each party’s role
in managing contract relationships and ensuring compliance to achieve set goals (Van Slyke,
2007, Zsidisin and Ellram, 2003, Frey, 1993, Ross, 1973). Ideally, the implementation team
is in a contractual relationship with the government whereby failure to fulfil obligations, the
government enforces compliance to successfully implement public road construction projects
legally through signed contract and governing regulatory framework, sanctions, monitoring
and reporting mechanism (Van Slyke, 2007).
Table 2.1 Theoretical tenets and application of Agency theory
Theme Tenets Application
22
Goal incongruence: Assumes goal divergence based on self-interested rational actors. Initial disposition is to distrust. Control-oriented management philosophy. Theoretical assumptions are from economics.
Use of incentives and sanctions to foster goal alignment:
Assign risk to the agent to ensure goal compliance
Monitoring
Reward systems
Use of bonding threats to reputation
Eliminate opportunistic behaviour
Provide level of incentives and sanctions which reduce the threat of information asymmetry
Correct through specific contract requirements for asset specificity and moral hazard
Uses reputation as an incentive and sanction
Ensure goal alignment
Source: (Van Slyke, 2007)
Table 2.1 summarises by linking and supporting the conceptual framework in Fig 3
to a theoretical foundation. The theory helped to establish factors causing lack of compliance
and affecting successful project implementation. For example, how sanction, monitoring,
effective and efficient regulatory framework and professionalism influence compliance with
a regulatory framework and successful implementation of public road construction projects.
Agency theory established that a lack of compliance is caused by goal conflict or
incongruence, information asymmetry, adverse selection and moral hazard, leading to self-
interest, opportunistic behaviour and mistrust that equally affect successful implementation
of public road construction projects. By linking to this thesis’s conceptual framework,
ensuring compliance with the public procurement regulatory and successful implementation
of public road construction projects, opportunistic behaviour could be eliminated through
sanctions on staff, monitoring activities, perceived inefficiency of regulatory framework in
terms of clear instructions and efficient contracts, professionalism and familiarity in terms of
competence, training and knowledge. The next section discusses institutional theory in light
of compliance and project success.
2.3 Institutional theory, Compliance in public procurement and Project success
Institutional theory is widely applied in different fields including but not limited to
organisational behaviour, economics, political science and business to advance respective
research objectives (Scaraboto and Fischer, 2012, Brammer et al., 2012, Hillebrand et al.,
2011, DiMaggio and Powell, 1991). Institutional theory is critical in identifying factors
23
useful for pursuing research (Bruton et al., 2010). Specifically, institutional theory is known
for explaining compliance within the organisation (Zadawa et al., 2018b). In this regard, the
theory is equally important to establish factors affecting a lack of compliance and successful
implementation of public road construction projects. Comparatively, institutions behave
similarly since the same forces influence them. Convincingly, institutional norms are
enforced through coercive, mimetic and normative governance mechanisms (DiMaggio and
Powell, 2015, DiMaggio and Powell, 2000). Interestingly, institutional theory is concerned
with how organisations legitimately positioned themselves by complying with institutional
environment. This is hedged on the premise that organisations are controlled under some
rules of which compliance with these rules defines organizational success (Scott, 2013,
Brammer et al., 2012, Scott, 1983). Organizational performance is attributed to adoption of
different norms in managing their affairs and creating competitive advantage that has seen
success of some organisations while others failing because of risk aversion and selfish interest
(Kondra and Hinings, 1998). Conversely, organisations are managed differently with
differing regulatory frameworks that determine their performance in terms of efficiency and
effectiveness (Greenwood and Hinings, 1988). This explains why certain projects fail while
others succeed. By linking to current study constructs, perceived inefficiency of a public
procurement regulatory framework would determine compliance and successful
implementation of public road construction projects.
Institutions use established formal rules that guide organisations to meet objectives
often through monitoring and forms of enforcement (North, 2016, North, 1993). Ideally,
institutions are designed and enforced to control human interaction in carrying out
organizational activities (North, 2016). For example, safety measures in construction projects
with multiple stakeholders have been enforced through regulative, normative, and cultural
cognitive mechanisms (Ju and Rowlinson, 2014). These institutional mechanisms provided
government the power to influence organizational results through sanctions and monitoring
employees which in turn influences their compliance (Hillebrand et al., 2011, Kondra and
Hinings, 1998). This is necessary in public road construction projects with a myriad of
stakeholders. However, compliance may be met with resistance from some players who find
alternative means to successfully accomplish tasks using their knowledge and interest
(Kondra and Hinings, 1998). A notion supported by the argument from Greenwood and
Hinings (1996) that compliance with institutional norms can be contingent on specific
reasons. Looking at this from the contractors’ perspective, respect for a contractors’
24
commitment to fulfill their obligations and providing moral guidance would ensure
successful team performance (Babalola et al., 2016). Furthermore, North (2016) notes that
institutions who have professional code of conduct and sanctions face retaliation that equally
challenges public road construction project teams.
Regulative, cultural cognitive and normative isomorphism form institutional theory
(Scott, 2005). Regulative dimensions help enforce legally binding contracts signed between
parties, for example the government and contractors for construction of public road
construction projects (Geels, 2004). The regulatory element deals with rules, laws and
sanctions as enforcement mechanisms that requires compliance for successful construction
project implementation (Su et al., 2018). However, to ascertain how public road construction
team perceives project activities and objectives in doing the right thing, a cultural cognitive
element is the key. It deals with symbols, beliefs and common understanding that defines
individual behavior (Scott, 2013). However, a normative element is about professionalism
and deals with norms and values, which form a set of rules to which staff must comply within
project implementation (DiMaggio and Powell, 2015, Scott, 2013). Professionalism is
necessary for road construction team because it deals with a members’ professional behavior,
better work methods and conditions. It is often enabled through formal university education,
specialized skills and professional networking (DiMaggio and Powell, 2015, Wall and
Ahmed, 2008). The road implementation team requires training and mentoring to reinforce
their skills and expertise crucial for familiarity, professionalism and successful performance
(Cullen et al., 2014). Such competencies describing staff personality characteristics
consequently influence their performance (de Jong et al., 2013). Professionalism compels
public road construction stakeholders to understand the norm of public road construction
projects, the values and social obligation of public entities.
Workers’ performance in project implementation is based on compliance and
credibility of enacted norms as well as sanctioning of underperforming employees (Styhre,
2011). Deviating from a regulatory framework governing public road construction projects
may result in different goals that affect successful implementation of these projects. Such
deviations are easily detected if the organizational norms are effective with strong sanctions
capable of correcting deviant behavior (North, 2016, Oliver, 1991). An efficient and effective
regulatory framework with strong sanctions is paramount for the road construction projects.
Because organizational success depends on effectiveness and compliance with institutional
25
norms called institutional fit (Oliver, 1991). For successful implementation of public road
construction project, stakeholders’ compliance with established public procurement
regulatory framework is important. Organizational success is emphasised because institutions
minimize risks and determine organizational performance through transaction costs and
production (North, 2016). Efficient regulatory framework and effective enforcement
mechanism would tame deviant public road construction stakeholders leading to improved
compliance and successful project implementation.
Firm’s successful performance depends on effective sanctions enforcement, staff
skills and knowledge to achieve organizational objectives (Hillebrand et al., 2011, North,
1993). The article notes that investing in staff competence by improving their skills and
knowledge coupled with professional code is paramount for organizational success. These
are components determining professionalism and familiarity in public road construction
which requires management intervention for its staff performance (Beltrán-Martín et al.,
2008). Relatedly, workforce diversity and structural differentiations are competitive
advantage for organisation’s successful performance (Greenwood and Hinings, 1996). With
different stakeholders involved in public road construction projects, each player seeks high
performance by accomplishing respective obligations and have specific reasons to do so
while resisting non-compliance. Thus, project performance evaluated through efficiency and
effective institutional norms (perceived efficiency) and monitoring arrangements determines
its success.
Convincingly, institutional theory uncovers organizational success as being reliant on
perceived efficiency of a regulatory framework, staff professionalism, familiarity based on
staff knowledge, compliance with a regulatory framework, monitoring activities, sanctions
on staff, contractors’ resistance and project success factors (Geels, 2004, Scott, 1995).
Table 2.2: Three dimensions of institutional theory.
Regulative Normative Cognitive
26
Examples Formal rules, laws,
sanctions, incentives
structures, reward and
cost structures,
governance systems,
power systems, protocols,
procedures and standards
Values, norms,
roles, authority
systems, duty,
expectations and
codes of conduct
Priorities, beliefs,
problem agendas, body
of knowledge
(Paradigms), modes of
reality, categories,
classifications, jargons,
search heuristics
Compliance
mechanism
basis
Expedience, coercive
force and punishments
Social obligations,
Normative pressure
like social sanctions
Taken for granted,
mimetic, learning and
imitation
Logic Instrumentality (creating
stability, rules of the
game)
Appropriateness
and being part of
the group and how
to do things
Orthodoxy (Shared
ideas and concepts)
Legitimacy
basis
Legal sanctions Morally governed Culturally supported
and conceptually correct
Source:(Scott, 1995, Geels, 2004)
Figure 2.1: Summarised theoretical foundation linked to literature review
Agency and institutional theories helped to support identification of eight factors used
in this dissertation. These factors include; familiarity (FAM), monitoring activities (MONT),
professionalism of staff (PROF), sanctions on staff (SANC), perceived inefficiency of a
27
public procurement regulatory framework (PEIR), contractors’ resistance to non-compliance
(CONTR), compliance with a public procurement regulatory framework (COMP) and project
success (PROJSU) as depicted from Fig 2.1 respectively.
These factors are explored through the literature review in the following chapter.
28
CHAPTER THREE LITERATURE REVIEW AND HYPOTHESES
DEVELOPMENT
29
3.1 Introduction` This chapter explores via a comprehensive literature review the factors derived from
the theoretical foundation in chapter two. The chapter explains the implications of public
procurement regulatory compliance and project success to determine the knowledge gap in
implementing public road construction projects. The knowledge gap in this thesis was
enhanced through a research question, three objectives and nineteen hypotheses. Literature
relating to familiarity with a public procurement regulatory framework, monitoring activities,
professionalism of staff involved in public road construction projects, sanctions on staff,
perceived inefficiency of a public procurement regulatory framework and contractor’s
resistance to non-compliance with a public procurement regulatory framework as
independent variables to compliance with a regulatory framework and project success
respectively is presented. In addition, methodical literature on mediation is explored as
guidance to determining mediation effects. Respective hypotheses are developed as
demonstrated in the conceptual model Fig 3c. The process explaining how the research model
was developed from literature review is also presented here. It ends with a justification for
using selected study variables after mediational effects.
3.2 Research Model
The model illustrates relationships between study variables linked by arrows as shown
in Figure 3.1 (a, b & c). A three step-process was used in formulating the research model.
The first step involved comprehensive literature review. In the literature review, compliance
and project success factors were identified and grouped into four major categories, which are
environmental, organizational, project and individual factors. The second step involved
analysis and interpretation that enabled merging and eliminating similar factors. Accordingly,
six compliance factors and seven project success factors were established (see Fig 3.1b). Note
that the six compliance factors double as project success factors and are superimposed by
arrows in the conceptual framework. Reducing factors helps in an in-depth understanding
since many factors are time consuming and wasteful of resources (Collin, 2002). The third
step involved identifying measurement indicators for each variable as illustrated in Fig 3.1c.
Note that according to the literature review, some factors are interchangeably used as
indicators. This is particularly evidenced in the project success factor. The final model is in
three segments. The first segment illustrates the relationship between six independent
variables (compliance factors) and compliance with a public procurement regulatory
30
framework is demonstrated by black arrows. The second segment illustrates the relationship
between seven project success factors including compliance with public procurement
regulatory framework and project success as demonstrated by blue arrows. The third invisible
segment illustrates the mediation effect between the six independent variables and project
success (Dependent) through compliance with public procurement regulatory framework
(Mediator). Hypotheses H1-H13 illustrates study variable relationships as well as mediation
effect hypotheses H14-H19 that were statistically tested for significance. The conceptual
framework is in the next section.
31
Figure 3.1(a) Broad conceptual model linking compliance factors with regulatory framework and project success
Note: Organizational incentives and pressure captures sanctions
Figure 3.1(b) Conceptual model showing selected compliance and project success factors
Compliance
factors
Project success
Compliance with
regulatory framework
Familiarity
Monitoring
activities
Professionalism
Contractor
resistance
Perceived
inefficiency
Sanctions
Environmental factors
Perceived inefficiency of
regulatory framework
Political interference
Project factors
Contractor’s resistance
Contract management
Record management
Organizational factors
Monitoring activities
Organizational incentives
Institutional factors
Organizational pressure
Individual factors
Familiarity
Professionalism
Compliance with regulatory framework
Regulations
Laws
Rules
Policies
Procedures
Formal instructions
Project Success factors
Client Satisfaction
Time
Cost
Quality
Safety
Others
32
Figure 3.1(c) Final conceptual model of compliance and Project Success with Respective Measurement Indicators
Source: Modified from (Mwakibinga and Buvik, 2013, Eyaa and Oluka, 2011, Basheka and Mugabira, 2008, Gelderman et al., 2006, Payan
and McFarland, 2005, Dvir and Lechler, 2004)
Familiarity with regulatory framework
Familiarity with applicability
Familiarity with exceptions
Overall regulatory Knowledge
Perceived clarity of regulatory framework
Qualifications
Monitoring activities
Inspection for timely recording
Inspection for proper storage methods
Inspection for timely deliveries
Inspection for actual deliveries
Inspection for authorization
Professionalism
Confidentiality
Competence
Integrity
Professional behaviour
Expertise
Training
Professional membership
Experience
Sanctions
Penalties for violation
Credibility of sanctions
Known stipulated sanctions
Consideration of outcome for non-compliance
Reasons for penalty
Compliance with regulatory framework
Regulatory adherence
Timeliness of delivery
Timeliness of recording
Loss/Damages
Unauthorized
procurement
Project success
Time
Cost
Quality
H1
H2
H3
H4
H7
Perceived inefficiency of
regulatory framework
Ban on Negotiations
Ban on contract
extension
Ban on exclusion of
underperforming
contractors
Contractor’s resistance
Readiness to take
action
Contractor’s
knowledge
Fear of being exposed
H5
H6
H12
H13
H10
H9
H8
H11
33
Globally, few studies have been undertaken on a lack of compliance in public
procurement. In addition, these studies were limited in nature and paid less attention to
compliance with a public procurement regulatory framework in construction sector especially
with respect to Uganda’s public road construction projects (Duraku, 2018, Gelderman et al.,
2017, Tender and Enterprises, 2016, Mwakibinga and Buvik, 2013, Eyaa and Oluka, 2011,
Gelderman et al., 2010). The main objectives of a public procurement regulatory framework
are to promote fairness, transparency, accountability and value for money with efficient and
effective procedures benefiting all stakeholders (Duraku, 2018, PPDA Authority, 2003,
Odhiambo and Kamau, 2003). Literature shows a number of challenges affecting successful
implementation of public road construction projects and enforcing compliance with a public
procurement regulatory framework (Hansen et al., 2018, KAPLIŃSKI, 2018, Marnewick et al.,
2018, Kingsford Owusu and Chan, 2018, Amann et al., 2016, PPDA Authority, 2016, Carr and
Sundaram, 2016, PPDA Authority, 2008, Agaba and Shipman, 2007). These challenges include
but are not limited to delayed completion of road construction projects, contract price
variations, inefficiency in regulatory framework and procurement irregularities. Interestingly,
challenges in the construction industry are partly blamed on a lack of theories underpinning
cost overruns experienced in transport infrastructure projects (Love et al., 2018b). Particular
road construction projects affected by these challenges are listed in Table 1.3. The next
subsections present a specific literature review starting with the implication of compliance with
a public procurement regulatory framework.
3.3 Implications of Compliance with Public Procurement Regulatory Framework Compliance refers to a target acting in accordance with influence from a power source
(Payan and McFarland, 2005). Alternatively, compliance is pursuing government objectives
through established frameworks (Krambia-Kapardis, 2019). While a lack of compliance is
disobedience with a regulatory framework (Obanda, 2010, Lisa, 2010). In the context of this
thesis, a lack of compliance implies that staff implementing public road construction projects
are not adhering to the public procurement regulatory framework. In addition, lack of
compliance encompassed all issues including but not limited to procurement/project
irregularities, corruption, unethical behaviours among others.
Promoting and managing compliance should identify what factors cause a lack of
compliance in procurement contracts. For example, GlaxoSmithKline company lost between
US$(80-120) million and failed to achieve its objectives because of procurement occurring
outside contractual agreements (Kulp et al., 2006). Relatedly, the root cause of poor
34
performance of transport infrastructure projects delivered over budget is referred to as a
planning fallacy (Love et al., 2019). Several writers suggest, a lack of compliance is caused
by self-interest, a weak enforcement mechanism, inefficient regulatory framework,
inducement, social pressure, obligation, habit/practice and unprofessional behaviour among
others as evidenced from theoretical foundation (Zadawa et al., 2018b, North, 2016, DiMaggio
and Powell, 2015, Saam, 2007, Van Slyke, 2007). Consequently, these factors among others
stand to fail government goals (Kingsford Owusu and Chan, 2018, Gambo et al., 2016,
Mwakibinga and Buvik, 2013, Trepte, 2004). Alternatively, complying with a public
procurement regulatory framework significantly enhances value for money by eradicating
procurement irregularities and ensuring successful implementation of government projects
(Signor et al., 2016b, Agaba and Shipman, 2007). For example, timely implementation of
public road construction projects that are durable and cost effective (Farshchian et al., 2017,
Amann et al., 2016). This notion is further support by Nielsen-Parker’s holistic compliance
model that stresses the need for regulators to enforce compliance with regulatory framework
to achieve set objectives (Parker and Nielsen, 2017, Krambia-Kapardis, 2019).
A lack of compliance in public procurement affects transparency, accountability and
leads to unsuccessful implementation of public construction projects (Signor et al., 2019,
Kingsford Owusu and Chan, 2018, Kling, 2008, Søreide, 2002). In Australia, but irrespective
of the country’s jurisdiction, government projects lack the implementation of best procurement
practices compared to private sector. This is due to procurement irregularities with inefficient
procurement processes that inevitably cost the taxpayer more (Duraku, 2018, Volintiru and
Olivas Osuna, 2018, Kajevska, 2018, Kling, 2008). Complying with a public procurement
regulatory framework saves funds; however, it requires an effective enforcement mechanism
to ensure compliance and the meeting of government targets (Oluka and Basheka, 2014). A
lack of compliance manifested into non-durable construction products are challenging
construction projects. For example, approximately 0.25-2.5% of contract value is spent on
reworks because of non-compliant products (Australian Procurement & Construction Council,
2013). Particularly, Australian examples show that lack of compliance manifested through cost
and schedule overruns accounts for 48% failed public road construction projects. These
projects include; Sydney cross city tunnel, Brisbane’s river city motorway and Sydney’s M7
Clem Jones Tunnel (Love et al., 2018b, Love et al., 2016a). Additional examples in Australia
show that Westconnex motorway suffered significant cost increase, Ipswich motorway upgrade
had a 196% cost overrun and the Forrest Highway Peel deviated by over 400% from the original
35
budgeted value (Love et al., 2019). Lack of compliance through contract variations,
substandard works and cost overrun is not only reported in Australia and Uganda but also
equally reported in Brazil, Hong Kong, Pakistan and Asian transport infrastructure projects
(Love et al., 2019, Hussain et al., 2019, Signor et al., 2017, Signor et al., 2016a, Park and
Papadopoulou, 2012).
In Uganda, the executive director of PPDA noted that improving compliance with a
public procurement regulatory framework requires compliance checks and strengthening
professionalism. Empowering the Institute of Procurement Professional Uganda (IPPU),
Uganda Association of Consulting Engineers (UACE) and Uganda National Association of
Building and Civil Engineering Contractors (UNABCEC) among others to regulate
procurement practitioners and promote ethical behaviours was emphasized the director (PPDA
Authority, 2009a, PPDA Authority, 2008). While currently these bodies are established and
recognised in Uganda’s procurement ranks, they lack the mandate and power to enforce
professionalism and compliance in public sector procurement. Additionally, PPDA revealed
that a lack of compliance in procurement contracts was high. For example, out of 1,520
contracts reviewed, only 21% of contracts were compliant against 79% non-compliant
contracts. In addition, 2005 procurement audit reports revealed that lack of compliance among
central Procuring and Disposal Entities (PDEs) was high. For example, out of 322 audited
contracts, only seven were compliant (representing 2%) and 315 (98%) were not compliant.
Unsurprisingly, local and international companies complain about Uganda’s procurement
officials not following a public procurement regulatory framework in implementing awarded
contracts (Daily Monitor, 12th March 2019, Agaba and Shipman, 2007). Reports show that
lack of compliance is manifest through corruption and challenges national road construction
projects (Uganda National Road Authority, 2018). A lack of compliance underpinned by
procurement irregularities has failed Uganda’s large construction projects. For example, the
World Bank funded Bujagali Hydroelectricity project worth US$550 million (AU$ 748M) was
suspended after a high ranking public official took a US$10,000 (AU$ 13,600) bribe and
influenced the contract award (Agaba and Shipman, 2007, Prayas Energy group, 2002).
Similarly, World Bank reports show that US$1 Trillion (AUD 1.360T) is lost in
procurement irregularities annually and specifically, US$79.65 million (AU$ 108.324M) was
lost in 2004/2005 financial year (Kaufman and Kaufman, 2004). Lengwiler and Wolfstetter
(2006) estimate that US$200 billion (AU$ 272B) is lost annually because of the lack of
36
compliance that is affecting public construction projects (Thai, 2008b, Stansbury, 2003).
Uganda is in a similar position with reports suggesting adoption of good procurement practices
to improve public construction sector performance are required (Kakitahi et al., 2013). These
recommendations are inevitable because a lack of compliance is common in both public and
private sectors (Kulp et al., 2006). Adopting good procurement practices and systems in the
public road construction subsector would enhance compliance, successful project
implementation, achieve value for money and foster economic development as the subsector is
heavily relied upon in Uganda’s transport system (Ministry of Works and Transport, 2014).
Good public procurement practices and governance saves approximately US$150
million (AU$ 204M) annually (Anvuur et al., 2006). In sub-Saharan Africa, 70% of public
contracts experience 20-30% contract price increase due to lack of compliance with a
regulatory framework (Ameyaw et al., 2012, Mawenya, 2008). While Africa lose US$148
billion (AU$ 201.28B) annually in procurement irregularities prevalent throughout
procurement process. This is attributed to poor governance, week enforcement, inefficient
regulatory framework especially in public works construction projects influenced by various
stakeholders (Zadawa et al., 2018b, Owusu et al., 2017, Osei-Tutu et al., 2010, Mawenya, 2008,
Li et al., 2000). A lack of compliance cost government significant funds including delivery of
substandard works affecting successful implementation of public road construction projects.
For example, substandard road construction projects not meeting contract specifications in
West Africa were approved (Frøystad et al., 2010). Interestingly, a lack of compliance in public
procurement is a common problem in both developed and developing countries and requires
reforms to successfully implement public projects (Zadawa et al., 2018b, Thai, 2008b). Without
an effective public procurement regulatory framework in developing countries, public funds
would be consumed without due care and diligence (Fofie, 2016). Investors, operators and
consumers would benefit from a regulatory governance system that fosters commitment and
industrial endowment (Eberhard, 2007).
An effective regulatory framework for public construction projects requires the design
of rules to align with clear reporting structures allowing transparency and accountability at all
stages when undertaking construction projects. In Bangladesh, World Bank funded post-flood
rehabilitation projects failed to achieve objectives because public roads construction projects
were marred with procurement irregularities (Mahmood, 2010). Accordingly, the World Bank
suspended funding of 14 road construction projects. Similarly, significant funds are wasted
37
annually in inefficient procurement practices where public procurement continues to
underperform (Kiama, 2014, Attaran and Attaran, 2002). For example, Uganda’s construction
industry experience value losses worth 2-25 % of the contract sum (Kakitahi et al., 2013).
Uganda’s national construction industry policy 2010 was established to improve integrity in
the industry, despite this, construction projects continue to be predominantly challenged
(Kakitahi et al., 2015). Lack of compliance with regulatory requirements in Uganda’s public
construction projects need attention otherwise substandard works will continue to occur leading
to unsuccessful construction projects.
It has been convincingly shown that successful public construction projects rely on
compliance with a regulatory framework (Owusu et al., 2017, Kassel, 2008). National integrity
survey 2009 Uganda chapter revealed that in 2009/2010 FY, the government earmarked
UGX7.3 trillion (AU$ 9.928B) for public procurement, however, value for money was not
achieved due to massive procurement irregularities leading to failed government projects and
objectives (PPDA Authority, 2009b). For example performance in construction projects was
below standard with contractors attributing substandard works to reduced amount for project
implementation after bribing public procurement officers (PPDA Authority, 2009b).
Contractors further noted that irrespective of substandard works, project monitors for works
would only approve work when bribed. Such procurement irregularities affect successful
implementation of public construction projects. In addition, lack of compliance is a double
tragedy for government since public funds are lost and substandard works delivered.
Consequently, affecting government objectives and programs to steer the economy forward
(Rogerson, 2018, Preuss and Walker, 2011, Ruddock and Lopes, 2006). The following
subsections (3.3.1 to 3.3.6) presents literature on the six compliance factors respectively.
3.3.1 Familiarity with regulatory framework and compliance In the context of public procurement, familiarity refers to one’s knowledge of an entire
regulatory framework, process and procedures in performing duties that extends beyond
academic qualifications (Hunja, 2003). Familiarity is important in most aspects. For example
researchers’ familiarity with analytical techniques and concepts motivates them to use certain
software (Hayes, 2012). Likewise, familiarity in public procurement of construction projects is
important because of the complex nature of these projects (Kagioglou et al., 2000). Familiarity
with regulatory framework is a key determinant of compliance in construction sector
(Abdullahi et al., 2017). Interestingly, academically qualified procurement officers lack
general knowledge on a comprehensive public procurement regulatory framework especially
38
on interpreting technical sections (Hunja, 2003). Public road construction projects are governed
by a myriad of policies and procedures in the form of regulatory frameworks. Management
should embrace familiarity by orienting staff on emerging issues in public procurement
regulatory framework to effectively implement construction projects (Chi and Nicole
Javernick‐Will, 2011). Orientation is crucial in public road implementation because it ensures
staff are familiar with current implementation issues (Kaluarachchi and Jones, 2007). Evidence
show that lack of familiarity with a regulatory framework underpins a lack of compliance
across nations (Decarolis et al., 2018, Zadawa et al., 2018a, Shan et al., 2017). For example in
Kenya, a lack of compliance significantly affected compliance with public procurement
requirements in secondary schools (Migosi et al., 2013). Additionally, a lack of familiarity with
organizational structures and governance mechanism caused capacity problems in public sector
procurement (Hunja, 2003). Similarly, Bangladesh failed to meet goals because staff were not
familiar with a regulatory framework governing public procurement (Mahmood, 2010). In the
Ugandan context, limited staff knowledge of public procurement process and the PPDA Act
2003 affected compliance with procurement system (PPDA Authority, 2009b).
The PPDA Act 2003 demands conducting public procurement in systematic stages to
enable fair treatment of stakeholders. A sound public procurement system requires a clear
regulatory framework that is easily interpreted and understood by different stakeholders (Thai,
2008a). Reports show that implementing public construction projects successfully, contractors
and project managers should thoroughly understand the project scope and governing regulatory
framework to avoid manipulations in the construction industry (Tabish and Jha, 2015, Tabish
and Jha, 2011). Furthermore, in Uganda National Roads Authority’s (UNRA) end of 2013/2014
performance workshop, a lack of familiarity with the roads management system was disclosed
as a factor affecting compliance with UNRA’s objectives (Uganda National Road Authority,
2014). Reports suggest increased staff knowledge over rules would ensure compliance with
formal elements (Shan et al., 2017, Preuss and Walker, 2011, McNutt and Rossi, 2010).
Improving staff familiarity through education and training would increase their competence
required for implementing public road construction projects (Decarolis et al., 2018, DiMaggio
and Powell, 2015, Wall and Ahmed, 2008).
Familiarity with a public procurement regulatory framework significantly influences
compliance with regulatory framework (Gelderman et al., 2006). However, procurement
officers were shown only to comply if the regulatory frameworks were clear. In recent research,
39
a lack of compliance with a regulatory framework was attributed to ignorance among
construction stakeholders who viewed compliance as a regulatory burden (Chitengi, 2018,
Becker, 2004). Pertinent report shows that Netherland’s municipalities experienced a lack of
compliance with procurement procedures due to lacking familiarity with procurement process
(Boer and Telgen, 1998). Similarly, misconception, ignorance and lacking familiarity with
procurement policies have been found to significantly affect compliance in Nigeria’s public
construction industry. These factors complicated implementation of Nigeria’s procurement Act
(Abdullahi et al., 2017, Zadawa et al., 2015). In United States’ (US) public procurement, a lack
of compliance is attributed to limited information available amongst procurement officers
(Kulp et al., 2006). This was because policies were made at the top level and procurement is a
tactical level task performed by middle-lower cadres who lack complete information for a
particular contract. This creates ambiguity in regulatory framework especially when
communication is not clear and delivered late.
Once there is ambiguity in a regulatory framework, staff interpretation would be difficult
thereby affecting compliance. On the contrary, when employees are too familiar with certain
processes and or suppliers, they tend not to comply with new company process or suppliers by
pretending to be ignorant (Kulp et al., 2006). Relatedly, Uganda’s public procurement is
becoming enhanced, since inception of the PPDA Act 2003 with subsequent amendments.
Accordingly, public procurement stakeholders may be unfamiliar with amended regulatory
frameworks that in turn affects compliance with public procurement regulatory frameworks
particularly in the context of governing complex construction projects. In addition, a lack of
compliance is affected by new organisations awarded contracts when they are not familiar with
amended regulatory framework governing road construction projects. Familiarity with ways
through which things are done makes work easier and completed within time (Sidwell et al.,
2002). Correspondingly, government agencies and stakeholders use procurement methods they
are familiar with for effective project implementation. However, the approach is not automatic
in yielding positive results as it is subject to prevailing project implementation circumstances.
Considering risk averse perception of agency theory, road construction stakeholders will only
use implementation methods known, rather than unknown despite of their ineffectiveness.
The above discussion shows that familiarity with a public procurement regulatory
framework particularly governing complex public road construction projects is important. This
leads to propose the hypothesis;
40
H1. Familiarity with public procurement regulatory framework increases compliance with
public procurement regulatory framework.
3.3.2 Monitoring activities and compliance Agency theory defines monitoring as a principal’s efforts to control its agent to comply
with contractual terms. Accordingly, monitoring is an organizational governance mechanism
that ensure staff meet goals. Correspondingly, for large and complex organizational structures
to realise their objectives, they require a well-defined system for supervising and controlling
procurement officers (Jha and Misra, 2007, Thai, 2001). Reports show that regular monitoring
of budgets for respective projects enables timely corrective actions to improve productivity
(Isaac and Navon, 2014, Schapper et al., 2006). Similarly, a lack of monitoring procurement
officials affects compliance with public procurement regulatory framework (Volintiru and
Olivas Osuna, 2018, Peprah, 2015, Adusei and Awunyo-Vitor, 2015). Hence, preventing
procurement irregularities in public road construction projects requires ongoing monitoring of
project implementation (Basheka et al., 2012, Helsby and Kaizer, 2005). In a public road
implementation context, constant monitoring of staff is suggested to support them to discount
unethical interest in pursuit of organizational goals (Zhang et al., 2016, DiMaggio and Powell,
2015).
According to Zhang et al. (2016), management should monitor its staff to avoid
undesirable behaviour as it has been found that monitoring construction projects ensures
quality implementation (Hussain et al., 2019, Lapidus and Yves, 2018, PPDA Authority, 2008).
For example, monitoring underground construction projects using Cyber-Physical Systems
have proved effective (Zhou et al., 2019). Considering agency theory approach, monitoring
alone could not significantly influence agent behaviour in complying with principal’s interest
and meeting goals (Kauppi and van Raaij, 2015, Rutherford et al., 2007). This notion is
supported by Tabish and Jha (2015) who established that monitoring is an insignificant factor
influencing public construction projects. These reports contradict Van Slyke (2007) assertion
that suggests monitoring as a mechanism to militate opportunistic behaviour. Hence, the need
to investigate the impact of monitoring public road construction projects on compliance with a
public procurement regulatory framework.
Despite criticising procurement irregularities in public construction industry, a study on
construction and rehabilitation of nursing schools in Uganda funded by the European Union
was unique. The project was free from procurement irregularities because of strict monitoring
41
by the project supervising authority (Kakitahi et al., 2013). The article adds that inadequate
works supervision and ineffective stakeholders’ management promotes lack of compliance and
results in rework in Uganda’s public construction projects. Poor construction supervision and
site management cause delays and affect project performance. However, complying with a
regulatory framework effectively reduce delays and improve project performance (Tabish and
Jha, 2015, Sweis and Bisharat, 2014). Systematic monitoring of an entire project
implementation process ensure efficiency, transparency and accountability (Zolfani et al.,
2018, Freeman et al., 2006). Notably, enforcing compliance in public road construction projects
requires on-site project monitoring and inspection by different stakeholders (Deng et al., 2014).
This notion is supported by reports demanding a holistic approach to contract monitoring to
improve contract performance (Oluka and Basheka, 2014). Such approaches could mitigate a
lack of compliance by militating deviant staff during project implementation.
Rework evident in the construction industry ensures construction projects meet desired
specification (Fellows and Liu, 2012, Love et al., 2010). However, lacking compliance and
persistent rework in the construction industry is attributed to limited inspection (Smolders and
Sher, 2016). Monitoring road construction is inevitable to achieve efficiency and value for
money (Owusu et al., 2017, PPDA Authority, 2009a). According to National Integrity Survey
report 2009 in Uganda, 75.4% households support public monitoring of government projects
to enforce compliance with project implementation requirement (PPDA Authority, 2009b).
Actively involving local community in monitoring project implementation enhances quality
project implementation. For example, in Kabale district, a road was rejected after the
community under Resident District Commissioner (RDC) leadership found it unsatisfactory. It
was reconstructed to comply with project specifications. Whereas local community could
monitor road construction projects, the civil society express fear for their lives when reporting
procurement irregularities (Kingsford Owusu and Chan, 2018). For example, an incidence in
Uganda Soroti district where a sub county chief with two officials were arrested and charged
with trespass when inspecting a construction project in their area (PPDA Authority, 2009b).
Monitoring public projects at a community level can be empowerment through sensitization,
providing resources and leaders taking short courses in monitoring and evaluation.
Since public construction projects use public funds, monitoring these projects could
enhance public confidence, transparency and promote compliance with project requirement
including governing regulatory framework. For example, the Malaysian construction industry
42
is marred with incomplete construction projects due to poor monitoring and auditing of project
implementation (Shu Hui et al., 2011). Relatedly, Bangladesh’s public procurement reforms
failed to attain its objectives due to poor monitoring of political and public stakeholders
sabotaging reform agenda (Frøystad et al., 2010). Consequently, observations suggest
intensifying supervision and monitoring of public road construction projects to enhance
compliance (Uganda National Road Authority, 2014, Uganda Road Fund, 2014). Effective
monitoring mechanisms would enhance compliance with public procurement regulatory
framework and enforcing contractors to meet their obligations. Such mechanisms would ensure
infrastructure development that accelerates economic development. For example, India’s
government earmarked US$514 billion (AU$ 699.04B) towards infrastructure development for
five years plan (2007-2015), however, realising its goals were reliant on effective governance
mechanism alone (Tabish and Jha, 2011).
Comprehensive monitoring and evaluation mechanisms could enhance compliance with
government policies (Uganda Road Fund, 2015, PPDA Authority, 2008). For example, when
constructing Kenya’s national insurance health fund, a lack of supervision and monitoring
project implementation resulted in substandard works measured against the required
specifications (Akech, 2004). In addition, substandard works were accepted, payments made
for non-deliveries and the contract price doubled. Relatedly, Uganda’s statistical compliance
reports show that effective monitoring and evaluation mechanisms detect procurement
irregularities arising from lack of compliance with a public procurement regulatory framework.
These irregularities affect value for money (Agaba and Shipman, 2007). Convincingly, agency
theory suggests monitoring of road construction projects enforce compliance and meet
government goals (Van Slyke, 2007).
This thesis aims to establish the relationship between monitoring activities and
compliance with regulatory framework through the following hypothesis;
H2. Monitoring activities on public road construction projects increases compliance with
public procurement regulatory framework
3.3.3 Professionalism of staff and compliance This section digests literature-linking professionalism of staff to compliance with a public
procurement regulatory framework. Professionalism in the context of this dissertation refers to
a collective term encompassing academic qualification, competence, experience, specialised
knowledge, skills, being ethical/not corrupt, having integrity, commitment and being a member
43
of a professional body. Scholarly, professionalism refers to one’s competence in skills, special
knowledge with experience and a member of a professional body exhibiting an ethical code
(Watson, 2002). Additionally, a profession results from distinct academic training and
specialised knowledge monopolised in certain positions guided by common ethical code
(Osland and Strand, 2010).
In the construction industry, operators focus on achieving professionalism through
professional bodies, code of conduct, monitoring and benchmarking to increase accountability
and ensure compliance (Sohail and Cavill, 2008, PPDA Authority, 2008). This is because
professionalism guide construction professionals based on knowledge and experience to ensure
compliance with a regulatory framework (Murtagh et al., 2018, PPDA Authority, 2008).
However, a lack of professionalism in construction industry is attributed to unethical behaviour
and the complex nature of construction projects (Shan et al., 2020a, Tayeh et al., 2018, Le et
al., 2014a). Relatedly, a lack of compliance with a public procurement regulatory framework
is caused by poor professionalism among public officers entrusted with specific tasks (Zhang
et al., 2016, Basheka and Mugabira, 2008, Boer and Telgen, 1998). Professionalism in public
procurement is achieved through training and instilling ethical standards among public
procurement stakeholders (PPDA Authority, 2016). In addition, professionalism of staff is
assessed through qualifications, adhering to professional code and continuous training
(Obanda, 2010). Implementing public road construction projects equally requires staff
professionalism enhanced through academic qualifications, skills and professional networking
(DiMaggio and Powell, 2015, Wall and Ahmed, 2008). This is important because
professionalism is effective in improving purchasing performance Boer and Telgen (1998) as
well as project success by limiting opportunistic behaviours among a project team (Um and
Kim, 2018).
Indeed compliance with in construction projects is tagged on staff adherence to their
respective ethical codes (Owusu et al., 2017). Consequently, in Uganda, public procurement
personnel are required to register with the Institute of Procurement Professionals of Uganda
(IPPU) that brings procurement personnel together in the country. Accordingly, UACE,
UNABCEC, Uganda Institute of Professional Engineers (UIPE), Engineering Registration
Board (ERB), Architecture Registration Board (ARB) and Surveyor’s Registration Board
(SRB) are formed to ensure professionalism in the construction sector (PPDA Authority, 2008).
These professional bodies would equally enforce compliance with a public procurement
44
regulatory framework governing an array of procurement contracts in Uganda (PPDA
Authority, 2016). Similarly, a well-functioning public procurement system is based on
integrity, transparency, accountability, regulatory framework and adequate resources (Basheka
and Mugabira, 2008). Interestingly, lacking skills, motivation and integrity among procurement
officers have been found to cause public procurement inefficiencies (Decarolis et al., 2018,
Nsanganzelu, 2015, Ojo and Gbadebo, 2014, Onyema, 2011). These unprofessional issues are
evidently affecting construction industry (Brown and Loosemore, 2015). Accordingly, Uganda
is branded a grand seat of unprofessional behaviour (Kalinzi, 2014). Ideally, Uganda’s public
procurement is at infant stage requiring increased staff professionalism and consequently
improving their procurement skills and competence (Decarolis et al., 2018, Kalinzi, 2014). For
example, during PPDA/UNRA stakeholder’s consultative workshop 2008 under the theme
“Uganda’s construction sector challenges”, lack of professionalism among construction
stakeholders was raised as a factor affecting the sector performance (PPDA Authority, 2008).
This was particularly regarding non-adherence to ethical code of conduct. Staff must adhere to
their professional code otherwise, they are embarrassed for acting contrary (Mawenya, 2008,
Larmour, 2007).
Lack of specialised training in road construction projects challenge their implementation
because general sensitisation and workshops on procurement are inadequate for complex public
road construction projects. Finding, hiring and maintaining dedicated, ethical and competent
employees is hard (Lan et al., 2005). This adversely affects Uganda’s construction projects
characterised with substandard works due to non-committed workforce exhibiting poor
contract implementation and lack of compliance with a public procurement regulatory
framework (Oluka and Basheka, 2014). A competent workforce is a critical factor in contract
implementation (Decarolis et al., 2018). Particularly, Uganda lacks trained, qualified and
experienced staff in the road construction subsector (Cornish and Mugova, 2014, Nadiope,
2005). This is equally evident in large construction projects experiencing inadequate trained
staff (Kim and Huynh, 2008). Professionalism in public road construction subsector could
improve compliance with the public procurement regulatory framework. Interestingly, Eyaa
and Oluka (2011) discovered that professionalism insignificantly affects compliance with
public procurement regulatory framework.
A lack of professionalism challenges Uganda’s road construction subsector as noted in
performance evaluation reports by different public organisations (PPDA Authority, 2014). This
45
was evidenced by lack of skilled and experienced staff and road contractors to implement
public roads (Ministry of Works and Transport, 2014, Ministry of works and Transport, 2012).
Consequently, staff training is important to ensure professionalism by boosting their
understanding of the road implementation procedures well to deliver goals (Preuss and Walker,
2011, Shaban, 2008). Training based on identified needs make staff understand operational
functionalities, thus promoting professionalism (Basheka et al., 2012). Reports show that lack
of and inadequately trained procurement staff underpin professionalism that affect compliance
with a public procurement regulatory framework (Obanda, 2010). Relatedly, Uganda’s
Country Procurement Assessment Report (CPAR 2004), reveals that unprofessional behaviour
affects public procurement process. This is particularly related to interference from politicians
and high ranking officials (Rogati, 2004). Embracing professionalism in public road
construction projects in important. For example, United States of America (USA) opted for
contracting out procurement opportunities to contractors with specialised expertise to deliver
timely quality contracts (Bartle and Korosec, 2003). In addition, United States’ defence
department is promoting education, training and developing staff so that they are competent in
contract implementation (Rendon, 2010). Professionalism is boosted through a variety of
training including formal, informal, in-house, contract compliance training and service contract
training conducted by different bodies (Bartle and Korosec, 2003). Hence, “a well-trained
officer need to be trained” (Bartle and Korosec, 2003).
Continuous training is crucial for staff implementing public road construction projects
because it keeps the workforce competent while increasing their knowledge and skills in
handling different construction tasks (Shaban, 2008). This is supported by institutional theory
advocating for staff professionalism based on specialised skills and competence (DiMaggio
and Powell, 2015). The article emphasised that professionalism could be achieved through
workshops, training, in-service educational programs, consultations, employer-professional,
school associations and career paths. Continuous upgrading of purchasing knowledge creates
organizational competitive advantage because training keeps staff updated on emerging issues
and allows for the design of appropriate strategies (Carr and Smeltzer, 2000, Duffy, 2000).
Correspondingly, organisations investing in effective staff training enhance professionalism.
However, training programs should be tailored to ever changing required skills (Taylor, 2002,
Duffy, 2000). Professionalism of a road construction team is paramount because competence
acquired from adequate training helps them to interpret and comply with a public procurement
regulatory framework (Trepte, 2004, Hunja, 2003).
46
Lack of professionalism is not only affecting Uganda’s construction industry, but other
countries as well. For example in China, unprofessional behaviour affects compliance in
China’s construction industry and requires promoting an ethical code to enforce regulatory
frameworks (Deng et al., 2014). In Malaysia, the public construction projects experience
unprofessional behaviour because public officers reveal government prices to preferred
contractors making quotations in open tendering system which is against confidentiality (Shu
Hui et al., 2011). They accept bribes and equally share profits of a successful quotation of a
fraudulent contractor (Shu Hui et al., 2011). However, some procurement officers demand
contractors to adhere to contract specifications by upholding professional integrity and ethical
code that promotes compliance with a public procurement regulatory framework governing
construction projects. Similarly, a lack of professionalism affects compliance with the
Ghanaian Public Procurement Act that requires recruiting qualified procurement personnel and
conducting regular training in procurement issues for proficiency (Ameyaw et al., 2012, Osei-
Tutu et al., 2011). Unethical behaviour amongst public road implementation team affects
professionalism and compliance with a public procurement regulatory framework governing
these projects. A lack of professionalism masterminded by conflicts of interest and
unprofessional attitude promotes lack of compliance leading to costly and substandard
procurements (Obicci, 2015).
Consequently, professionalism of staff in public road construction projects could have
implications on compliance with a regulatory framework. Hence, propose the hypothesis;
H3. Professionalism of staff in public road construction projects increases compliance with
public procurement regulatory framework
3.3.4 Sanctions on staff and compliance This section discusses literatures relating to sanctions on staff and compliance with a
public procurement regulatory framework. In the context of this dissertation, sanction means
negative incentives including threats and punishments/penalties imposed on violators of
regulatory framework governing public road construction projects. Sanctions are an
enforcement mechanism used by regulatory bodies to ensure compliance with a regulatory
framework (Zadawa et al., 2018b, Zubcic and Sims, 2011). Surprisingly, the application of
sanctions to achieve compliance with respective regulatory frameworks has mixed reactions.
For example, looking through the lens of agency theory, sanctions make violators/agent plot
how to prevent and conceal detection of wrong doing by the principal (Zubcic and Sims, 2011,
47
Sparrow, 2000). However, many studies agree that sanctions improve compliance with
regulatory framework (Rajab and Eydgahi, 2019, Zadawa et al., 2018b, Mwakibinga and
Buvik, 2013, Zubcic and Sims, 2011, Ntayi et al., 2010a, Thai, 2008b). Beside the complexity
of construction projects, lack of compliance with the public procurement regulatory framework
is attributed to ineffective sanctions in the construction industry (Rizk et al., 2018, Chan and
Owusu, 2017, Ameyaw et al., 2017, Bowen et al., 2012). Convincingly, imposing sanction on
staff implementing public road construction projects is inevitable to achieve compliance since
these projects are equally complex (Owusu et al., 2017). However, imposing legal sanctions to
improve regulatory compliance should be cautiously applied as it is not obvious to enhance
compliance (Gunningham and Kagan, 2005).
Whereas principal’s powers influence agent to comply in attaining set objectives,
corporate governance studies in Africa blame weak enforcement mechanisms affecting
compliance with the regulatory frameworks and failing government objectives (Owusu et al.,
2017, Okeahalam, 2004). Enforcing sanctions would ensure a transparent procurement process
that could allow bidders to verify an effective public procurement regulatory framework and
would encourage procurement officials to comply. For example, the Malaysian government is
under pressure to enforce strict penalties including cutting public officers’ salaries and
confiscating their property to enhance compliance with their public procurement regulatory
framework (Shu Hui et al., 2011). In USA, punitive actions including contract termination,
suspension, non-payment and use of performance bonds and securities have enhanced
compliance (Bartle and Korosec, 2003). Such punitive actions ensure compliance with
respective regulatory frameworks. For example, in Ghana, punishments of procurement
officers engaging in maverick buying has increased compliance with their public procurement
Act (Peprah, 2015). Correspondingly, enforcing strict punitive action have been recommended
for Nigeria’s construction industry (Zadawa et al., 2018b, Gambo et al., 2016).
Sanctions applicable to many fields are linked to agency theory where the agent is
required to comply with the principal’s instructions and meeting set goals (Van Slyke, 2007,
Saam, 2007). Sanctions in public construction projects would enforce compliance with a public
procurement regulatory framework since staff fear consequences when apprehended (Wirick,
2009). This is equally inevitable for implementing public road construction projects by
applying rigorous sanctions if public procurement regulatory framework is deliberately flouted
(Agaba and Shipman, 2007). Rigorous sanctions will protect the law from being a dead letter
48
and ensure value for money. Reports show that ineffective punitive measures affect compliance
in public procurement and that the Ugandan government has lost significant funds especially
in the public road construction subsector (PPDA Authority, 2009b, PPDA Authority, 2008).
This is worsened by laxity in enforcing sanction on public procurement stakeholders (Obanda,
2010). Convincingly, penalising the whole group/department where violation occurred
compels staff to work collectively by watching one another and ensure compliance (Kulp et
al., 2006). In public procurement, effective sanctions compel the staff to comply with a public
procurement regulatory framework and government’s assignments (Payan and McFarland,
2005). Whereas Gelderman et al. (2010) report that certainty and severity of sanctions do not
significantly influence compliance with regulatory framework, sanctions do compel public
officers to comply (Van Snellenberg and van de Peppel, 2002, Sutinen and Kuperan, 1999).
In a threat influence strategy, the principal imposes sanctions on the agent to reduce free
riding behaviour and help meet expectations (Rokkan and Buvik, 2009, Rokkan and Buvik,
2003, Kumar et al., 1998). Additionally, Venkatesh et al. (1995), advocates using threats,
promises and legalistic pleas involving formal laws, policies, norms, ethical code and written
contracts in ensuring compliance. Convincingly, compliance is enforced through coercive
sanctions (Scheer and Stern, 1992, Hunt et al., 1987). These sanctions are necessary in
compelling contracting parties to fulfil their obligations and avoid fines (Kumar et al., 1998,
Scheer and Stern, 1992). Threat based sanctions are widely applied in enforcing compliance
because employees fear to lose their jobs and to be imprisoned. Despite wide application of
sanctions, institutional theory posed that its effectiveness relies on organizational complexity
(DiMaggio and Powell, 2015). This caution is equally applicable to public road construction
project because they too are complex.
In Uganda, PPDA Act 2003 spells out punitive actions on defiant officers including fine
and imprisonment. However, credibility of such sanctions is still questionable since there are
numerous reports showing lack of compliance in the public road subsector losing significant
funds (Daily Monitor, 24th October 2016, Red Pepper, 21st October 2016, New Vision, 20th
October 2016). Human behaviour has been shown to be reinforced through rewards Braun
(2003) or sanctions (Mwakibinga and Buvik, 2013).
This dissertation was limited to sanctions by ascertaining its impact on compliance with
a public procurement regulatory framework governing public road construction projects
through the proposed hypothesis,
49
H4. Sanctions on staff in public road construction projects increases compliance with public
procurement regulatory framework
3.3.5 Perceived Inefficiency of public procurement regulatory framework and compliance This section discusses literatures relating to the perceived inefficiency of a public
procurement regulatory framework and compliance within a public procurement regulatory
framework. Inefficiency in the context of this dissertation refers to loopholes within a
regulatory framework that is manipulated for personal interest once noticed by unethical
stakeholders (Eeckhout and Munshi, 2005). A public procurement regulatory framework is
designed to facilitate procurement activities in an accountable and transparent manner to
achieve value for money (Agaba and Shipman, 2007). Consequently, implementing public road
construction projects requires an efficient public procurement regulatory framework to achieve
value for money. Notably, the Ugandan government has prioritised funding of the road
subsector for economic transformation (Ministry of Works and Transport, 2015). However,
detailed description of the regulatory framework is perceived as inefficient particularly
regarding implementation processes that question its effectiveness. Whenever the regulatory
framework is inefficient, stakeholders find difficulties in adopting it leading to compliance and
enforcement problems (Chitengi, 2018).
An efficient and effective public procurement regulatory framework is capable of saving
significant funds and better service delivery (Decarolis et al., 2018). Literature shows that the
nature of procurement irregularities depend on efficient procurement structures and regulatory
framework (Ameyaw et al., 2017, Shan et al., 2017). In support, institutional theory suggest
efficiency and effectiveness of institutional norms to achieve set objectives (Greenwood and
Hinings, 1988). In addition, institutional theory contends that organizational performance relies
on compliance with its norms (Greenwood and Hinings, 1988). Reports attribute a lack of
compliance with construction norms to perceived inefficiency of regulatory framework
(Styhre, 2011). Whenever regulatory framework is perceived ineffective in capturing a user’s
application, lack of compliance is prone to occur. For example, the European Union (EU)
directives governing public procurement among EU member states were flouted because the
directives were perceivably ineffective (Gelderman et al., 2006). Such inefficiencies equally
affect Uganda’s regulatory framework governing public road construction projects evidenced
with contradictory decisions by public officers. For example, contract price variations are
common in public road construction projects beyond allowable (20-30) % (PPDA Authority,
50
2003). Similarly, Love et al. (2019) reveals that 47% (5 out 10) of transport construction
projects deviate from approved budgets. While Park and Papadopoulou (2012), Flyvbjerg et al.
(2002) put the deviations at 9 out of 10 projects. Particularly 20% of road construction projects
suffer from cost escalations (Flyvbjerg et al., 2003, Flyvbjerg et al., 2002). This shows that
detailed guiding procedures to handle contract variations among other project implementation
issues are lacking.
Institutional theory reports that unprofessional behaviours occur when there is
inefficiencies within the institutional framework that affects its enforcement (Oliver, 1991).
Similarly, public procurement in East Africa is disorderly because of inefficient regulatory
frameworks that affect stakeholders’ compliance (Odhiambo and Kamau, 2003). Such
inefficiencies are evidenced with persistent procurement reforms by respective governments to
strengthen public procurement regulatory framework accordingly (Thai, 2010, Odhiambo and
Kamau, 2003). These persistent public procurement reforms in developing countries prove that
the regulatory framework governing public contracts is inefficient and ineffective,
consequently promoting lack of compliance through manipulation (Thai, 2008b, Odhiambo
and Kamau, 2003, Thai, 2001). This notion is supported by reports showing that inefficient
regulatory framework affects construction projects and poses interpretation difficulties (Owusu
et al., 2017, Zhang et al., 2016). Convincingly, infrastructure effectiveness rests in efficiency
of public procurement regulatory framework (Estache and Iimi, 2009).
In a PPDA consultative workshop with construction sector stakeholders, major
challenges affecting Uganda’s construction sector were identified. These challenges included
unclear National Construction Standards and regulations (PPDA Authority, 2008). The
challenges render the regulatory framework ineffective, consequently affecting
implementation of public road construction projects. Public procurement stakeholders find it
hard to comply with an ineffective regulatory framework due administrative issues and time
wastage that directly affect set targets (Gelderman et al., 2006, Boer and Telgen, 1998). This
is an area of concern since inefficiency of public procurement regulatory framework could
encourage unethical personnel to pursue selfish interests when implementing infrastructure
projects. Interestingly, infrastructure projects boost economic development that requires an
efficient regulatory framework (Bogiatzis et al., 2018, Decarolis et al., 2018, Shan et al., 2017).
51
Despite current public procurement reforms, inefficiencies still exist and this thesis aims
to ascertain how it effects compliance in public road construction projects through the proposed
hypothesis,
H5. Perceived inefficiency of public procurement regulatory framework reduces compliance
with a public procurement regulatory framework.
3.3.6 Contractors’ resistance and compliance This section discusses literatures relating contractors’ resistance to non-compliance with
public procurement regulatory framework by public officers and compliance with a public
procurement regulatory framework. In the context of this dissertation, contractor’s resistance
refers to contractor’s refusal to take unethical decisions of public officers regarding
procurement of public road construction projects. Implementing public road construction
projects requires complementary efforts from the implementation team and complying with
governing regulatory framework is inevitable (Scott, 2005). Convincingly, contractors’
professional skills would potentially influence project results (Hemström et al., 2017).
Surprisingly, institutional theory notes that different players with varying ambitions and means
of accomplishing tasks meet compliance with resistance (Kondra and Hinings, 1998).
Considering contractors’ perception, promoting compliance with the public procurement
regulatory framework demands contractors to take action against public procurement officers
deviating from a procurement regulatory framework (Gelderman et al., 2010, Gelderman et al.,
2006, Pachnou, 2005a). However, contractors’ knowledge over public procurement regulatory
framework governing implementation of public road construction projects determine their
action. Contractors use the knowledge to report deviant officers through right channels that
compels public officers to comply with the governing regulatory framework when
implementing these projects because they fear being exposed. However, contractors should be
careful to balance between winning and losing cases because of efficiencies within remedy
mechanism (Pachnou, 2005a, Braun, 2003).
Contractors are unwilling to take action against defiant public officers if the remedy
enforcement mechanism is weak. Perceived inefficiency of a public procurement regulatory
framework coupled with ineffective remedy mechanism encourages defiant public officers to
pursue unethical interests and not complying with a public procurement regulatory framework
governing public road project implementation. Strengthening the remedy mechanism would
encourage contractors to boldly report deviant public officers that would in turn promote
52
compliance with regulatory framework (Braun, 2003). Additionally, strengthening the remedy
mechanism would bar public officers from attempted manipulations and retaliating against
contractors in awarding future contracts (Pachnou, 2005a). A strong remedy mechanism is
necessary because public officers are charged with overseeing the whole procurement process
including contract initiation, award, implementation and project handover. Such
responsibilities make them powerful to victimize innocent contractors if not managed well in
a way that could affect compliance in public road construction projects.
This leads to propose the hypothesis,
H6. Contractors’ resistance to non-compliance with public procurement regulatory framework
by public officers increases compliance with public procurement regulatory framework.
3.4 Implications of Construction Project success Construction projects are unique, set up for a specified period, purpose and implemented
by a team of members from different organisations (Hussain et al., 2019, Samaraweera et al.,
2018, Papadonikolaki, 2018). These projects are heterogeneous and complex with various
activities to deliver specified objectives that require effective management for successful
implementation (Sutrisna et al., 2018, Papadonikolaki, 2018, Jari and Bhangale, 2013, Doloi
et al., 2011, Chan et al., 2002). Project success is evaluated on long-term, strategic term and
short-term outcomes (Gledson et al., 2018). Accordingly, project success is the successful
accomplishment of tasks/operations by meeting predetermined objectives including cost, time,
performance and safety (Tayeh et al., 2018, Gambo et al., 2016, Jari and Bhangale, 2013, Kog
and Loh, 2011, Chan et al., 2002, Lim and Mohamed, 1999). For example, successful project
implementation is achieved if employees comply with safety measures to avoid accidents and
ensure successful project performance without causalities (Love et al., 2016b). In addition, a
construction project is deemed successful if client satisfaction is achieved (Hussain et al., 2019,
Tayeh et al., 2018, Hwang et al., 2014, Kog and Loh, 2011, Shaban, 2008, Furneaux et al.,
2006, Pheng and Chuan, 2006, Chan et al., 2002).
Previously, Chan and Chan (2004), Sidwell et al. (2002), Atkinson (1999) presented the
Iron triangle performance indicators for construction projects as time, cost and quality (Love
and Smith, 2019, Sinesilassie et al., 2019). More recently, additional performance indicators
including safety, functionality and satisfaction have been established to determine construction
project success (Walker and Lloyd-Walker, 2015, Lam et al., 2008). However, from the
contractors’ view, a construction project is considered successful when it is implemented
53
within scope, time, cost and quality (Tayeh et al., 2018, Gledson et al., 2018, Zadawa et al.,
2018b). This equally applies to public road construction projects where the government would
consider these projects successful if they are implemented according to predetermined quality,
time and budget (Shivambu and Thwala, 2019, Kog and Loh, 2011). Disappointingly, cost and
schedule overruns derail satisfaction among stakeholders in transport infrastructure projects
(Love et al., 2015c). Hence, in the context of this thesis, successful implementation of public
road construction projects means that these projects are implemented according to
predetermined specifications, time and estimated costs. These indicators are chosen to
determine achievement of government goals and expectations because success means project
goals and expectations are achieved (Gudienė et al., 2013, Jari and Bhangale, 2013, Chan et
al., 2002).
Pertinent reports show that many construction projects have failed because they do not
comply with predetermined objectives including governing regulatory framework. For
example in Australia, non-compliant construction products account for 50% unsuccessful
project implementation (Australian Procurement & Construction Council, 2013). On average,
48% of infrastructure projects entirely are not completed on time, within estimated cost and
expected quality (Love et al., 2018a, Love et al., 2018b). A lack of compliance is affecting
Australian construction industry (Gambo et al., 2016, Brown and Loosemore, 2015). Further
international reports show that unsuccessful construction projects are caused by cost and
schedule overruns (Signor et al., 2019, Zadawa et al., 2018a, Liu et al., 2016, Shaban, 2008).
Specifically, overruns endemically challenge transport infrastructure projects (Signor et al.,
2016a, Love et al., 2015c). Cost escalation is a pervasive problem in the construction industry
that has affected public construction projects (Love et al., 2019, Ali et al., 2018b, Signor et al.,
2017, Signor et al., 2016a, Flyvbjerg et al., 2003). Scholars are now calling for strict
enforcement of regulatory framework in a transparent manner for successful implementation
of construction projects (Signor et al., 2019, Ali et al., 2018b, Ameyaw et al., 2017). Given the
complexity of construction projects, poor performance of infrastructure projects require an
interwoven of factors to determine their successful implementation (Sinesilassie et al., 2019,
Love et al., 2018b). Accordingly, seven probable success factors are discussed in the following
subsections (3.4.1 to 3.4.7).
3.4.1 Compliance with public procurement regulatory framework and Project success This section discusses literatures relating compliance with public procurement regulatory
framework to the success of public road construction projects. Public road construction projects
54
are temporary unique endeavours that should comply with selected performance policies for
successful implementation (Zadawa et al., 2018b, Parker and Nielsen, 2017, Ogunlana et al.,
2003). For example, complying with contract specifications and scope of works ensures
successful project implementation (Hussain et al., 2019, Gambo et al., 2016, Snyder, 2013).
However, for compliance to ensure project success, project inspections and audits are crucial
(Snyder, 2013). Convincingly, compliance with a regulatory framework significantly
influences successful performance of construction projects (Zadawa et al., 2018b, Zadawa et
al., 2018a, Ameyaw et al., 2017, Tabish and Jha, 2011). Disappointingly, road construction
stakeholders are dissatisfied with project cost and schedule overruns affecting 30% of roads
and bridges performance (Love et al., 2015c, Ford, 2011). Such overruns are attributed to lack
of compliance with project requirements that equally affect government satisfaction with
implementing road construction projects. Yet satisfaction is a key project success factor
(Ameyaw et al., 2017, Hwang et al., 2014, Sadeh et al., 2000). The government would be
satisfied with public road construction projects if they were implemented according to project
specifications, budget and time (Gambo et al., 2016, Dvir and Lechler, 2004).
Lack of compliance arising from mistrust amongst contractors competing for public
construction projects accounts for unsuccessful implementation of these projects
(Samaraweera et al., 2018, Papadonikolaki, 2018, Ntayi et al., 2010b). This attitude coupled
with lack of commitment and cooperation contributes to continuous cost and schedule overruns
in road construction projects, thereby affecting successful project implementation (Munyasya
and Chileshe, 2018, Zadawa et al., 2018b, Ameyaw et al., 2017, Kaliba et al., 2009). Indeed,
lack of cooperation among parties involved in projects has been found to affect the construction
industry (Papadonikolaki, 2018, Gambo et al., 2016, Adafin et al., 2015, Kim and Huynh,
2008). However, it is imperative for infrastructure stakeholders to cooperate and ensure cost
effective and timely implementation of transport infrastructure projects (Love et al., 2018b).
Notably, cost overruns in road construction projects have been found to affect public sector
performance (Love et al., 2019, Odeck, 2004). In addition, these overruns affect productivity
and performance of public construction projects rendering them unsuccessful (Shan et al.,
2020b, Zadawa et al., 2018a, Love and Smith, 2016). Whenever a road construction team does
not comply with project specification, the quality of these projects is affected and yet quality
defines successful construction project performance (Hussain et al., 2019, Marnewick et al.,
2018, Rwelamira, 1999). A lack of compliance with project requirements affect successful
implementation of construction projects. For example, the Ugandan President attributed
55
delayed road construction projects in Kanungu district to lack of compliance characterized by
irregularities (Red Pepper, 2018).
Furthermore, lack of compliance morfed into poor quality workmanship significantly
contributes to reworks in construction projects (Zadawa et al., 2018b, Love et al., 1998).
Reworks is an indicator of poor construction quality rendering the project unsuccessful since
it measures what correction are required to comply with project specifications (Love and Smith,
2019, Love et al., 2015a). Such project failures are prominent in road construction projects due
to a lack of compliance with governing regulatory framework, quality deviations, failures and
defects accounting for 5 – 20% of the project contract value (Love and Smith, 2019, Love et
al., 2015c, Love, 2002). Initiating an effective regulatory framework to sustain compliance
within the construction industry is important for successful implementation of construction
projects (Chileshe et al., 2018). Such an effective regulatory framework would deter fraudulent
practices challenging compliance and performance of the construction industry (Zadawa et al.,
2018a).
Public road construction projects use public funds and these projects are successful if
they meet government goals aligned with public expectation. Additionally, these projects are
successfully implemented if they comply with governing regulatory framework including
contract terms and conditions outlined in a signed governing contract. The terms and conditions
include among others, project specifications, quality, cost and time (Gambo et al., 2016).
Whereas scholars have considered various success factors in the construction industry, less
attention was paid to compliance with public procurement regulatory framework in
construction industry particularly when implementing public road construction projects.
Accordingly, this dissertation determines the effect of compliance with public
procurement regulatory framework on the successful implementation of public road
construction projects through the proposed hypothesis,
H7. Compliance with public procurement regulatory framework in public road construction
projects leads to project success
3.4.2 Familiarity with public procurement regulatory framework and Project success This section discusses literatures relating familiarity with public procurement regulatory
framework to the successful public road construction projects. As defined in section 3.3.1, staff
familiarity extends beyond academic qualifications and refers to one’s knowledge of the entire
56
regulatory framework including process and procedures (Hunja, 2003). Accordingly, staff
implementing public road construction projects should be knowledgeable with project
activities to successfully implement these projects. Hence, for the project to be successful,
project stakeholder need to understand detailed implementation process (Gambo et al., 2016).
Complex construction projects bring together different stakeholders with varying
perceptions and attitudes when implementing different projects (Tayeh et al., 2018). This calls
for careful planning and control right from project initiation stage to completion by making the
project well defined and recruiting competent staff to implement these projects (Gambo et al.,
2016, Gudienė et al., 2013, Doloi et al., 2011). Staff competence is enabled through specified
training to enhance their familiarity with project requirements (Decarolis et al., 2018, North,
2016). Continuously enabling staff competence through training is equally important for
implementing public road construction projects (Zadawa et al., 2018a, Shaban, 2008). This is
because poor training accounts for flaws in the construction sector (Hussain et al., 2019,
Othman et al., 2018). Enabling staff competence ensures accumulated knowledge and expertise
in project implementation that creates competitive advantage and enhancing project success
(Gambo et al., 2016, Love et al., 2015a, Swart and Harcup, 2013, Prencipe and Tell, 2001,
Argote and Ingram, 2000).
Implementing public road construction projects successfully requires staff familiarity
with project requirements. For example, familiarity with ways through which things are done
make work easier and completed within time (Sidwell et al., 2002). Furthermore, successful
implementation of public construction projects requires the project implementation team to
understand its scope with clear governing regulatory framework to avoid manipulations
(Tabish and Jha, 2015, Tabish and Jha, 2011). The construction team should be skilful and
knowledgeable to successfully implement construction projects within specified parameters
Jari and Bhangale (2013) as lack of understanding and knowledge affects project
implementation (Shan et al., 2017, Hwang et al., 2014). Indeed, ignorance is detrimental to
successful implementation of construction projects (Ika, 2018, Flyvbjerg, 2016). This is
attributed to lack of education and training affecting sustainability in the construction sector
(Abduh et al., 2018, Abdullahi et al., 2017). Scholars are calling on management to improve
staff knowledge in the construction sector for successful implementation of construction
projects (Munyasya and Chileshe, 2018). This is necessary because most government agencies
and stakeholders find it easier and effective to implement projects using procurement methods
57
they understand. Ideally reinforcing staff skills and expertise enhances their familiarity with
project requirements that are paramount in successful implementation of public road
construction projects (Cullen et al., 2014, Gudienė et al., 2013).
Previous studies used familiarity to explore its effect on compliance with regulatory
framework in public procurement (Eyaa and Oluka, 2011, Gelderman et al., 2006). However,
these studies paid less attention on the effect of familiarity in implementing public road
construction projects. Accordingly, this thesis bridges the gap by determining how familiarity
affects successful implementation of public road construction projects through the following
hypothesis,
H8. Familiarity with public procurement regulatory framework governing public road
construction projects leads to project success
3.4.3 Monitoring activities and project success This section discusses literatures relating monitoring activities to successful
implementation of public road construction projects. North (2016) noted that monitoring
activities is an organizational governance mechanism that ensures that staff meet set goals. This
notion is supported by Schapper et al. (2006) reporting that regular monitoring of budgets for
respective projects and taking corrective actions is important for successful implementation of
these projects. Indeed, successful performance of construction projects rely on regular
monitoring of activities undertaken (Shan et al., 2017, Obanda, 2010, Lam et al., 2008, Reeves,
2008, Ng et al., 2002). For example, successful performance of the United States’ construction
sector is attributed to effective monitoring and tracking of contractors thus avoiding shoddy
workmanship, cost overruns and corruption (Bartle and Korosec, 2003). In China, monitoring
underground construction projects was found to enhance successful implementation of these
projects (Zhou et al., 2019). Recent studies emphasise monitoring mechanisms to successfully
implement quality construction projects (Lapidus and Yves, 2018, Othman et al., 2018, Ali et
al., 2018b, Kog and Loh, 2011, Shaban, 2008). These mechanisms encourage total supervision
and performance monitoring of construction projects starting with contractors by reducing risks
that typically antagonise successful project implementation (Hussain et al., 2019, Topchiy et
al., 2018, Love et al., 2015c). Furthermore, effective monitoring of irresponsible construction
staff ensures successful implementation of public construction projects (Love et al., 2016b).
Road construction projects in Uganda are monitored by different agencies including
Ministry of Works and Transport, Public Procurement and Disposal of Public Assets Authority,
58
Uganda National Roads Authority among others. However, policy makers should clearly define
roles for each agency to avoid conflict and confusion. Clearly, defining supervision and
monitoring responsibilities is crucial to successfully implement large and complex construction
projects (Rajab and Eydgahi, 2019, Owusu et al., 2017, Jha and Misra, 2007, Thai, 2001).
Uganda’s construction industry is challenged with failed projects due to ineffective monitoring,
lack of commitment and cooperation amongst contractors competing with one another (Ntayi
et al., 2010b, PPDA Authority, 2008). Despite Tabish and Jha (2015) study reporting
insignificant relationship between monitoring activities and the successful implementation of
public construction projects, agency theory encourages monitoring mechanism as a governance
tool (Van Slyke, 2007). This assertions are in line with reports contending that whereas (42-52
%) of costs are incurred in project inspection, direct monitoring of construction projects is an
effective method of successfully implementing these projects (Woo et al., 2019).
Hence, this thesis investigates the relationship through the following hypothesis.
H9. Monitoring activities on public road construction projects leads to project success
3.4.4 Professionalism of staff and project success This section discusses literatures relating professionalism of staff to success of public
road construction projects. Professionalism refers to one’s competence in skills, special
knowledge with experience and a member of a professional body exhibiting an ethical code
(Watson, 2002). Ethical codes are vital in controlling staff in the construction industry Owusu
et al. (2017) and professionalism is inevitable for public road construction projects Ogunlana
et al. (2003) that requires using staff with competent skills, ethical, experienced and
knowledgeable to successfully implement these projects (Hussain et al., 2019, Decarolis et al.,
2018, Gambo et al., 2016, DiMaggio and Powell, 2015). Giroud et al. (2018), Pheng and Chuan
(2006) noted that professional competence is essential for successful performance and it is
achieved through the training, coaching, mentoring, developing and retaining of a competent
workforce (Walker and Lloyd-Walker, 2015, Obanda, 2010, Witting, 2005). In addition,
professional experience is vital for successful construction industry (Hwang et al., 2014).
Interestingly, lack of construction expertise affects quality of construction projects in Australia
(Rafferty and Toner, 2018). Consequently, the Australian government has recommended all
public agencies handling construction projects to have professionals with required skills and
expertise for successful project implementation (Furneaux et al., 2006, Australian Procurement
& Construction Council, 2002). Such recommendations were meant to minimise pushing risks
59
to contractors and relying on costly external consultants especially in managing capital works
(Furneaux et al., 2006).
Considering professionalism from project management perspective, staff with technical
skills from relevant qualifications and practice, need specialised skills for successful project
implementation (Walker and Lloyd-Walker, 2015, Gudienė et al., 2013). Accordingly,
specialised skills should be determined in the tendering process for each project (Runeson and
Skitmore, 1999). This would ensure that the project has the right and committed team for
successful implementation (Kagioglou et al., 2000). Wall and Ahmed (2008) noted that staff
skills and experience are of paramount importance for a successful construction industry.
Because professionalism ensures timely completion of construction projects that are within
estimated budget (Wall and Ahmed, 2008). It has been found that inflated project cost and
substandard works underpin lack of professionalism in the construction sector (Ameyaw et al.,
2017, Signor et al., 2016b). Whereas inflated project cost is partly blamed on construction
design variations, professional workforce could reduce such variations to successfully
implement construction projects (Xiao and Proverbs, 2003).
Lack of professionalism is a barrier to project success according to Um and Kim (2018)
that is globally challenging the construction industry (Shan et al., 2020a). For example,
shortage of a skilled, qualified and experienced workforce in South Africa, Jordan, Gaza strip,
and India among others have been found to affect project success (Tabish and Jha, 2015, Sweis
and Bisharat, 2014, Enshassi et al., 2009, Shaban, 2008, Faridi and El‐Sayegh, 2006, Hanson,
2006). Equally, Uganda’s construction industry is unsuccessful because it is marred by an
incompetent workforce lacking necessary skills in construction due to poor training and
recruitment methods (Alinaitwe et al., 2007). Accordingly, Uganda’s construction stakeholders
are calling for use of expertise and professionals when implementing construction projects
(PPDA Authority, 2008). Professional management of construction projects is required to
manage quality, cost and time for a successful construction industry (Woo et al., 2019). Lack
of professionalism is acerbated by poor employment terms forcing few competent staff in road
construction projects to seek better opportunities in the private sector and overseas. These
incompetency affect productivity and construction performance calling for a learning culture
that transforms errors into experience by encouraging no blame philosophy in team work (Love
and Smith, 2016). In addition, such a culture accumulates knowledge, experience and creates
competitive advantage enhancing project success (Love et al., 2015a, Swart and Harcup, 2013,
60
Prencipe and Tell, 2001, Argote and Ingram, 2000). Thus, scholars are now calling for
experienced and highly qualified staff to successfully implement construction projects (Tayeh
et al., 2018, Gambo et al., 2016, Jari and Bhangale, 2013, Kim and Huynh, 2008).
This leads to propose the following hypothesis,
H10. Professionalism of staff in public road construction projects leads to project success
3.4.5 Perceived inefficiency of public procurement regulatory framework and project success This section discusses literatures relating to perceived inefficiency of public procurement
regulatory framework in public road project success. A clear and simple regulatory framework
governing complex public road construction projects is inevitable for road subsector players to
understand and interpret easily (See Latham and Egan reports) (Kagioglou et al., 2000). This
is important because it limits unethical manipulators to drive their ambitions progressively
(Shan et al., 2017, Saam, 2007). Furthermore, an efficient regulatory framework facilitates a
timely road implementation process by eliminating frequent legal consultation with legal
fraternity for interpretation. Such a framework would ensure a clear scope of construction
projects which is important for successful project implementation (Tayeh et al., 2018).
Convincingly, inefficient public procurement regulatory frameworks affect successful
implementation of procurement projects in East Africa (Odhiambo and Kamau, 2003). Further
international literature shows that inefficient regulatory framework affects construction
projects (Owusu et al., 2017, Ameyaw et al., 2017, Zhang et al., 2016, Brown and Loosemore,
2015, Le et al., 2014b, Le et al., 2014a). This view is supported by recommendations for a
proper regulatory framework to govern construction industry with appropriate enforcement
mechanism (Zadawa et al., 2018b, Shaban, 2008).
A pertinent example in Uganda’s construction sector showed that the sector is challenged
with unclear National Construction Standards and regulations (PPDA Authority, 2008). These
challenges underpin an unsuccessful construction sector because public procurement
stakeholders find difficulties in complying with an ineffective regulatory framework due to
administrative issues and time wastage in meeting targets (Gelderman et al., 2006, Boer and
Telgen, 1998). In essence, inefficient regulatory framework emanating from poor quality
legislative actions cause difficulties and inconsistencies in the construction sector (Chitengi,
2018). Additionally, inefficient regulatory framework creates administrative barriers that affect
implementation and enforcement of construction projects (Chitengi, 2018). Conversely,
61
inefficiencies within the construction sector account for delayed and costly construction
projects (Othman et al., 2018, Gambo et al., 2016). Perceived inefficient regulatory frameworks
equally affect implementation of public road construction projects since it is the project-
governing instrument. This suggests a need for clarity and efficiency to eradicate loopholes
and enhance successful implementation of these projects. This need is vital because an efficient
regulatory framework would enable construction sector players to manage project
implementation with greater success (Othman et al., 2018, Zadawa et al., 2018b).
Accordingly, this dissertation addresses this need by determining the role of perceived
inefficiency with regulatory framework in successful implementation of public road
construction projects through the proposed hypothesis,
H11. Perceived inefficiency of public procurement regulatory framework reduces project
success
3.4.6 Contractors’ resistance and project success This section presents literature relating to contractors’ resistance to non-compliance with
public procurement regulatory framework and the success of public road construction projects.
In the context of this thesis, contractors’ resistance refers to their refusal to accept bad decisions
of public officers regarding project implementation. As observed earlier, different public road
construction stakeholders come to accomplish specific assignments and as they do so, they may
have conflicting interest contrary to project success (Wirick, 2009, Wright et al., 2001). This
notion is emphasised by institutional theory noting that compliance meets resistance from
different players with varying ambitions and means of successfully accomplishing project tasks
(Babalola et al., 2016, Kondra and Hinings, 1998). Ideally, project success is about teamwork
through coordination whereby contractors’ commitment and cooperation to fulfil their
obligations and resisting bad decisions would lead to successful implementation of
construction projects (Babalola et al., 2016, Ntayi et al., 2010b). Interestingly, coordination
among construction participants is significant in project success by reducing risks associated
with cost estimation (Hussain et al., 2019, Adafin et al., 2015, Shaban, 2008). This is in line
with Latham 1994 recommending openness, cooperation, trust, honesty, commitment and
mutual understanding among team members for a successful construction industry (Love et al.,
2015c). Accordingly, successful implementation of road construction projects is crucial for
contractors. Because they compete for limited government contracts and yet winning future
contracts is tagged on previous performance. Notably, contractors’ capability and performance
62
is inevitable for successful implementation of public construction projects (Hussain et al., 2019,
Doloi et al., 2011).
Reports show that substandard works are attributed to little funds left for contractors to
implement public construction projects after public officers take lamp sum bribes (Daily
Monitor, 12th March 2019, Agaba and Shipman, 2007). Further in international literature,
contractors bribe public officials by paying 10-20% of contract price to secure public contracts
(Ameyaw et al., 2017). However, in most cases, substandard works cost contractors by losing
future contracts. To mitigate this, compliance with regulatory framework is inevitable. This
has prompted contractors’ actions against deviant public officers for a successful public
procurement (Gelderman et al., 2010, Gelderman et al., 2006, Pachnou, 2005a). Such actions
to resist bad decisions are equally important in successful implementation of public road
construction projects. However, contractors’ knowledge of the entire regulatory framework
governing these projects is key. Being knowledgeable enables contractors to resist public
officers and compelling them to adhere to project requirements. Whereas previous studies
determined project success factors (Love et al., 2016a, Kaliba et al., 2009, Lam et al., 2008,
Shaban, 2008, Atkinson, 1999), less attention was paid to contractors’ resistance in successful
implementation of construction projects.
This dissertation bridges the gap by ascertaining whether contractors’ resistance would
lead to the successful implementation of public road construction projects through the proposed
hypothesis.
H12. Contractor’s resistance to non-compliance with public procurement regulatory
framework by public officers in public road construction projects leads to project success
3.4.7 Sanctions on staff and project success This section presents literature-relating sanctions on staff to project success. Sanction are
coercive strategies involving threats and penalties levied on staff working contrary to
predetermined targets (Zadawa et al., 2018b, Hartley, 2009). Despite mixed reaction on using
sanctions to achieve these targets, they are widely applied to militate deviant staff (Scheer and
Stern, 1992). Applying sanctions in public road construction projects is important given the
current wave of procurement irregularities (New Vision, 28th July 2016). Because public road
construction projects are setup for a specific purpose using public funds, the government should
enforce strategies that would successfully implemented these projects in an accountable and
transparent manner. Extant literature shows that successful implementation of road
63
construction projects requires punitive measure to achieve set targets (Paulson Jr and Fondahl,
1983). This notion is supported by Ministry of works and Transport (2012) calling for strong
enforcement mechanisms involving sanctions to successfully implement road construction
projects. Such calls could sustain an effective and efficient transport sector with sound transport
policy to achieve government goals. Correspondingly, failed construction projects are a
consequence of either laxity in enforcing punitive measures or ineffective sanctions that
encourage unethical acts among project implementers (Zadawa et al., 2018b, Rizk et al., 2018,
Owusu et al., 2017, Ameyaw et al., 2017, Saam, 2007, Runeson and Skitmore, 1999).
Public road construction projects involve multiple stakeholders and co-funded by
multilateral bodies including World Bank, International Monetary Fund (IMF) among others
including respective governments. However, implementing these projects requires strict
punitive actions against perpetrators to avoid suspension of funding by respective international
bodies (Zadawa et al., 2018b, Ali et al., 2018b, Chan and Owusu, 2017, Gambo et al., 2016).
For example in Bangladesh, the World Bank suspended funding of fourteen highway road
construction projects as a punitive measure to safeguard public funds (Mahmood, 2010). The
World Bank noted that failure to impose sanctions on public procurement violators account for
US$100 million (AU$136M) financial loss annually (Mbabazi et al., 2015). To mitigate against
these losses and reduce unacceptable practices, the Australian construction sector emphasised
enforcing sanctions to successfully implement construction projects (Hartley, 2009). In
addition, institutional theory suggests effective sanctions to correct deviant behaviours for
successful organizational performance (North, 2016, Oliver, 1991). This suggestion is equally
inevitable for implementing Uganda’s public road construction projects.
The road subsector is Uganda’s major transport mode providing goods and services
(Ministry of Works and Transport, 2014). Currently the Ugandan government has embarked
on massive economic development through prosperity for all and modernisation of agriculture
among other programs. However, one key success factor in these programs is the public road
construction projects that have to facilitate these programs in order to achieve government
objectives. Accordingly, imposing stringent actions when implementing these projects is
necessary to achieve government objectives and value for money (Kakitahi et al., 2016,
Ameyaw et al., 2012, Kenny, 2007). Interestingly, tough sanctions including forfeiture of
contract and exclusion of companies for future bidding are proposed for an effective
construction industry (Sohail and Cavill, 2008).
64
This dissertation determines the relationship between sanctions on staff and project
success through the proposed hypothesis,
H13. Sanctions on staff in public road construction projects leads to project success
3.5 Mediation effects and Hypotheses This section presents literature on mediation effects and extends further by examining the
mediating role of compliance with public procurement regulatory framework between six
compliance factors and public road construction project success. It ends by developing six
mediation hypotheses that were tested for statistical significance. Many researchers are mainly
concerned with predicting direct relationships among study constructs and overlook any
mediation effect (Carrión et al., 2017, Nitzl et al., 2016). However, there is need to unearth an
underlying criterion explaining how variables are associated beyond simple relationship
prediction (Hayes and Scharkow, 2013, Fairchild and McQuillin, 2010, Cheung and Lau,
2008). Because ignoring mediation effects creates bias in interpreting results when a certain
variable does not influence another variable directly and researchers assuming it is irrelevant
in answering a research question completely (Nitzl et al., 2016). Mediation testing helps in
further examining how variables are related (Hayes and Scharkow, 2013, Fairchild and
McQuillin, 2010, MacKinnon et al., 2002). In other words, mediation provides an
indispensable scientific understanding of the mechanism intervening in the relationship
between independent and dependent variables (Memon et al., 2018, Aguinis et al., 2017,
Carrión et al., 2017). Convincingly, mediation has been shown as the significant relationship
between independent and dependent variable that is partially or fully explained by the
mediating variable in a specified causal order (Mojtahedi and Oo, 2017, Miller et al., 2007,
Mathieu and Taylor, 2006).
In many studies, scholars use the terms mediator and moderator interchangeably
however, researchers should clearly distinguish mediation from moderation at the research
onset (Hayes, 2012, Garcia and Kandemir, 2006, Muller et al., 2005, Baron and Kenny, 1986).
Ideally, the goal of mediation is to determine how an independent variable influences
dependent variables through a mediating variable (Hayes and Rockwood, 2017, Hayes and
Preacher, 2014, Hayes, 2012). Despite mediation studies increasingly gaining momentum,
mediation is a new arena in the construction industry and public procurement. Consequently,
little is known about the mediating role of compliance with public procurement regulatory
framework in the construction industry and particularly in the road construction subsector.
65
Convincingly, compliance with regulatory framework has been shown to significantly
influence successful implementation of construction projects (Tabish and Jha, 2011).
Accordingly, this thesis was limited to mediation testing in road construction projects involving
eight factors. Particularly the thesis was concerned with establishing whether compliance with
public procurement regulatory framework mediates the relationship between six probable
compliance factors and the success of public road construction projects in Uganda.
Researchers should explicitly conceptualise the relationship through hypotheses before
testing mediation (Memon et al., 2018). Mediation effect is vital when an identified third
variable contributes an effect between two existing variables as illustrated in Fig 3.2. In
addition, the two existing variables (independent and dependent) should have a strong
relationship. Under this consideration, the mediating variable influences the relationship
between independent and dependent variables that is measured by the predictive power of
coefficient of determination (R2) (Baron and Kenny, 1986). However, partial mediation testing
requires sufficient coefficient of determination Cheung and Lau (2008), Mathieu and Taylor
(2006), MacKinnon et al. (2002) with significant relationship between the six compliance
factors and project success (Hayes, 2009, Preacher and Hayes, 2004). Furthermore, mediation
is also possible if the indirect relationship between the six factors and compliance is significant
as well as compliance and project success (Tabassi et al., 2014, MacKinnon et al., 2002).
Significance of regression coefficients and effect size were tested through multiple regressions
that assumed compliance was not caused by project success (MacKinnon et al., 2002). Ideally,
these causal steps coupled with mediation assumptions should be satisfied before mediational
tests. Surprisingly, majority of researchers violate these steps (Shaver, 2005).
Figure 3.2: Mediation illustration
b c
a
According to Baron and Kenny, there are two types of path relationship. Compliance factors
(A) can directly cause project success (C) demonstrated by path <a> or indirectly cause C
through compliance (B) indicated by path <b> and <c>.
A
B
C
66
Mediation is possible when the following assumptions are satisfied (Preacher and
Leonardelli, 2001, Baron and Kenny, 1986).
1. Variations in the levels of independent variable should be significantly accountable to
variations in the mediating variable. This implies that the six compliance factors should be
significantly related to compliance variable.
2. Variations in mediating variable should significantly account for variations in dependent
variable. Implying that compliance with public procurement regulatory framework and project
success should be significantly related.
3. When path <b> and <c> are controlled, previous significant relationship between
independent and dependent variables should be zero for perfect (Full) mediation. Full
mediation can occur when the mediator explains total effect size (Hayes and Rockwood, 2017).
This implies that direct relationship between independent and dependent variables is
insignificant while partial mediation occurs when the mediator significantly accounts for a
portion of total effect size (Hayes and Rockwood, 2017, Zhao et al., 2010, Mathieu and Taylor,
2006, James et al., 2006). However, in the real world, it is not possible for a single perfect
mediator. In this regard, the thesis sought a significant reduction in the direct relationship
between A and C rather than eliminating it to zero (Mathieu and Taylor, 2006). This implies
that compliance factors and project success should be significantly related. Interestingly, there
is a lack of statistical evidence on assumptions surrounding mediation tests (James et al., 2006,
Frazier et al., 2004).
The theoretical ground enables a conceptual model for cross-sectional research
specifically demonstrating causal relationship to test mediation effects (Mitchell and James,
2001, Sutton and Staw, 1995, Whetten, 1989). Implying that the direct relationship between
compliance factors (familiarity, monitoring activities, professionalism, sanctions, perceived
inefficiency and contractors’ resistance) and project success should be significantly related
without involving compliance (mediating variable) (Mathieu and Taylor, 2006). In addition,
on introducing compliance, indirect path should also be significant (Hair et al., 2016, Hair et
al., 2014, Preacher and Hayes, 2004, Shrout and Bolger, 2002). This process aims at
establishing the magnitude of both direct effect between the six compliance factors and project
success as well indirect effect between compliance factors through compliance and project
success.
67
In practice, mediation testing is performed via two approaches namely; Structural
Equation Modelling approach (SEM), and Baron and Kenny approach. Despite ongoing debate,
none of the approaches is superior to the other (James et al., 2006). The two approaches’
baseline for mediation differ with SEM based on full mediation while Baron and Kenny
focused on partial mediation. Interestingly, Hayes and Rockwood (2017) noted that statistical
tools aid researchers to draw conclusions amidst uncertainty and yet these tools make mistakes
since they are fallible in nature. Accordingly, researchers should clearly state whether they are
testing for full or partial mediation. Problems with mediation tests arise due to many statistical
approaches. However, these approaches are similar on most aspects but differ on few (James
et al., 2006). Many researchers have continuously used hierarchical regression approach to
examine significant mediation effects based on Sobel test with more than 2,000 citations
(Bolin, 2014, Cheung and Lau, 2008, MacKinnon et al., 2002). While Zhao et al. (2010) puts
the figure to 12,688 citations with an annual increase of 1,762 in 2009. While other reports
express credibility of Baron and Kenny mediation procedures with 8,120 citations (Bontis et
al., 2007).
Conversely, the popularity of the Sobel test has seen many research projects rejected for
not applying Baron and Kenny mediation approaches (Zhao et al., 2010, Cheung and Lau,
2008). Surprisingly, a majority of these mediation studies are in behavioural sciences, social
sciences, marketing and business research fields (Hayes, 2012). Hence, this dissertation bridges
the gap by considering mediation effects in the field of construction management and public
procurement. As part of this thesis, partial mediation testing was sequentially performed
corresponding to the six compliance factors including familiarity, monitoring activities,
professionalism, sanctions, perceived inefficiency and contractors’ resistance following Baron
and Kenny assumptions in conjunction with a Sobel test (Preacher and Leonardelli, 2001,
Baron and Kenny, 1986, Sobel, 1982). This approach was adopted because it is the best
alternative, its causal steps are widely applied, with greater statistical power, clearly
demonstrating conceptual linkage between each hypothesised relationship and their respective
statistical tests (Memon et al., 2018, Bontis et al., 2007, MacKinnon et al., 2002, Shrout and
Bolger, 2002). This leads to six hypotheses corresponding to the six compliance factors
grounded in theoretical foundation and discussed in the literature review.
H14. Compliance with public procurement regulatory framework mediates the relationship
between familiarity with public procurement regulatory framework and project success.
68
H15. Compliance with public procurement regulatory framework mediates the relationship
between monitoring activities in public road construction and project success.
H16. Compliance with public procurement regulatory framework mediates the relationship
between professionalism of staff in public road construction projects and project success.
H17. Compliance with public procurement regulatory framework mediates the relationship
between sanctions on staff in public road construction projects and project success.
H18. Compliance with public procurement regulatory framework mediates the relationship
between perceived inefficiency of public procurement regulatory framework and project
success.
H19. Compliance with public procurement regulatory framework mediates the relationship
between contractors’ resistance to non-compliance with public procurement regulatory
framework by public officers and project success.
3.6 Selection of study variables Evidence from literature summarised in appendix F, shows that over 700 peer reviewed
journals and public documents were reviewed and found relevant to answer the research
question. Whereas different studies have used different factors to explain compliance and
project success, it is noteworthy that most studies were tailored to specific scenarios with some
repetitive factors, for example;
Participant’s satisfaction, user satisfaction and environmental performance collectively
described as satisfaction when determining project success. Satisfaction with project
success comes when the project is completed within time, budget and conforms to
project specifications (Quality).
Training, knowledge, academic qualification, skills and experience leads to staff
competence that describes staff professionalism and familiarity.
Professionalism encompass competence, ethical behaviour/code, corruption, integrity,
transparency, accountability, fraudulent practices, opportunism, perceived gain, self-
interest, political influence and influence peddling. All these attributes together
determines one’s professionalism in doing the right thing.
69
Familiarity with the regulatory framework encompasses awareness of, limited knowledge
of the law/Act, clarity and communications as stressed in literature by different scholars
describing different phenomena.
Audits, inspections, E-procurement system and reporting collectively described
monitoring activities. Different organisations applied varying monitoring techniques as
explained by scholars to enhance compliance, successful implementation of projects
and meeting set objectives.
Enforcement, policing, threats, punishments and control collectively describe sanctions.
Effectiveness of sanctions relies on mode of enforcement by respective organisations
to achieve desired objectives.
Through literature review, twelve compliance factors and seventeen project success
factors were established although some of them are used interchangeably depending on study
phenomena. This dissertation compressed them analytically into six and seven factors to
determine compliance with public procurement regulatory framework and success of public
road construction projects respectively as follows,
Familiarity with public procurement regulatory framework.
Monitoring activities.
Professionalism of staff.
Sanctions on staff.
Perceived inefficiency of public procurement regulatory framework.
Contractors’ resistance to non-compliance.
These factors were considered because they are comprehensive and include other factors
to avoid them being discarded. For example, organizational pressure, institutional factors and
organizational incentives are governance mechanisms explained through supervision,
monitoring, coordination, administrative pressure, motivation, punishments among others.
These were covered under either sanctions on staff or monitoring activities. Perceived gains,
irregularities, fraudulent practices and corruption are covered under professionalism of staff.
Supplier resistance refers to supplier demand for fair and transparent procurement process
through retaliating bad decisions of public procurement officers (Gelderman et al., 2010).
70
Supplier resistance was modified to mean contractors’ resistance to fit current study covering
public road construction projects where government undertakes public road construction
projects in the public interest. These projects are considered successful when the project
conforms to predetermined specifications, terms and conditions, delivered on time, within
budget, of right quality, safe to use and capable of meeting government objectives. These
indicators were compressed to time, cost and quality (specifications) and selected to measure
public road construction project success (Dvir and Lechler, 2004, Atkinson, 1999).
Relatedly, sanctions not rewards were used to establish impact on compliance with public
procurement regulatory framework and project success. Dropping rewards, was based on
Maslow’s hierarchy of needs stating that satisfying human beings is hard to achieve
(Udechukwu, 2009, Wachter, 2003). Furthermore as a rational human being, meeting set
targets is a positive self-motivation leading to promotion for hard work contrary to non-
achieving due to unprofessional behaviour that attracts sanctions (Mwakibinga and Buvik,
2013). Familiarity with public procurement regulatory framework was determined through
staff masterly knowledge on public road construction projects and governing regulatory
framework. Government can reinforce familiarity and professionalism by investing in staff
competence through education, training and orientation (DiMaggio and Powell, 2015,
Kaluarachchi and Jones, 2007). Finally, perceived inefficiency of public procurement
regulatory framework aimed at ascertaining effectiveness of the regulatory framework
governing public road construction projects. Selected factors underpinned this dissertation by
enabling clear understanding, interpretation and generalising study results. However, little is
known about combined use of these factors to explain compliance with public procurement
regulatory framework and successful public road construction projects. Hence, this gap
motivated the thesis to provide scholarly contribution and expand the body of knowledge
generally and particularly in public procurement and construction management.
3.7 Justification for used study variables
This section presents evidence justifying why the current dissertation used the eight
factors as well as considering mediation tests. Throughout the literature review, different
authors were found to establish common compliance factors and attempted to solve lack of
compliance without considering project success in the road construction sub-sector. Despite
their efforts, a lack of compliance persists in public procurement with failing construction
projects. A few studies built their argument on agency theory with cross-sectional research
71
design but different results emerge. However, there are limited compliance studies in
construction industry particularly in the public road construction subsector. In addition, less
attention is paid to success factors for implementing public road construction projects.
Accordingly, a research question was developed to enhance this dissertation. Subsequently, six
probable compliance factors were established to determine their impact on compliance with a
public procurement regulatory framework. Additionally, compliance with a public regulatory
framework together with these six compliance factors (plus seven Success factors) were
examined to determine their impact on successful implementation of public road construction
projects. Appendix G demonstrates the literature gap based on these factors shown in the
conceptual model. Proof of using these factors was founded on scholarly areas of further
research suggested by various peer reviewed journal article as discussed below.
Familiarity with regulatory framework and organizational incentives was shown to
have a positive significant impact on compliance (Gelderman et al., 2006). Due to the fact that
the sample was drawn from Dutch public entities, the study acknowledged its limitation and
recommended using these factors, including professionalism and involving top management in
studies in other countries. Similar reports based on Uganda’s public entities suggested using
staff familiarity to establish its effect in public procurement (Tukamuhabwa, 2012, Eyaa and
Oluka, 2011). Furthermore, familiarity with public procurement guidelines was used to
determine compliance levels in Nigeria’s construction industry (Zadawa et al., 2015). Since the
study was limited to Nigeria’s construction industry, was theoretical in nature, qualitative, and
lacked theory backing, a quantitative approach using similar factor was suggested to provide
additional empirical evidence (Zadawa et al., 2015).
There are contradictions in using monitoring activities and sanctions to enhance
compliance. For example, Kauppi and van Raaij (2015) established that monitoring does not
influence agent compliance with principal’s instructions. Since the study was cross-sectional,
further studies were encouraged across other countries and sectors to determine its influence in
more details. Meanwhile, there are reports that argue using monitoring and sanctions cautiously
to enhance compliance. They suggested investigations to establish their influence on regulatory
compliance in public sector procurement (Mwakibinga and Buvik, 2013). Whereas there is a
positive association between sanctions and compliance in Tanzania’s public sector
procurement, sanctions insignificantly enhanced compliance. Similar studies in other sectors
and countries were suggested using sanctions to evaluate compliance (Mwakibinga and Buvik,
72
2013, Tukamuhabwa, 2012, Payan and McFarland, 2005). Relatedly, Rokkan and Buvik
(2009) recommended sanction for further research based on agency theory in investigating how
the agent complies with principal’s instructions to achieve set objectives.
Institutional theory recommends staff professionalism through education, skilling and
professional networking (DiMaggio and Powell, 2015). Surprisingly, professionalism was an
insignificant predictor of compliance in public procurement (Eyaa and Oluka, 2011). The
article recommended further investigations to establish consistency by extending the study to
other sectors and using more factors. This move was supported by Tukamuhabwa (2012)
proposing a quantitative research based model with more factors to examine compliance in
public procurement through future research. Furthermore, Gelderman et al. (2006), Gelderman
et al. (2010) encouraged future researchers to replicate compliance studies using factors
including perceived inefficiency of regulatory framework, sanctions, organizational pressure
and contractors’ resistance to other countries, sectors and agencies.
Project success is measured through time, cost, quality, satisfaction and safety (Chan
and Chan, 2004, Atkinson, 1999). With complex construction projects operating in a dynamic
environment, scholars are encouraged to use these indicators as a benchmark for future research
since results change over time (Chan and Chan, 2004, Atkinson, 1999). In addition, future use
of these indicators is recommended since they are key in determining successful project
implementation and client satisfaction (Pinto and Mantel, 1990). Relatedly, Tabish and Jha
(2015) identified compliance with regulatory framework as a key success factor for
construction safety performance and suggested further investigation on its effectiveness in the
construction industry. This notions was supported by Mbabazi et al. (2015) who investigated
compliance in local government service delivery. Despite using time, cost and quality to
measure compliance in service delivery, the study objective was different, majorly qualitative,
lacked background theory and limited to district roads without considering national roads.
Finally, reports showed that mediation studies are emerging and important globally
(Mojtahedi and Oo, 2017, Hayes, 2009, Baron and Kenny, 1986). However, mediation studies
in the construction management research are only recently emerging. For example, reports
show mediation studies in Nigerian construction industry that are encouraged in other countries
(Zadawa et al., 2018b, Zadawa et al., 2018a). Accordingly, researchers are calling for
expansion of mediation studies in the construction industry since they have proved useful in
other fields (Mojtahedi and Oo, 2017, Cheung and Lau, 2008, James et al., 2006). In
73
conclusion, suggested recommendations supported this research in adopting eight factors
including familiarity, monitoring activities, professionalism, sanctions, perceived inefficiency,
contractors’ resistance, compliance and projects success for this thesis.
This leads to the overall research methodology described in the next chapter.
74
CHAPTER FOUR METHODOLOGY
75
4.1 Introduction This chapter describes the research methodology used to address the research question,
objectives and hypotheses. It outlines; research approach, research design, measurement
development, data collection procedures, sampling techniques and ethical considerations. The
methodology described was considered because a research methodology is important for an
academic study since it provides an overarching strategy that sets out systematic procedures to
answer a specific research question and ensures robustness of entire research (Sutrisna et al.,
2018).
4.2 Research Question
The research was guided by the following research question extended from chapter one:
What factors affect compliance in performance of public road construction projects?
This research question was handled in two parts. Part one focused on establishing factors
influencing compliance with the public procurement regulatory framework governing public
road construction projects and part two focused on how compliance with public procurement
regulatory framework together with compliance factors influence successful implementation
of public road construction projects. This manifested into the research aim and objectives (See
section 1.4 and 1.5 respectively) that were addressed through respective hypotheses in chapter
three.
4.3 Literature Review Approach
A comprehensive literature review was carried out in the domain of public procurement,
regulatory compliance and construction projects. To arrive at this, published research in peer-
reviewed journals were retrieved by use of different databases by title on the University of
Newcastle library catalogue. They included; Scopus, Google Scholar and Science direct search
engines. The journal articles were filtered to get relevant journals and articles from mass
downloads by a quick look at their respective abstracts. Textbooks, conference papers, public
reports were also used in this thesis. The literature search produced over 700 journal articles
and public reports from a period of 1987 to 2018. All downloaded materials were grouped and
stored on Endnote X8 library. Key search terms were used to ease searching of journal articles
including; Public procurement and construction, construction projects, compliance and
regulatory framework, regulations, regulatory framework, public procurement, public sector,
legal and compliance, non-compliance, Australia, Uganda, performance, road construction and
76
performance. Furthermore, emphasis was put on; Road construction projects, compliance in
project implementation, enforcement mechanism, performance outcome, project success,
determinants of regulatory compliance and success factors in construction industry. Additional
articles were discovered from bibliographies of downloaded articles. Finally, the supervisors
provided articles relevant to the thesis topic. Reviewing literature, guided the study in a
theoretical context and reviewing public documents helped to establish compliance and project
success issues at entity level.
4.4 Research Framework and Approach
This dissertation adopted the research framework of Hair et al. (2014), Urbach and
Ahlemann (2010) to guide the research methodology as depicted in Table 4.1. The research
framework started with problem identification and research design to drive the study. The
second step involved theoretical foundation including; reviewing relevant literature that
unearthed theories, compliance and project success factors. The third step involved
constructing a conceptual model and developed hypotheses based on research objectives.
Model construction further linked study variables in a structural model and developing
measurement indicators for respective study variables. The fourth step was concerned with data
collection. This step involved establishing sampling frame, target sample size and type of data.
A questionnaire was used to solicit views from respondents in participating organisations.
Ethics approval was also considered in this step as a requirement before collecting data
involving human beings and animals. The fifth step concentrated on model validation through
evaluating coefficient of determination, path analysis, reliability, convergent and discriminant
validity as well as model fitting using Standardized Root Mean Square Residual (SRMR). The
final step involved discussion, implications, contributions, recommendations and consideration
for future research. Of recent, these steps have been modified to reflect determination of
research gap, structural model specification, measurement model specification and model
estimation and results evaluation (Ringle et al., 2018).
Table: 4.1. Research framework
Phase Activities and results
Problem definition and research design Research question: What factors affect
compliance in performance of public road
construction projects?
77
Research design: A cross-sectional and
questionnaire based was adopted. A
conceptual model transformed into structural
equation model for empirical testing
(Estimation).
Theoretical foundation and literature review Literature review: Reviewing relevant
literature and theories, tuned the research
question, conceptual framework, variables,
measurement indicators and hypotheses.
Comprehensive literature review discovered
compliance and project success factors as
well as mediational effects in public road
construction projects.
Model construction and instrument
development
Structural model: Hypothesised compliance
factors were linked to compliance and
project success respectively.
Measurement model: This involved
modification of existing measurement items
with a reflective mode. Self-administered
questionnaire was used.
Data collection Sampling frame: Public road construction
players including; MoWT, UNRA, URF,
PPDA and Contractors formed a sampling
frame.
Data type: Primary data collected using
questionnaire and secondary data from
public documents for example, annual
performance reports, compliance reports,
and audit and investigation reports. The
questionnaire was piloted for improvement.
78
Ethics approval: Human Resource Ethics
Committee (HREC) of University of
Newcastle approved this study and a permit
number H-2017-0056 was obtained.
Target sample: 200 respondents were
targeted and actual 194 responses received.
However, 192 valid responses were usable.
Model validation Analysing results on compliance and project
success factors in public road construction
projects using Smart-PLS3, SPSS24 and
Med-Graph3.
Measurement model: Internal consistence,
convergent and discriminant validity were
respectively evaluated through composite
reliability ( 𝜌𝑐), AVE and HTMT.
Structural model: Path coefficients (α),
Coefficient of determination (R²), and effect
size (ƒ²) were evaluated.
Model fit: Standardized Root Mean Square
Residual (SRMR) determined model fit.
Mediation: SPSS regression and Med-graph
Sobel test based on (Baron and Kenny 1986)
were handy used.
Reporting results Discussion of results: Hypotheses
evaluation, implications, contributions,
limitations, recommendations, future
research and conclusion.
79
4.4.1 Research Approach Research is normally conducted through quantitative or qualitative methodology. The
quantitative approach is statistically based and deductive in nature to explain variable
relationships while qualitative approach is non-numerical and inductive (Bryman and Bell,
2007). Quantitative research includes the benefits of statistical techniques to analyse data and
allows testing of variables for relationship strength and direction (Saunders, 2012, Mark et al.,
2009). A deductive research approach was used in this thesis because it enabled testing of the
hypotheses developed for strength of relationships between variables and variance through
statistical techniques including mediation effects. Furthermore, previous construction studies
have used this approach over time and yielding reliable results. Such support prompted this
thesis to use similar methodology for consistence and concretising its application in
construction research.
4.4.2 Research Design and Justification A research design is a guided plan that initiates questions to be answered up to
conclusion and includes study questions, unit of analysis, linking of data to study questions and
criteria for data interpretation (Yin, 2003). It is essential in directing research, determining
research contributions, enabling research problem specification and resolution (Babbie, 2015,
Rubin and Babbie, 2012, Knight and Ruddock, 2009). The design enabled in developing the
conceptual model for answering research questions linked through hypotheses and generalising
study results based on collected data and assessment (Bryman and Bell, 2011). A cross-
sectional study also called snapshot, is a good one point in time study for drawing inferences
on an existing phenomenon (Barratt and Kirwan, 2009). A cross-sectional study using a
questionnaire survey is commonly applied in construction research by getting original data
from a sampled population cheaply, timely and reliably yielding robust results for
generalisation (Ameyaw et al., 2017, Darko et al., 2017, Abdullahi et al., 2017, Robson and
McCartan, 2016, Babbie, 2015, Rubin and Babbie, 2012, Dainty, 2008, Robson, 2002). This
dissertation used a cross-sectional research design as it deals with the causal effect between
independent and dependent variables that required testing relationships. Additionally, a cross-
sectional survey research is good at generating information from both primary and secondary
data suitable for specific research study. This design was selected because its statistical
techniques are good for accuracy, validity, reliability generalisability and objectivity compared
to a qualitative design (Mwakibinga and Buvik, 2013, Sekaran and Bougie, 2010).
80
Determining the correlational effect between independent and dependent variables,
justified why a cross-sectional design was selected for this dissertation and for consistency as
previous studies in the construction management research have used it. Survey research using
the questionnaire was also preferred due to its ability to obtain secondary data from public
documents on performance of public road construction projects through performance and
compliance reports as well as primary data from actual staff involved in these projects (Sekaran
and Bougie, 2010). Furthermore, since this dissertation was time constrained, this snapshot was
convenient compared to longitudinal studies in meeting the PhD timeframe. Major weaknesses
of cross-sectional survey include weak internal validity, bias, missed data and low response
rates (Babbie, 2015, Bryman, 2004). However, this was solved through piloting the
questionnaire for improvement by getting input from respective experts in public procurement,
construction projects and academia. The questionnaire was precisely written to encourage
respondents and minimise completion time. Additionally, persistent reminders as a follow-up
and checking for completeness before collecting the questionnaires from respondents increased
response rate and reduced missing values.
4.5 Measurement Development This subsection contains questionnaire details, variables, measurement scales, validity
and reliability. This is an important stage in research involving questionnaire survey as it helps
in obtaining viable measurement indicators for specific study variables (Hair and Black, 2009).
Through literature review, study variables and measurement indicators were respectively
determined as discussed below.
4.5.1 Questionnaire Design, Justification and Variables Questionnaire survey research is commonly applied where secondary data is available
and accessible (Darko et al., 2017, Abdullahi et al., 2017, Sekaran and Bougie, 2010, Sekaran,
2006). Furthermore, public road construction projects involve different stakeholders with
varying opinions and expectations. Hence, use of a questionnaire for primary data collection
was viable to solicit stakeholders’ views (Chan et al., 2018, Mojtahedi and Oo, 2017, Liu et
al., 2016, Olander, 2007). The questionnaire is appropriate in obtaining sensitive views and
securing anonymity of respondents (Ameyaw et al., 2017). The questionnaire is also
appropriate in studying attitudes in the construction sector (Shaban, 2008). Ideally, the major
concern for scale establishment is item inter-correlation, variance, unidimensionality,
reliability and validity. Accordingly, the questionnaire was developed in a three-step process
including; item generation, measurement purification and validation (Diamantopoulos and
81
Siguaw, 2006). The questionnaire was developed and designed to answer study objectives and
hypotheses derived from general research question.
The questionnaire is a set of standardised questions that are precisely written for easy
interpretation by respondents across the sampling frame (Robson and McCartan, 2016, Robson,
2002). The questionnaire contained eight variables including; familiarity with regulatory
framework, monitoring activities, professionalism of staff, sanctions on staff, contractors’
resistance to non-compliance, perceived inefficiency of regulatory framework, compliance
with public procurement regulatory framework and project success anchored on a 5-point
Likert scale as depicted in Table 4.2. This dissertation adopted an ordinal level data with Likert
scales because it is appropriate for measuring attitude in quantitative studies (Mwakibinga and
Buvik, 2013, Aaker et al., 2008, Kumar et al., 2002, Likert, 1932). A Likert scale is efficient
unidimensional scale that ensures all items measure the same thing (Zadawa et al., 2018a,
Zadawa et al., 2018b, Cornalba and Giudici, 2004). In addition, a Likert scale is widely used
in construction management research (Darko et al., 2017, Abdullahi et al., 2017, Qin et al.,
2016). This was considered because of correlational and causality of the study in this
dissertation. For consistency and reliability, the dissertation maintained odd numbered scales
as compared to even point Likert scale which avoid mid-points (neutral statements) for definite
answers (Raaijmakers, 2000).
Through extensive literature review, a number of variables were identified with various
measurement items. The measurement items for respective variables were developed and given
to different experts in the field of procurement and construction management for comments.
Before the questionnaire was given to the experts, two university professors supervising this
research scrutinised the instrument carefully for possible errors and misrepresentation to ensure
validity and reliability. The aim was to establish irrelevant, ambiguous and poor worded
questions for elimination. In this way, the questionnaire was development and piloted in order
to have relevant and valid measurement items representing respective study variables. Piloting
is good at getting constructive feedback used to update the instrument accordingly (Memon et
al., 2017, Babbie, 2015). Pretesting the questionnaire ensures validity and reliability to yield
quality and dependable results (Chandran, 2004, Gupta, 2002). All these steps were taken to
address content validity of the questionnaire. Because content validity ensures validation of the
instrument by assessing how well instrument items represent the respective constructs (Gambo
et al., 2016, Sekaran and Bougie, 2016).
82
The questionnaire was administered to selected procurement officers and construction
managers for clarity, relevance and updating. Participants in the pilot study did not take part in
the final study. One professor and chair of construction management identified experts in
procurement and construction industry from New South Wales Australia for their input on the
instrument. The feedback from the pilot study enabled rewording of the questionnaire and
deleting ambiguous statements. This resulted in a questionnaire with ninety-three questions.
Further statistical validation of the measurement items including reliability and validity were
performed after data collection (Urbach and Ahlemann, 2010). Whereas the questionnaire
adopted measurement items previously used as evidenced in Table 4.2, modifications was
made to fit current study by raising questions that reflected study variables and phenomenon
accordingly. Modification was necessary since previous studies that used these indicators were
not in road construction projects, did not use these independent variables together and their
respective models were either limited to compliance with public procurement regulatory
framework or project success and without considering mediation effect.
Table 4.2 Variable measurement and Questionnaire design
Variable Number of
question
Measurement
item code
Measurement
Scale
Reference
Familiarity with public
procurement regulatory
framework
15 F1 – F15 5-point Likert
scale
Mwakibinga & Buvik 2013,
Eyaa & Oluka 2011, &
Gelderman et al 2006
Monitoring activities 16 M1 – M16 5-point Likert
scale
Mwakibinga & Buvik 2013,
Rokkan & Buvik 2003 & 2009
Professionalism of staff 24 PR1 – PR24 5-point Likert
scale
Basheka & Mugabira 2008 &
Eyaa & Oluka 2011
Sanctions on staff 16 S1 – S16 5-point Likert
scale
Mwakibinga & Buvik 2013 &
Payan & McFarland 2005
Perceived inefficiency of
regulatory framework
4 PI1 – PI4 5-point Likert
scale
Gelderman et al 2006; 2010
Contractor’s resistance to
non-compliance
3 CR1 – CR3 5-point Likert
scale
Gelderman et al 2006
83
Compliance with public
procurement regulatory
framework
11 CP1 – CP11 5-point Likert
scale
Mwakibinga & Buvik 2013 &
Gelderman et al. 2006 Payan &
McFarland 2005
Project success 4 PS1 – PS4 5-point Likert
scale
Pinto & Mantel 1990 and Dvir
& Lechler 2004
Source: Researcher
Familiarity with Regulatory Framework
Familiarity with public procurement regulatory framework was measured through
familiarity with applicability of regulatory framework, familiarity with exceptions, overall
knowledge and perceived clarity of rules. Different authors with reliable results as depicted in
Table 4.2 had consistently used these items and were earlier used by Gelderman et al. (2006)
in evaluating public procurement and EU tendering directives. They were later modified and
applied in Uganda’s and Tanzania’s public procurement system respectively (Mwakibinga and
Buvik, 2013, Eyaa and Oluka, 2011).
Monitoring Activities
Monitoring activities on public road construction projects was measured through;
Frequent inspection for timely delivery, frequent inspection for timely recording, frequent
inspection for actual delivery and frequent inspection for proper storage. These were adopted
and modified from (Mwakibinga and Buvik, 2013, Rokkan and Buvik, 2009, Rokkan and
Buvik, 2003). Actual and timely delivery were based on set performance targets and
completion dates for implementing public road construction projects. While proper storage
referred to how safe, road construction materials and equipment were stored to prevent theft
and damage.
Professionalism of Staff
Professionalism of staff involved in public road construction projects was measured
through; Confidentiality, competence, integrity and professional membership. These were
adopted and modified from (Eyaa and Oluka, 2011, Basheka and Mugabira, 2008). Whereas
there are limited public procurement studies using professionalism factor, little is known about
its application in procurement of public road construction projects. The questions raised in the
instrument were directly linked to the above indicators with modification to fit public road
construction study.
84
Sanctions on Staff
Sanctions were measured through; Penalties for violation, consideration of outcome for
non-compliance, credibility of sanction and known stipulated sanctions. These were adopted
and modified from (Mwakibinga and Buvik, 2013, Payan and McFarland, 2005). As noted
earlier, sanctions have been applied in general concept of restoring sanity in an appealing
situation where principal’s goals are in stagnation under agency theory. However, application
of coercive means is still debatable despite its application in Tanzania’s public procurement
study (Mwakibinga and Buvik, 2013). The sanction’s application in public road construction
subsector is at infant stage and this was a premise for its application in this thesis using those
measurement indicators to iron some contrivance.
Perceived Inefficiency of Regulatory Framework
Perceived inefficiency of public procurement regulatory framework was measured
through ban on negotiation during project implementation, ban on contract extension and ban
on exclusion of underperforming contractors. These items were adopted and modified from
(Gelderman et al., 2010, Gelderman et al., 2006). Perceived inefficiency is an emerging
variable and its application is not known in the construction industry. Its indicators were used
in EU public procurement directives and is crawling slowly in application. Despite its infancy,
this thesis adopted the indicators and modified questions in the instrument to match public
procurement of road construction projects.
Contractors’ Resistance to Non-Compliance
Contractors’ resistance was measured through readiness to take action, contractors’
knowledge of regulatory framework and public officers’ fear of being exposed. These items
were adopted and modified from (Gelderman et al., 2006). This is an armature factor in public
procurement generally. Having been applied in the EU public procurement directives
Gelderman et al. (2006), little is known about this variable in the construction industry and
specifically in public road construction projects. This dissertation adopted these indicators and
modified the questions to link them to public road construction projects since developing new
indicators requires substantial efforts and time for reliability and validity.
Compliance with Regulatory Framework
Compliance can be measured either through dichotomous (comply or not comply) or
through probability. However, weakness of dichotomous is that it lacks a degree of compliance
85
and probability is challenged by estimating actual and future compliance (Mwakibinga and
Buvik, 2013, Gelderman et al., 2006). In order to determine compliance, this thesis adopted
and modified approaches of Mwakibinga and Buvik (2013), earlier developed by (Gelderman
et al., 2006, Payan and McFarland, 2005). Respondents were asked to indicate their level of
agreement on compliance indicators comprising of timely delivery, timely recording, use of
imprest, damages or loss and unauthorised procurement on a 5-point Likert scale.
Project Success
A wide range of project success studies have concentrated on critical success factors of
construction projects. However, few of these studies have specifically identified critical items
measuring project success (Atkinson, 1999). Despite this shortfall, works of (Pinto and Mantel,
1990, Pinto, 1986) are the foundation for underlying indicators measuring project success
including; time, cost and quality that many studies are now applying in the construction
industry. This dissertation adopted these measurement indicators that have been earlier
developed and used by Pinto and Mantel (1990) and later adopted with modifications by (Dvir
and Lechler, 2004).
4.5.2 Questionnaire Validity and Reliability
Validity is concerned with question of good fit or concurrence between what
researchers have defined as a characteristic of phenomenon under study and what researchers
are reporting in the measurement (Bryman and Cramer, 1997). Alternatively, validity refers to
the degree to which the instrument measures what it is supposed to measure (Shaban, 2008). It
implies that variable measurement by the instrument should measure what the researcher
intended. Validity is the accuracy of information presented (Santosh, 2007, Mehmetoglu,
2004). On the other hand, data reliability is important when there is trust in data source and in
respondents filling the questionnaire (Oppenheim, 1992). Reliability involves removal of
mistakes in the measurement instrument for data consistency (McDaniel and Gates, 2010,
Santosh, 2007, Gupta, 2002). Additionally, reliability is the consistency and stability of
measures. Accordingly, this thesis used staff who are knowledgeable in procurement and public
road construction projects as respondents. This boosted data reliability and consistency with a
right data collection source. The questionnaire was pretested to improve the instrument. In
addition, using existing scales and measurement items previously used with good Cronbach’s
alpha coefficients, increased reliability. Furthermore, instrument validity can be in the form of
86
internal validity, content validity, face validity, external validity and stability of the
questionnaire as discussed in the proceeding break down.
4.5.2.1 Internal Validity
A pilot study was conducted outside a wider selected sample where the questionnaire
was given to procurement and construction experts to ascertain whether the questions raised,
covered all key study issues to ensure reliability and consistency. This ensured that conclusions
made are well supported and free of bias.
4.5.2.2 Face Validity
This is the degree to which findings correctly map the phenomenon in question. The
questionnaire was organised in sections systematically matching independent variables
influencing compliance and project success to determine representative measurement items.
With the help of experts who examined the questionnaire, measurement items were grouped in
their respective variables.
4.5.2.3 Content Validity
This looked at representativeness of the measurement item for the main variables under
study. The manner to which questions are raised in the questionnaire should fully correspond
to the variables and match developed hypotheses and objectives of the study. This was
enhanced through piloting the questionnaire by getting input and feedback from experienced
personnel working in public procurement and construction projects. Content validity is
concerned with how manifested variables represent respective latent variable (Sekaran and
Bougie, 2016, Gambo et al., 2016, Götz et al., 2010). Content validity was achieved by raising
questions matching hypotheses for respective variables. The factors were operationalised in the
form of manifested variables to enable representation of measurement indicators for each
variable. In addition, after content validity, further evaluation for construct reliability and
validity is recommended (Götz et al., 2010). This was achieved by running PLS-algorithm
using Smart-PLS 3 version 3.2.3 (Ringle et al., 2015a).
4.5.2.4 External Validity
This deals with generalisation of study results to the whole population. Since the study
was quantitative and the sample was statistically selected, its appropriateness warranted
application to population as it was free of researchers’ bias (Clark-Carter, 2009). The sample
87
was carefully and statistically selected through stratified proportionate random sampling to
allow generalisation of dissertation findings.
4.5.2.5 Stability
This refers to consistency of results produced by the same research instrument with
duplication of measurement items over time (Wood and Ross-Kerr, 2011). Stability ensures
reliability of measurement instrument for the same variables and this was achieved by using
variables and measurement indicators used in previous studies with necessary modification for
suitability of public road construction project study.
4.6 Data Collection Upon ethics approval, data collection commenced and participants were selected from
organisations involved in road construction projects in Uganda.
4.6.1 Data Collection Method and Questionnaire Justification
Research in construction is conducted through surveys, case studies and experiments
(Liu et al., 2016, Babbie, 2015, Ferber, 1980). Survey questionnaires are commonly used in
obtaining appropriate data responding to study objectives with small samples representing a
big population. In this regard, a structured self-administered questionnaire was employed as a
primary data collection instrument to solicit views, attitudes and procurement practices in
public road construction projects. A structured questionnaire was selected for consistency since
a cross-sectional design requires use of quantitative analysis (Gupta, 2003). The questionnaire
was prepared to reflect the research hypotheses, objectives and variables with structured
questions. This method was selected because it is widely used to obtain views of professionals
in construction management and allows determining correlation and causal links for statistical
significance among study variables (Liu et al., 2016, Hwang et al., 2015, Deng et al., 2014). It
is straightforward, clearly outlined, replicable, easy to administer and time saving compared to
an interview guide (Malhotra and Peterson, 2006). Whereas the questionnaire does not prompt
and allow probing for more data, it gives a high degree of standardisation and adoption for
generalising the population. It allows respondents to make their own interpretation of study
variables and avoid researchers’ bias (Chandran et al., 2003).
Permission by top management from participating organisations was officially granted
and respectively assigned staff to facilitate in questionnaire distribution and make follow-up.
The questionnaires were physically delivered and picked when completed. This systematic
88
process enabled smooth and timely data collection. Additionally, follow-up through phone
calls and frequent physical visits secured approximately 65% response rate. The response rate
attained for the thesis is good enough since a response rate of 50% is adequate, 60% good and
above 70% is very good for vibrant findings, conclusions and recommendations (Mugenda and
Mugenda, 2003). Additional reports indicate that a response rate of 20-30% when using a
questionnaire in construction management is appropriate (Liu et al., 2016, Hwang et al., 2015).
4.6.2 Data Type and Sources
This thesis used both primary and secondary data. Secondary data was retrieved from
annual performance reports, compliance reports, monitoring and evaluation reports, audit and
investigation reports and national media. These sources are vital since potential data sources
include but are not limited to; documentation, archival records, interviews and physical
artefacts (Yin, 2006, Yin, 2003). Primary data was obtained from the Ministry of Works and
Transport (MoWT), Uganda Road Fund (URF), Public Procurement and Disposal of Public
Assets Authority (PPDA) and private road contractors awarded respective public road
construction projects. These organisations were considered because they are involved in public
road construction projects in Uganda. The data collected from these partisans enabled
researchers’ in-depth understanding of compliance and implementation issues surrounding
public road construction projects.
4.6.3 Study Population and Sample
Population is a totality of items including people, firms and objects that forms a research
base from which study sample is drawn (Kerlinger and Lee, 2000). A sample is a subset of a
population that is drawn to represent a population and sampling is a statistical procedure for
selecting a study sample (Grove et al., 2014). Whereas (Kothari, 2004, Mugenda and Mugenda,
2003) argue that sampling is a uniform selection of a sample from a population and a sample
size of 10-20% is adequately representative, sample size formulation is complex and depends
on population homogeneity, cost, time and respondents available (Churchill and Iacobucci,
2002). According to UNRA’s website, there are 42 public road construction projects (5
completed and 37 on going) as at July 2016. Since this dissertation was limited to the public
road implementation stage, all 42 projects were considered. In addition, these projects were
based on to generate a list of private contractors who were awarded respective contracts (See
Table 4.3). Both the unity of analysis and unity of inquiry were the respondents from five strata
with a population of 299 staff as depicted in Table 4.4.
89
Table 4.3 Completed and On-going National Road Construction Projects
No Project Contractor
Completed Road Construction Projects
1 Vurra-Arua-Koboko-Oraba Chongqing International
Construction Corporation
(CICO)
2 Kawempe-Luwero-Kafu (Overlay) Energo Projekt
3 Gulu-Atiak road CHICO
4 Kampala Busega-Masaka RCC/SBI
5 Mukono-Jinja Sterling Civil Engineering
On-going road construction projects
1 Ishaka-Kagamba General Nile & Dotti
services
2 Nakapiripirit-Moroto road China Road & Bridge
Corporation
3 Kamwenge-Fort Portal China Railway Seven Group
4 Atiak-Nimule China Railway Group 5
5 Mbarara-Bypass China Railway Seven Group
6 Mpigi-Kanoni China Railway number 3
7 Ntungamo-Kakitumba/Mirama Hills Zhongmei Engineering
Group
8 Mukono-Kyetume-Katosi/Kisoga-Nyenga SBI/RCC JV
9 Luuku-Kalangala Spencon Services
10 Kanoni-Ssembabule-Villa Maria China Railway number 3
11 Musiita-Lumino-Busi/Majanji China Railway 18th Bureau
90
12 Acholi Bur-Musingo Chongqing International
Construction Corporation
(CICO)
13 Olwiyo-Gulu Zhongmei Engineering
Group
14 Gulu-Acoli Bur China Railway No.5
15 Mukono-Kayunga-Njeru SBI
16 Mbale-Soroti Dott Services
17 Mbarara (Buteraniro)-Ntungamo RCC
18 Ntungamo-Katuna road RCC
19 Kafu-Kiryandongo Energo Projekt
20 Kiryandongo-Kamdini China Communication
Construction Company
(CCCC)
21 Kamdini-Gulu China Communication
Construction Company
(CCCC)
22 Pakwach-Nebbi Shengil Engineering
Construction Company
(CECC)
23 Sironko-Namusi-Muyembe Shengil Engineering
Construction Company
(CECC)
24 Iganga-Tirinyi Dott Services
25 Nansana-Busunju Spencon services
26 Iganga-Kaliro Sterling Civil Engineering
91
27 Seeta-Namugongo-Kireka Abu baker Technical
services
28 Selected National roads Lira District(Lot 6) Multiplex LTD
29 Kampala-Entebbe Expressway/Munyonyo China Communication
Construction Company
(CCCC)
30 Kampala Northern Bypass Mota Engil Enginharia E
Construcao SA
31 Mpigi-Kanoni road Energo Projekt
32 Bulima-Kabwoya China Railway No.5
Engineering Group
33 Kyenjojo-Kabwoya Shengil Engineering
Construction Company
(CECC)
34 Mubende-Kakumiro-Kagadi China Communication
Construction Company
(CCCC)
35 Tororo-Mbale road Dott services
36 Jinja-Kamuli road Dott services
37 Mvara-Ediofe Cathedral road Chongqing International
Construction Corporation
(CICO)
Source: UNRA 2016
4.6.4 Study Participants Participants for this study included staff from Directorate of Engineering and Works
(DE&W), Directorate of Transport (DT), Procurement and Disposal Unit (PDU), Policy &
Planning (P&P) and Finance & Administration (F&A) of Ministry of Works and Transport.
Directorate of Performance and Monitoring (DP&M), Directorate of Legal & Investigations
(DL&I), Directorate of Operations (DOP), Directorate of Capacity Building & Advisory
92
Services (DCB&AS) and Directorate of Corporate (DCP) of Public Procurement and Disposal
of Public Asset Authority. Fund Management Department (FMD) of Uganda Road Fund and
contractors for respective public road construction projects. Participants were majorly road
engineers, procurement managers, project managers, finance managers, accountants and
human resource managers. These departments were selected because they are involved in road
construction projects and had necessary information for this study. In addition, the participants
in these departments were selected based on their knowledge and experience in road
construction projects (Darko et al., 2017). Table 4.4 shows the total number of staff from
respective directorates/department that formed sampling frame.
Table 4.4 Participants
Organization Directorate/Department Number of staff Total Sample size
MoWT DE&W 26 94 54
DT 10
PDU 6
F&A 40
P&P 12
UNRA DP 21 21 12
URF FMD 12 12 7
PPDA DP&M 55 130 74
DOP 30
DCB&AS 15
DL&I 12
DCP 18
Contractors Contract Managers 42 42 25
Total 299 299 171
Source: Researcher
93
4.6.5 Sample In PLS-SEM, minimum sample size is determined by multiplying a number of variable-
paths in a model by ten (Ten times rule of thumb) for reflective model (Hair et al., 2012a,
Urbach and Ahlemann, 2010). This rule of thumb is extensively used because of its simplicity
in determining the minimum sample size in PLS-SEM (Kock and Hadaya, 2018). This implies
that the minimum sample size for this study model based on this rule would be 130 i.e. (13*10).
All 299 respondents were selected as depicted in Table 4.4. This move was considered to
reduce none response rate, increase accuracy and objectivity of the results (Stopher, 2012).
Furthermore, whereas PLS-SEM can handle small sample sizes, precaution should be exercised
since sampling error may arise yielding inflated bootstrap error and reducing statistical power
especially with highly skewed data (Hair et al., 2012a). Such sampling errors are minimised
through increasing the sample size. Increasing the sample size, further improves accuracy since
the sample size is a major determinant of statistical power (Henseler et al., 2014). Based on the
consistency at large principle, correct model parameter estimators are observed when indicators
per variable increase to infinity (Sawyer, 2005, Chin, 1998). According to Krejcie and Morgan
(1970) sample table, the right sample size for a population of 300 is 169. However, the sample
size was determined using Slovene’s formula stated in equation (i) following Krejcie & Morgan
at 0.05 significance level (Nsanganzelu, 2015).
4.6.5.1 Sample Size Determination
n =𝑁
1+𝑁(e2) ……………………………………………………………………………………………………………………i
Where; n = Sample size, N = population and e = significance level of 0.05
By substituting in formula i, the actual sample size for population of 299 is 171.
4.6.6 Sampling Technique Uganda’s national roads sprout across the entire country with participating
organisations having staff stationed at both head and upcountry offices. Bearing in mind that
respondents are from different organisations, stratified proportionate random sampling was
appropriate in selecting key respondents involved in public road construction projects and
generalising findings (Clark-Carter, 2009). Stratification was based on organisations of which
there are broadly two categories involved in public road construction projects
(Government/public and private). Government organisations included; Ministry of Works and
Transport (overall supervisor), Uganda National Road Authority (implementer), Uganda Road
Fund (custodian of road funds) and Public Procurement and Disposal of Public Assets
94
Authority (Public procurement regulator), while private included road construction firms
(contractors). These formed five strata and respondents in each stratum were randomly
selected.
Despite Uganda National Roads Authority’s decline to participate in this study, the
targeted sample size was not affected since it was compensated by issuing more questionnaire
in other participating organisations within the sampling frame. Noteworthy, participation is
voluntary and the study was obliged to University of Newcastle Human Resource Ethics
Committee regulations that emphasis voluntary participation and liberty of participants to
withdraw in research at will and anytime. Stratified proportionate random sampling was
preferred because of wanting all key national road sector players to participate in this study
without bias in selecting respondents (Clark-Carter, 2009). Furthermore, stratified
proportionate random sampling yields better responses and all staff have equal chances of being
selected in each stratum involving only those organisations knowledgeable in public road
construction projects. This dissertation considered all the population since the numbers were
manageable and to have a good response rate. However, 194 responses were obtained forming
a 64.9% response rate as depicted in Table 4.5. This is an extremely successful attained
response rate since it is above recommended threshold of 37% when using questionnaire survey
for data collection (Almarri et al., 2019, Doloi et al., 2011).
Table 4.5: Response rate
Organization Number of responses Proportionate response rate (%)
MoWT 88 45
PPDA 56 29
URF 12 6
Contractors 38 20
Total 194 100
4.7 Ethical Consideration The Australian government requires all research involving human and animal subjects
to seek clearance from Human Resource Ethics Committee (HREC) of University of Newcastle
before data collection. This is in line with Becker et al. (2012) necessitating researchers
involving humans and animals to always consider safety, informed consent and privacy of
study participants. Ethics clearance was obtained before data collection since the study
95
involved human beings as a unit of inquiry. Notable issues considered were privacy and safety
of all participants in the research project, anonymity, confidentiality of information obtain and
voluntary consent from participants. Participation in this research project was voluntary and
participants were free to withdraw at any time. The right procedure was followed by seeking
permission from selected entities and obtaining organizational consent to allow individual
respondents for voluntary participation. Finally, privacy, anonymity and confidentiality of
information obtained was ensured. Organisations and individuals who declined participation
were excused accordingly. The ethics approval permit (Number: H-2017-0056) from
University of Newcastle human resource ethics committee helped the researcher’s introduction
and seeking of permission from respective organisations to allow their staff participate in this
survey.
Conclusion
A quantitative cross-sectional research design was employed in this dissertation with
both primary and secondary data collected through administering a structured questionnaire
and reviewing public documents respectively. The questionnaire was developed through
phases consisting of reviewing existing measurement indicators, modification, content
verification and relevancy by academic professors and finally piloting to get expert opinion for
reliability and validity. Proportionate random sampling was adopted to select respondents from
five participating organisations involved in public road construction projects. The
questionnaires were physically distributed and collected from respondents. A response rate of
64.9% was obtained.
This leads to chapter five that report on data analysis.
96
CHAPTER FIVE DATA ANALYSIS
97
5.1 Introduction This chapter presents data processing, techniques and tools used in analysing data.
Three statistical tools consisting of Smart-PLS version 3, Statistical Package for Social
Scientist version (SPSS) version 24 and Med-graph Excel programme version 3.0 were adopted
in the analysis process with respective techniques employed as discussed below.
5.2 Data Processing and Analysis Data analysis techniques include; pattern matching, linking data to propositions,
explanation building, time-series analysis, logic models and cross-case synthesis (Yin, 2003).
One important practice during analysis phase is returning to hypotheses. These lead to a
focused analysis when otherwise tempted to analyse data outside the research question’s scope
and exploring rival hypotheses by engaging an iterative process (Yin, 2003). Confidence in the
findings will increase as number of hypotheses are addressed and accepted or rejected.
Furthermore, quantitative research through a cross-sectional survey focuses on how variables
interact or are inter-linked (Field, 2013). The analysis started with establishment of descriptive
statistics performed in SPSS24 and since this dissertation was guided by nineteen hypotheses,
analysis was linked to developed hypotheses and facilitated by Smart-PLS version 3 statistical
software for data analysis (Ringle et al., 2015b). Smart-PL 3 is the latest version that offers
great range of Modeling and algorithmic functions with improved usability compared to
previous versions (Sarstedt and Cheah, 2019). In addition, Smart-PLS was considered because
it is more advantageous compared to ADANCO, PLS-Graph and Warp-PLS that have limited
algorithmic functions and not regularly updated (Sarstedt and Cheah, 2019). Mediation tests
were determined through Sobel tests following Baron and Kenny (1986) in Med-graph version
3.0 excel programme (Jose, 2013). Data was screened thoroughly for reliability to ensure
completeness and accuracy.
5.2.1 Data Preparation Descriptive statistics was performed to check for normality in data distribution,
completeness and accuracy. This was good at providing background information on both
respondents and characteristics of the study variables. Descriptive statistics summarise huge
data through: frequency and distribution tables, central tendency, normal distribution,
variability, skewness and kurtosis (Davis et al., 2004, Mugenda and Mugenda, 2003). Whereas
PLS-SEM is flexible in handling non-normal data with less stringent constraints, some level of
data screening is necessary (Ringle et al., 2018, Le et al., 2014a, Henseler et al., 2009). Before
detailed analysis, data was subjected to screening. This was important in handling reliability,
98
validity, multi-collinearity, normality, outliers and missing values. This purification process is
majorly concerned with obtaining final measurement items with high inter-correlation that
enable internal consistency for reflective models (Diamantopoulos and Siguaw, 2006). Data
screening was conducted to enable data normality and extreme collinearity (Diamantopoulos
and Siguaw, 2006). Data cleaning, diagnostic tests, reliability tests, factor analysis, computing
of variables, correlations and regression were performed using both Smart-PLS version 3
Ringle et al. (2015b) and SPSS version 24 (George and Mallery, 2016, Field, 2013).
With the help of Smart-PLS statistical software, PLS-algorithm and bootstrapping
resampling approach were employed to determine relationship between variables by estimating
path coefficients and significance. Path coefficients helped to determine strength, direction and
significance of relationships and coefficient of determination helped to examine variance of
dependent variable explained by combined independent variables (Newbold and Agiakloglou,
1991). Bootstrap techniques are good in parameter estimation and are commonly applicable in
analysing risks in construction projects (Mojtahedi et al., 2009). Model fitting was examined
through Standardized Root Mean Square Residual (SRMR). Finally, mediation effects were
performed to determine interactive effects among compliance factors and public road
construction project success following procedures by (Baron and Kenny, 1986). The screening
process involved checking for unidimensionality, collinearity, unreasonable values, missing
values, outliers and normality as described below.
Unidimensionality: Refers to how measurement items for a particular variable relate to that
variable better than any other (Um and Kim, 2018). Unidimensionality was conducted in line
with Kline (2015) to determine construct validity. This was important for data analysis since
reflective models’ variables are supposed to be unidimensional (Kline, 2015). This was handled
in Smart-PLS3 by running PLS-algorithm and determining discriminant validity. To determine
discriminant validity, HTMT values, cross loadings and Fornell-Larcker criterion were
assessed. This process requires particular variable indicator loading to correlate higher than
any other variable. This is achieved if the indicator coefficients are above or equal to 0.6 but
below 0.95 while indicators with coefficients below 0.5 are rejected (Urbach and Ahlemann,
2010).
Collinearity: Extreme collinearity can occur if indicators that seem to measure separate
variables, actually measure the same thing, for example, if indicator coefficient α > 0.90 (Kline,
2015). Extreme collinearity are issues of discriminant validity that occur when variables
correlate highly as if they are measuring the same thing. Hence, poor discriminant validity
99
leading to poor model prediction. This is solved through positive definiteness common in some
computer tools. With reflective measurement models, measurement errors for individual
indicators are established and removed through factor analysis. Whereas extreme collinearity
makes estimations hard and can be solved by removing indicators, researchers should pay
attention to not affect content validity. Data screening is good at solving these problems.
Extreme collinearity was solved by eliminating variables’ indicators with very high collinearity
(α > 0.95) and retained ones (α ≥ 0.5 α ≤ 0.95). This is recommended for reflective models
where the variable meaning is not changed unlike formative models (Urbach and Ahlemann,
2010).
Outliers: Data screening also aims at getting rid of outliers that affect results by either
overstating or understating regression coefficients. Notably, outliers distort statistical results
and affect validity of structural equation models and questionable conclusions (Schamberger
et al., 2019). Outliers are scores that are different from the rest and they are either univariate or
multivariate. This happens when standard deviation scores are three times more than the mean.
This is solved by either applying mathematical transformation or converting extreme scores to
a value equal to next most extreme score that is within three standard deviation of the mean. In
this thesis, the second option was chosen by converting to the next extreme score. Z score were
used with the condition: Z ≥ ± 2.5 (i.e. Z ≥ -2.5, implies extreme low value and hence add 1
to that value and Z ≥ 2.5, implies high extreme value and hence subtract 1 from that value).
Missing data: Missing data occurs when certain values are skipped during data input or if
respondents’ failure to answer certain questions. There are several methods of solving missing
data including; available case method whereby the incomplete cases are deleted thus only
analysing available complete data, using a single imputation method whereby each missing
score is replaced with a single calculated score done by use of mean or regression substitution
technique. Missing values can also be solved through a model-based imputation method that
generates more than one score for each missing observation. However, each of these methods
will depend on the percentage of missing values. This dissertation adopted available case
method for missing data by excluding two questionnaire with 178 (86.4%) total missing data.
They were removed from analysis since they would distort prediction of variable relationships
(Ali et al., 2018a, Hair et al., 2014). This reduced the number of collected questionnaire from
194 to 192 valid responses. Consequently, affecting the sample size while maintaining quality
analysis (Kline, 2015).
100
Normality test: This is concerned with data distribution (Darko et al., 2017). Whereas
PLE-SEM is flexible in handling non-normal data, some level of fair normal distribution is
paramount in yielding strong significant statistical findings and recommendations (Ali et al.,
2018a, Henseler et al., 2009). Additionally, highly skewed data can inflate bootstrap error that
reduce statistical power (Ali et al., 2018a, Hair et al., 2012a). Descriptive statistics was
performed using SPSS24 to test for normality under the following methods:
Graphical methods involving Histogram with normal curve, PP-plot and QQ-plot. The
former requires majority of the bar graphs to be under the normal curve (Doane and
Seward, 2011, Gan and Koehler, 1990).
Skewness and Kurtosis: Skewness and Kurtosis statistics should lie between ±3 and ±5
respectively to exhibit fair normal data distribution.
According to the histogram output, all study variables (familiarity with public procurement
regulatory framework, monitoring activities, professionalism of staff, sanctions on staff,
perceived inefficiency of public procurement regulatory framework, contractors’ resistance to
non-compliance, compliance with public procurement regulatory framework and public road
construction project success) exhibited fairly normal distribution. The majority of the bar
graphs are under the normal distribution curve as shown by respective figures. Additionally,
all the PP-plots and QQ-plots of the study variables exhibited fairly normal distribution since
the majority of the points are close to the straight line as demonstrated by respective figures.
Furthermore, descriptive statistics using Skewness and Kurtosis was performed to determine
normality. Findings show that Skewness and Kurtosis for all study variables are within
acceptable limits of ±3 and ±5 respectively (Jondeau and Rockinger, 2003). Hence, data for
all study variables exhibited fairly normal distribution as depicted in Table 6.16.
Additional Diagnostic Tests
Diagnostic tests are good for data normalisation before embarking on detailed analyses.
These were performed based on Ordinary Least Squares (OLS) assumptions. Diagnostic tests
involved testing for normality, multi-collinearity, linearity and homogeneity as a requirement
for cross-sectional data. If not corrected, these issues contribute to poor predictive power of the
model, poor t-values and misleading data specifications (Chen and So, 2006, Walfish, 2006,
Grewal et al., 2004, Min and Mentzer, 2004, Jarvis et al., 2003). Normality and collinearity are
already discussed in section 5.2.1. Linearity and homogeneity were handled in SPSS24 as
discussed in respective subsections.
101
Linearity Test Linearity was determined based on F-statistics and significance level by running a linear
regression and evaluating ANOVA and coefficient results. Under this method, F-statistics are
supposed to be greater than 3, to demonstrate linear model (Grewal et al., 2004, Faraway,
2002). In addition, a graphical method was used. Under the graphical method, when a straight
line among scatter points exits, it shows the model is linear (Faraway, 2002).
Homogeneity Tests
Homogeneity test is important at initial stage of data analysis to avoid occurrence of
heteroscedastic that may be caused by the same variance of different population and from
unknown distribution (Chen and So, 2006). Simple regression analysis was performed with
plots option to establish data homogeneity among study variables. This was measured based
on scatter plot (Z-prediction value Vs Z-residual value). Under this method, when the points
converge, it proves that the data was homogeneous (Faraway, 2002). Furthermore, Levene test
was also performed under SPSS descriptive and explore options. According to this test, p-
values should be above 0.05 (Sig ≥ 0.05) based on mean for dependent variables to prove that
the data was homogeneous (Sattari et al., 2012, Scotti et al., 2011).
5.3 Adoption and Justification for Using PLS-SEM Whereas there are various regression techniques used in estimating models, Structural
Equation Modeling (SEM) was preferred for this analysis. SEM is widely used in different
fields for example; social sciences, information systems, international business, marketing and
construction management among others (Sarstedt et al., 2019b, Rasoolimanesh et al., 2019, Ali
et al., 2018a, Kock and Hadaya, 2018, Cheah et al., 2018, Ringle et al., 2018). Additionally,
SEM is a powerful statistical tool capable of producing robust results (Hussain et al., 2019,
Hwang et al., 2019, Hair et al., 2019, Memon et al., 2017). Convincingly, SEM is most suitable
for analysing relationships among variables in construction management research field (Shan
et al., 2020b, Sinesilassie et al., 2019, Müller et al., 2018, Newaz et al., 2018, Shan et al., 2017,
Liu et al., 2016). This analysis’s suitability is due to PLS-SEM prediction- oriented approach
unlike Covariance based-SEM (CB-SEM) (Sarstedt et al., 2019b, Ali et al., 2018a, Ringle et
al., 2018). Specifically, Partial Least Square Structural Equation Modeling is suitable for
theoretical explanations of outcome results (Rajab and Eydgahi, 2019, Chileshe et al., 2018,
Kumar and Purani, 2018).
Whereas there are two types of SEM, Partial Least Square - Structural Equation Modeling
(PLS-SEM) was preferred to Covariance-Based Structural Equation Modeling (CB-SEM)
102
because of its prominence in various research fields, ability to handle non-normal data and use
of small sample size (Ali et al., 2018a, Memon et al., 2017, Liu et al., 2016). Particularly,
PLSE-SEM is good when premises (distribution assumptions) of CB-SEM are violated (Ali et
al., 2018a, Kumar and Purani, 2018, Ringle et al., 2018). In addition, PLS-SEM can combine
factor analysis and regression in simultaneous analysis when determining the relationships
among study variables (Müller et al., 2018, Shan et al., 2017, Hair et al., 2014, Le et al., 2014a,
Gefen et al., 2000). The approach is good at theory confirmation, predicting variable
relationships and identifying hypotheses within structural model (Foroughi et al., 2019, Memon
et al., 2017, Chin, 1998). Furthermore, PLS-SEM is good for exploratory research, using non-
normal distribution data and can solve complex scenarios using small samples (Chileshe et al.,
2018, Hair et al., 2017, Le et al., 2014a, Hair et al., 2011, Henseler, 2010). The ability to handle
skewed data with less stringent assumptions compared to CB–SEM was good enough to adopt
PLS-SEM (Hair et al., 2017, Memon et al., 2017, Henseler et al., 2014, Urbach and Ahlemann,
2010, Chin, 1998).
Whereas in covariance based SEM, maximum likelihood estimation method does not deal
with incomplete raw data file, PLS-SEM uses an iterative sequence of ordinary least square
estimation method capable of handling incomplete data (Memon et al., 2017, Gefen et al.,
2000). PLS-SEM is efficient in dealing with low missing values (Memon et al., 2017, Hair et
al., 2014, Little and Rubin, 2002). In addition, PLS-SEM is capable of using nominal, ordinal
and scale measures in predictor constructs (Ringle et al., 2018). Previously, scholars criticised
PLS-SEM approach for lacking a global goodness fit to estimate the models. However, current
Smart-PLS version 3 use Standardized Root Mean Square Residual (SRMR) to estimate model
fit (Hair et al., 2019, Ringle et al., 2015b, Hair et al., 2014, Henseler, 2010). Conclusively,
reports show that PLS-SEM is suitable for small sample size, its ability to produce acceptable
statistical power with small samples, complex models with reflective or formative indicators,
and parameter estimation that provides significant relationships (Sarstedt et al., 2019b,
Rasoolimanesh et al., 2019, Ali et al., 2018a, Kock and Hadaya, 2018, Kumar and Purani, 2018,
Ringle et al., 2018, 2014, Henseler, 2010). Hence, with eight study variables, nineteen
hypotheses and 192 valid responses together qualify PLS-SEM as a suitable approach for data
analysis in this dissertation. Furthermore, because this dissertation aimed at predicting variable
relationships in the theoretical model, PLS-SEM was appropriate to determine prediction
following correlational linkages in simultaneous analysis. This was achieved by running PLS-
algorithm and bootstrapping techniques, and examining path coefficients.
103
5.4 Measurement Model Evaluation The measurement model (outer model) defines the relationship between manifested
variables (indicators) and their respective latent variables that can be reflective or formative
(Sarstedt and Cheah, 2019, Ringle et al., 2018, Götz et al., 2010). Under measurement model
evaluation, four key estimations are determined including; indicator reliability, construct
reliability (internal consistency), Average Variance Extracted (AVE) and discriminant validity
(Chileshe et al., 2018, Kumar and Purani, 2018, Ringle et al., 2018, Müller et al., 2018, Ali et
al., 2018b). After verifying content validity, determining both indicator reliability and internal
consistence is equally important. Indicator reliability ascertains how much of the indicator
variance is explained by its variable established through indicator loadings. The variance
should be above 50% (Le et al., 2014a, Götz et al., 2010, Urbach and Ahlemann, 2010). Internal
consistency (construct reliability) is determined by how adequately, combined indicators
measure their variable together. Strong indicator association is good and was determined
through composite reliability that measures representativeness of indicators to their respective
variable. PLS-SEM explores a three-step process in obtaining factor loadings, path coefficients
and coefficient of determination (R²). In the first step, an iterative process involving multiple
regressions on the model is performed until a solution converges on a group of weights
estimating latent variable scores. Step 2 and 3 are none-iterative and uses ordinary least squares
to establish factor loadings, path coefficients and mean scores for latent variables and indicators
(Chin, 1998). Recently, Kumar and Purani (2018) categorized the steps into iterative estimation
of latent variable scores, estimation of parameters for structural and measurement models.
To have good scales for measuring study variables, measurement items were generated and
validated in line with model validation process (Hair et al., 2014, Urbach and Ahlemann, 2010).
This was done to achieve better reliability and validity of study variables and avoiding random
errors (Mwakibinga and Buvik, 2013, Forza, 2002). This was achieved by running PLS
algorithm and evaluating indicator coefficients. Indicators with coefficients ≥ 0.7 were
retained while indicators with coefficients < 0.5 were dropped (Chileshe et al., 2018, Ali et al.,
2018a, Kline, 2015, Wong, 2013). All variables were measured reflectively and dropping
indicators with coefficients below 0.5 did not affect construct meaning since these were
reflective measures (Müller et al., 2018, Gefen and Straub, 2005, Gefen et al., 2000). The
process of retaining and deleting measurement items was systematic and was done by accepting
items with indicator loadings ≥ 0.6, then removing items that correlated negatively.
104
Figure 5.1: Types of construct measurement
(a) (b)
There are two measurement models in structural equation Modeling (i.e. Formative and
Reflective) as depicted in Fig 5.1 (Sarstedt et al., 2019a, Sarstedt and Cheah, 2019, Müller et
al., 2018, Ringle et al., 2018). The models for this thesis were measured reflectively. According
to Müller et al. (2018), reflective models are characterized by:
Any variation in latent variable does not vary their indicators. Accordingly,
removing an indicator does not affect that variable.
The causal direction is indicated by arrows originating from the variable towards
indicators as seen from Fig 5.1a.
The indicators in reflective models are highly correlated, positive and covary with
each other.
5.4.1 Validity and Reliability Extending questionnaire reliability and validity from section 4.5.2, and since the study
model is reflective, it was important to test the measurement model for internal consistency ,
indicator reliability, convergent and discriminant validity (Urbach and Ahlemann, 2010).
5.4.1.1 Reliability
Having obtained data from the right source by using staff knowledgeable in public road
construction projects as respondents and eliminating mistakes from the questionnaire through
systematic improvement for better instrument reliability, the next stage embarked on statistical
test for reliability. PLS-Algorithm based on factor analysis was conducted to obtain
measurement indicators with sufficient reliability and internal consistency for respective study
variables. Composite reliability and Cronbach alpha are used to test internal consistency based
on data collected from the questionnaire administered. In determining internal consistency, a
composite reliability coefficient (𝜌𝑐 ) of 0.7 is acceptable, 0.8 very good and above 0.90
excellent (Rasoolimanesh et al., 2019, Ali et al., 2018a, Ringle et al., 2018, Kline, 2015, Le et
al., 2014a, Field, 2013, Hair et al., 2012a). Composite reliability is recommended in reporting
internal consistency than Cronbach’s alpha and the 𝜌𝑐 coefficient should be above 0.7.
Reflective Formative
105
However, 0.6 is acceptable (Chileshe et al., 2018, Wong, 2013, Bagozzi and Yi, 1988).
Composite reliability is preferred to Cronbach alpha because composite reliability assume more
accurate parameter estimation compared to Cronbach alpha (Müller et al., 2018, Ali et al.,
2018b, Chin, 2010). High coefficient values indicate that all indicators are similar with the
same range. While values below 0.6 show lack of reliability (Urbach and Ahlemann, 2010,
Gefen and Straub, 2005).
Indicator reliability shows how a set of measurement items measure a particular
variable different from other variables. It is achieved by observing reflective indicator
coefficients (outer loadings) that are squared to obtain respective indicator reliability (Wong,
2013). The variable should at least explain 50% of individual indicator’s variance (Urbach and
Ahlemann, 2010). Ideally, indicator reliability with standardized loadings more than 0.7 is
desirable (Ringle et al., 2018). The PLS-algorithm results for both construct reliability and
indicator reliability were satisfactory as demonstrated in section 6.3 and 6.4 respectively.
5.4.1.2 Convergent and Discriminant Validity
Validity refers to whether measurement tests meet researcher’s intended measures
(Clark-Carter, 2009). In addition, validity establishes whether the measurement indicators
capture underlying construct (Um and Kim, 2018). Construct validity is either convergent or
discriminant.
Convergent validity: Is concerned with individual measurement indicators reflecting
a particular variable to converge in respect to indicators of another construct or how well
indicators represent their variable. Simply, convergent validity measures the representativeness
of measurement indicators in respective variables (Cheah et al., 2018, Müller et al., 2018, Ali
et al., 2018b). For indicators to converge, the range between lowest and highest loading should
be narrow. However, Chin (2010) notes that there is no minimum set range for estimating
convergent validity for example, 0.7 to 0.9 (narrow range) is better than 0.5 to 0.9 (wide range).
Convergent validity is examined through Average Variance extracted (AVE) that is useful in
determining construct validity and test for model development (Rasoolimanesh et al., 2017,
Hair et al., 2012a). Average Variance Extracted values greater or equal to 0.5 shows that the
latent variable explains more than 50% variance of its indicators. Hence, representing
sufficient convergent validity (Rasoolimanesh et al., 2019, Chileshe et al., 2018, Ali et al.,
2018a, Cheah et al., 2018, Ringle et al., 2018, Müller et al., 2018, Le et al., 2014a, Urbach and
Ahlemann, 2010).
106
Discriminant Validity: Reflective model validation ends with discriminant validity
tests (Götz et al., 2010). Discriminant validity measures inter-construct relationship. It ensures
that the indicators of one variable are different from indicators of another variable. It ascertains
how distinct latent variables are from one another (Müller et al., 2018). Ideally, discriminant
validity ensures that the indicators should measure what they are supposed to measure.
Indicator loadings for each latent variable should correlate highly with each other in the same
variable than any other latent variable. This process enabled the study by obtaining right
measurement indicators to facilitate further model estimation. This was enhanced by
eliminating indicators that are poorly loaded on hypothetical variables while balancing with
content validity. There are different methods of determining discriminant validity including;
Cross loadings, Fornell-Larker and Heterotrait-Monotrait ratio (HTMT) (Rasoolimanesh et al.,
2019, Ringle et al., 2018, Müller et al., 2018, Ali et al., 2018b). Under cross loadings, indicator
reliability is calculated by squaring each corresponding factor loadings. In addition, when each
variable loads highly with its indicators rather than other variable’s indicators, it proves that
they are distinct. The AVE of individual variable should be higher than the highest squared
correlation of another variable that is observed in cross loadings criterion (Müller et al., 2018,
Urbach and Ahlemann, 2010).
Alternatively, square root of AVE should be higher than correlations among latent
variables that is demonstrated by Fornell-Larker criterion (Müller et al., 2018, Ali et al., 2018b,
Wong, 2013, Chin, 2010). Discriminant validity is also determined using HTMT currently
available in Smart-PLS 3 version. Under this method, HTMT values below 0.85 or < 0.9 are
recommended (Sarstedt et al., 2019a, Ali et al., 2018a, Rasoolimanesh et al., 2017, Hair et al.,
2017, Ringle et al., 2015b). Notably, HTMT is now recommended as a superior criterion for
determining discriminant validity because the other two criterion overstate discriminant
validity (Sarstedt et al., 2019b, Ali et al., 2018a, Kumar and Purani, 2018, Ringle et al., 2018,
Rasoolimanesh et al., 2017, Hair et al., 2017). After running PLS-algorithm, HTMT, Fornell-
Larker criterion and cross-loadings coefficients were verified and results are presented in
interpretation chapter under respective tables.
5.5 Structural Model Evaluation Structural model also called inner model is concerned with relationships between
hypothetical variables established by the researcher. It is profound on the path coefficients
using empirical data to prove or disprove theory surrounding the conceptual model. PLS-SEM
follows a three-step process of evaluating the structural model including; specification,
107
identification and validation. Under model specification, the researcher clearly explains
whether the model is reflective or formative. Under identification, the reflective model
identification follows a “Three thumb rule” that requires each variable in the model to have at
least three indicators for identification (Freeze and Raschke, 2007). After validating the
measurement model, the structural model needs to be validated using non-parametric tests to
establish structural model quality. Parametric tests have constrained assumptions that are
satisfied before they are applied. For example, they assume normal data distribution. A series
of parametric tests are used in the analysis and interpretation of results to confirm the
researcher’s hypotheses. The hypotheses are either supported or not supported depending on
significance of Chi-Square (ᵡ²) values (Naoum, 1998).
While non-parametric tests (t-statistics) in PLS-SEM are generated by bootstrapping
techniques/ procedure and are not constrained by many assumptions and are applicable for
ordinal and nominal data (Müller et al., 2018, Rasoolimanesh et al., 2017, Nitzl et al., 2016).
This dissertation adopted non-parametric techniques based on the significance of t-statistics for
path coefficients, coefficient of determination (R²) and model fit to validate the structural
model. This dissertation followed Hair et al. (2012b) five step structural model assessment
process consisting of assessment for: 1. Collinearity 2. Significance and relevance of structural
model relationships 3. Level of coefficient of determination (R²), 4. Effect size (ƒ²) and 5.
Model fitting. These basic steps are commonly used in PLS-SEM (Chileshe et al., 2018, Ringle
et al., 2018). These are good cross-validation and relevant function fitting technique like hands
in the glove (Hair et al., 2012b). The steps are described below.
5.5.1 Collinearity Assessment Collinearity was primarily handled in data preparation (section 5.2.1)). This was enabled by
running PLS-algorithm and assessing Variance Inflation Factor (VIF) values for all study
variables. Verifying VIF for reflective measurement models is important since multi-
collinearity can inflate bootstrapping standard errors and misinterpretation of indicators (Ali et
al., 2018a, Hair et al., 2012b). VIF values for both compliance and project success models were
verified and reported in Table 6.15a. PLS-algorithm unlike SPSS, only gives VIF values.
Hence, a parallel collinearity analysis was performed in SPSS24 based on linear regression for
all study variables. Under this analysis, VIF and tolerance values were verified and results
compared to PLS-algorithm output. Both results are satisfactory as depicted in Table 6.14 (a &
b) corresponding to compliance and project success models. Tolerance values of ≥ 0.20 and
108
VIF ≤ 5.00 are recommended thresholds for retaining dependent variables (Chileshe et al.,
2018, Ali et al., 2018a, Ringle et al., 2018, Hair et al., 2012b).
5.5.2 Significance and Relevance of Structural Model Relationships Path coefficients represent the linkage between study variables demonstrating hypothesised
relationships and the values range between -1 and +1 (Rajab and Eydgahi, 2019). The
relationship is confirmed and supported if a path coefficient is significant after performing
bootstrapping (Chileshe et al., 2018, Ali et al., 2018a, Ali et al., 2018b, Müller et al., 2018,
Hair et al., 2014). Individual path coefficients are based on standardized beta coefficients
estimated from ordinary least squares (Ali et al., 2018a, Ali et al., 2018b, Götz et al., 2010).
Bootstrapping resampling technique was performed and significance of t-values for respective
paths coefficients determined. Determining path coefficients involves establishing signs,
magnitude and significance levels (Ali et al., 2018a). In this step, signs contrary to stated
hypotheses indicate that the hypothesis is not supported and vice-verse. The magnitude
indicates the strength or impact size of relationship between the variables. The strength is
assessed through path coefficients that should exceed 0.10 to show impact in the model, while
their significance should be at-least at 0.05 level. Significance of t-values is achieved at the
following levels: t > 1.96 at 0.05 significance level, t > 2.576 at 0.01 level of significance and
t > 3.29 at 0.001 significance level using a two-tailed test or t > 0.98 using a one-tailed test (Le
et al., 2014a, Hair et al., 2012b). After performing bootstrapping resampling with 5000
subsamples, all path coefficients for independent variables corresponding to compliance and
project success models were respectively assessed to determine individual impact size. The
results are presented in Table 6.20 section 6.9 showing supported and unsupported hypotheses.
5.5.3 Coefficient of Determination (R²) The structural model’s predictive accuracy is determined through coefficient of
determination whose values range from zero to one (Hussain et al., 2019). A good model fitting
is achieved with significant path coefficients, high R² and when the construct reliability is ≥
0.7 (Kumar and Purani, 2018, Hair et al., 2012a, Gefen et al., 2000). Coefficient of
determination of dependent variable represents its explained variance by the total independent
variables (antecedent constructs) also known as predictive power assessment (Müller et al.,
2018). Recommended values of R² ≥ 0.1 demonstrate a well explained variance by the
dependent variables while R2 less than 0.1 is unsuitable (Hussain et al., 2019, Falk and Miller,
1992). However, R² values of 0.670, 0.333 and 0.190 show substantial, average and weak
explained variance respectively (Urbach and Ahlemann, 2010, Chin, 2010, Chin, 1998). While
109
Hussain et al. (2019) asserts that R2 values greater than 0.26, between 0.13 and 0.26, and
between 0.02 and 0.13 are considered substantial, moderate and weak respectively.
Alternatively, recent reports show that R2 measure model’s predictive power and values of
0.25, 0.50 and 0.75 shows that model’s in-sample predictive power is weak, moderate and
strong respectively (Ringle et al., 2018). Whereas there are no cut off points for acceptable R2,
its size depends on the complexity of the structural model (Kumar and Purani, 2018, Hair et
al., 2011, Götz et al., 2010, Henseler et al., 2009). However, large R2 implies large variance
explained (Kumar and Purani, 2018, Götz et al., 2010). By running PLS-algorithms and
bootstrapping, significant R2 values for compliance with public procurement regulatory
framework and public road construction project success were respectively determined and
presented in Table 6.37 section 6.10.
5.5.4 Effect Size (ƒ²) Whereas R2 is more concerned with predictive model accuracy, structural model evaluation
requires determining individual independent variable impact on a dependent variable. This is
called effect size. Respective effect size is achieved through omission of one independent
variable from the analysis and rerunning the model to ascertain its influence on corresponding
dependent variable. To examine individual independent variable impact on dependent variable,
changes in R² are used to determine effect size of each path through Cohen’s ƒ². Each
independent latent variable effect size measure (ƒ²) shows the magnitude of influence on the
corresponding dependent latent variable. Ideally, ƒ² measures changes in R² when specified
independent variable is excluded from the model and re-estimate R² to determine its impact
(Hair et al., 2012b). Values of ƒ² ranging between 0.020 and 0.150, 0.150 and 0.350 and above
0.350 show that independent variable has small/weak, medium/moderate and large/strong
effect on dependent latent variable respectively (Rajab and Eydgahi, 2019, Ali et al., 2018a,
Kumar and Purani, 2018, Müller et al., 2018, Urbach and Ahlemann, 2010, Götz et al., 2010,
Chin, 2010, Gefen et al., 2000, Chin, 1998).
Estimating effect size follows systematic steps by omitting independent latent variable one
by one and rerunning the model to re-estimate R² for corresponding dependent variable and
their respective effect size as per the formula ii. Previous versions of Smart-PLS software
lacked effect size estimation feature as opposed to the current version used in this analysis.
PLS-algorithm and bootstrapping resampling technique in Smart-PLS3 were performed and
the effect size on both compliance and project success by respective independent variables
automatically calculated. Despite simultaneous effect size determination, the calculations
110
follow the same procedures described above corresponding to formula ii. Respective ƒ² values
for the six independent variables predicting compliance with public procurement regulatory
framework and ƒ² value for the seven independent variables predicting public road construction
project success are presented in Table 6.38 section 6.10.
𝑓2 = 𝑅2𝑖𝑛𝑐𝑙𝑢𝑑𝑒𝑑−𝑅2𝑒𝑥𝑐𝑙𝑢𝑑𝑒𝑑
1−𝑅2𝑖𝑛𝑐𝑙𝑢𝑑𝑒𝑑 ii
5.5.5 Model Fitting Acceptable model fitting is important to determine whether the underlying theory is
reflected in the data (Sinesilassie et al., 2019). Hence, it is simply an empirical evidence to
prove that the estimated model fits the data collected (Müller et al., 2018). Fitting of structural
model and significance of coefficient of determination are now possible with current Smart-
PLS3. Previous versions of Smart-PLS software lacked statistic for model fit. Indeed, the
software was criticised for lack of a global model fit statistic. However, the current version is
inbuilt with Standardized Root Mean Square Residual (SRMR) to determine model fit (Hair et
al., 2019, Ringle et al., 2015a). SRMR measures the mean absolute correlation residual as a
difference between observed and predicted correlation (Kline, 2015, Hu and Bentler, 1999).
For acceptable model fit, SRMR ≤ 0.08 is recommended (Rasoolimanesh et al., 2019, Hair et
al., 2019, Sinesilassie et al., 2019, Ali et al., 2018a, Nitzl et al., 2016). Alternatively, values of
0.08 is good while 0.1 is fair (Kumar and Purani, 2018, Newaz et al., 2018, Mathieu and Taylor,
2006, Browne and Cudeck, 1989). Hence, this dissertation adopted Standardized Root Mean
Square Residue statistic to determine the model fit and the findings are presented in Table 6.37
section 6.10.
5.6 Mediational Effect Mediation is based on the framework that assumes that the independent variable
predicts the mediating variable that finally predicts the dependent variable. This is achieved by
specifying the causal order of these variables (Mojtahedi and Oo, 2017, Mathieu and Taylor,
2006). The article further notes that mediation refers to significant total relationship between
independent and dependent variables that is either partially or fully explained by the mediating
variable. Testing for mediation effect is vital when a third variable is identified as contributing
an effect between the two existing variables. This thesis was concerned with establishing
whether compliance with public procurement regulatory framework mediates the relationship
between each of the six probable compliance factors and the success of public road construction
111
projects in Uganda. The mediation test was sequentially carried out six times corresponding to
the six hypothesised compliance factors (Familiarity, monitoring activities, professionalism,
sanctions, perceived inefficiency and contractors’ resistance) following Baron and Kenny’s
assumptions in conjunction with Sobel test (Preacher and Leonardelli, 2001, Sobel, 1982). The
analyses were performed concurrently using SPSS24 and Med-graph3 Excel program. Detailed
findings for respective mediational effects and corresponding tables and figures are reported in
section 6.9.2.
This leads to the interpretation of results presented in chapter six.
112
CHAPTER SIX RESULTS INTERPRETATION
113
6.1 Introduction This chapter presents results performed by Smart-PLS3, Statistical Package for Social
Scientist (SPSS24) and Med-Graph Excel program based on research objectives and
hypotheses. It begins with descriptive statistics majorly performed in SPSS24, preliminary
analysis, assessment of the measurement model, structural model, hypotheses testing
performed in Smart-PLS3, and mediation tests performed using Med-Graph3 Excel program.
It ends with validated models resulting from Smart-PLS-SEM bootstrapping resampling
technique (Ringle et al., 2015b).
6.2 Profile of Respondents and their Organisations Descriptive statistics are recommended for summarising huge data on the
characteristics of study variables for easy and quick interpretation (Davis et al., 2004). This is
important for the forthcoming data analysis stages with respect to normal distribution,
frequencies, means, skewness and kurtosis. Descriptive statistics provided background
information on study variables and were performed in SPSS24 (George and Mallery, 2016,
Field, 2013).
Table 6.1: Organisations
Frequency Percent Valid Percent Cumulative
Percent Valid MOWT 87 45.3 45.3 45.3
URF 12 6.3 6.3 51.6 PPDA 55 28.6 28.6 80.2 Contractors 38 19.8 19.8 100.0 Total 192 100.0 100.0
Table 6.1 presents number of participating organisations in this study showing
respective percentage to the study sample size. Ministry of Works and Transport had the
highest percentage of participants followed by Public Procurement and Disposal of Public
Assets Authority.
Table 6.2: Education
Frequency Percent Valid Percent Cumulative
Percent Valid Primary 1 0.5 0.5 0.5
Diploma 10 5.2 5.2 5.7 Bachelors 75 39.1 39.1 44.8 Masters 103 53.6 53.6 98.4
114
PhD 3 1.6 1.6 100.0 Total 192 100.0 100.0
Table 6.2 presents respondents’ education level who participated in this study showing
respective percentage to the study sample size. Education is one of the factors determining
seniority and maturity of respondents to give reliable and credible information on
organizational affairs. It was clear that over 94% of the respondents possessed a bachelor’s
degree and above. This implied that the majority of the respondents were academically
qualified staff and competent to interpret and answer questions raised. This increased
confidence and reliability of the responses obtained.
Table 6.3: Professional Training
Frequency Percent Valid Percent Cumulative
Percent Valid CIPS 38 19.8 19.8 19.8
CILT 9 4.7 4.7 24.5 ACCA 11 5.7 5.7 30.2 CPA 18 9.4 9.4 39.6 Others 116 60.4 60.4 100.0 Total 192 100.0 100.0
Table 6.3 presents professional training attained by respondents in this study showing
respective percentage to the sample size. The majority of respondents had professional
qualifications, which was majorly in the engineering profession. This option was not listed in
the questionnaire. The respondents only expressed their profession by choosing ‘other’ option
and briefly explaining what the profession was. In further evaluation of these responses,
respondents indicated that they possessed professional certificate provided by respective
engineering association. This was because road construction is largely implemented by staff
with engineering background. Professional qualification was an added advantage on normal
academic qualification that influences staff competence and capability (DiMaggio and Powell,
2015).
Table 6.4: Age
Frequency Percent Valid Percent Cumulative
Percent Valid 30 years and below 43 22.4 22.4 22.4
31 to 40 Years 75 39.1 39.1 61.5 41 to 50 years 69 35.9 35.9 97.4
115
Above 50 years 5 2.6 2.6 100.0 Total 192 100.0 100.0
Table 6.4 presents age brackets for respondents who participated in this study showing
respective percentages. The thesis aimed at obtaining credible information based on maturity
of respondents. Statistics indicate that 77.6% of staff were above 30 years old. This increased
confidence and reliability of the responses obtained because age is one of the components that
determine staff maturity in understanding organisation matters.
Table 6.5: Title
Frequency Percent Valid Percent Cumulative
Percent Valid Below officer 30 15.6 15.6 15.6
Officer or Manager and above
162 84.4 84.4 100.0
Total 192 100.0 100.0
Table 6.5 presents the level of seniority among study participants within organizational
ranks. According to respective percentages, most of the respondents were senior officers as
demonstrated by 84.4% compared to 15.6% who were below officer level in organizational
hierarchy. This indicates that the study involved suitable respondents who are knowledgeable
within their respective activities. Hence, they were well positioned and able to give reliable
information in their respective organisations, which increased confidence in this dissertation
having credible information regarding compliance and project success factors in the
procurement of public road construction projects.
Table 6.6: Gender
Frequency Percent Valid Percent Cumulative
Percent Valid Male 121 63.0 63.0 63.0
Female 71 37.0 37.0 100.0 Total 192 100.0 100.0
Table 6.6 presents gender representation of study participants showing respective
percentages. Since study participants were at senior level, it was worth noting to establish any
bias in responses based on gender. The findings indicate that 63.0% of study participants were
male compared to 37.0% female. Initially, males dominated most of organizational positions
compared to female and now with gender equality, the numbers of female participants are
116
increasing considerably. Accordingly, this study registered a good gender distribution balance
with small difference given the current generation.
Table 6.7: Registration with any professional body
Frequency Percent Valid Percent Cumulative Percent Valid No 87 45.3 45.3 45.3
Yes 105 54.7 54.7 100.0 Total 192 100.0 100.0
Table 6.7 presents the respondents’ professional body registration status with respective
percentages. Most of the respondents are registered with their respective professional bodies.
This reaffirms earlier report on professional training. With practical road construction projects,
professional training is just emerging. Professional bodies have a mandate of controlling their
members and issuing them with practising certificates. In this dissertation, the majority of the
participants had an engineering background and were registered under their professional body
as an added requirement for employment. Hence, in Uganda’s case most of these staff under
ministry of works and transport, Uganda road fund and contractors were registered with
Uganda Institute of Professional Engineers (UIPE).
Table 6.8: Name of registered professional body
Frequency Percent Valid Percent Cumulative
Percent Valid NO 88 45.8 45.8 45.8
CIPS 14 7.3 7.3 53.1 UIPE 36 18.8 18.8 71.9 ERB 6 3.1 3.1 75.0 IPPU 21 10.9 10.9 85.9 ICPAU 3 1.6 1.6 87.5 ACCA 4 2.1 2.1 89.6 CPA 6 3.1 3.1 92.7 CILT 2 1.0 1.0 93.8 USS 1 .5 .5 94.3 IKS 1 .5 .5 94.8 SMED 1 .5 .5 95.3 CISSCO 1 .5 .5 95.8 CMAU 1 .5 .5 96.4 ULIA 1 .5 .5 96.9 ULS 1 .5 .5 97.4 EC (UK) 1 .5 .5 97.9 CFDE 1 .5 .5 98.4
117
SRB 1 .5 .5 99.0 CEEM 1 .5 .5 99.5 KTA 1 .5 .5 100.0 Total 192 100.0 100.0
Table 6.8 presents the respondents’ respective professional body. The results indicate
that out of 192 participants, 88 (45.8%) do not belong to any of the listed professional bodies
and a majority of the participants 104 (54.2%) were registered. By analysing their registration
further, 36 (18.8%) were registered with Uganda Institute of Professional Engineers (UIPE)
and 6 (3.1%) were registered with Engineers Registration Board (ERB). Procurement
professional bodies including; Chartered Institute of Purchasing and Supplies (CIPS),
Chartered Institute of Logistics and Transport (CILT) and Institute of Procurement
Professionals Uganda (IPPU) collectively had 37 (19.2%) study participants. This is relatively
a good number because the study revolved around public procurement of road construction
projects. Hence, a good blending of engineers and procurement professionals formed large
percentage of participants. While others comprised of accountants and financial professionals
for accountability purposes. This built further reliability and validity of responses obtained in
this dissertation.
Table 6.9: Descriptive Statistics for Years in Current Position in the organization and number of employees
N Minimum Maximum Mean Std. Deviation Years in current position 192 .3 27.0 5.112 4.3645 Number of employees 192 2 150 20.64 21.941 Years in Organisation 192 .3 22.0 6.340 5.0871
Table 6.9 presents respondents’ years in their current position and in the organisation.
It was necessary to look into the experience of study participants in their respective
organisations. Statistics show that most of the respondents have served in both their current
position and organisation for a long period as demonstrated by respective means of 5.1 and 6.3
years. This implied that participants were experienced and able to give reliable information to
support the results of this dissertation. The demographic characteristics proved helpful in
understanding the nature of study participants before embarking on the data characteristics in
terms of data reliability and validity that follows in the next section.
6.3 Composite Reliability With satisfactory demographic results, the thesis assessed reliability for the
measurement instrument aimed at obtaining valid and consistent output. Data reliability is
118
important when there is trust in data source from respondents filling the questionnaire
(Oppenheim, 1992). Reliability is getting rid of mistakes in the measurement instrument for
data consistency (McDaniel and Gates, 2010, Gupta, 2002, Santosh, 2007). The purpose of the
reliability test enabled the retention of indicators that qualified to measure study variables in
the initial factor analysis stage. Both indicator and construct reliabilities determination are
important. Composite reliability results from Smart-PLS algorithm are above 0.7 and in
conformance with literature cited as depicted in Table 6.10 (Rasoolimanesh et al., 2019,
Hussain et al., 2019, Foroughi et al., 2019).
Reliability results were extracted as follows; Familiarity with public procurement
regulatory framework had originally fifteen indicators and only three were retained with 𝜌𝑐 =
0.792. Monitoring activities had sixteen indicators originally and four were retained with 𝜌𝑐 =
0.830. Professionalism had originally twenty-four indicators and five were retained with 𝜌𝑐=
0.838. Sanctions had originally sixteen indicators and three were retained with 𝜌𝑐 = 0.798.
Perceived inefficiency of public procurement regulatory framework had originally four
indicators and only three were retained with 𝜌𝑐 = 0.817. Contractors’ resistance to non-
compliance with public procurement regulatory framework had originally three items and only
two were retained with 𝜌𝑐 = 0.802. Compliance with public procurement regulatory
framework had originally eleven indicators and only four were retained with 𝜌𝑐 = 0.840.
Project success had originally four indicators and only three were retained with 𝜌𝑐 = 0.865.
Table 6.10: Reliability test results
Variable N of Items Scale Composite
Reliability (𝜌𝑐)
Familiarity
3 1 - 5 0.792
Monitoring activities
4 1 - 5 0.830
Professionalism
5 1 - 5 0.838
Sanctions
3 1 - 5 0.798
perceived inefficiency 3 1 - 5 0.817
Contractors’ Resistance 2 1 - 5 0.802
119
Compliance
4 1 - 5 0.840
Project success
3 1 - 5 0.865
6.4 Factor Loadings
PLS-algorithm with factor analysis helps in obtaining indicators to explain a study
variable through correlational patterns and data reduction. PLS-algorithm aimed at further
retaining indicators that represent the variable very well (Wong, 2013). Factor loadings (outer
loadings) were examined for indicator reliability by extracting suitable indicator for respective
study variables. Through running PLS algorithm, outer loadings for each variable with
coefficient ≥ 0.6 were retained while indicators with coefficients < 0.5 were dropped (Wong,
2013). The results of indicator loadings also called outer loadings are presented in Table 6.11.
Table 6.11: Outer Loadings
Compliance
Contractors' resistance Familiarity Monitoring Perceived
inefficiency Professionalism Sanctions Project success
CP1 0.895 CP10 0.727
CP2 0.663 CP3 0.719 CR1 0.856 CR2 0.779 F1 0.746 F13 0.675 F3 0.818 M13 0.597 M14 0.858 M15 0.820 M4 0.675 PI1 0.730 PI2 0.845 PI3 0.742 PR18 0.682 PR19 0.686 PR20 0.714 PR21 0.791
PR3 0.690 S7 0.812
120
S8 0.862 S9 0.569 PS1 0.728 PS2 0.883 PS3 0.858
6.5 Average Variance Extracted (AVE)
Construct validity is either convergent or discriminant validity. Convergent validity
was concerned with individual measurement indicators converging on a particular variable in
respect to indicators of another variable. The results show that AVE values for all study
constructs are above 0.5 proving sufficient convergent validity as portrayed in Table 6.12
(Rasoolimanesh et al., 2019, Hussain et al., 2019, Ali et al., 2018a, Ali et al., 2018b, Hair et
al., 2014, Urbach and Ahlemann, 2010).
Familiarity with Public Procurement Regulatory Framework
Fifteen indicators were initially determined to measure familiarity with public
procurement regulatory framework governing public road construction projects. However,
after running PLS-algorithm and bootstrapping technique, only three indicators were retained
to measure this variable i.e. F1, F3 and F13 (See Table 6.11). It shows that these indicators
explained 56.0% of total variance as presented in Table 6.12.
Monitoring Activities
There were sixteen indicators originally for measuring monitoring activities of public road
construction projects. However, on performing PLS-algorithm and bootstrapping and verifying
factor loadings, only four indicators qualified and correlated highly on the variable. The four
indicators including; M4, M13, M14 and M15 accounted for 55.5% total variance as depicted
in Table 6.12.
Professionalism of Staff
Originally, there were twenty-four indicators to measure professionalism of staff involved
in public road construction projects. However, only five indicators including; PR3, PR18,
PR19, PR20 and PR21 were retained after performing PLS-algorithm and bootstrapping. These
indicators represent a strong correlation and explained 50.9% of total variance as presented in
Table 6.12.
Sanctions on Staff
121
Sixteen indicators were initially identified to measure sanctions on staff involved in public
road construction projects. However, after running PLS-algorithm and bootstrapping, three
indicators comprising of S7, S8 and S9 were retained. These indicators explained 57.6% total
variance as shown in Table 6.12.
Perceived Inefficiency of Public Procurement Regulatory Framework
Four indicators were initially established to measure perceived inefficiency of public
procurement regulatory framework. However, after running PLS-algorithm and bootstrapping,
and verifying indicator loadings, three indicators were retained after deleting one that was
poorly loaded. Retained indicators including PI1, PI2 and PI3 explained 59.9% variance as
shown in Table 6.12.
Contractors’ Resistance to Non-Compliance
Three indicators were originally established to measure contractors’ resistance to non-
compliance with public procurement regulatory framework. However, after performing PLS-
algorithm and bootstrapping, two indicators showing strong indicator loading were retained.
The qualified indicators CR1 and CR2 explain 67.0% total variance as presented in Table 6.12.
Compliance with Public Procurement Regulatory Framework
Eleven indicators were initially identified to measure compliance with public
procurement regulatory framework governing public road construction projects. However,
after running PLS-algorithm and bootstrapping techniques, four indicators including CP1, CP2,
CP3 and CP10 qualified to measure this variable. They explain 57.2% total variance as shown
in Table 6.12.
Project Success
Four indicators were originally identified to measure public road construction project
success. However, after running PLS-algorithm and bootstrapping, and verifying indicator
loadings, three indicators including PS1, PS2 and PS3 were retained. Retained indicators
represent a strong association and explained 68.3% total variance as seen in Table 6.12.
122
Table 6.12: Average Variance Extracted (AVE)
Average Variance Extracted (AVE) Compliance 0.572 Contractors' resistance 0.670 Familiarity 0.560 Monitoring 0.555 Perceived inefficiency 0.599 Professionalism 0.509 Sanctions 0.576 Project success 0.683
6.6 Discriminant Validity
Discriminant validity ensured that the indicators measured what they were supposed to
measure. This was determined through three methods including; Fornell-Larker criterion,
cross-loadings and Heterotrait-Monotrait ratio (HTMT). All the results are satisfactory
showing that the indicators loaded highly on to their respective variables demonstrating
acceptable discriminant validity as presented in Table 6.13 (a, b & c). However, HTMT values
take precedence since they are more reliable (Rasoolimanesh et al., 2019, Ali et al., 2018a, Ali
et al., 2018b, Hair et al., 2017, Rasoolimanesh et al., 2017).
Table 6.13 a: Fornell-Larker Criterion
Compliance
Contractors' resistance
Familiarity
Monitoring
Perceived inefficiency
Professionalism
Sanctions
Project success
Compliance 0.756 Contractors' resistance 0.266 0.818 Familiarity 0.121 0.279 0.748 Monitoring 0.064 0.279 0.352 0.745 Perceived inefficiency -0.432 -0.361 -0.295 -0.178 0.774 Professionalism 0.047 0.335 0.449 0.522 -0.249 0.714 Sanctions 0.451 0.277 0.224 0.256 -0.521 0.205 0.759 Project success 0.262 0.421 0.465 0.574 -0.385 0.600 0.285 0.826
Table 6.13 b: Cross Loadings
Compliance
Contractors' resistance
Familiarity
Monitoring
Perceived inefficiency
Professionalism
Sanctions
Project success
CP1 0.895 0.298 0.200 0.105 -0.450 0.105 0.410 0.323 CP10 0.727 0.203 0.052 0.128 -0.319 0.050 0.390 0.254 CP2 0.663 0.086 0.029 -0.098 -0.190 -0.049 0.252 0.003 CP3 0.719 0.137 0.009 -0.057 -0.259 -0.047 0.254 0.061 CR1 0.263 0.856 0.260 0.279 -0.366 0.267 0.266 0.360 CR2 0.165 0.779 0.192 0.169 -0.213 0.284 0.182 0.328 F1 0.021 0.195 0.746 0.250 -0.123 0.361 0.192 0.373 F13 0.052 0.227 0.675 0.282 -0.194 0.346 0.130 0.286
123
F3 0.181 0.213 0.818 0.268 -0.332 0.312 0.176 0.377 M13 -0.035 0.219 0.168 0.597 -0.036 0.334 0.091 0.290 M14 0.138 0.276 0.329 0.858 -0.207 0.425 0.290 0.450 M15 0.072 0.208 0.325 0.820 -0.221 0.408 0.249 0.447 M4 -0.012 0.143 0.203 0.675 -0.039 0.381 0.104 0.482 PI1 -0.267 -0.284 -0.260 -0.137 0.730 -0.185 -0.304 -0.290 PI2 -0.395 -0.313 -0.274 -0.169 0.845 -0.296 -0.486 -0.358 PI3 -0.327 -0.239 -0.142 -0.101 0.742 -0.068 -0.400 -0.232 PR18 0.028 0.216 0.302 0.364 -0.215 0.682 0.197 0.420 PR19 -0.011 0.125 0.205 0.315 -0.134 0.686 0.085 0.323 PR20 -0.064 0.164 0.276 0.373 -0.042 0.714 0.105 0.389 PR21 0.092 0.275 0.347 0.458 -0.281 0.791 0.208 0.524 PR3 0.084 0.369 0.433 0.330 -0.173 0.690 0.108 0.443 S7 0.380 0.250 0.089 0.194 -0.401 0.124 0.812 0.215 S8 0.436 0.237 0.232 0.190 -0.469 0.134 0.862 0.235 S9 0.122 0.113 0.226 0.240 -0.298 0.296 0.569 0.220 PS1 0.053 0.310 0.371 0.494 -0.083 0.455 0.097 0.728 PS2 0.298 0.390 0.420 0.497 -0.421 0.532 0.306 0.883 PS3 0.270 0.338 0.361 0.438 -0.411 0.497 0.281 0.858
Table 6.13 c: Heterotrait-Monotrait Ratio (HTMT)
Compliance
Contractors' resistance
Familiarity
Monitoring
Perceived inefficiency
Professionalism
Sanctions
Project success
Compliance Contractors' resistance 0.378 Familiarity 0.195 0.501 Monitoring 0.180 0.460 0.524 Perceived inefficiency 0.555 0.602 0.451 0.249 Professionalism 0.140 0.518 0.650 0.691 0.340 Sanctions 0.572 0.453 0,381 0.389 0.769 0.335 Project success 0.305 0.671 0.677 0.761 0.512 0.770 0.410
6.7. Diagnostic Tests
6.7.1 Collinearity Test
Extreme collinearity are issues of discriminant validity, solved by eliminating
indicators with very high collinearity (α > 0.95), and retained ones (α ≥ 0.5 α ≤ 0.95). To
achieve this, PLS-algorithm was performed to establish collinearity among study variable by
verifying Variance Inflation Factor (VIF) values. The results are satisfactory since the VIF
values are far less than the threshold of five. Implying that there is no high relationship
(Collinearity) among study variables (Rajab and Eydgahi, 2019, Ali et al., 2018a, Kline, 2015,
124
Hair et al., 2014, Hair et al., 2012b). These results were compared to SPSS results for
collinearity assessment and they are similar as depicted in Table 6.14 and 6.15 respectively.
Table 6.14 a: Smart-PLS Inner VIF Values
Variable Compliance Project success Compliance 1.387 Contractors' resistance 1.273 1.298 Familiarity 1.348 1.348 Monitoring 1.462 1.465 Perceived inefficiency 1.528 1.616 Professionalism 1.602 1.617 Sanctions 1.434 1.572 Project success
Table 6.14 b: Smart-PLS Outer VIF Values
Indicators VIF CP1 2.005 CP10 1.330 CP2 1.586 CP3 1.564 CR1 1.133 CR2 1.133 F1 1.195 F13 1.190 F3 1.289 M13 1.222 M14 2.746 M15 2.569 M4 1.192 PI1 1.263 PI2 1.379 PI3 1.287 PR18 1.372 PR19 1.570 PR20 1.606 PR21 1.597 PR3 1.344 PS1 1.305 PS2 1.973 PS3 1.903 S7 1.325 S8 1.393 S9 1.161
Table 6.15 a: SPSS Compliance model Coefficientsa results
125
Model 1
Unstandardized Coefficients
Standardized Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF (Constant) 1.035 .443 2.334 .021
Familiarity with PPRF .110 .101 .084 1.083 .280 .752 1.329 Monitoring Activities -.179 .112 -.145 -
1.592 .113 .539 1.856
Professionalism .310 .159 .196 1.949 .053 .446 2.244 Sanctions .277 .123 .209 2.253 .025 .524 1.910 Perceived inefficiency -.023 .048 -.033 -.484 .629 .983 1.018 Contractors' Resistance .117 .066 .139 1.786 .076 .744 1.343 a. Dependent Variable: Compliance
Table 6.15 b: SPSS Project success model Coefficientsa results
Model 2
Unstandardized Coefficients
Standardized Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF (Constant) -1.435 .521 -
2.757 .006
Compliance with PPRF .177 .085 .127 2.077 .039 .830 1.204 Familiarity with PPRF .005 .117 .003 .046 .964 .748 1.338 Monitoring Activities .590 .131 .346 4.518 .000 .532 1.881 Professionalism .602 .186 .274 3.240 .001 .437 2.290 Sanctions -.156 .144 -.084 -
1.079 .282 .510 1.962
Perceived inefficiency -.084 .056 -.085 -1.500
.135 .981 1.019
Contractors' Resistance .209 .077 .178 2.724 .007 .732 1.366 a. Dependent Variable: Project Success
6.7.2 Normality Test
Descriptive statistics was performed to test for normality under the following methods:
Graphical methods including; Histogram with normal curve, PP-plot and QQ-plot.
Skewness and Kurtosis.
According to the histogram output, all study variables exhibited fairly normal distribution since
a majority of the bar graphs are respectively under the normal distribution curve as
demonstrated by respective figures (Doane and Seward, 2011, Gan and Koehler, 1990).
Additionally, all the PP-plots and QQ-plots of study variables exhibited fairly normal
distribution since a majority of the points are close to the straight line as demonstrated by
respective figures (Doane and Seward, 2011, Gan and Koehler, 1990). After determining
126
normality through the graphical method, further normality tests were performed based on
Skewness and Kurtosis. Findings show that Skewness and Kurtosis for all study variables are
within acceptable limits of ±3 and ±5 respectively as demonstrated in Table 6.16 (Jondeau and
Rockinger, 2003). This implies that the data for all study variables exhibit fairly normal
distribution.
Table 6.16: Statistics for skewness and Kurtosis results
Familiarity
with PPRF
Monitoring
Activities Professionalism Sanctions
Perceived
inefficiency
Contractors'
Resistance
Compliance
with PPRF
Project
Success
N Valid 192 192 192 192 192 192 192 192
Missing 0 0 0 0 0 0 0 0
Mean 3.5874 3.5592 3.5187 3.4544 2.9427 3.7161 3.2054 3.3611
Std. Error of
Mean
.03857 .04110 .03191 .03804 .07091 .05972 .05050 .07012
Std.
Deviation
.53441 .56945 .44215 .52716 .98249 .82747 .69980 .97158
Skewness -.345 -.545 -.063 .086 -.018 -.699 .069 -.509
Std. Error of
Skewness
.175 .175 .175 .175 .175 .175 .175 .175
Kurtosis -.333 .973 .277 -.328 -.331 .266 -.619 -.407
Std. Error of
Kurtosis
.349 .349 .349 .349 .349 .349 .349 .349
6.7.3 Linearity Test
Regression was performed to determine model linearity for both compliance with
public procurement regulatory framework and project success respectively. By evaluating
ANOVA results based on F-statistic, the compliance model comprising of six independent
variables including; familiarity, monitoring activities, professionalism, sanctions, perceived
inefficiency and contractors’ resistance is linear since the F-statistic is significantly greater than
three as depicted in Table 6.17a (F = 6.301, p = 0.000) (Grewal et al., 2004, Faraway, 2002).
While the project success model comprising of seven independent variables including;
compliance, familiarity, monitoring activities, professionalism, sanctions, perceived
inefficiency and contractors’ resistance is also linear, since the F-statistic is significantly
greater than three as depicted in Table 6.17b (F = 19.534, p = 0.000) (Grewal et al., 2004,
Faraway, 2002). Additionally, graphical tests results show that both compliance with public
procurement regulatory framework and project success models have a linear relationship with
127
their respective independent variables since straight lines exist among scatter points
respectively (Faraway, 2002).
Table 6.17 a: Compliance model Regression linearity results
Model 1(Compliance) Sum of Squares df Mean Square F Sig. Regression 15.871 6 2.645 6.301 .000b Residual 77.665 185 .420 Total 93.536 191 a. Dependent Variable: Compliance with PPRF b. Predictors: (Constant), Contractors' Resistance, Perceived inefficiency, Familiarity with PPRF, Sanctions, Monitoring Activities, Professionalism
Table 6.17 b: Project success model Regression linearity results.
Model 2 (Project Success) Sum of Squares df Mean Square F Sig.
Regression 76.864 7 10.981 19.534 .000b Residual 103.432 184 .562 Total 180.296 191 a. Dependent Variable: Project Success b. Predictors: (Constant), Contractors' Resistance, Perceived inefficiency, Familiarity with PPRF, Compliance with PPRF, Monitoring Activities, Sanctions, Professionalism
6.7.4 Homogeneity Tests Homogeneity test results show that the data is homogeneous since the scatter points
have converged (Faraway, 2002). Furthermore, Levene test for homogeneity show that the data
is homogenous since the Levene statics for both compliance and project success models are
significantly greater than 0.05 based on the mean for variables as depicted in Table 6.18 (P ≥
0.05) (Sattari et al., 2012, Scotti et al., 2011). The p-values for dependent variables compliance
with public procurement regulatory framework and public road construction project success
respectively are 0.374 and 0.550 based on mean.
Table 6.18: Levene test of Homogeneity of Variance results
Levene Statistic df1 df2 Sig. Familiarity Based on Mean .829 1 190 .364 Monitoring Activities Based on Mean .062 1 190 .803 Professionalism Based on Mean .570 1 190 .451 Sanctions Based on Mean .201 1 190 .654 Perceived inefficiency Based on Mean 4.905 1 190 .028 Contractors' Resistance Based on Mean .118 1 190 .732 Compliance Based on Mean .795 1 190 .374 Project Success Based on Mean .359 1 190 .550
128
6.8 Analysis of Variance (ANOVA) of Study Variables The aim of performing a one-way ANOVA was to ascertain staff perception on the
items raised in the study instrument across participating organisations. This was based on F-
statistics to determine whether respondents across these organisations understood the questions
in the same way or not. According to Table 6.19, there is no significant difference between the
views of employees across participating organisations on the study variables since the
significance level is above 0.05 (Faraway, 2002). This implies that the statements raised on the
study variables in the instrument were perceived in the same way across these organisations as
demonstrated by P-values. Familiarity with public procurement regulatory framework (F =
0.821, P = 0.484). Under this construct, being aware of public procurement regulatory
framework governing public road construction projects was perceived in the same way across
all staff of participating organisations. Hence, respondents’ views on familiarity with road
construction implementation processes, regulating framework, qualifications and experience
were the same.
Monitoring activities on public road construction projects was perceived in the same
way across participating staff of MoWT, URF, PPDA and contractors (F = 2.492, P = 0.062).
This implied that monitoring activities, regular reports, and extensive provision of required
information, supervision and timely completion among others were understood similarly.
Professionalism among staff involved in public road construction projects was viewed
similarly among staff of MoWT, URF, PPDA and contractors (F= 1.330, P = 0.266). This
implied that staff were not under pressure, guided by professional code, integrity, competent
and knowledgeable of public road construction projects. Sanctions on staff involved in public
road construction projects was understood in the same way by all staff who participated in this
study (F = 1.658, P = 0.178). They were knowledgeable on penalties being enforced, reasons
for penalties and consequences of violating the public procurement regulatory framework
governing road construction projects. Perceived inefficiency of public procurement regulatory
framework was also perceived in the same way by staff of MoWT, URF, PPDA and contractors
(F = 0.808, P = 0.491). They similarly viewed banning of underperforming contractors, contract
extension and negotiation among contractors and public staff as good for meeting government
targets.
Contractors’ resistance to non-compliance with public procurement regulatory
framework was perceived in the same manner by all staff who participated in this study (F =
0.303, P = 0.823). Contractors being knowledgeable of the governing regulatory framework,
129
as well as readiness to take action on violating public officers was viewed in the same way to
achieve set government targets. Compliance with public procurement regulatory framework
was viewed similarly by all study participating staff (F = 1.422, P = 0.238). They believed that
timely recording of road construction activities, proper transaction payment systems,
authorisation and timely delivery were basics in meeting government targets. Finally, the
success of public road construction projects was similarly tagged on road specifications, time
and budget by all staff of MoWT, URF, PPDA and contractors (F = 0.417, P= 0.741).
Table 6.19: One-Way ANOVA results
N Mean Std. Deviation
Std. Error
F Sig
Familiarity MOWT 87 3.6396 .50928 .05460 0.821 0.484 URF 12 3.5298 .63776 .18410 PPDA 55 3.5013 .54058 .07289 Contractors 38 3.6109 .55221 .08958 Total 192 3.5874 .53441 .03857
Monitoring Activities
MOWT 87 3.6133 .59218 .06349 2.492 0.062 URF 12 3.5298 .47718 .13775 PPDA 55 3.3935 .50878 .06860 Contractors 38 3.6842 .59103 .09588 Total 192 3.5592 .56945 .04110
Professionalism MOWT 87 3.5617 .39535 .04239 URF 12 3.4205 .51431 .14847 1.330 0.266 PPDA 55 3.4347 .48246 .06505 Contractors 38 3.5730 .45449 .07373 Total 192 3.5187 .44215 .03191
Sanctions MOWT 87 3.5352 .48895 .05242 URF 12 3.4531 .64023 .18482 1.658 0.178 PPDA 55 3.3341 .58658 .07909 Contractors 38 3.4441 .46676 .07572 Total 192 3.4544 .52716 .03804
Perceived inefficiency
MOWT 87 2.8621 1.02495 .10989 0.808 0.491 URF 12 2.9167 .79296 .22891 PPDA 55 2.9273 .89968 .12131 Contractors 38 3.1579 1.05334 .17087 Total 192 2.9427 .98249 .07091
Contractors' Resistance
MOWT 87 3.7126 .76869 .08241 0.303 0.823 URF 12 3.7917 .78214 .22578 PPDA 55 3.6455 .90099 .12149 Contractors 38 3.8026 .88179 .14305
130
Total 192 3.7161 .82747 .05972 Compliance MOWT 87 3.0969 .67059 .07189 1.422 0.238
URF 12 3.2738 .60135 .17360 PPDA 55 3.2597 .67852 .09149 Contractors 38 3.3534 .80452 .13051 Total 192 3.2054 .69980 .05050
Project Success MOWT 87 3.3870 .93022 .09973 0.417 0.741 URF 12 3.1667 1.02986 .29729 PPDA 55 3.2909 1.00217 .13513 Contractors 38 3.4649 1.02386 .16609 Total 192 3.3611 .97158 .07012
6.9 Relationship between Study Variables Since the data and sample characteristics are satisfactory, the next step embarked on
relationship analysis in line with study objectives outlined in chapter one and hypotheses stated
in literature review. Under these analyses, degree and direction of the relationship, magnitude
and predictive significance are determined. Furthermore, Structural Equation Modelling (PLS-
SEM) was estimated using Smart-PLS3 software by performing PLS-algorithms and
bootstrapping resampling techniques. Additionally, mediation effects were tested and results
presented in section 6.9.2. The prediction significance was based on to support and reject stated
study hypotheses as discussed below.
6.9.1 Path Coefficients and Significance Level
This section interprets the results for the thirteen hypotheses based on PLS-SEM
bootstrapping. All the analysis converged at 11 interactions far below the pre-set 300-stop
criterion that implied good convergence and prediction (Sarstedt et al., 2019b, Ringle et al.,
2015a). The findings show individual path analysis indicated by respective path coefficients
with corresponding p-values for both compliance with public procurement regulatory
framework and public road construction project success as presented in Table 6.20.
Familiarity with Public Procurement Regulatory Framework and Compliance with
Public Procurement Regulatory Framework
There is an insignificant relationship between familiarity with public procurement
regulatory framework governing public road construction projects and compliance with public
procurement regulatory framework (α = 0.000, t = 0.001, p = 0.999). This implies that
familiarity with public procurement regulatory framework did not predict compliance with
public procurement regulatory framework and H1 is not supported.
Monitoring Activities and Compliance with Public Procurement Regulatory Framework
131
There is an insignificant inverse relationship between monitoring activities on public
road construction projects and compliance with public procurement regulatory framework (α
= -0.046, t = 0.522, p = 0.601). This implies that monitoring activities did not predict
compliance with public procurement regulatory framework and H2 is not supported.
Professionalism of Staff on Public Road Construction Projects and Compliance with
Public Procurement Regulatory Framework
There is an insignificant inverse relationship between professionalism of staff on public
road construction projects and compliance with public procurement regulatory framework (α
= -0.102, t = 1.250, p = 0.211). This implies that professionalism of staff on public road
construction projects did not predict compliance with public procurement regulatory
framework and H3 is not supported.
Sanctions and Compliance with Public Procurement Regulatory Framework
There is a significant positive relationship between sanctioning of staff on public road
construction projects and compliance with public procurement regulatory framework (α =
0.315, t = 3.540, p = 0.000). This implies that sanctioning of staff on public road construction
projects predicted compliance with public procurement regulatory framework and H4 is
significantly supported.
Perceived Inefficiency of Public Procurement Regulatory Framework and Compliance
with Public Procurement Regulatory Framework
There is an inverse significant relationship between perceived inefficiency of public
procurement regulatory framework and compliance with public procurement regulatory
framework (α = -0.253, t = 3.052, p = 0.002). This implies that perceived inefficiency of public
procurement regulatory framework predicted and reduced compliance with public procurement
regulatory framework. Hence, H5 is significantly supported.
Contractors’ Resistance and Compliance with Public Procurement Regulatory
Framework
There is a significant positive relationship between contractors’ resistance to non-
compliance with public procurement regulatory framework governing public road construction
projects and compliance with public procurement regulatory framework (α = 0.135, t = 2.002,
p = 0.045). This implies that contractors’ resistance predicted compliance with public
procurement regulatory framework and H6 is significantly supported.
Compliance with Public Procurement Regulatory Framework and Public Road
Construction Project Success
132
There is a significant positive relationship between compliance with public
procurement regulatory framework and success of public road construction projects (α = 0.147,
t = 1.960, p = 0.05). This implies that compliance with public procurement regulatory
framework by staff on public road construction projects predicted the success of these projects
and H7 is significantly supported.
Familiarity with Public Procurement Regulatory Framework and Public Road
Construction Project Success
There is a significant positive relationship between familiarity with public procurement
regulatory framework and public road construction project success (α = 0.140, t = 2.231, p =
0.026). This implies that familiarity with public procurement regulatory framework predicted
the success of public road construction projects and H8 is significantly supported.
Monitoring Activities and Public Road Construction Project Success
There is a significant positive relationship between monitoring activities on public road
construction projects and success of these projects (α = 0.314, t = 4.875, p = 0.000). This
implies that monitoring activities predicted success of these projects. Hence, H9 is significantly
supported.
Professionalism of Staff on Public Road Construction Projects and Public Road
Construction Project Success
There is a significant positive relationship between professionalism of staff on public
road construction projects and public road construction project success (α = 0.305, t = 4.695, p
= 0.000). This implies that professionalism of staff involved in public road construction
projects predicted the success of these projects. Hence, H10 is significantly supported.
Perceived Inefficiency of Public Procurement Regulatory Framework and Public Road
Construction Project Success
There is an inverse significant relationship between perceived inefficiency of public
procurement regulatory framework and public road construction project success (α = -0.135, t
= 2.099, p = 0.036). This implies that perceived inefficiency of public procurement regulatory
framework predicted and reduced success of public road construction projects. Hence, H11 is
significantly supported.
Contractors’ Resistance to Non-Compliance with Public Procurement Regulatory
Framework and Public Road Construction Project Success
There is a positive insignificant relationship between contractors’ resistance to non-
compliance with public procurement regulatory framework governing public road construction
133
projects and success of public road construction projects (α = 0.121, t = 1.792, p = 0.073). This
implies that contractors’ resistance predicted successful implementation of public road
construction projects. However, H12 is not statistically supported at 0.05 significance level.
Sanctions on Staff on Public Road Construction Projects and Public Road Construction
Project Success
There is an insignificant inverse relationship between sanctions on staff involved in
public road construction projects and public road project success (α = -0.059, t = 0.856, p =
0.392). This implies that sanctions imposed on these staff did not predict success of public road
construction projects and H13 is not supported.
Table 6.20: Path Coefficients Table 6.20 presents Smart-PLS bootstrap results used to accept and reject hypotheses one to
thirteen.
Path coefficient (α)
Sample Mean (M)
Standard Deviation (STDEV)
T Statistics (t) P Values
Familiarity - Compliance 0.000 0.005 0.082 0.001 0.999 Monitoring - Compliance -0.046 -0.045 0.088 0.522 0.601 Professionalism - Compliance -0.102 -0.105 0.082 1.250 0.211
Sanctions - Compliance 0.315 0.323 0.089 3.540 0.000 Perceived inefficiency - Compliance -0.253 -0.253 0.083 3.052 0.002
Contractors' resistance - Compliance 0.135 0.138 0.067 2.002 0.045
Compliance - Project success 0.147 0.145 0.075 1.960 0.050
Familiarity - Project success 0.140 0.142 0.063 2.231 0.026
Monitoring - Project success 0.314 0.311 0.064 4.875 0.000
Professionalism - Project success 0.305 0.305 0.065 4.695 0.000
Perceived inefficiency - Project success -0.135 -0.136 0.064 2.099 0.036
Contractors' resistance - Project success 0.121 0.123 0.067 1.792 0.073
Sanctions - Project success -0.059 -0.056 0.068 0.856 0.392
6.9.2 Mediational Effect Analyses This section interprets the mediation effects corresponding to the six hypotheses based
on significance of correlations, hierarchical regressions and Sobel z-value following Baron and
Kenny (1986). This was aimed at establishing whether compliance with public procurement
134
regulatory framework mediated the relationship between the six compliance factors and project
success as presented below.
H14. Compliance with Public Procurement Regulatory Framework Mediates the
Relationship between Familiarity with Public Procurement Regulatory Framework and
Project Success.
Results for a five-step mediation process are as flows:
Step 1: When compliance was regressed on familiarity, the results show that compliance and
familiarity are significantly related (β = 0.194, p = 0.007).
Step 2: When project success was regressed on compliance, the results show that project
success and compliance are significantly related (β = 0.305, p = 0.000).
Step 3: When project success was regressed on familiarity, the results show that project success
and familiarity are significantly related (β = 0.315, p = 0.000). Hence, as depicted in Table
6.21, all the three steps are satisfied and mediation testing is possible.
Table 6.21: Coefficient results for the three steps above
Familiarity Compliance Project Success
Familiarity Pearson Correlation 1 .194** .315** Sig. (2-tailed) .007 .000 N 192 192 192
Compliance Pearson Correlation .194** 1 .305** Sig. (2-tailed) .007 .000 N 192 192 192
Project Success Pearson Correlation .315** .305** 1 Sig. (2-tailed) .000 .000 N 192 192 192
**. Correlation is significant at the 0.01 level (2-tailed).
Step 4: Results from a hierarchical regression indicate that both compliance and
familiarity are significantly related to project success as demonstrated in Table 6.22. This
implies that compliance could be mediating the relationship between familiarity and project
success. Hence, Sobel test is possible to determine mediation effect.
135
Table 6.22: Hierarchical regression results for familiarity, compliance and project success
Variable Model 1 Model 2
B β B β
Constant 2.005 0.502
Compliance .423*** .305*** 0.351*** 0.253***
Familiarity 0.483*** 0.266***
R2 0.093 0.161
Adjusted R2 0.088 0.152
∆R2 0.093*** 0.068***
∆F 19.448*** 15.296***
F 19.448 18.103
Sig .0000 .000 ***p<.001;**p<.01;*p<.05
Step 5: Sobel test
According to Sobel test results, compliance with public procurement regulatory
framework mediates the relationship between familiarity with public procurement regulatory
framework and public road construction project success (Sobel z-value = 2.204441, p =
0.027493). As depicted from Table 6.23 and Fig 6.1, there is a significant partial mediation
because familiarity with public procurement regulatory framework predicts project success
directly (0.266) and indirectly (0.049) through compliance with public procurement regulatory
framework. Hence, H14 is significantly supported.
Table 6.23: Compliance Mediating Familiarity and Project Success
Type of mediation Significant Sobel z-value = 2.204441 p = 0.027493 95% Symmetrical Confidence interval Lower 0.00989 Higher 0.16842 Unstandardized indirect effect a*b 0.08915 se 0.04044 Effective Size measures Standardised Coefficients R² Measures (Variance) Total: 0.315 0.099 Direct: 0.266 0.068 Indirect: 0.049 0.031
136
Indirect to Total ratio 0.155 0.313
Figure 6.1: Compliance Mediating Familiarity and Project Success
Independent Variable
0.315*** [c] Dependent Variable Familiarity Project Success (0.266***) [c']
0.305*** 0.194** [a] (0.253***) [b]
Mediating Variable
Compliance
H15. Compliance with Public Procurement Regulatory Framework Mediates the
Relationship between Monitoring Activities in Public Road Construction and Project
Success
Results for a five-step mediation process are as flows:
Step 1: When compliance was regressed on monitoring activities, the results show that
compliance and monitoring activities are significantly related (β = 0.172, p = 0.017).
Step 2: When project success was regressed on compliance, results show that project success
is significantly related to compliance (β = 0.305, p = 0.000).
Step 3: When project success was regressed on monitoring activities, the results show that
project success and monitoring activities are significantly related (β = 0.547, p = 0.000).
According to the results in Table 6.24, all the three steps are satisfied and hence, there is need
for mediation testing.
Table 6.24: Coefficient results for the three steps above
Monitoring Activities
Compliance with PPRF
Project Success
Monitoring Activities Pearson Correlation 1 .172* .547** Sig. (2-tailed) .017 .000 N 192 192 192
Compliance with PPRF
Pearson Correlation .172* 1 .305** Sig. (2-tailed) .017 .000 N 192 192 192
137
Project Success Pearson Correlation .547** .305** 1 Sig. (2-tailed) .000 .000 N 192 192 192
*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).
Step 4: Results from a hierarchical regression indicate that both compliance and
monitoring activities are significantly related to project success as demonstrated in Table 6.25.
Implying that compliance could be mediating the relationship between monitoring activities
and project success. Hence, Sobel test is necessary.
Table 6.25: Hierarchical regression results for monitoring activities, compliance and project success
Variable Model 1 Model 2
B β B β
Constant 2.005 -0.697
Compliance 0.423*** 0.305*** 0.301*** 0.217***
Monitoring
activities
0.869*** 0.509***
R2 0.093 0.344
Adjusted R2 0.088 0.338
∆R2 0.093*** 0.253***
∆F 19.448*** 72.542***
F 19.448 49.656
Sig .0000 .000 ***p<.001;**p<.01;*p<.05
Step 5: Sobel test
According to Sobel test results, compliance with public procurement regulatory
framework mediates the relationship between monitoring activities in public road construction
and project success. (Sobel z-value = 2.000092, p = 0.04549). Table 6.26 and Fig 6.2 show that
there is a significant partial mediation because monitoring activities in public road construction
predicts project success directly (0.509) and indirectly (0.037) through compliance with public
procurement regulatory framework. Hence, H15 is significantly supported.
138
Table 6.26: Compliance Mediating Monitoring activities and Project Success
Type of mediation Significant Sobel z-value = 2.000092 p = 0.04549 95% Symmetrical Confidence interval Lower 0.00127 Higher 0.12575 Unstandardized indirect effect a*b 0.06351 se 0.03175 Effective Size measures Standardised Coefficients R² Measures (Variance) Total: 0.547 0.298 Direct: 0.509 0.252 Indirect: 0.037 4.646 Indirect to Total ratio 6.823 0.155
Figure 6.2: Compliance Mediating Monitoring activities and Project Success
Independent Variable
0.547*** [c] Dependent Variable Monitoring Activities
Project Success (0.509***) [c']
0.305*** 0.172* [a] (0.217**) [b] Mediating Variable Compliance
H16. Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Professionalism of Staff in Public Road Construction Projects and Project Success
Results for a five-step mediation process are as flows:
Step 1: When compliance was regressed on professionalism, results show that compliance and
professionalism are significantly related (β = 0.338, p = 0.000).
Step 2: When project success was regressed on compliance, the results show that project
success and compliance are significantly related (β = 0.305, p = 0.000).
139
Step 3: When project success was regressed on professionalism, results show that project
success and professionalism are significantly related (β = 0.553, p = 0.000).
Summary results in Table 6.27 show that all the three steps are satisfied and hence, there is
need for mediation testing.
Table 6.27: Coefficient results for the three steps above
Professionalism Compliance with PPRF
Project Success
Professionalism Pearson Correlation 1 .338** .553** Sig. (2-tailed) .000 .000 N 192 192 192
Compliance with PPRF
Pearson Correlation .338** 1 .305** Sig. (2-tailed) .000 .000 N 192 192 192
Project Success Pearson Correlation .553** .305** 1 Sig. (2-tailed) .000 .000 N 192 192 192
**. Correlation is significant at the 0.01 level (2-tailed).
Step 4: Results from a hierarchical regression indicate that both compliance and
professionalism are significantly related to project success as demonstrated in Table 6.28. This
is an indication that compliance could be mediating the relationship between professionalism
and project success. Hence, Sobel test of mediation is inevitable.
Table 6.28: Hierarchical regression results for professionalism, compliance and project success
Variable Model 1 Model 2
B β B β
Constant 2.005 -1.160
Compliance 0.423*** 0.305*** 0.185* 0.133*
Professionalism 1.117*** 0.508***
R2 0.093 0.322
Adjusted R2 0.088 0.314
∆R2 0.093*** 0.229***
∆F 19.448*** 63.744***
F 19.448 44.807
Sig .0000 .000
***p<.001;**p<.01;*p<.05
140
Step 5: Sobel test
Sobel test results show that compliance with public procurement regulatory framework
does not significantly mediate the relationship between professionalism of staff in public road
construction projects and project success (Sobel z-value = 1.935215, p = 0.052964). As
depicted from Table 6.29 and Fig 6.3, compliance with public procurement regulatory
framework insignificantly mediates the relationship between professionalism of staff on public
road construction projects and success of these projects. Implying that H16 is not statistically
supported.
Table 6.29: Compliance Mediating Professionalism and Project Success
Type of mediation Null Sobel z-value = 1.935215, p = 0.052964 95% Symmetrical Confidence interval Lower -0.00127 Higher 0.19922 Unstandardized indirect effect a*b 0.09898 se 0.05114 Effective Size measures Standardised Coefficients R² Measures (Variance) Total: 0.553 0.305 Direct: 0.508 0.228 Indirect: 0.044 7.727 Indirect to Total ratio 8.129 0.252
Figure 6.3: Compliance Mediating Professionalism and Project Success
Independent Variable 0.553*** [c] Dependent Variable
Professionalism Project Success (0.508***) [c']
0.305*** 0.338*** [a] (0.133) [b] Mediating Variable Compliance
H17. Compliance with Public Procurement Regulatory Framework Mediates the
Relationship between Sanctions on Staff in Public Road Construction Projects and
Project Success
141
Results for a five-step mediation process are as flows:
Step 1: When compliance was regressed on sanctions, the results show that compliance and
sanctions are significantly related (β = 0.341, p = 0.000).
Step 2: When project success was regressed on compliance, the results show that project
success and compliance are significantly related (β = 0.305, p = 0.000).
Step 3: When project success was regressed on sanctions, the results show that project success
and sanctions are significantly related (β = 0.401, p = 0.000).
Summary results in Table 6.30 show that all the three steps are satisfied and there is need for
mediation testing.
Table 6.30: Coefficient results for the three steps above
Correlations
Sanctions Compliance with PPRF
Project Success
Sanctions Pearson Correlation 1 .341** .401** Sig. (2-tailed) .000 .000 N 192 192 192
Compliance with PPRF Pearson Correlation .341** 1 .305** Sig. (2-tailed) .000 .000 N 192 192 192
Project Success Pearson Correlation .401** .305** 1 Sig. (2-tailed) .000 .000 N 192 192 192
**. Correlation is significant at the 0.01 level (2-tailed).
Step 4: Results from a hierarchical regression indicate that both compliance and sanctions
are significantly related to project success as demonstrated in Table 6.31. Implying that
compliance could be mediating the relationship between sanctions and project success. Hence,
Sobel test for mediation is necessary.
Table 6.31: Hierarchical regression results for sanctions, compliance and project success
Variable Model 1 Model 2
B β B β
Constant 2.005 0.373
Compliance 0.423*** 0.305*** 0.264*** 0.190***
142
Sanctions 0.620*** 0.337***
R2 0.093 0.193
Adjusted R2 0.088 0.184
∆R2 0.093*** 0.100***
∆F 19.448*** 23.443***
F 19.448 22.594
Sig .0000 .000 ***p<.001;**p<.01;*p<.05
Step 5: Sobel test
According to Sobel test results, compliance with public procurement regulatory
framework mediates the relationship between sanctions in public road construction and project
success (Sobel z value = 2.388039, p = 0.016939). Table 6.32 and Fig 6.4 show that there is a
significant partial mediation because sanctions on staff in public road construction predicts
project success directly (0.337) and indirectly (0.114) through compliance with public
procurement regulatory framework. Hence, H17 is significantly supported.
Table 6.32: Compliance Mediating Sanctions and Project Success
Type of mediation Significant Sobel z-value = 2.388039, p = 0.016939 95% Symmetrical Confidence interval Lower 0.02144 Higher 0.21775 Unstandardized indirect effect a*b 0.11959 se 0.05008 Effective Size measures Standardised Coefficients R² Measures (Variance) Total: 0.574 0.203 Direct: 0.337 0.099 Indirect: 0.114 0.104 Indirect to Total ratio 0.199 0.510
143
Figure 6.4: Compliance Mediating Sanctions and Project Success
Independent Variable
0.574*** [c] Dependent Variable Sanctions Project Success (0.337***) [c']
0.690*** 0.603*** [a]
(0.190**) [b] Mediating Variable Compliance
H18. Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Perceived Inefficiency of Public Procurement Regulatory Framework and Project Success.
Results for a three-step mediation process are as flows:
Step 1: When compliance was regressed on perceived inefficiency of public procurement
regulatory framework, the results show that compliance and perceived inefficiency of public
procurement regulatory framework are not related significantly (β = -0.020, p = 0.785).
Step 2: When project success was regressed on compliance, the results show that project
success is significantly related to compliance (β = 0.305, p = 0.000).
Step 3: When project success was regressed on perceived inefficiency of public procurement
regulatory framework, the results show that project success and perceived inefficiency of
public procurement regulatory framework are not related significantly (β = -0.064, p = 0.377).
These results in Table 6.33 indicate that the three steps are not satisfied since perceived
inefficiency of public procurement regulatory framework is insignificantly related to
compliance with public procurement regulatory framework and project success. Hence,
mediation testing is not possible implying that H18 is not supported (Baron and Kenny, 1986).
Table 6.33: Coefficient results for the three steps above
Perceived
inefficiency Compliance with PPRF
Project Success
Perceived inefficiency Pearson Correlation 1 -.020 -.064 Sig. (2-tailed) .785 .377 N 192 192 192 Pearson Correlation -.020 1 .305**
144
Compliance with PPRF
Sig. (2-tailed) .785 .000 N 192 192 192
Project Success Pearson Correlation -.064 .305** 1 Sig. (2-tailed) .377 .000 N 192 192 192
**. Correlation is significant at the 0.01 level (2-tailed).
H19. Compliance with Public Procurement Regulatory Framework Mediates the
Relationship between Contractors’ Resistance to Non-Compliance with Public
Procurement Regulatory Framework and Public Road Construction Project Success
Results for a five-step mediation process are as flows:
Step 1: When compliance was regressed on contractors’ resistance to non-compliance, the
results show that compliance and contractors’ resistance are significantly related (β = 0.292, p
= 0.000).
Step 2: When project success was regressed on compliance, the results show that project
success and compliance are significantly related (β = 0.305, p = 0.000).
Step 3: When project success was regressed on contractors’ resistance to non-compliance, the
results show that project success and contractors’ resistance are significantly related (β = 0.419,
p = 0.000).
The summary results in Table 6.34 show that all the three steps are satisfied since all the three
variables are significantly related. Hence, mediation testing is required.
Table 6.34: Coefficient results for the three steps above
Contractors' Resistance
Compliance with PPRF
Project Success
Contractors' Resistance
Pearson Correlation 1 .292** .419** Sig. (2-tailed) .000 .000 N 192 192 192
Compliance with PPRF
Pearson Correlation .292** 1 .305** Sig. (2-tailed) .000 .000 N 192 192 192
Project Success Pearson Correlation .419** .305** 1 Sig. (2-tailed) .000 .000 N 192 192 192
**. Correlation is significant at the 0.01 level (2-tailed).
145
Step 4: Results from a hierarchical regression indicate that both compliance and
contractors’ resistance to non-compliance are related significantly to project success as
demonstrated in Table 6.35. This indicates that compliance could be mediating the relationship
between contractors’ resistance to non-compliance and project success. Hence, Sobel test is
vital.
Table 6.35: Hierarchical regression results for contractors’ resistance to non-compliance, compliance and project success
Variable Model 1 Model 2
B β B β
Constant 2.005 0.900
Compliance 0.423*** 0.305*** 0.277*** 0.199***
Contractors’
resistance
0.424*** 0.361***
R2 0.093 0.212
Adjusted R2 0.088 0.204
∆R2 0.093*** 0.119***
∆F 19.448*** 28.551***
F 19.448 25.409
Sig .0000 .000 ***p<.001;**p<.01;*p<.05
Step 5: Sobel test
According to Sobel test results, compliance with public procurement regulatory
framework mediates the relationship between contractors’ resistance to non-compliance and
public road construction project success (Sobel z value = 2.409704, p = 0.015965). As depicted
from Table 6.36 and Fig 6.5, there is a significant partial mediation because contractors’
resistance to non-compliance predicts project success directly (0.361) and indirectly (0.058)
through compliance with public procurement regulatory framework. Hence, H19 is
significantly supported.
Table 6.36: Compliance Mediating Contractors’ Resistance and Project Success
Type of mediation Significant Sobel z-value = 2.409704, p = 0.015965 95% Symmetrical Confidence interval Lower 0.01277 Higher 0.12407
146
Unstandardized indirect effect a*b 0.06842 se 0.02839 Effective Size measures Standardised Coefficients R² Measures (Variance) Total: 0.419 0.175 Direct: 0.361 0.119 Indirect: 0.058 0.056 Indirect to Total ratio 0.138 0.322
Figure 6.5: Compliance Mediating Contractors’ Resistance and Project Success
Independent Variable
0.419*** [c] Dependent Variable Contractors' Resistance
Project Success (0.361***) [c']
0.305*** 0.292*** [a] (0.199**) [b] Mediating Variable Compliance
According to mediation results, four hypotheses out of the six hypotheses (H14, H15,
H17 and H19) are supported significantly while H16 and H18 are not supported. This implies
that compliance with public procurement regulatory framework is a key mediator between the
four compliance factors (familiarity with public procurement regulatory framework,
monitoring public road construction activities, sanctions on staff and contractors’ resistance to
non-compliance with public procurement regulatory framework) and success of public road
construction projects. Overall, twelve (12) hypotheses are statistically supported out of
nineteen (19). Three hypotheses (H4, Sanctions, H5, Perceived inefficiency and H6,
Contractors’ resistance) are significantly supported under compliance model, five hypotheses
(H7, Compliance, H8, Familiarity, H9, Monitoring activities, H10, Professionalism and H11,
Perceived inefficiency) are significantly supported under project success model and four
hypotheses (H14, Familiarity, H15, Monitoring activities, H17, Sanctions and H19,
Contractors’ resistance) are significantly supported under mediation.
This implies that sanctioning on staff involved in public road construction, perceived
inefficiency of public procurement regulatory framework and contractors’ resistance to non-
147
compliance with public procurement regulatory framework enhance compliance with public
procurement regulatory framework governing public road construction projects. While
compliance with public procurement regulatory framework, familiarity with public
procurement regulatory framework, monitoring activities on public road construction projects,
professionalism of staff involved in public road construction projects and perceived
inefficiency of public procurement regulatory framework governing public road construction
projects, enhance the success of these projects. Finally, compliance with public procurement
regulatory framework is a key mediator between the success of public road construction
projects and familiarity with public procurement regulatory framework, monitoring activities
on these projects, sanctions on staff and contractors’ resistance against public officers who
wish to deviate from established regulatory framework governing public road construction
projects. The study also established that two hypotheses are supported but statistically
insignificant. They comprise of contractors’ resistance to non-compliance with public
procurement regulatory framework by public officers (H6) and mediating effect of compliance
with public procurement regulatory framework on professionalism of staff involved in public
road construction projects and success of these project (H16).
6.10 Coefficient of Determination (R2), Effect size (f2) and Model Fit
Coefficient of determination was used to determine predictive performance for both
compliance with public procurement regulatory framework and public road construction
project success models. The results show that respective explained variances for both models
are significantly good as depicted in Table 6.37 (Compliance, R2 = 0.279, p < 0.001 and Project
success, R2 = 0.552, p < 0.001) implying acceptable predictive performance (Rasoolimanesh
et al., 2019, Ali et al., 2018a, Ali et al., 2018b). Consequently, 27.9% variance in compliance
with public procurement regulatory framework is substantially explained by the six compliance
factors and 55.2% variance in public road construction project success is substantially
explained by the seven project success factors (Hussain et al., 2019). Furthermore, individual
effect size on both models by their respective independent variables in Table 6.38 were
assessed. The findings show that sanctions on staff, perceived inefficiency of regulatory
framework and contractors’ resistance to non-compliance have a small significant influence on
compliance with public procurement regulatory framework (Sanctions, f2 = 0.096, Perceived
inefficiency, f2 = 0.058 and Contractors’ resistance, f2 = 0.020) (Rasoolimanesh et al., 2019,
Ali et al., 2018a). While monitoring activities and professionalism of staff are the most
influential factors with medium effect size on successful implementation of public road
148
construction projects (Monitoring, f2 = 0.150, and Professionalism, f2 = 0.128) (Rasoolimanesh
et al., 2019, Ali et al., 2018a). Other factors including: compliance with public procurement
regulatory framework (f2 = 0.035), familiarity with public procurement regulatory framework
(f2 = 0.032), perceived inefficiency of public procurement regulatory framework (f2 = 0.025),
and contractors’ resistance to non-compliance (f2 = 0.025) have a small significant influence
on successful implementation of public road construction projects (Rasoolimanesh et al., 2019,
Ali et al., 2018a). Finally, by evaluating standardized root mean square residual, it shows that
the overall model is significantly fitting well since SRMR is less than 0.08 as depicted in Table
6.37 (SRMR= 0.068, P < 0.001) (Rasoolimanesh et al., 2019, Ali et al., 2018a, Nitzl et al.,
2016). This implies that the estimated model compared to the saturated model proved that the
model in set-up theory represented by the conceptual model matches the collected data (Müller
et al., 2018). Hence, the validated model has appropriate reliability and validity capable of
ensuring compliance with regulatory framework and successful implementation of public road
construction projects. Note that the saturated model is the model that perfectly fits the data
(Müller et al., 2018).
Table 6.37: R2, Adjusted R2 and Standardized Root Mean square Residual (SRMR)
Original Sample (α)
Sample Mean (M)
Standard Deviation (STDEV)
T Statistics (t|) P Values
R2 Compliance 0.279 0.315 0.054 5.199 0.000 Project success 0.552 0.578 0.048 11.517 0.000
Adjusted R2 Compliance 0.256 0.293 0.055 4.613 0.000 Project success 0.535 0.562 0.050 10.753 0.000
Standardized Root Mean square Residual (SRMR) 0.068 0.085 0.005 13.729 0.000
Table 6.38: Effect size (f2) results
Dependent variable Independent variable f2 Inference Hypothesis
Remarks
Compliance
Familiarity 0.000 Insignificant Not supported Monitoring 0.002 Insignificant Not supported Professionalism 0.009 Insignificant Not supported Sanctions 0.096 Small Significantly
supported Perceived inefficiency 0.058 Small Significantly
supported Contractors' resistance 0.020 Small Significantly
supported
Project success Compliance 0.035 Small Significantly supported
149
Familiarity 0.032 Small Significantly supported
Monitoring 0.150 Medium Significantly supported
Professionalism 0.128 Medium Significantly supported
Perceived inefficiency 0.025 Small Significantly
supported Contractors' resistance 0.025 Small Insignificantly
supported Sanctions 0.005 Insignificant Not supported
Table 6.39: Total effect
Construct relationship
Path coefficient (α)
Sample Mean (M)
Standard Deviation (STDEV)
T Statistics (t) P Values
Hypothesis Remarks
Familiarity - Compliance 0.000 0.005 0.082 0.001 0.999 Not supported
Monitoring - Compliance -0.046 -0.045 0.088 0.522 0.601 Not supported
Professionalism - Compliance -0.102 -0.105 0.082 1.250 0.211 Not supported
Sanctions - Compliance 0.315 0.323 0.089 3.540 0.000 Significantly
supported Perceived inefficiency -Compliance -0.253 -0.253 0.083 3.052 0.002 Significantly
supported Contractors' resistance - Compliance 0.135 0.138 0.067 2.002 0.045 Significantly
supported Compliance - Project success 0.147 0.145 0.075 1.960 0.050 Significantly
supported Familiarity - Project success 0.140 0.143 0.062 2.247 0.025 Significantly
supported Monitoring - Project success 0.307 0.304 0.063 4.849 0.000 Significantly
supported Professionalism - Project success 0.290 0.290 0.068 4.261 0.000 Significantly
supported Perceived inefficiency - Project success -0.172 -0.172 0.061 2.817 0.005 Significantly
supported Contractors' resistance -Project success 0.141 0.142 0.065 2.147 0.032 Insignificantl
y supported Sanctions - Project success -0.012 -0.010 0.059 0.210 0.833 Not supported
Mediation
Total Effective Size measures
R² Measures
(Variance)
Sobel Z-Value
Familiarity – Compliance - Project 0.315 0.099 2.204 0.027 Significantly
supported Monitoring – Compliance - Project 0.547 0.298 2.000 0.045 Significantly
supported Professionalism – Compliance - Project success
0.553 0.305 1.935 0.053 Insignificantly supported
150
Sanctions – Compliance - Project success
0.574 0.203 2.388 0.017 Significantly supported
Contractors' resistance - Compliance- Project success
0.419 0.175 2.410 0.016 Significantly supported
Figure 6.6: Final Structural and Measurement model (PLS-Algorithms)
151
Figure 6.7: Final validated Structural model (Bootstrapping output)
6.11 Validation of Results This section tabulates the nineteen hypotheses results as indicated in study conceptual model
based on interpreted results.
Table 6.40: Summary of hypotheses results Hypotheses Hypothesized
effect
Results Sig level Remarks
H1 + Neutral P > 0.05 Not supported
H2 + - P > 0.05 Not supported
152
H3 + - P > 0.05 Not supported
H4 + +*** P < 0.001 supported
H5 - -** P < 0.01 supported
H6 + +* P < 0.05 supported
H7 + +* P < 0.05 supported
H8 + +* P < 0.05 supported
H9 + +*** P < 0.001 supported
H10 + +*** P < 0.001 supported
H11 - -* P < 0.05 supported
H12 + + P > 0.05 Not supported
H13 + - P > 0.05 Not supported
H14 + +* P < 0.05 supported
H15 + +* P < 0.05 supported
H16 + + P > 0.05 Not supported
H17 + +* P < 0.05 supported
H18 + - P > 0.05 Not supported
H19 + +* P < 0.05 supported
Note: Two tailed *** p < 0.001, Two tailed ** p < 0.01, Two tailed * p< 0.05
6.12 Final Validated Models
The final validated model is a summation of measurement and structural models showing
relationship linkages that are supported as well as those that are not supported for compliance,
project success and mediation as depicted by respective coloured arrows. After respective
validated models, a discussion of the results follows in chapter seven.
153
Figure 6.8: Combined Validated Model
Compliance effect Project success effect Mediation effect Combined mediation effect
Familiarity
Monitoring activities
Professionalism
Sanctions
Compliance
Project
success
Not supported
Not supported
Not supported
Supported
Supported
Perceived inefficiency
Contractor’s resistance
Supported
Supported
Not supported
Not supported
Supported
Supported
Supported
Supported
Supported
Supported
Not Supported
Supported
Supported
Not Supported
154
Figure 6.8.1 Compliance Validated Model
Figure 6.8.2 Project Success Validated Model
Familiarity
H8 :( α = 0.140, t = 2.231, p = 0.026) H7 :( α = 0.147, t = 1.960, p = 0.050)
Compliance
Project Success
Sanctions
H13 :( α = -0.059, t = 0.856, p = 0.392)
Monitoring Activities
H9 :( α = 0.314, t = 4.875, p = 0.000)
Contractors’ Resistance
H12 :( α = 0.121, t = 1.792, p = 0.073)
Perceived Inefficiency
H11 :( α = -0.135, t = 2.099, p = 0.036)
Professionalism H10 :( α = 0.305, t = 4.695, p = 0.000)
Familiarity
Compliance
H1 :( α = 0.000, t = 0.001, p = 0.999)
Contractor’s
Resistance H6: (α = 0.135, t =
2.002, p = 0.045)
Perceived Inefficiency
H5: (α = -0.253, t =
3.052, p = 0.002)
Monitoring Activities
H2: (α = 0.046, t =
0.522, p = 0.601)
Professionalism
H3: (α = -0.102, t =
1.250, p = 0.211)
Sanctions
H4: (α = 0.315, t = 3.540, p = 0.000):
155
CHAPTER SEVEN DISCUSSIONS
156
7.1 Introduction This chapter unveils the impact relationships between study variables based on the
interpreted results in chapter six. It starts with shedding light on the impact of familiarity with
public procurement regulatory framework, monitoring activities, professionalism of staff,
sanctions on staff, perceived inefficiency of public procurement regulatory framework and
contractors’ resistance on compliance. This is followed by explanations of the effect of
compliance with public procurement regulatory framework, familiarity with public
procurement regulatory framework, monitoring activities, professionalism of staff, perceived
inefficiency of public procurement regulatory framework, contractors’ resistance to non-
compliance and sanctions on staff on the success of public road construction projects. Finally,
the mediation impact between compliance factors and public road construction project success
is discussed. The relationship effects are discussed in line with significant measurement
indicators for respective variables.
7.2 Compliance Relationships
7.2.1 The Relationship between Familiarity with Public Procurement Regulatory Framework and Compliance with Public Procurement Regulatory Framework.
The study objective for H1 was to ascertain whether familiarity with public
procurement regulatory framework affects compliance with public procurement regulatory
framework governing public road construction projects. According to PLS-algorithm path
coefficient results, there is an imperfect relationship between familiarity with public
procurement regulatory framework and compliance with public procurement regulatory
framework. This implies that familiarity with public procurement regulatory framework does
not predict increase in compliance. Meanwhile bootstrapping results show that there is an
insignificant relationship between familiarity with public procurement regulatory framework
and compliance with public procurement regulatory framework (α = 0.000, t = 0.001, p = 0.999)
at 5% significance level. Hence, H1 is not supported and the objective is not achieved. Implying
that simplifying the regulatory framework governing public road construction projects for easy
interpretation, using staff who are familiar with project implementation and employing staff
with appropriate academic qualification to work on applicable road construction projects is not
effective in achieving compliance. Compliance was measured through proper authorisation of
road construction projects, timely delivery of road construction projects, timely recording of
road construction transactions and achievable road construction project objectives.
157
This is contrary to earlier findings that established that familiarity significantly
enhanced compliance in public procurement (Eyaa and Oluka, 2011, Gelderman et al., 2006).
Notably, their research was based on responses from procurement officials in Procuring and
Disposal Entities (PDEs) in Uganda and Netherlands respectively without specific reference to
public road construction projects. Nevertheless, this is because staff handling public road
construction projects are academically qualified with vast experience ranging between 1-22
years. Evidence show that 93.8% of staff hold first degree and above. In addition, 84.4% of
these staff are senior officers who are capable of managing public road implementation
processes. Being academically qualified alone does not guarantee familiarity with complex
public road construction projects having many stakeholders and regulatory framework in a
dynamic context (Chi and Nicole Javernick‐Will, 2011). However, in Uganda’s case, it appears
experienced staff working on these projects would ensure compliance. Previously, a lack of
familiarity has been documented to hamper compliance in public road subsector and
consequently, considerable efforts have been made to improve the situation (Uganda National
Road Authority, 2014). Such efforts include involving highly qualified staff in road
implementation and UNRA’s continuous improvement in staff competence through capacity
building (Uganda National Road Authority, 2018). Interestingly, high staff qualifications are
associated with innovativeness (Czarnitzki et al., 2018). Hunja (2003) notes that compliance
with public procurement regulatory framework requires stakeholders’ full awareness with the
practical details in public procurement. This is inevitable for complex construction projects
whose implementation require a lot of personal attributes and their consideration (Uganda
National Road Authority, 2014, Migosi et al., 2013).
In the light of the foregoing analysis, a lack of familiarity with public procurement
regulatory framework leads to poor quality road construction projects that are completed late
thereby hampering government goals. These projects deteriorate faster than their life
expectancy. This contrasts with both regional and global findings showing that government
objectives are affected by failed projects and not complying with regulatory framework
because stakeholders lack familiarity with project details (Zadawa et al., 2015, Boer and
Telgen, 1998). Hence, the need for public procurement regulatory framework governing road
construction projects to be written in a nonprofessional’s language that can easily be interpreted
by respective stakeholders. In addition, management should encourage qualified and competent
staff involvement in public road implementation since these are key indicators measuring
familiarity with public procurement regulatory framework. Transparent and merit based
158
selection criterion involving required formal academic qualifications and experienced
competent team is encouraged.
7.2.2 The Relationship between Monitoring Activities and Compliance with Public Procurement Regulatory
The objective for H2 was to ascertain whether monitoring activities affect compliance
in public road construction projects. PLS-algorithm path coefficient results show that there is
an inverse relationship between monitoring activities and compliance with public procurement
regulatory frameworks. This implies that monitoring activities does not predict increase in
compliance with public procurement regulatory governing public road construction projects.
Meanwhile bootstrapping results show that there is an inverse insignificant relationship
between monitoring activities on public road construction projects and compliance with public
procurement regulatory framework (α =- 0.046, t = 0.522, p = 0.601) at 5% significance level.
Hence, H2 is not supported and the objective is not achieved. This implies that increased
frequent inspections to check on timely recording of project progress, timely project
completion and proper storage methods is not effective in achieving compliance with public
procurement regulatory framework. These results are in line with Tabish and Jha (2015),
Rutherford et al. (2007) findings, whose theories suggest a use of effective monitoring
mechanism to enhance compliance with principal goals (Rajab and Eydgahi, 2019, Kauppi and
van Raaij, 2015).
The findings are in contradiction with previous scholars emancipating for increased
monitoring in public procurement to meet goals (Adusei and Awunyo-Vitor, 2015, Jha and
Misra, 2007). Notably, these scholars’ findings were based on general procurement practiced
with less emphasis on complex public road construction projects. Nonetheless, current findings
are attributed to various improvement strategies involving different monitoring agencies for
public construction projects through consultative forum (PPDA Authority, 2008). Furthermore,
Uganda’s Parliament and various judicial arms are currently investigating irregularities in
public road construction projects. Electronically, Uganda National Roads Authority is currently
implementing Enterprise Resource Planning software to ensure efficient monitoring of its
functions through road assets management and maintenance systems (Uganda National Road
Authority, 2018). Consequently, all these together compel project implementers to comply.
Such strategies encourage project implementers to comply with project specifications because
continuous monitoring of government projects prevent fraud (Basheka et al., 2012). In addition,
regular and random inspection of construction projects is inevitable for construction industry
159
(Owusu et al., 2017). Studies across the globe have revealed failed government projects
especially in construction because of inadequate supervision (Blount et al., 2017, Jha and
Misra, 2007). This concurs with reports showing that effective monitoring of construction
projects ensures that set targets are met and mitigating against cost and time overruns
commonly reported in the construction industry (Lapidus and Yves, 2018, Love et al., 2016a,
Tabish and Jha, 2015, Kakitahi et al., 2013).
7.2.3 The Relationship between Professionalism and Compliance with Public Procurement Regulatory Framework
The objective for H3 was to ascertain whether professionalism affects compliance in
public road construction projects. According to PLS-algorithm path coefficient results, there is
an inverse relationship between professionalism of staff involved in public road construction
projects and compliance with public procurement regulatory framework. This implies that
professionalism among these staff does not predict increase in compliance with public
procurement regulatory framework. Meanwhile bootstrapping results show that there is an
insignificant relationship between professionalism of staff involved in public road construction
projects and compliance with public procurement regulatory framework (α = -0.102, t = 1.250,
p = 0.211) at 5% significance level. Hence, H3 is not supported and the objective is not
achieved. This implies that increased demonstration of high professional integrity by staff,
professional judgement during decision-making, high level of confidentiality, employing
practically experienced road construction staff with required expertise is not effective in
achieving compliance with public procurement regulatory framework. These indicators
measured professionalism of staff involved in public road construction projects to meet
government objectives. However, basing on the analysis of respondents’ answers, even if there
were mechanisms of ensuring professionalism of staff involved on these projects, enforcement
was not effective.
Whereas these results are in line with findings that found insignificant relationship
between professionalism and compliance in public procurement (Eyaa and Oluka, 2011),
reports show that unprofessional behaviour significantly affects compliance in China’s and
Malaysian construction industries (Deng et al., 2014, Shu Hui et al., 2011). Conversely,
Loosemore and Malouf (2019) observed that training as a component of professionalism, was
largely ineffective in achieving workers’ compliance with safety measures in the construction
industry. Furthermore, the findings contradict previous recommendations emphasising
increased training of staff, professional code, confidentiality, expertise and professional
160
membership in public procurement (PPDA Authority, 2016, Sohail and Cavill, 2008, Wall and
Ahmed, 2008, Gelderman et al., 2006). This is attributed to highly qualified staff involved in
public road construction projects. For example 93.8% hold a bachelor’s degree and above and
60.4% are professional engineers registered by various engineering boards. In addition, UNRA
has embraced continuous investment in staff professionalism through capacity building that is
improving staff skills, knowledge and utilisation of required tools and equipment (Uganda
National Road Authority, 2018). This is boosted by increased higher institutions of learning
offering degrees that is associated with increasing employment of qualified staff.
Consequently, ensuring staff competence and increasing their innovativeness (Czarnitzki et al.,
2018, Appelt and Galindo-Rueda, 2016).
In addition, tremendous efforts has been applied in the past to improve professionalism
in the construction industry through upholding professional ethics and honest culture (Owusu
et al., 2017). For example, Uganda is enforcing an ethical code of conduct through Ministry of
Ethics and Integrity. This is complemented by establishing various professional bodies
including; Institute of Procurement Professionals of Uganda (IPPU), UACE, UNABCEC,
Uganda Institute of Professional Engineers (UIPE), Engineering Registration Board (ERB),
Architecture Registration Board (ARB) and Surveyor’s Registration Board (SRB) to ensure
professionalism in the construction sector national wide (PPDA Authority, 2008). Such efforts
are meant to address lack of required skills and integrity among procurement staff that are
causing inadequacies in public sector procurement (Nsanganzelu, 2015, Ojo and Gbadebo,
2014). The fact that public road construction projects are complex, multidimensional skills are
required and management need to embrace continuous professionalism of public sector
procurement. With persistent public procurement reforms globally and particularly in Uganda
where currently public procurement regulatory framework is under review for possible
amendments, professionalism in the sector is mandated to government and should be in
harmony with international standards as proposed by earlier scholars (Deng et al., 2014). This
would address incompetence in Uganda’s construction workforce characterised with
inappropriate skills due to poor training and recruitment methods (Ministry of works and
Transport, 2012, Alinaitwe et al., 2007). Consequently, the public road construction subsector
should be appropriately staffed with a qualified, competent and experienced work force. Bodies
like Institute of Procurement Professionals of Uganda and Uganda Institute of Professional
Engineers (UIPE) among others should be fully empowered to enforce respective standards in
public procurement and construction sectors.
161
7.2.4 The Relationship between Sanctions and Compliance with Public Procurement Regulatory Framework
The objective of H4 was to ascertain whether sanctions affect compliance in public road
construction projects. PLS-algorithm path coefficient results show that there is a positive
relationship between sanctions on staff involved in public road construction projects and
compliance with public procurement regulatory framework. This implies that sanctioning of
these staff predicted increase in compliance with public procurement regulatory framework. In
addition, bootstrapping results show that there is a significant relationship between sanctions
on staff involved in public road construction projects and compliance with public procurement
regulatory framework (α = 0.315, t = 3.540, p = 0.000) at 1% significance level. Hence, H4 is
supported and the objective is achieved corresponding to previous findings that found sanctions
as an effective mechanism ensuring compliance in public procurement (Peprah, 2015,
Mwakibinga and Buvik, 2013). This implied that increased penalties on both contractors and
public officers found in wrong during public road implementation period is effective in
achieving compliance with public procurement regulatory framework as supported by
institutional theory (Chan and Owusu, 2017, Scott, 2013). Such sanctions will ensure that staff
implement properly authorised road construction projects, timely delivery of road construction
projects, timely recording of road construction transactions and achieving objectives of the
road construction projects.
Analysis of responses reveal that contractors are punished when they do not meet
specifications as well as not following the regulatory framework during road construction,
proportional sanctions are effected immediately after a violation of the regulatory framework
is detected and timely administrative sanction e.g. warnings, suspension, disqualification,
dismissal and fines on errant officers are enforced. Credible sanctions with negative
consequences are imposed on road implementation team without any warning for non-
compliance. Additionally, imposed sanctions compel the team to work consciously. These
indicators effectively measured sanctions on staff involved in public road construction projects
to meet government objectives. Ensuring effective sanctions on staff involved on these projects
should be continuously applied with transparency and objectivity. This is in line with previous
studies emphasising strict and swift penalties on offenders who deliberately flout public
procurement regulatory framework (Shu Hui et al., 2011, PPDA Authority, 2009a, Agaba and
Shipman, 2007). Such sanctions increase fear among staff involved in public road construction
162
projects when implementing the projects that in turn ensure government goals are attained
(Wirick, 2009).
Whereas some studies suggest non-coercive sanctions (including rewards,
recommendations and requests), threats are widely applied to instil fear among staff in public
sector procurement (Payan and McFarland, 2005, Braun, 2003, Venkatesh et al., 1995).
Surprisingly, Gelderman et al. (2010) revealed that sanctions are not significant in influencing
compliance with EU directives. Nonetheless, sanctions including tough penalties restore sanity
in a corrupt public procurement sector and save government from loosing significant funds
because staff will be compelled to comply (Mwakibinga and Buvik, 2013, Van Snellenberg
and van de Peppel, 2002, Sutinen and Kuperan, 1999). Generally, tougher sanctions on
contractors and public officers in respective departments handling public road construction
projects influence these players to ensure that government objectives are achieved (Rajab and
Eydgahi, 2019, Agaba and Shipman, 2007). Furthermore, punitive sanctions including;
contract termination, suspension, confiscation of property and none payments are widely
applied globally to achieve compliance, value for money and saving government significant
funds (Shu Hui et al., 2011).
7.2.5 The Relationship between Perceived Inefficiency of Public Procurement Regulatory Framework and Compliance with Public Procurement Regulatory Framework
The objective of H5 was to ascertain whether perceived inefficiency of public
procurement regulatory framework affect compliance in public road construction projects.
PLS-algorithm path results reveal that there is an inverse relationship between perceived
inefficiency of public procurement regulatory framework and compliance with public
procurement regulatory framework. This implies that perceived inefficiency of public
procurement regulatory framework predicted reduction in compliance with public procurement
regulatory framework. In addition, bootstrapping results show that there is a significant
relationship between perceived inefficiency of public procurement regulatory framework and
compliance with public procurement regulatory framework (α = -0.253, t = 3.052, p = 0.002)
at 1% significance level. Hence, H5 is supported and the objective is achieved contrary to
findings that established an insignificant relationship between these factors in Netherland’s
public procurement (Gelderman et al., 2006). The results found in this thesis imply that banning
negotiation between contractors and public officers during road construction, banning contract
extension beyond agreed period and banning of underperforming contractors are effective in
163
achieving compliance with public procurement regulatory framework. Enforcing these key
indicators would ensure efficiency of public procurement regulatory framework governing
public road construction projects and achieving government objectives.
Effective enforcement of these indicators is required at all times on each public road
construction project. Clear and detailed description on every clause cited in the main public
procurement regulatory framework should be brought to the attention of participants during
public road construction implementation. Otherwise, if perceived as unclear, then non-
compliance is highly unavoidable (Gelderman et al., 2006). Public procurement among
developing countries is disorderly because of unclear regulatory framework and with
complexity of public road construction projects, a vibrant public regulatory framework is
necessary to meet government objectives. Reference is made on persistent public procurement
reforms in East Africa aimed at closing the loopholes within the framework to achieve value
for money and fighting corruption (Obanda, 2010, Odhiambo and Kamau, 2003). It is
recommended that governments should develop clear policies and procedures operating these
projects and public procurement regulatory framework should be explicitly written in a
nonprofessional language for easy interpretation. Strengthening regulatory framework is
inevitable for construction projects (Shan et al., 2017, Zhang et al., 2016). Where possible,
legal interpretation assistance from experts on technical issues would assist in project
implementation. Whereas there are limited studies on perceived inefficiency of public
procurement regulatory framework in achieving compliance, this thesis has discovered that it
is effective in reducing non-compliance in public road construction projects.
7.2.6 The Relationship between Contractors’ Resistance and Compliance with Public Procurement Regulatory Framework
The objective of H6 was to ascertain whether contractors’ resistance affect compliance
in public road construction projects. According to PLS-algorithm path coefficient results, there
is a positive relationship between contractors’ resistance to non-compliance with public
procurement regulatory framework governing public road construction projects and
compliance with public procurement regulatory framework. This implies that contractors’
resistance to non-compliance predicted increase in compliance with public procurement
regulatory framework. Further bootstrapping results show that there is a significant relationship
between contractors’ resistance to non-compliance with public procurement regulatory
framework by public officers and compliance with public procurement regulatory framework
governing these projects (α = 0.135, t = 2.002, p = 0.045) at 5% significance level. Hence, H6
164
is supported and the objective is achieved. This implied that increased contractors’ knowledge
on public road procurement process and encouraging them to take action against defiant public
officers is effective in achieving compliance with public procurement regulatory framework.
These findings contradict previous study that found an insignificant relationship between
contractors’ resistance and compliance with EU directives in Netherlands public procurement
(Gelderman et al., 2010).
Respondents agreed that contractor’s knowledge on procurement process helps in
controlling public officers from making bad decisions and contractor’s readiness to take action
against a bad decision makes public officers fear reprisals in turn achieving compliance.
Contractors may be unable to take action if they fear retaliation from public procurement staff
who are responsible for awarding and managing future contracts. However, when the
regulatory framework is transparent and effective in outlining remedies and protecting
suppliers from public officers’ retaliation, compliance with public procurement regulatory
framework would be achieved. These remarks were earlier applauded in the compliance studies
covering USA and Netherlands (Pachnou, 2005b, Braun, 2003). Contractors’ readiness and
willingness to take action as well as being knowledgeable of the public procurement regulatory
framework were basic indicators measuring contractors’ resistance. Enforcing these indicators
would eradicate non-compliance with public procurement regulatory framework governing
public road construction projects and meet government objectives. Institutional theory avers
that different stakeholders with specific reasons and experience to accomplish organizational
tasks resist others failing to comply with the norms of meeting organisation’s objectives
(Greenwood and Hinings, 1996). Contractors should be encouraged to take action against bad
decisions by public officers and increase their knowledge on public procurement regulatory
framework in order to control these officers in entire procurement process.
7.3 Project Success Relationships
7.3.1 The Relationship between Compliance with Public Procurement Regulatory Framework and Project Success
The objective of H7 was to ascertain the effect of compliance with public procurement
regulatory framework on public road construction project success. PLS-algorithm coefficient
results show that there is a positive relationship between compliance with public procurement
regulatory framework and success of public road construction projects. This implies that
compliance with public procurement regulatory framework predicted the success of public road
construction projects. Additionally, bootstrapping results show that there is a significant
165
relationship between compliance with public procurement regulatory framework and project
success (α = 0.147, t = 1.960, p = 0.05) at 5% significance level. Hence, H7 is supported and
the objective is achieved. Implying that emphasising proper authorisation of road construction
projects, timely delivery of road construction projects, timely recording of road construction
transactions and achieving road construction objectives are effective in implementing these
projects successfully. Successful implementation is realised if public road construction projects
are implemented according to specifications, on time and within budget (Hussain et al., 2019,
Gledson et al., 2018, Dvir and Lechler, 2004, Atkinson, 1999). Alinaitwe et al. (2013), Tabish
and Jha (2011) contended that compliance with regulatory framework is a significant factor in
the performance of construction projects. These findings correspond to current thesis findings
and thus, for successful public construction projects, compliance with governing regulatory
framework is essential (Zadawa et al., 2018a, Kassel, 2008).
Compliance in public road construction projects is achieved if causes of non-
compliance are established and mitigation strategies accordingly determined (Kulp et al.,
2006). Many projects have failed due to selfish interests, inefficient regulatory framework,
inducement and weak enforcement mechanism (Mwakibinga and Buvik, 2013). Complexity of
public road construction projects with multiple stakeholders and directives from government
and donors complicate implementation process with multi-stakeholders’ demands. However,
harmonising all the policies, procedures and directives from different stakeholders is
paramount for the success of these projects. Stakeholders are dissatisfied with cost and
schedule overruns that affect road construction projects by 30% (Ford, 2011). Cost and
schedule escalations surrounding Uganda’s road construction projects are evidenced with
complaints from multi-stakeholders community (Red Pepper, 2018, PPDA Authority, 2009b).
Furthermore, lack of cooperation, mistrust and not complying with regulatory framework
account for failed construction projects (Ntayi et al., 2010b).
Relatedly, in Australia, non-compliance accompanied with non-durable construction
materials are challenging the construction industry (Australian Procurement & Construction
Council, 2013). Comparatively, cost and schedule overruns are reportedly affecting
international construction industry specifically accounting for (47- 48)% failed Australian
public road construction projects (Love et al., 2019, Love et al., 2016a). Complying with the
public procurement regulatory framework is inevitable for the successful public road
construction projects and stakeholders should pay attention to road specifications, cost and time
166
throughout the implementation process (Gambo et al., 2016, Walker and Lloyd-Walker, 2015,
Chan and Chan, 2004, Atkinson, 1999). Additionally, emphasising timely recording of road
construction transaction, project delivery, proper authorisation and achieving project objectives
is important when implementing public road construction projects since they are key indicators
measuring compliance with public procurement regulatory framework. These will ensure value
for money, transparency, accountability, successful road construction delivery, saving
significant funds and increasing quality-paved roads. Saved funds can be channelled to other
priority sectors for example; modernisation of agriculture, poverty eradication and extending
road network to rural agricultural areas to market agricultural products.
7.3.2 The Relationship between Familiarity with Public Procurement Regulatory Framework and Project Success
The objective of H8 was to ascertain whether familiarity with public procurement
regulatory framework leads to project success. According to PLS-algorithm path coefficient
results, there is a positive relationship between familiarity with public procurement regulatory
framework and project success. This implies that familiarity with public procurement
regulatory framework predicted success of public road construction projects. Meanwhile
bootstrapping results show that there is a significant relationship between familiarity with
public procurement regulatory framework and project success (α = 0.140, t = 2.231, p = 0.026)
at 5% significance level. Hence, H8 is supported and the objective is achieved. These findings
are supported by the previous studies contending that successful public construction projects
rely on managers’ thorough understanding of the project scope and governing regulatory
framework (Gambo et al., 2016, Tabish and Jha, 2015, Jari and Bhangale, 2013, Shaban, 2008).
Implying that simplifying regulatory framework governing public road construction projects
for easy interpretation, using staff who are familiar with implementation of these projects and
employing staff with appropriate academic qualification to work on applicable road
construction projects is effective in successful implementation of public road construction
projects.
The government should emphasise improving staff familiarity with public road
construction projects through training and inductions as proposed by institutional theory
(North, 1993). Gelderman et al. (2006) observed that staff training and education are important
in achieving public procurement targets. However, the training programs should be tailored to
project needs and learner centric (Loosemore and Malouf, 2019). These projects should be
implemented in accordance with specifications, budget and time since these are major
167
indicators measuring the success of public road construction projects. In addition, management
should encourage qualified and competent staff involvement in public road implementation
since these are key indicators measuring familiarity with public procurement regulatory
framework. This is inevitable since many construction projects have failed due to using staff
who are unfamiliar with project requirements (Jari and Bhangale, 2013, Mahmood, 2010). Staff
familiarity is achieved through transparent and merit based selection criterion such as formal
required academic qualifications and experienced competent team (DiMaggio and Powell,
2015). Once staff involved in public road construction projects comprehensively understand
the detailed requirements of these projects, it would be easy to implement them within
described parameters leading to successful project completion. Interestingly, construction
projects are completed easily and within schedule if staff are familiar with ways of doing works
related to that project (Sidwell et al., 2002). Hence, improving staff knowledge is important for
successful construction sector (Munyasya and Chileshe, 2018).
7.3.3 The Relationship between Monitoring Activities and Project Success The objective of H9 was to ascertain whether monitoring activities leads to project
success. PLS-algorithm path coefficient results show that there is a positive relationship
between monitoring activities of public road construction projects and the success of these
projects. This implies that monitoring activities predicted the success of public road
construction projects. Furthermore, bootstrapping results show that there is a significant
relationship between monitoring activities on public road construction projects and project
success (α = 0.314, t = 4.875, p = 0.000) at 1% significance level. Hence, H9 is supported and
the objective is achieved. This is in conformance with the recommendations revealing that
successful public construction projects rely on regular monitoring of project activities (Hussain
et al., 2019, Owusu et al., 2017, Obanda, 2010, Reeves, 2008, Lam et al., 2008). This implies
that frequent inspections to check on timely recording of project progress, timely project
completion and proper storage methods were effective in successful implementation of public
road construction projects. Despite significant results, they contradict previous study that
established that monitoring construction staff was insignificant in ensuring safety in
construction projects (Tabish and Jha, 2015). Considering a theoretical approach, agency and
institutional theories support current results contending that monitoring public road
construction projects ensure that government objectives are met and value for money achieved
(DiMaggio and Powell, 2015, Van Slyke, 2007).
168
Successful procurement of public projects is highly dependent upon increased
monitoring of procurement activities (Adusei and Awunyo-Vitor, 2015, Jha and Misra, 2007).
Whereas Kauppi and van Raaij (2015) revealed that monitoring activities is not significant in
influencing agents’ actions to meet principals’ goals, evidence shows that continuous
monitoring of government projects prevents fraud and saves the projects from collapsing
(Basheka et al., 2012, PPDA Authority, 2008). Management should actively monitor public
road construction projects to determine if they are implemented in accordance with project
specifications, on time and within budget. This would ensure that set objectives are achieved.
Studies across the globe attach inadequate supervision to failed government projects especially
in construction (Blount et al., 2017, Ntayi et al., 2010b, Olken, 2005). On the contrary,
successful performance of USA’s construction sector that was previously marred by cost
overrun, shoddy works by contractors and corruption is attributed to effective monitoring of
entire construction procurement process (Bartle and Korosec, 2003). This notion is supported
by extant literature in the construction industry calling for effective monitoring of construction
projects to reduce reworks, cost and time overruns (Lapidus and Yves, 2018, Love et al., 2016a,
Kakitahi et al., 2013). This would be achieved through timely recording of public road
construction activities, frequent inspections to ensure timely completion of these projects and
proper storage methods to avoid damage and stealing of public road construction materials.
7.3.4 The Relationship between Professionalism and Project Success The objective of H10 was to ascertain whether professionalism of staff leads to project
success. According to PLS-algorithm path coefficient results, there is a positive relationship
between professionalism of staff involved in public road construction projects and project
success. This implies that professionalism of staff involved in public road construction projects
predicted the success of public road construction projects. Furthermore, bootstrapping results
show that there is a significant relationship between professionalism of staff involved in public
road construction projects and project success (α = 0.305, t = 4.695, p = 0.000) at 1%
significance level. Hence, H10 is supported and the objective is achieved. The findings are
supported by recommendations agitating for trained, experienced and skilful staff for
successful construction project implementation (Hussain et al., 2019, Tayeh et al., 2018,
Gambo et al., 2016, Walker and Lloyd-Walker, 2015, Shaban, 2008, Wall and Ahmed, 2008).
This implies that high professional integrity by staff, professional judgement during decision-
making, high level of confidentiality, employing practically experienced road construction staff
169
with required expertise is effective in successful implementation of public road construction
projects.
Institutional theory contends that professionalism is achieved through academic
qualifications, training, professional networking capable of empowering staff competence for
successful organizational performance (DiMaggio and Powell, 2015). This notion is further
supported by (Gelderman et al., 2006). Professionalism ensures project success when staff are
knowledgeable with particular project requirements (Giroud et al., 2018). In addition,
professionalism is enforced through emphasising ethical codes and honesty in the construction
sector (Owusu et al., 2017). Hence, investing in staff competence is important for public road
construction projects (Kalinzi, 2014, Wall and Ahmed, 2008). For example through continuous
training (Loosemore and Malouf, 2019, Shaban, 2008). Management should determine project
requirements from initiation stage through to project completion. This would help management
to source the rightful personnel with required expertise and competence to execute the project.
Expertise in project implementation especially in managing capital works is the cornerstone
for successful project completion (Furneaux et al., 2006). In addition, implementing public
road construction projects require rightful machinery, qualified and competent staff who are
knowledgeable with public road construction implementation process. Careful selection of
project team based on their competencies will lead to successful delivery of these projects
PPDA Authority (2016) because the selection would ensure the team is composed of
experienced, skilful and competent staff to enforce successful project performance (Gambo et
al., 2016).
7.3.5 The Relationship between Perceived Inefficiency of Public Procurement Regulatory Framework and Project Success
The objective of H11 was to ascertain whether perceived inefficiency with public
procurement regulatory framework reduces project success. PLS-algorithm path coefficient
results reveal that there is an inverse relationship between perceived inefficiency of public
procurement regulatory framework and the success of public road construction projects. This
implies that perceived inefficiency of public procurement regulatory framework predicted
reduction in the success of public road construction projects. Additionally, bootstrapping
results show that there is a significant inverse relationship between perceived inefficiency of
public procurement regulatory framework and project success (α = -0.135, t = 2.099, p = 0.036)
at 5% significance level. Hence, H11 is supported and the objective is achieved. This finding
corresponds to recommendations calling for an efficient and effective regulatory framework to
170
govern construction industry (Shaban, 2008). In addition, stakeholder experience difficulties
in accomplishing tasks when the regulatory framework is unclear (Gelderman et al., 2006).
This implied that enforcing ban on negotiation between contractors and public officers during
road construction, ban on contract extension beyond agreed period and banning of
underperforming contractors is effective in successful implementation of public road
construction projects. Emphasising these indicators ensures that regulatory framework is
effective and cannot be manipulated (Thai, 2008a).
Relatedly, enforcing these indicators would ensure successful public road construction
projects since successful organisations rely on effective institutional norms (Oliver, 1991). This
proposal is further supported by the argument that successful public construction projects
require stakeholders’ understanding of the project scope with a clear governing regulatory
framework capable of eradicating manipulations (Tayeh et al., 2018, Zhang et al., 2016, Tabish
and Jha, 2015, Tabish and Jha, 2011). Surprisingly, little is known about the role of perceived
inefficiency of public procurement regulatory framework in implementing public road projects.
However, with concerns from public construction stakeholders lamenting on unclear national
standards and regulations challenges facing construction sector PPDA Authority (2008),
government should explicitly come up with clear public procurement regulatory framework in
a nonprofessional’s language for easy interpretation during public road implementation.
Otherwise, deviating from clarity will continuously affect successful completion of public road
construction projects (Shan et al., 2017). Unsuccessful public road construction projects is
possible since previous studies established that East African public procurement legal
framework is unclear requiring respective governments to strengthen the frameworks for
proper guidance in procurement activities (Odhiambo and Kamau, 2003). Consequently,
Uganda National Roads Authority has improved on implementation of regulatory framework
to ensure successful road construction projects (Uganda National Road Authority, 2018).
7.3.6 The Relationship between Contractors’ Resistance and Project Success The objective of H12 was to ascertain whether contractors’ resistance to non-
compliance with public procurement regulatory framework leads to project success. According
to PLS-algorithm path coefficient results, there is a positive relationship between contractors’
resistance to non-compliance with public procurement regulatory framework and success of
public road construction projects. This implies that contractors’ resistance to non-compliance
with public procurement regulatory framework governing public road construction projects
predicted success of these projects. Meanwhile bootstrapping results show that there is an
171
insignificant relationship between contractors’ resistance to non-compliance with public
procurement regulatory framework and project success (α = 0.121, t = 1.792, p = 0.073) at 5%
significance level. Hence, H12 is not statistically supported and the objective is not achieved.
This implies that contractors’ knowledge on public road procurement process and encouraging
them to take action against defiant public officers predicted successful implementation of
public road construction projects. However, the prediction is not sufficient to ensure that public
road construction projects are implemented according to specifications, on time and within
budget. This is attributed to contractors’ reluctance to report defiant public officers fearing
retaliation from these officers in awarding future contracts if the remedy mechanism is
ineffective (Gelderman et al., 2010, Gelderman et al., 2006).
Institutional theory contends that different players have specific reasons and knowledge
to perform an organisation’s tasks successfully (Greenwood and Hinings, 1996). This explains
why contractors should resist bad decisions by public officers during road construction.
Notably, contractors are obliged to meet project demands by fulfilling their mandate and
protect their name for future contract award. Despite contractors’ commitment to fulfil their
mandate, an effective regulatory framework is inevitable to support their actions. Whereas,
contractors’ resistance does not significantly lead to successful public road construction
projects implementation, empowering them through knowledge and readiness cannot be
ignored as these are key indicators to influence project implementation (Gelderman et al.,
2010).
7.3.7 The Relationship between Sanctions and Project Success The objective of H13 was to ascertain whether sanctions on staff leads to project
success. PLS-algorithm path coefficient results show that there is an inverse relationship
between sanctions on officers involved in public road construction projects and public road
project success. Implying that sanctions imposed on these staff did not predict success of public
road construction projects. Furthermore, bootstrapping results show that there is an
insignificant relationship between sanctions on staff involved in public road construction
projects and project success (α = -0.059, t = 0.856, p = 0.392) at 5% significance level. Hence,
H13 is not supported and the objective is not achieved. This is contrary to reports suggesting
tough sanctions for successful construction industry (Chan and Owusu, 2017, Sohail and
Cavill, 2008). The contradiction could be linked to the fact that these studies supported use of
sanctions in eradicating corruption for successful construction industry without acknowledging
specific attention to public road construction subsector. The findings suggest that imposing
172
penalties during public road implementation period is not effective in successfully
implementing these projects. This is because currently the Ugandan government through the
Parliament and Anti-corruption court have embarked on serious condemnation and prosecution
of guilty public road stakeholders including imprisonment and recovering lost funds.
Furthermore, PPDA is empowered to punish deviant stakeholders and enforce termination of
contracts (PPDA Authority, 2008). Such measures have caused fear amongst public road
implementation team in Uganda.
Interestingly, Uganda’s condemnation is in line with recommendations that suggest
strict sanctions in the construction industry to ably implement construction projects
successfully (Kakitahi et al., 2016, Gambo et al., 2016, Hartley, 2009). Despite these
recommendations, application of sanctions should be carefully considered and enforcing
sanctions depends on player’s attitude and interest to meet set objectives (Saam, 2007,
Gunningham and Kagan, 2005). In addition, sanctions at times makes violators plan how to
conceal detection by the principal (Zubcic and Sims, 2011, Sparrow, 2000). Nevertheless, for
an efficient and effective transport sector to meet its goals, a sound transport policy needs
strong sanctions’ enforcement mechanism (Ministry of works and Transport, 2012). This is
economically vital since significant funds are lost globally due to failure in sanctioning
violators (Mbabazi et al., 2015).
7.4 Mediation Relationships
7.4.1 Compliance with Public Procurement Regulatory Framework Mediates the
Relationship between Familiarity with Public Procurement Regulatory Framework and
Project Success.
The objective of H14 was to ascertain whether compliance with public procurement
regulatory framework mediates the relationship between familiarity with public procurement
regulatory framework and project success. Compliance with public procurement regulatory
framework measured by proper authorisation of road construction projects, timely delivery of
road construction projects; timely recording of road construction transactions and achievable
road construction project objectives has a mediating effect on the relationship between
familiarity with public procurement regulatory framework and the success of public road
construction projects. Direct effect is represented by standardized coefficient of 0.266 and
indirect effect accounts for 0.049 totalling to 0.315. According to Sobel test, compliance with
public procurement regulatory framework significantly mediates the relationship between
173
familiarity and project success as demonstrated by Sobel z-value (Sobel z-value = 2.20, p <
0.05) at 5% significance level. There is a partial mediation since familiarity with public
procurement regulatory framework predicts the success of public road construction projects
directly and indirectly through compliance with public procurement regulatory framework
(Miller et al., 2007). Hence, H14 is supported and the objective is achieved. Implying that
successful implementation of public road construction projects is achieved when familiarity
with public procurement regulatory framework and compliance with public procurement
regulatory framework governing these projects are simultaneously applied (Zadawa et al.,
2018a, Gelderman et al., 2006, Sidwell et al., 2002).
The findings of this dissertation are aligned with recommendations and guideline
encouraging mediation testing (James et al., 2006, Mathieu and Taylor, 2006). Despite
significant relationships between the three study variables as a precondition for mediation
testing Hayes (2009), no similar studies have tested mediation involving familiarity with public
procurement regulatory framework, compliance with public procurement regulatory
framework and project success before. Nonetheless, the findings have enabled further
understanding on how these study variables are related as proposed by earlier advocates for
mediational studies (Fairchild and McQuillin, 2010, Preacher and Hayes, 2004, MacKinnon et
al., 2002, Baron and Kenny, 1986). Accordingly, compliance with public procurement
regulatory framework plays a crucial role in influencing familiarity with public procurement
regulatory framework for successful implementation of public road construction projects.
Consequently, commitment and compliance approaches have registered successful
performance by achieving government objectives (Su et al., 2018). Commitment approach
emphasises familiarity through staff knowledge, skills and abilities, while regulatory
compliance eliminates role ambiguity, controlling staff and guiding firm capabilities leading
to successful performance (Su et al., 2018).
Introducing compliance significantly improves staff familiarity which actively
increases organisation performance (Andrevski et al., 2014). Successful project performance
is achieved if projects are implemented in accordance with project specifications, completed in
time and within budget (Hussain et al., 2019). The government can emphasise; proper
authorisation of road construction projects, timely delivery of road construction projects, timely
recording of road construction transactions and achievable road construction objectives. In
addition, simplifying a regulatory framework governing these projects for easy interpretation,
174
employing staff who are familiar with implementing these projects and staff with appropriate
academic qualifications to work on road construction projects is important. Accordingly,
management need to reinforce human capital appropriately to ensure familiarity and capability
in successful task performance (Beltrán-Martín et al., 2008). Because appropriate staff
competence through proper staffing procedures and skill development are important in
ensuring familiarity leading to successful organizational performance (Hussain et al., 2019,
Beltrán-Martín et al., 2008). A combination of these two factors displays a good interactive
effect on the success of public road construction projects by changing the mindset of staff who
are familiar with traditional methods (Kaluarachchi and Jones, 2007).
7.4.2 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Monitoring Activities in Public Road Construction and Project Success
The objective of H15 was to ascertain whether compliance with public procurement
regulatory framework mediates the relationship between monitoring activities and project
success. Regression results show that compliance with public procurement regulatory
framework has a mediating effect on the relationship between monitoring activities and the
success of public road construction projects. Direct effect is represented by standardized
coefficient of 0.509 and indirect effect accounts for 0.037 totalling to 0.547. Furthermore,
Sobel test results show that compliance with public procurement regulatory framework
significantly mediates the relationship between monitoring activities and project success as
demonstrated by Sobel z-value (Sobel z-value = 2.00, p < 0.05) at 5% significance level. There
is a partial mediation since monitoring activities predicts the success of public road
construction projects directly and indirectly through compliance with public procurement
regulatory framework (Miller et al., 2007). Hence, H15 is supported and the objective is
achieved, implying that successful implementation of public road construction projects is
realised when both monitoring activities and compliance with public procurement regulatory
framework governing these projects are applied simultaneously (Tabish and Jha, 2015, Jha and
Misra, 2007).
The findings are in line with recommendations and guideline of (James et al., 2006,
Mathieu and Taylor, 2006). Despite significant relationships between the three study variables
as a precondition for mediation testing Hayes (2009), no similar studies have tested mediation
involving monitoring activities, compliance with public procurement regulatory framework
and project success before. However, this mediation test has enabled further understanding on
175
how these study variables are related (Memon et al., 2018, Fairchild and McQuillin, 2010,
Preacher and Hayes, 2004, MacKinnon et al., 2002, Baron and Kenny, 1986). Effective
monitoring methods are paramount for project success because they provide quicker failure
identification that ensures reduced reworks and enhances value for money (Robinson and Scott,
2009). Additionally, staff supervision helps management to evaluate their experience and
performance in meeting set objectives (Babalola et al., 2016). Such effective mechanisms are
capable of eradicating opportunistic behaviour, increasing performance, controlling costs and
enhancing firm efficiency (Martin et al., 2016). However, management should avoid abusive
supervision that demoralises public road implementation staff (Krasikova et al., 2013).
The findings suggest that government should emphasise both monitoring activities and
compliance with public procurement regulatory framework to successfully implement public
road construction projects since these factors have portrayed a good interactive effect (Preacher
and Hayes, 2004, Baron and Kenny, 1986). This can be emphasised through proper
authorization of road construction projects, timely delivery of road construction projects,
timely recording of road construction transactions and achieving project objectives as well as
frequent inspections to check on timely recording of project progress, timely project
completion and proper storage methods. Such continuous monitoring improves project
productivity (Isaac and Navon, 2014).
7.4.3 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Professionalism of Staff in Public Road Construction Projects and Project Success
The objective of H16 was to ascertain whether compliance with public procurement
regulatory framework mediates the relationship between professionalism and project success.
Regression results show that compliance with public procurement regulatory framework has a
mediating effect on the relationship between professionalism of staff on public road
construction projects and the success of public road construction projects. Direct effect is
represented by standardized coefficient of 0.508 and indirect effect accounts for 0.044 totalling
to 0.553. According to Sobel test results, compliance with public procurement regulatory
framework insignificantly mediates the relationship between professionalism of staff on public
road construction projects and project success as demonstrated by Sobel z-value (Sobel z-value
= 1.94, p = 0.05) at 5% significance level. This is an insignificant partial mediation since
professionalism of staff on public road construction projects predicts the success of public road
construction projects directly and indirectly through compliance with public procurement
176
regulatory framework. Hence, H16 is not statistically supported and the objective is not
achieved. This implies that successful implementation of public road construction projects is
realised when professionalism of staff on public road construction projects and compliance
with public procurement regulatory framework governing these projects are applied
sequentially.
The findings unveil management understanding on how these factors interact that helps
in determining their application during project implementation (Memon et al., 2018, Fairchild
and McQuillin, 2010, Preacher and Hayes, 2004, MacKinnon et al., 2002). Whenever staff lack
professionalism, compliance with regulatory framework will be affected thereby undermining
successful construction project implementation (Tabish and Jha, 2015, Deng et al., 2014).
Despite importance of professionalism, scholars cast doubt in the relevancy of staff
competence, skills and commitment in meeting set performance targets (Beltrán-Martín et al.,
2008). Whereas the findings are not statistically supported, construction professionals have a
fiduciary duty to perform to client’s expectations (Hussain et al., 2019, Bowen et al., 2012).
Hence, the government should not ignore the interactive effect between these two factors since
it has shown predictive relevance in achieving the success of public road construction projects.
These findings cannot be compared to any earlier studies that have tested mediation involving
professionalism among staff on public road construction projects, compliance with public
procurement regulatory framework and project success.
The government should emphasise proper authorisation of road construction projects,
timely delivery of road construction projects, timely recording of road construction transactions
and achieving objectives of road construction projects. Additionally, high professional integrity
by staff, professional judgement during decision-making, high level of confidentiality and
employing practically experienced road construction staff with required expertise all together
are crucial indicators for implementing public road construction projects. Successful
implementation of public road construction projects is achieved if these projects conform to
project specifications, completed in time and within budget (Hussain et al., 2019, Dvir and
Lechler, 2004, Atkinson, 1999).
7.4.4 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Sanctions in Public Road Construction Projects and Project Success
The objective of H17 was to ascertain whether compliance with public procurement
regulatory framework mediates the relationship between sanctions and project success.
177
Regression results show that compliance with public procurement regulatory framework has a
mediating effect on the relationship between sanctions on staff involved in public road
construction projects and the success of public road construction projects. This is shown by
direct effect represented by standardized coefficient of 0.337 and indirect effect accounts for
0.114 totalling to 0.574. In addition, Sobel test results show that compliance with public
procurement regulatory framework significantly mediates the relationship between sanctions
on staff involved in public road construction projects and project success (Sobel z-value = 2.39,
p < 0.05) at 5% significance level. There is a partial mediation since sanctions on staff predicts
the success of public road construction projects directly and indirectly through compliance with
public procurement regulatory framework (Miller et al., 2007). Hence, H17 is supported and
the objective is achieved. This implies that successful implementation of public road
construction projects is achieved when sanctions on staff involved in public road construction
projects and compliance with public procurement regulatory framework governing these
projects are applied simultaneously (Zadawa et al., 2018b, Shu Hui et al., 2011). This notion is
supported by evidence showing that whereas sanctions could not predict project success
directly (see H13, section 7.3.7), it was able to predict project success through compliance with
regulatory framework (Nitzl et al., 2016).
The findings are supported by the recommendations and guideline of mediation testing
(Mathieu and Taylor, 2006, James et al., 2006). Despite significant mediation effect among
these variables Hayes (2009), these findings are not directly compared with any studies since
no similar studies have tested mediation involving sanctions on staff involved in public road
construction projects, compliance with public procurement regulatory framework and project
success before. However, these findings have enabled further understanding on how these
factors interact (Memon et al., 2018, Fairchild and McQuillin, 2010, Preacher and Hayes, 2004,
MacKinnon et al., 2002, Baron and Kenny, 1986). Management should consider
simultaneously applying these factors when implementing public road construction projects.
Whereas there are costly procedures to enforce prosecution in courts of law, sanctions mitigate
staff crimes in performing company duties through governing regulatory framework (Pierce,
2015). Both sanctions and compliance with the regulatory framework display a good interactive
effect in successful road implementation. This is reinforced through disciplined and bonded
governance mechanisms enforcing team commitment and compliance (Su et al., 2018).
However, management should refrain from destructive enforcement styles that demotivate
implementation team (Krasikova et al., 2013). Additionally, studies show that organizational
178
power to enforce tough sanctions may frustrate staff and increase deviance in meeting set goals
(Lawrence and Robinson, 2007). Thus, the projects implemented should meet project
specifications, completed in time and within budget as well as effective penalties on those
found guilty.
7.4.5 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Perceived Inefficiency of Public Procurement Regulatory Framework and Project Success.
The objective of H18 was to ascertain whether compliance with public procurement
regulatory framework mediates the relationship between perceived inefficiency of public
procurement regulatory framework and project success. As required by Baron and Kenny
guidelines, mediational testing is applicable when a significant relationship exists among study
variable (Hayes, 2009, James et al., 2006, Mathieu and Taylor, 2006). This condition was not
satisfied since perceived inefficiency of public procurement regulatory framework is
insignificantly related to both compliance with public procurement regulatory framework and
project success (Compliance: β = -0.020, p = 0.785, Project success: β = -0.064, p = 0.377),
consequently, rendering the mediational test impossible. Hence, H18 is not supported and the
objective is not achieved. This implies that perceived inefficiency of the public procurement
regulatory framework does not reduce the success of public road construction projects when
compliance with public procurement regulatory framework is introduced. However, when
applied separately, perceived inefficiency with public procurement regulatory framework
reduces project success (Tabish and Jha, 2015).
7.4.6 Compliance with Public Procurement Regulatory Framework Mediates the Relationship between Contractor’s Resistance to Non-Compliance and Project Success
The objectives of H19 was to ascertain whether compliance with public procurement
regulatory framework mediates the relationship between contractors’ resistance to non-
compliance with public procurement regulatory framework and project success. Regression
results show that compliance with public procurement regulatory framework has a mediating
effect on the relationship between contractors’ resistance to non-compliance with public
procurement regulatory framework and the success of public road construction projects. This
is demonstrated by a direct effect of 0.361 and an indirect effect of 0.058 totalling to 0.419.
Furthermore, Sobel test results reveal that compliance with public procurement regulatory
framework significantly mediates the relationship between contractors’ resistance to non-
compliance with public procurement regulatory framework and project success (Sobel z-value
= 2.41, p < 0.05) at 5% significance level. This is a partial mediation since contractors’
179
resistance to non-compliance with public procurement regulatory framework predicts the
success of public road construction projects directly and indirectly through compliance with
public procurement regulatory framework (Miller et al., 2007). This is in line with Nitzl et al.
(2016) emphasising importance of mediation effect in answering a research question rather
than relying only on direct effect. Hence, H19 is supported and the objective is achieved.
Implying that successful implementation of public road construction projects is achieved when
contractors’ resistance to non-compliance with public procurement regulatory framework and
compliance with public procurement regulatory framework governing these projects are
applied simultaneously (Shu Hui et al., 2011, Gelderman et al., 2010).
The findings correspond to the recommendations and guidelines of mediation tests
(James et al., 2006, Mathieu and Taylor, 2006). Preliminary results proved that a significant
relationship among the three variables existed rendering mediational testing possible (Hayes,
2009). However, the final findings could not be directly compared to other studies since no
similar studies have tested mediation involving contractors’ resistance, compliance with public
procurement regulatory framework and project success before. Nonetheless, the findings have
unearthed interact effect involving these factors beyond simple prediction (Memon et al., 2018,
Fairchild and McQuillin, 2010, Preacher and Hayes, 2004, MacKinnon et al., 2002, Baron and
Kenny, 1986). Whereas staff deviance is attributed to stressful and frustrating governance
mechanism Lawrence and Robinson (2007), government should encourage contractors’
resistance to non-compliance by defiant public officers and enforce compliance with public
procurement regulatory framework to successfully implement public road construction
projects. These factors through their measurement indicators exhibited a good interactive
effect, capable of meeting government goals. Contractors’ resistance is inevitable because they
are accountable for project implementation. Notably, accountability is crucial in work
performance (Breaux et al., 2009). Furthermore, contractors’ capability and performance is
important for successful implementation of construction projects (Hussain et al., 2019, Doloi
et al., 2011).
Management should emphasise proper authorisation of road construction projects,
timely delivery of road construction projects, timely recording of road construction transactions
and achieving objectives of the road construction projects. Additionally, increasing
contractors’ knowledge on public road procurement process and encouraging them to take
action against defiant public officers are critical indicators in road implementation.
180
Empowering and relying on contractors is necessary since they have the experience, skills,
knowledge, competence and expertise in road construction projects. All these together would
ensure successful implementation of public road construction projects that should be
implemented as per project specifications, completed in time and within budget (Hussain et al.,
2019, Dvir and Lechler, 2004, Atkinson, 1999).
7.5 Hypotheses Summary
The thesis was divided into three segments with respective study objectives and hypotheses.
The first segment established compliance factors. Under this segment, six hypotheses (H1, H2,
H3, H4, H5 and H6) were proposed, of which three hypotheses (H4, H5 and H6) are
significantly supported. The second segment established factors responsible for the success of
public road construction projects. Under this segment, seven hypotheses (H7, H8, H9, H10,
H11, H12 and H13) were proposed, of which five hypotheses (H7, H8, H9, H10 and H11) are
significantly supported. The third segment determined the mediating effects. Here, the main
objective was to establish whether compliance with the public procurement regulatory
framework mediated the relationship between each compliance factor and the success of public
road construction projects sequentially. Under this segment, six hypotheses (H14, H15, H16,
H17, H18 and H19) were proposed, of which four hypotheses (H14, H15, H17 and H19) are
significantly supported. Overall, twelve (12) hypotheses are significantly supported out of
nineteen (19) hypotheses. Finally, this dissertation also established that two hypotheses (H12
and H16) were supported but statistically insignificant.
This leads to chapter eight that provides the study implications and contributions.
181
CHAPTER EIGHT STUDY IMPLICATIONS AND CONTRIBUTIONS
182
8.1 Introduction The thesis adopted agency and institutional theories to establish factors responsible for
compliance with regulatory framework and success of public road construction projects as well
as determining the mediation effects. This was enhanced through reviewing literature in peer
reviewed journals and public documents. Accordingly, the discussions and conclusions made
here are compared and aligned with agency and institutional theories in conjunction with peer
reviewed articles. Results in chapter six were discussed in line with thirteen hypotheses (direct
relationship prediction) developed in the conceptual model and six mediation hypotheses that
were respectively analysed based on PLS-SEM and Sobel test of mediation. Accordingly, this
chapter presents study implications and contributions in the order of theoretical, managerial,
methodological, knowledge and practical subsections.
8.2 Theoretical Implication and Contributions
Whereas agency and institutional theories advocate use of sanctions, monitoring, familiarity,
professionalism, perceived inefficiency and contractors’ resistance to meet goals, study
findings show that sanctions on staff involved in public road construction projects, perceived
inefficiency of public procurement regulatory framework and contractors’ resistance to non-
compliance are key factors determining compliance with public procurement regulatory
framework. While familiarity with public procurement regulatory framework, monitoring
activities and professionalism among staff involved in public road construction projects are not
predictors of compliance with public procurement regulatory framework. These results are
compared with the findings of Mwakibinga and Buvik (2013) where monitoring and sanctions
are supported when applied separately but when increasing monitoring occurred, sanctions
were reduced. Basing on these theories, the findings of this dissertation show that sanctions on
staff can address non-compliance issues when implementing public road construction projects
(DiMaggio and Powell, 2015, Van Slyke, 2007). Contractor’s resistance and perceived
inefficiency of regulatory framework enhance compliance with public procurement regulatory
framework based on institutional theory (Kondra and Hinings, 1998, Greenwood and Hinings,
1988). However, these findings are contrary to previous studies that found these factors were
insignificant in Netherlands’s public procurement (Gelderman et al., 2010, Gelderman et al.,
2006). This is because in Uganda, increased awareness of the benefits of a transparent public
procurement and strengthening of public procurement regulatory framework has encouraged
contractors to resist bad decisions during project implementation.
183
The dissertation extended a compliance with public procurement regulatory framework
model to project success in public road construction projects guided by agency and institutional
theories. Under this extension, the aim was to establish success factors for implementing public
road construction projects. The findings show that compliance with public procurement
regulatory framework, familiarity with public procurement regulatory framework, monitoring
activities, professionalism of staff involved in public road construction projects and perceived
inefficiency of public road construction projects are significant factors enhancing successful
implementation of public road construction projects. Successful economies including
Singapore, USA and UK have embraced these factors to sustain their respective construction
industries (Owusu et al., 2017, Le et al., 2014a). Accordingly, this thesis contributes by
encouraging governments to ensure application of these significant factors in the
implementation and management of construction projects. Sanctions on staff involved in public
road construction projects and contractors’ resistance to non-compliance with public
procurement regulatory framework are insignificant factors. This is attributed to
comprehensive investigations and strict measures enforced by Ugandan Parliament and Anti-
corruption courts implicating those involved in procurement irregularities reported in public
road construction projects. These measures have caused fears among current project
implementers. On the other hand, contractors are not sure of the safety of the remedy
mechanism to deter retaliation from deviant public officers when reported.
Agency theory proposes monitoring, sanctions, professionalism and familiarity to mitigate
against agency problems (Van Slyke, 2007). In this thesis, familiarity, monitoring activities
and professionalism predicted the success of public road construction projects. Implying that
government should invest in staff familiarity and professionalism in order to successfully
implement public road construction projects as supported by institutional theory (DiMaggio
and Powell, 2015). In addition, management should effectively monitor public road
construction projects regularly for their successful implementation as proposed by institutional
theory (North, 2016, Zhang et al., 2016). All these factors would ensure that the public road
construction projects are implemented within respective project scope, time, cost and quality
(Gledson et al., 2018). Ensuring successful implementation of these projects is inevitable since
the construction sector accounts for economic development of nations (Shan et al., 2020b,
Munyasya and Chileshe, 2018, Zadawa et al., 2018a, Abdullahi et al., 2017, Gudienė et al.,
2013). Particularly, transport construction projects are pivotal in economic development
worldwide (Love et al., 2019, Sinesilassie et al., 2019).
184
Furthermore, this thesis determined the mediating role of compliance with public
procurement regulatory framework between six compliance factors and project success. The
findings of this thesis show that compliance with public procurement regulatory framework
significantly mediated the relationship between familiarity with public procurement regulatory
framework, monitoring activities, sanction on staff and contractors’ resistance to non-
compliance and the success of public road construction projects. However, compliance with
public procurement regulatory framework was shown not to mediate the relationship between
professionalism of staff, and perceived inefficiency of public procurement regulatory
framework with the success of public road construction projects. Hence, governments should
emphasise compliance with public procurement regulatory framework to successfully
implement public road construction projects, again supported by institutional theory
(DiMaggio and Powell, 2015, Scott, 2013, Kondra and Hinings, 1998). Whereas sanctions were
a key predictor of compliance with public procurement regulatory framework, they were not
significant in predicting project success. However, sanctions on staff enhanced project success
through mediation. Thus, government should enforce sanctions to promote compliance that in
turn enhance successful implementation of public road construction projects as proven by
interactive effect of compliance and sanctions in mediation testing (Memon et al., 2018,
Zadawa et al., 2018b, Preacher and Hayes, 2004, MacKinnon et al., 2002).
8.3 Managerial Implications and Contributions
The dissertation objectives were to discover compliance factors in public procurement of
road construction projects and further establish their effect together with compliance with
public procurement regulatory framework on success of these projects and to make
recommendations. Notably, this is not a policy statement but suggestions if incorporated;
government would expect positive changes to successfully implement public road construction
projects.
The findings show that sanctions on staff involved in public road construction projects,
perceived inefficiency of public procurement regulatory framework and contractors’ resistance
to non-compliance with regulatory framework are significant factors enhancing compliance
with public procurement regulatory framework. Furthermore, compliance with public
procurement regulatory framework, familiarity with public procurement regulatory framework,
monitoring activities, professionalism of staff and perceived inefficiency of public
procurement regulatory framework governing these projects are significant factors influencing
successful implementation of public road construction projects. These factors call on
185
management attention for better implementation of road construction projects. Management
should choose from these factors carefully when implementing public road construction
projects and it could necessitate inter-mixing of factors based on specific projects. This is
proven from a mediating role of compliance with public procurement regulatory framework
that was found as a key mediating factor. This is suggested in the light of the fact that particular
factors will produce a different outcome contingent on the project scope and deliverables
expected. Given the complexity of public road construction projects, flexibility in factor
selection is paramount (Shan et al., 2017). Evidently, construction projects experience unique
complexities and risks throughout construction process (Doloi et al., 2011). This is true as
empirical findings by different scholars vary when testing similar factors across different fields
over time horizons.
Management should consider these factors with their respective indicators carefully for
enforcing compliance. In addition, these factors can be used to influence and increase the
successful implementation of public road construction projects (Jari and Bhangale, 2013).
These factors forming a validated governance model would ensure government achieves its
objectives and value for money. Management needs to understand the culture of project
implementation staff in application of such factors, as this could have an implication on
achieving intended goals. Given the empirical results, the government should invest in staff
professionalism, increasing familiarity with public procurement regulatory framework,
effectively monitoring of public road construction activities, imposing effective sanctions,
empowering contractors and strengthening the public procurement regulatory framework for
successful implementation of road construction projects. Strengthening the regulatory
framework and improving staff professionalism are essential for a successful construction
industry (Ameyaw et al., 2017, Chan and Owusu, 2017). Familiarity with public procurement
regulatory framework, process and road implementation procedures are paramount for
consideration by management. However, public procurement regulatory framework should be
written in nonprofessional language for easy understanding and interpretation. Whereas
monitoring public road construction projects is significant factor, government need to
streamline monitoring agencies with clear roles of each agency. This will avoid confusing
implementers on goal conflict that will affect successful implementation of public road
construction projects. Coordination among various monitoring agencies and departments is
helpful in construction sector (Hussain et al., 2019, Owusu et al., 2017). Additionally, the
government should empower public involvement in road construction projects as emphasised
186
by senior officers in the participating organisations. Safety of public participation should be
assured to encourage them in actively monitoring and reporting unpleasant issues that may
arise in the course of implementing public road construction projects.
Key indicators of professionalism with strong factor loading above 0.7 reveal that staff high
professional integrity, professional judgement during decision-making, high level of
confidentiality, practical experience in road construction and required expertise in road
construction are crucial in successfully implementing public road construction projects. Indeed,
employing trained and experienced staff is key in successful construction projects (Hussain et
al., 2019, Tayeh et al., 2018, Gudienė et al., 2013). In familiarity, key indicators with strong
factor loadings ranging from 0.7 to 0.8 considered in successful public road implementation
include; precisely written regulatory framework for easy interpretation, using staff who are
familiar with implementation of public road construction projects and employing staff with
appropriate academic qualifications. Under monitoring activities, key indicators with
respective factor loadings of 0.675, 0.597, 0.858 and 0.820 are frequent inspections to check
on timely recording of project progress, ensure timely project completion, proper storage
methods to prevent damage and theft of construction materials. For sanctions to achieve
compliance, key indicators with corresponding factor loadings are penalties on those found
guilty without any warning (0.812), implementing sanctions in secret (0.862) and imposing
sanctions with negative consequences (0.569) all together determine effective sanctions.
While in contractors’ resistance, key indicators with strong corresponding factor loadings
include; contractors’ readiness to take action against bad decisions (0.856) and contractors’
knowledge on public road procurement process (0.779). Perceived inefficiency of regulatory
framework obtained three key indicators with strong factor loadings including; banning
negotiation between contractors and public officers during road construction (0.730), banning
contract extension beyond agreed schedule (0.845) and banning underperforming contractors
(0.742). Compliance with regulatory framework obtained four key indicators with strong
indicator loadings including; proper authorisation of road construction projects (0.895), timely
delivery of road construction projects (0.663), timely recording of road construction
transactions (0.719) and achieving construction project objectives (0.727). While three key
indicators with strong coefficients measured the success of public road construction projects.
They include; that road construction projects should be implemented in accordance with
specifications (0.728), completed within schedule (0.883) and road completed within budget
187
(0.858). Hence, management should pay attention to these indicators to enforce compliance
and successful implementation of public road construction projects.
8.4 Methodological Contribution
This thesis drew a sample from Uganda’s public road construction subsector comprising
of both public and private entities. Opinions of participants on items raised in the research
instrument were tested using a One-way-ANOVA and found to be similar. A cross-sectional
survey involving quantitative data analysis tools was used to establish significant factors
enhancing compliance with public procurement regulatory framework and the success of public
road construction projects. Additionally, mediation effect of compliance with public
procurement regulatory framework on project success of public road construction was
determined quantitatively. Notably, mediation effects are emerging in the construction
industry. Accordingly, this thesis contributes to construction management and public
procurement fields by considering a mediating role of compliance with regulatory framework
in implementing public road construction projects.
Robustness of Structural Equation Modeling using partial Least Square in Smart-PLS
established reliable measurement indicators and estimated a combined validated model
including compliance and project success that management should emphasise when
implementing public road construction projects. This dissertation contributes by providing
empirical findings using a combination of statistical tools including; Partial least squares
Structural Equation Modeling in Smart-PLS version 3, Statistical Package for Social Scientists
version 24 and Sobel test in Med-Graph Excel programme version 3. Little is known about
combined use of these statistical tools in one study. Previous studies that explored compliance
and project success models sequentially used either correlations or regressions in SPSS.
Comparatively, this dissertation applied combined software applications to estimate
compliance model, project success model and determined mediation effects in an extended
model.
8.5 Knowledge Contribution
In this section, the dissertation presents contribution to the body of literature under three
main themes including compliance model, project success model and mediation effects. Under
compliance model, this thesis contributes to existing public procurement compliance and
construction management studies generally and particularly in public road construction by
proving that sanctions on staff, perceived inefficiency of public procurement regulatory
188
framework and contractors’ resistance to non-compliance are significant compliance factors
enhancing compliance with public procurement regulatory framework governing public road
construction projects. Thesis findings conform to the two theories emphasising these factors in
achieving compliance with principal’s goals and organizational norms respectively (Van Slyke,
2007, Greenwood and Hinings, 1988). In addition, these findings are in line with Parker’s
holistic compliance model (Krambia-Kapardis, 2019, Parker and Nielsen, 2017)
Under the project success model, this thesis contributes by determining that compliance with
public procurement regulatory frameworks, familiarity with these regulatory frameworks,
monitoring activities on public road construction projects, professionalism of staff concerned
with public road construction projects, and perceived inefficiency of public procurement
regulatory frameworks are significant factors responsible for successful implementation of
public road construction projects. Researchers are encouraged to shift from previously used
project success factors such as time, cost, quality and, safety and consider these new significant
factors in meeting project objectives since little is known about using these factors in the
construction industry internationally. For example, to successfully implement quality
construction projects, monitoring various implementation activities is important (Hussain et al.,
2019, Lapidus and Yves, 2018, Blount et al., 2017). Furthermore, training of staff is important
to enhance familiarity and professionalism by having a competent construction team (Tayeh et
al., 2018). Such training would ensure construction team obtain necessary skills and knowledge
to successfully implement public construction projects (Gambo et al., 2016, Jari and Bhangale,
2013). This is inevitable because successful construction projects rely on successful
performance of the implementation team (Doloi et al., 2011, Shaban, 2008). This notion is
evidenced in UK where continuous professionalism is encouraged leading to a successful
construction industry (Wall and Ahmed, 2008).
Under mediation, the dissertation contributes to construction management and public
procurement research field by uncovering the strong mediating role of compliance with the
public procurement regulatory framework that collectively would help government to
implement public road construction projects successfully. Since no single factor can reliably
lead to attainment of objectives, blending these factors through a hybrid governance system Su
et al. (2018), would enable the government to achieve value for money, increase quality and
quantity of paved roads and saving funds that can be channeled to other priority sectors for
economic development (Tayeh et al., 2018). The findings enrich stakeholders’ understanding
189
of interactive mechanism through a mediating role of compliance with public procurement
regulatory framework and compliance factors in successfully implementing public road
construction projects. Management should note that relying on staff familiarity, monitoring
activities, sanctions and contractors’ resistance alone might not be effective in implementing
public road construction projects successfully. However, simultaneously introducing
compliance with public procurement regulatory framework proves more effective in an
interactive process.
8.6 Practical Contribution
Despite the Public Procurement and Disposal of Public Assets Authority (PPDA)
conducting various procurement reforms, public procurement sensitisation, proposing
sanctions, all aiming at increasing efficiency of regulatory framework, a lack of compliance is
persistent (Agaba and Shipman, 2007). Complex public road construction projects in a dynamic
environment require careful attention to meet their objectives. Eradicating inefficiencies within
a regulatory framework for clear interpretation, effective sanctions enforcement and
empowering contractors to take actions against deviant public officers through an effective and
efficient remedy mechanism, altogether enhance compliance in public road construction
projects. Integrating these factors during public road implementation would stand to increase
the coverage of the quality paved road network. However, influence peddling exemplified by
executive orders by His Excellency the President among others with conflicting opinions and
interests render the regulatory framework ineffective thereby affecting compliance in public
road construction projects. Influence peddling predominantly affects compliance in the
construction industry (Zadawa et al., 2018b, Signor et al., 2017). Such executive orders should
work within a formal framework to identify potential providers and produce good contracts in
complex construction projects with many emergent requirements (Fellows and Liu, 2012).
Political influence accounts for cost overruns in construction projects (Love et al., 2018a).
International literature show that cost overruns in construction projects are not seldom on
procurement irregularities but political interference and government announcing of budgeted
project cost early without detailed analysis are potential factors that could affect
implementation process (Love et al., 2019, Love and Ahiaga-Dagbui, 2018). Early cost
estimations are misleading and count for 25% of the actual project cost (Terrill and Danks,
2016). This is crucial because a number of factors that contribute significantly to contract value
variations challenges construction projects. For example, cost of labour, materials, equipment,
190
interest rates on borrowing, market conditions among others (Love et al., 2019, Adafin et al.,
2015).
Referring to item PR14 of the instrument, senior staff agreed that road implementation teams
lack required knowledge in road implementation and hence suggesting project-based training.
Furthermore, contractor managers should not change road implementation team without
government’s knowledge. It has been a common practice for road contractors to change staff
on particular road construction projects after contract award without government approval
especially by subcontracting. Substandard road construction works are blamed on
inexperienced staff in road construction as reflected by item PR19. For example, contractors
may have 15 years’ experience in road construction but not necessarily in constructing highway
roads. This is attributed to lack of capacity locally, hence depending on foreign work forces
that are costly. Road construction projects are not completed on time due to lack of strict
adherence to contract specifications and bureaucracies as reflected in item PS1 of the
instrument. Such findings are useful to stakeholders by understanding effects of not complying
with project specifications and governing regulatory framework. Understanding consequences
of non-compliance, would in turn help to develop factors for promoting compliance with public
procurement regulatory framework and successfully implement public road construction
projects.
The dissertation has identified key measurement indicators for study variables with high
internal consistency, strong convergent and discriminant validities which provides the
government and future researchers a solid reliable ground to explore set targets. Additionally,
the study exhumed strong blended and interactive effects among significant factors including
compliance, familiarity, monitoring activities, sanctions and contractors’ resistance to
successfully implement public road construction projects. This should be achieved by
simultaneously applying these significant factors as portrayed from mediation effects (Su et
al., 2018). Strong interactive effects are enhanced through established measurement indicators
of compliance including; proper project authorisation, timely project delivery and recording of
project transactions, and achievable project objectives with corresponding measurement
indicators of familiarity, monitoring activities, sanctions and contractors’ resistance that
strongly influence successful project implementation. As noted in literature, over 77% of
Uganda’s national road network is not paved (Uganda National Road Authority, 2018). Given
the findings of this thesis, once government implements them carefully, more national roads
would be paved within ten years. This could be achieved by improving compliance with public
191
procurement regulatory framework and project implementation based on the significant
factors, recommendations provided in this dissertation and increasing awareness about these
factors. This leads to the conclusions and recommendations in chapter nine.
192
CHAPTER NINE CONCLUSIONS AND RECOMMENDATIONS
193
9.1 Introduction Under this chapter, conclusions, recommendations, limitations and areas for further research
are presented. The conclusions are in line with respective study objectives and hypotheses
based on validated results in chapter seven.
9.2 Compliance with Public Procurement Regulatory Framework Hypothesis one: Familiarity with public procurement regulatory framework increases
compliance with public procurement regulatory framework. The results established that
familiarity with public procurement regulatory framework has an insignificant effect on
compliance with public procurement regulatory framework (α = 0.000, t = 0.001, p = 0.999).
Hence, H1 was not supported. The findings imply that simplifying regulatory framework
governing public road construction projects for easy interpretation, using staff who are familiar
with implementation of these projects and employing staff with appropriate academic
qualification to work on applicable road construction projects are not effective in increasing
compliance with public procurement regulatory framework. The results are not consistent with
earlier studies and theory recommendations (Eyaa and Oluka, 2011, Gelderman et al., 2006).
This is because qualified and experienced staff who are familiar with project requirements as
demonstrated by demographic results in chapter six are used to implement Uganda’s public
road construction projects. Indicators used might have not been exhaustive, further
investigation is needed.
Hypothesis two: Monitoring activities on public road construction projects increases
compliance with public procurement regulatory framework. The results established that
monitoring activities on public road construction projects has an insignificant inverse effect on
compliance with public procurement regulatory framework (α = -0.046, t = 0.522, p = 0.601).
Hence, H2 was not supported. This implies that increased frequent inspections to check on
timely recording of project progress, timely project completion and proper storage methods are
not effective in increasing compliance with public procurement regulatory framework. The
findings are in both support of Tabish and Jha (2015), Rutherford et al. (2007), yet contradict
earlier studies as well as theory recommendations (Kauppi and van Raaij, 2015). Given current
investigations in public road construction projects, staff are aware of the consequences of not
complying with the project requirements and regulatory framework. Though all these studies
were in different fields and at different times with varying factors, further studies are
encouraged to establish a firm ground for consistency.
194
Hypothesis three: Professionalism of staff in public road construction projects
increases compliance with public procurement regulatory framework. The findings revealed
that professionalism of staff in public road construction projects has an insignificant inverse
effect on compliance with public procurement regulatory framework (α = -0.102, t = 1.250, p
= 0.211). Hence, H3 was not supported. Measurement indicators of professionalism of staff
consisted of high staff professional integrity, professional judgement during decision-making,
high level of confidentiality, practical experience in road construction and required expertise
in road construction. This implies that these indicators are not effective in increasing
compliance with public procurement regulatory framework because road implementation team
is competent and experienced. This is demonstrated by improvement strategies through
capacity building embraced by respective government agencies (Uganda National Road
Authority, 2018). In addition, the team observes ethical codes enforced by their respective
professional bodies. The findings are in line with previous studies Eyaa and Oluka (2011) while
contradicting other scholars and theory recommendations (DiMaggio and Powell, 2015). While
these studies are in different fields globally and tackle compliance in a limited context, little is
known about professionalism in the construction sector and the results of this thesis suggest
further studies for consistency.
Hypothesis four: Sanctions on staff in public road construction projects increases
compliance with public procurement regulatory framework. The findings proved that sanctions
on staff in public road construction projects have positive significant effect on compliance with
public procurement regulatory framework (α = 0.315, t = 3.540, p = 0.000). Hence, H4 was
supported significantly. Sanctions on staff was measured through imposing penalties on those
found guilty without any warning and implementing sanctions with negative consequences.
This implied that these indicators were effective in increasing compliance with public
procurement regulatory framework. Consequently, the government should emphasise the use
of sanctions in public road construction projects. These findings are consistent with many
previous studies and theory recommendations (Shan et al., 2017, Mwakibinga and Buvik, 2013,
Scott, 2013, Wirick, 2009).
Hypothesis five: Perceived inefficiency of public procurement regulatory framework
reduces compliance with public procurement regulatory framework. The findings found that
perceived inefficiency of public procurement regulatory framework has a significant inverse
effect on compliance with public procurement regulatory framework (α = -0.253, t = 3.052, p
195
= 0.002). Hence, H5 was supported significantly. Perceived inefficiency of public procurement
regulatory framework was measured using three indicators including; banning negotiation
between contractors and public officers during road construction, banning contract extension
beyond agreed schedule and banning underperforming contractors. This implied that if these
indicators were not enforced effectively, compliance with public procurement regulatory
framework would be reduced. Thesis findings are contrary to previous works of Gelderman et
al. (2006) but consistent with theory recommendations (Greenwood and Hinings, 1988).
Whereas Gelderman et al. (2006) explored Netherland’s public procurement compliance with
EU Directives using this factor, it was not about compliance in road construction subsector.
Furthermore, this factor is new and need further exploration in various sectors to determine its
consistence.
Hypothesis six: Contractors’ resistance to non-compliance with public procurement
regulatory framework by public officers increases compliance with public procurement
regulatory framework. The findings revealed that contractors’ resistance to non-compliance
has a positive significant effect on compliance with public procurement regulatory framework
(α = 0.135, t = 2.002, p = 0.045). Hence, H6 was supported significantly. Two indicators
strongly measured contractors’ resistance and they included; contractors’ readiness to take
action against bad decisions and contractors’ knowledge on public road procurement process.
This implied that contractors’ knowledge on public road procurement process and encouraging
them to take action against defiant public officers were effective in increasing compliance with
public procurement regulatory framework. These findings contradict the two previous studies
covering compliance with European Union (EU) Directives among EU member states
(Gelderman et al., 2010, Gelderman et al., 2006). However, the findings are supported by
theory recommendations encouraging contractors’ empowerment to ensure compliance in
public procurement (Greenwood and Hinings, 1996). As an emerging factor in determining
compliance, further investigations are recommended globally and across different fields using
this factor to cement current findings.
9.3 Public Road Construction Project Success Hypothesis seven: Compliance with public procurement regulatory framework in
public road construction projects leads to project success. The findings showed that compliance
with public procurement regulatory framework in public road construction projects has a
positive significant effect on the success of these projects (α = 0.147, t = 1.957, p = 0.050).
Hence, H7 was supported significantly. Compliance with public procurement regulatory
196
framework was measured using; Proper authorisation of road construction projects, timely
delivery of road construction projects, timely recording of road construction transactions and
achievable road construction objectives. While success of public road construction projects
was measured using; road construction projects are implemented in accordance with
specifications, road construction projects are completed within schedule and road construction
projects are completed within budget. Implying that emphasising these indicators, would
ensure successful implementation of public road construction projects and meeting government
objectives. The findings are supported by previous recommendations requiring strengthening
of the regulatory framework and adhering to it for successful project implementation (Zadawa
et al., 2018a, Shan et al., 2017, Tabish and Jha, 2011, Obanda, 2010, Lisa, 2010). Despite
compliance studies emerging in the construction industry, few studies indirectly mentioned
road construction subsector. This calls for further investigations to concretise current findings.
Hypothesis eight: Familiarity with public procurement regulatory framework
governing public road construction projects leads to project success. The findings show that
familiarity with public procurement regulatory framework governing public road construction
projects has a positive significant effect on the success of these projects (α = 0.140, t = 2.231,
p = 0.026). Hence, H8 was supported significantly. Implying that simplifying regulatory
framework governing public road construction projects for easy interpretation, using staff who
are familiar with implementation of these projects and employing staff with appropriate
academic qualification to work on applicable road construction projects effectively leads to
successful implementation of public road construction projects. These findings correspond to
previous studies and institutional theory advocating for staff familiarity to enhance project
success (Tabish and Jha, 2015, Mahmood, 2010, North, 1993). This emerging project success
factor requires further investigation to establish consistency with current findings.
Hypothesis nine: Monitoring activities on public road construction projects leads to
project success. The findings showed that monitoring activities on public road construction
projects has a positive significant effect on the success of these projects (α = 0.314, t = 4.875,
p = 0.000). Hence, H9 was supported significantly. This implies that increased frequent
inspections to check on timely recording of project progress, timely project completion and
proper storage methods effectively measured monitoring activities leads to successful
implementation of public road construction projects. The findings are in conformance with
previous studies and theories emphasising effective monitoring of project activities to realise
197
goals (North, 2016, Love et al., 2016b, DiMaggio and Powell, 2015, Van Slyke, 2007).
Management should enforce monitoring of road construction projects and further testing of this
factor in construction industry is paramount.
Hypothesis ten: Professionalism of staff in public road construction projects leads to
project success. The findings show that professionalism of staff has a positive significant effect
on the success of public road construction projects (α = 0.305, t = 4.695, p = 0.000). Hence,
H10 was supported significantly, implying that high staff professional integrity, professional
judgement during decision-making, high level of confidentiality, employing practically
experienced road construction staff with required expertise strongly measured professionalism
leading to successful implementation of public road construction projects. While little is known
about the effect of professionalism in promoting project success, limited studies and theories
encourage staff competence and expertise in project implementation (Tayeh et al., 2018,
Walker and Lloyd-Walker, 2015, DiMaggio and Powell, 2015, Kalinzi, 2014, Wall and
Ahmed, 2008, Alinaitwe et al., 2007). This compels researchers to roll the ball forward by
expanding current dissertation findings to greater heights for concrete recommendations.
Hypothesis eleven: Perceived inefficiency of public procurement regulatory
framework reduces project success. The findings have proved that perceived inefficiency of
public procurement regulatory framework has a significant inverse effect on the success of
public road construction projects (α = -0.135, t = 2.099, p = 0.036). Hence, H11 was supported
significantly. This implied that banning negotiation between contractors and public officers
during road construction, banning contract extension beyond agreed period and banning of
underperforming contractors if not enforced effectively, successful implementation of public
road construction projects will be reduced. The findings conform to recommendations
encouraging an efficient regulatory framework in managing project implementation (Shan et
al., 2017, Zhang et al., 2016, Tabish and Jha, 2015, Tabish and Jha, 2011, Oliver, 1991). Since
this is an emerging factor in public procurement and construction industry, further research
using this factor is encouraged to cement current findings.
Hypothesis twelve: Contractors’ resistance to non-compliance with public
procurement regulatory framework leads to project success. The findings revealed that
contractors’ resistance to non-compliance has a positive insignificant effect on the success of
public road construction projects (α = 0.121, t = 1.792, p = 0.073). Hence, H12 was supported
but statistically insignificant. Implying that contractors’ knowledge on public road
198
procurement process and encouraging them to take action against defiant public officers
measured contractors’ resistance effectively to predict successful implementation of public
road construction projects. However, the predictive effect is not significant at 5% significance
level. Despite the findings corresponding to scanty studies exploring compliance with EU
procurement directives (Gelderman et al., 2010), this factor is new in public procurement and
construction industry. Hence, further investigation is needed to build strong ground for its
application.
Hypothesis thirteen: Sanctions on staff in public road construction projects leads to
project success. The findings show that sanctions on staff in public road construction projects
has an inverse insignificant effect on the success of public road construction projects (α = -
0.059, t = 0.856, p = 0.392). Hence, H13 was not supported. This implied that imposing
sanctions in the form of penalties on staff were not effective in implementing public road
construction projects successfully. This is attributed to massive investigation by judicial arms
ordered by Ugandan Parliament (Red Pepper, 21st October 2016). Whereas sanctions on staff
on public road construction projects were effective in achieving compliance with public
procurement regulatory framework (see section 7.2.4) Mwakibinga and Buvik (2013), they
contradict limited studies and theories recommending use of sanctions to successfully
implement construction projects (Kakitahi et al., 2016, Hartley, 2009, Sohail and Cavill, 2008,
Saam, 2007). Further investigation is recommended to establish consistency of these findings.
9.4 Mediational effects Hypothesis fourteen: Compliance with public procurement regulatory framework
mediates the relationship between familiarity with public procurement regulatory framework
and project success. The findings proved that compliance with public procurement regulatory
framework partially mediated the relationship between familiarity with public procurement
regulatory framework and project success (Sobel z-value = 2.204, p = 0.027). Hence, H14 was
significantly supported. Implying that successful implementation of public road construction
projects is realised when both familiarity with public procurement regulatory framework and
compliance with public procurement regulatory framework governing these projects are
applied simultaneously (Su et al., 2018, Andrevski et al., 2014). Combining these two factors
provided a good interactive effect on the success of public road construction projects.
Hypothesis fifteen: Compliance with public procurement regulatory framework
mediates the relationship between monitoring activities on public road construction projects
199
and project success. The findings have established that compliance with public procurement
regulatory framework partially mediated the relationship between monitoring activities on
public road construction projects and project success (Sobel z-value = 2.000, p = 0.045). Hence,
H15 was significantly supported. This proves that successful implementation of public road
construction projects is achieved when both monitoring activities and compliance with public
procurement regulatory framework governing these projects are enforced simultaneously
(Tabish and Jha, 2015, Jha and Misra, 2007).
Hypothesis sixteen: Compliance with public procurement regulatory framework
mediates the relationship between professionalism of staff in public road construction projects
and project success. The findings show that compliance with public procurement regulatory
framework insignificantly mediated the relationship between professionalism of staff in public
road construction projects and project success (Sobel z-value = 1.935, p = 0.0530). Hence, H16
was not supported. This implies that successful implementation of public road construction
projects is realised when both professionalism among staff on public road construction projects
and compliance with public procurement regulatory framework governing these projects are
applied sequentially (Tabish and Jha, 2015, Deng et al., 2014). Despite insignificant partial
mediation, combining these two factors displayed a fair interactive effect on success of public
road construction as demonstrated by the z-value and p-value that are close to cut-off points.
Hypothesis seventeen: Compliance with public procurement regulatory framework
mediates the relationship between sanctions on staff in public road construction projects and
project success. The findings have proved that compliance with public procurement regulatory
framework partially mediated the relationship between sanctions on staff in public road
construction projects and project success (Sobel z-value = 2.388, p = 0.017). Hence, H17 was
significantly supported. Implying that successful implementation of public road construction
projects is realised when both sanctions on staff in public road construction projects and
compliance with public procurement regulatory framework governing these projects are
simultaneously applied (Zadawa et al., 2018b, Shu Hui et al., 2011). These two factors have
displayed a good interactive effect on the success of public road construction projects through
their respective indicators.
Hypothesis eighteen: Compliance with public procurement regulatory framework
mediates the relationship between perceived inefficiency of public procurement regulatory
framework and project success. The findings revealed that compliance with public procurement
200
regulatory framework does not mediate the relationship between perceived inefficiency of
public procurement regulatory framework and project success. Hence, H18 was not supported.
Whereas compliance with public procurement regulatory framework and perceived
inefficiency of public procurement regulatory framework predicted public road construction
project success when applied separately, there is a poor interactive effect between these factors
through their respective indicators. Hence, sequential application of these factors is preferred
rather than applying them simultaneously.
Hypothesis nineteen: Compliance with public procurement regulatory framework
mediates the relationship between contractors’ resistance to non-compliance with public
procurement regulatory framework by public officers and project success. The findings show
that compliance with public procurement regulatory framework partially mediated the
relationship between contractors’ resistance to non-compliance with public procurement
regulatory framework and project success (Sobel z-value = 2.410, p = 0.016). Hence, H19 was
significantly supported. Thus, successful implementation of public road construction projects
is realised when both contractors’ resistance to non-compliance with public procurement
regulatory framework and compliance with public procurement regulatory framework
governing these projects are applied simultaneously (Shu Hui et al., 2011, Gelderman et al.,
2010).
9.5 Recommendations
This section presents recommendations in line with respective study objectives and
hypotheses based on discussion of results in chapter seven.
Whereas there are limited studies on perceived inefficiency of public procurement
regulatory framework in achieving compliance, this dissertation discovered that it is effective
in reducing non-compliance in public road construction projects. It is recommended that the
government should stick to banning negotiations during project implementation, banning
contract extension beyond agreed schedule and banning underperforming contractors. These
indicators would ensure a clear and efficient public procurement regulatory framework capable
of enforcing compliance with public procurement regulatory framework, successful
implementation of public road construction projects and meeting government goals. A vibrant
public procurement regulatory framework is necessary for complex public road construction
projects to meet government objectives. This would ensure eradicating loopholes within
regulatory framework and achieve value for money. The government should come up with
201
clear policies and procedures operating these projects to avoid confusing public road
implementation team.
Furthermore, there are limited studies on contractors’ resistance in achieving
compliance, this dissertation discovered effectiveness of contractors’ contribution to this effect.
The government should empower contractors by increasing their knowledge over the public
procurement regulatory framework and encouraging them to take action against bad decisions
from public officers during project implementation. These were basic indicators measuring
contractors’ resistance to non-compliance with public procurement regulatory framework
governing public road construction projects and are effective to meet government objectives.
Empowering contractors would ensure successful implementation of public road construction
projects because they are competent and experienced in implementing these projects. However,
government should strengthen regulatory framework with well-outlined remedial mechanisms
to protect contractors from retaliation of public officers. An effective remedy mechanism
would encourage contractors to resist bad decisions from public officers without fear. This is
important since public officers manage the whole procurement process that makes them
powerful and can victimise contractors in awarding future contracts.
Management should redesign an effective sanctions enforcement mechanism including
penalising those found guilty without any warning, implementing sanctions in secret and
imposing sanctions with negative consequences. These key indicators measuring sanctions
would form effective sanctions that increase fear among staff implementing public road
construction projects leading to compliance with public procurement regulatory framework and
successful implementation of public road construction projects. Punitive sanctions like contract
termination, suspension, confiscation of property and none payments are widely applied. For
example, in the US, UK and Australia among others to achieve compliance and once the legal
fraternity is strengthened, value for money will be attained (Wirick, 2009). Furthermore, strict
penalties are inevitable for the construction sector (Zadawa et al., 2018b, Gambo et al., 2016).
Regular transfers and rotation of staff is recommended in curbing unethical behaviours since
holding one position for long time allow officers to create links. This is an indirect sanctioning
measure to eradicate collusion associated with over staying in one position or workstation.
Additional punitive measures may include but are not limited to; demotion, long time prison
sentencing, confiscating property of those found guilty and introducing attractive rewarding
schemes for outperforming staff.
202
The government should embark on improving staff familiarity with public procurement
regulatory framework governing public road construction projects since it has a positive impact
in implementing these projects successfully. Strengthening and clarity of the public
procurement regulatory framework should be enforced to avoid loopholes that are manipulated
by unethical public road stakeholders especially on contract variation during project
implementation. The public procurement regulatory framework governing road construction
projects should be written in a nonprofessional language that can easily be interpreted by
stakeholders involved. Management should encourage qualified and competent staff in public
road implementation. This would be through a transparent and merit-based selection criterion
requiring formal academic qualifications and experienced competent team. These indicators
strongly represent staff familiarity in implementing public road construction projects
successfully. Because public road construction projects are complicated, multidimensional
skills are required to cope with ever changing project needs in the dynamic environment.
Careful selection of the team based on their capabilities would lead to successful
implementation of public road construction projects.
Management should proactively monitor public road construction projects to determine if
project activities are in line with government objectives. Monitoring project activities ensures
successful implementation of public road construction projects. Effective monitoring of public
road construction projects further ensures that set targets are met and eliminating cost and time
overruns which are common in the construction industry. Effective monitoring should
emphasise strong measurement indicators including; timely recording of public road
construction progress, frequent inspections to ensure timely completion of these projects and
proper storage methods to avoid damage and stealing of public road construction materials.
Furthermore, multi-agency monitoring of project activities is vital in enforcing successful
project implementation. However, management should set up a clear description of the roles
of each agency and scope to avoid clashes and confusion that hamper successful
implementation of public road construction projects. Additionally, involving and empowering
the civil society in monitoring public road construction projects is encouraged. Involving civil
society would help in ensuring that public road construction projects are implemented
according to project specifications. Whereas the Whistle-blowers Act encourages this,
literature shows that the civil society is not empowered and protected from powerful unethical
fraudsters who can do anything to the lives of those daring to report them.
203
Management need to embrace continuous professionalism of public sector procurement
covering public road construction projects. Continuously investing in staff professionalism is
embraced by the UK construction industry (Wall and Ahmed, 2008). Professionalism should
be in harmony with international standards. Professionalism in public road construction
projects should be enforced by ensuring high staff professional integrity, confidentiality,
professional judgement in decision-making during construction process and engaging staff who
are practically experienced with required expertise. Emphasising these indicators and investing
in staff competence through skill-needs assessment and project-based training would ensure
professionalism of staff in public road construction projects. Additionally, enforcing
professionalism can be achieved through bodies including; Institute of Procurement
Professionals of Uganda (IPPU) and Uganda Institute of Professional Engineers (UIPE) by
fully empowering them to enforce respective standards in public procurement and construction
sectors.
Complying with the public procurement regulatory framework is encouraged to ensure
successful implementation of public road construction projects. Management should rely on
compliance measurement indicators including; proper authorisation of road construction
projects, timely delivery of road construction projects, timely recording of road construction
transaction and achievable road construction objectives. Emphasising these indicators would
ensure that public road construction projects are implemented according to project
specifications, completed within time and budget as indicators of project success. Once
compliance with public procurement regulatory framework is effectively enforced in
implementing public road construction projects, the government would save significant funds
and achieve value for money by building quality durable roads. Saved funds could be
channelled to other priority sectors for example; modernisation of agriculture, poverty
eradication and increasing paved road network countrywide especially to rural agricultural
areas to beef up marketing of agricultural products.
Finally, for the government to successfully implement public road construction projects,
mediating role of compliance with the public procurement regulatory framework should be
considered. Management should consider mediation effects sequentially involving familiarity
with public procurement regulatory framework, monitoring activities on public road
construction projects, sanctions on staff involved in these projects and contractors’ resistance
through compliance with public procurement regulatory framework. A combination of these
factors demonstrated good interactive effects in successful implementation of public road
204
construction projects. Applying compliance with one of these factors simultaneously would
ensure that public road construction projects are implemented in accordance with project
specifications, completed in time and within budget. This demonstrates successful
implementation of public road construction projects. Furthermore, mediation effect involving
professionalism of staff in public road construction projects and compliance with public
procurement regulatory framework should not be ignored since its scored significance level of
0.05 is at the border mark showing good effective size measures of both direct and indirect
relationship that are predictively relevant.
9.6 Limitations
Like any academic research endeavour, this dissertation acknowledges a number of
limitations. Public procurement is broad since it includes procurement of works, supplies and
services. With works, public procurement of works is not only broad but also complex. Because
of these factors, the thesis was limited to implementation stage of public road construction
projects. Under this level, the dissertation was concerned with compliance and project
implementation issues affecting successful implementation of public road construction
projects. Specifically, the thesis focused on national road construction projects and left out
local governments’ roads including districts and urban roads. Under national roads category,
the thesis considered responses from five organisations that it believed had necessary
information. Despite the UNRA’s voluntary refusal to participate in this study, other
organisations were left out that are indirectly involved in public road construction activities.
For example; Ministry of Finance Economic Planning and Development (MoFEP&D),
Inspector General of Government (IGG), Attorney General (AG), President’s office and the
public. This move was considered to meet time constraint placed on PhD studies. Accordingly,
generalising dissertation results are limited to national road construction projects since not all
factors affecting implementation of national road construction projects are applicable to local
government roads. Furthermore, given that the sample was drawn from Uganda, dissertation
results should be consciously applied beyond Uganda’s public road construction subsector in
general and particularly beyond national roads. However, since sample size determination
criteria following a ten time’s thumb rule required by PLS-SEM was satisfactory, statistical
generalisation of this results is allowed (Hussain et al., 2019). In addition, given high
standardisation of construction projects globally, there is little difference in factors influencing
successful implementation of these projects (Hussain et al., 2019). Accordingly, with
interesting findings and good lessons for construction industry stakeholders, some level of
205
generalisation is inevitable but full generalisation would not be allowed (Papadonikolaki,
2018). In addition, selection of participants as a unit of inquiry was limited to particular
departments and not entire organisations. This was another limitation since the study could
have missed important information from other departments.
Another limitation was lack of empirical literature on public road construction projects in
Uganda. This affected study examples and the thesis majorly relied on international literature
from nations including Australia, United Kingdom (UK) and United States of America (USA).
Since there is substantial difference in each country’s jurisdiction, with varying problem
causes, examples used could have a different impact on compliance with the public
procurement regulatory framework and successful implementation of public road construction
projects. Additionally, the study emphasised government agencies in road construction and
paid little attention to private sector that could have had relevant information. Despite including
private contractors, their representation to private sector was insufficient. There were
challenges in accessing premises and respondents failing to complete questionnaires because
they were suspicious about the use of data provided. However, assurance was given by stating
that the study was purely academic and identification of participants was purely anonymous.
Furthermore, the research permit from the University of Newcastle’s human research ethics
committee was used to seek permission and reassure participants. This resulted in a 64.9%
response rate with relevant data ensuring the study success.
Furthermore, limited mediation studies and examples in public road construction subsector
affected this study to comprehensively investigate and compare mediation results. With
dynamic road construction projects, expanding mediating role of compliance with regulatory
framework is important to compare these findings. Limited resources affected this study. For
example, time and financial constraints involving transport cost, follow up phone calls,
repeated visits and some respondents and road construction projects were far upcountry.
However, the deadline for data collection was set and obeyed to work within the given
timeframe. Accordingly, researchers tried to minimise cost and work within budget while
maintaining the goal of achieving target response rate. Finally, the thesis adopted a cross-
sectional research design that limits responses to one point in time compared to longitudinal
studies. Further research considering a longitudinal design is important after completing PhD
that would form part of research publications.
206
9.7 Further Research
Based on the study limitations in this thesis, doors are now open for future research. The
current public procurement regulatory compliance and project success models have been
developed and tested for future use. However, factors used here are not exhaustive. This
requires scholars to investigate further to bring on board other factors for comprehensive
compliance and project success models. Whereas these models included six compliance and
seven project success factors respectively, it appears these are the first of their kind. Hence, for
consistency and reliability, using these factors in other sectors would concretise their
application. Furthermore, results from the thesis show that some factors are significant while
others are not and with contradictions from earlier studies, there is need to establish this
inconsistency through conducting similar research using insignificant compliance and project
success factors to determine consistency and concretise these findings.
Mediation studies are emerging in the construction industry compared to other sectors.
Coupled with limited compliance studies, there is need to carry out mediation studies in the
construction sector generally and public road construction subsector particularly using similar
factors as well as introducing new factors. Expanding mediation studies should not only be
industry based but global geographical consideration is paramount. By extending mediation
studies, researchers would ably establish interaction effects in the construction industry based
on compliance with the public procurement regulatory framework, success of public road
construction projects and beyond. Such studies would appreciate and cement usefulness of
mediation effects.
9.8 Conclusion The thesis presented study background, theoretical foundation, literature review, research
methodology, results, discussions and ended with areas for future research. The thesis explored
issues surrounding compliance with the public procurement regulatory framework, public road
construction project success and the mediating role of compliance with public procurement
regulatory framework between compliance factors and the success of public road construction
projects. This thesis study was motivated by numerous reports revealing lack of compliance in
Uganda’s public road construction subsector. In addition, limited studies if any have been
undertaken to determine factors responsible for successful implementation of public road
construction projects. Three validated models (Compliance, Project Success and Mediation)
are established to guide in implementing public road construction projects. Implementing
public road construction projects following these models would enable government to meet its
207
objectives, save significant funds and increase the paved road network nationwide. Saved funds
could be channelled to other priority sectors to steer economic development and eradicate
poverty.
It is established that because of the complexity of public road construction projects with
huge budget allocations, unethical issues arose affecting successful implementation of public
road construction projects, thus failing government objectives. The dissertation established that
key factors including sanctions on staff, perceived inefficiency of public procurement
regulatory framework and contractors’ resistance to non-compliance significantly enhanced
compliance with public procurement regulatory framework. While compliance with public
procurement regulatory framework, familiarity with public procurement regulatory framework,
monitoring activities on public road construction projects, professionalism of staff involved in
public road construction projects and perceived inefficiency of public procurement regulatory
framework significantly enhanced successful implementation of public road construction
projects. Furthermore, compliance with public procurement regulatory framework is a key
mediating factor between familiarity with public procurement regulatory framework,
monitoring activities on public road construction projects, sanctions on staff, and contractors’
resistance and success of public road construction projects. This informs the government and
management on the importance of strengthening and enforcing compliance with the regulatory
framework to ensure successful implementation of public construction projects.
The research question “What factors affect compliance in performance of public road
construction projects”, together with the dissertation objectives and hypotheses, enabled this
work to traverse through factors responsible for compliance with the public procurement
regulatory framework and successful implementation of these projects. The thesis dug out
significant and insignificant compliance and project success factors as well as the mediating
effects responsible for successful implementation of public road construction projects to make
recommendations. Whereas previous studies attempted to establish success factors for the
construction industry, scholars only concentrated on direct factors influencing success of
construction projects. This thesis went a step beyond to establish an interactive effect among
success factors by considering a mediating role of compliance with regulatory framework in
implementing public road construction projects. These mediation effects have proved effective.
Hence, suggesting future scholars to shift from predicting direct relationships among factors
but to consider mediation in finding possible solutions on challenges facing public procurement
and construction sectors. Several recommendations are drawn based on significant results.
208
Once these recommendations are carefully implemented, the government would be able to
achieve its objectives in the interest of public community. These recommendations are in line
with reports demanding an effective procurement of transport construction projects to sustain
a competitive advantage and economic growth (Love et al., 2019, Sinesilassie et al., 2019).
209
REFERENCES AAKER, D. A., KUMAR, V. & DAY, G. S. 2008. Marketing research, John Wiley & Sons. ABDUH, M., WIRAHADIKUSUMAH, R. D. & MESSAH, Y. Framework Development
Methodology for Sustainable Procurement of Construction Works in Indonesia. MATEC Web of Conferences, 2018. EDP Sciences, 02014.
ABDUL-RAHMAN, H. 1995. The cost of non-conformance during a highway project: a case study. Construction Management and Economics, 13, 23-32.
ABDULLAHI, N., HUSSIN, A. & OSMADI, A. 2017. Mediation Effects Of Innovative Procurement Practices Between The Determinants Of Non-compliance With Public Procurement Guidelines And Construction Project Cost Performance In The Nigerian Construction Industry. WIT Transactions on Ecology and the Environment, 210, 99-109.
ADAFIN, J., ROTIMI, J. O. & WILKINSON, S. 2015. Why do the design stage elemental cost plan and final tender sum differ in New Zealand? Journal of financial Management of property and construction, 20, 116-131.
ADUSEI, C. & AWUNYO-VITOR, D. 2015. Implementation Challenges of the Public Procurement Act by Selected Metropolitan, Municipal and District Assemblies in the Ashanti Region, Ghana. iBusiness, 7, 39.
AGABA, E. & SHIPMAN, N. 2007. Public procurement reform in developing countries: The Ugandan experience. Advancing Public Procurement: Practices, Innovation and Knowledge-Sharing, 373-391.
AGUINIS, H., EDWARDS, J. R. & BRADLEY, K. J. 2017. Improving our understanding of moderation and mediation in strategic management research. Organizational Research Methods, 20, 665-685.
AKECH, J. 2004. Development partners and governance of public procurement in Kenya: enhancing democracy in the administration of aid. NYUJ Int'l. L. & Pol., 37, 829.
ALI, F., RASOOLIMANESH, S. M., SARSTEDT, M., RINGLE, C. M. & RYU, K. 2018a. An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30, 514-538.
ALI, Z., ZHU, F. & HUSSAIN, S. 2018b. Risk Assessment of Ex-Post Transaction Cost in Construction Projects Using Structural Equation Modeling. Sustainability, 10, 4017.
ALINAITWE, APOLOT, R. & TINDIWENSI, D. 2013. Investigation into the causes of delays and cost overruns in Uganda's public sector construction projects. Journal of Construction in Developing Countries, 18, 33.
ALINAITWE, MWAKALI, J. A. & HANSSON, B. 2007. Factors affecting the productivity of building craftsmen‐studies of Uganda. Journal of Civil Engineering and Management, 13, 169-176.
ALMARRI, K., ALZAHRANI, S. & BOUSSABAINE, H. 2019. An evaluation of the impact of risk cost on risk allocation in public private partnership projects. Engineering, Construction and Architectural Management.
AMANN, E., BAER, W., TREBAT, T. & LORA, J. V. 2016. Infrastructure and its role in Brazil's development process. The Quarterly Review of Economics and Finance, 62, 66-73.
AMEYAW, C., MENSAH, S. & OSEI-TUTU, E. 2012. Public procurement in Ghana: the implementation challenges to the public procurement law 2003 (Act 663). International Journal of Construction Supply Chain Management, 2, 55-65.
210
AMEYAW, E. E., PÄRN, E., CHAN, A. P., OWUSU-MANU, D.-G., EDWARDS, D. J. & DARKO, A. 2017. Corrupt practices in the construction industry: Survey of Ghanaian experience. Journal of Management in Engineering, 33, 05017006.
ANDREVSKI, G., RICHARD, O. C., SHAW, J. D. & FERRIER, W. J. 2014. Racial diversity and firm performance: The mediating role of competitive intensity. Journal of Management, 40, 820-844.
ANVUUR, A., KUMARASWAMY, M. & MALE, S. Taking forward public procurement reforms in Ghana. 2006. CIB.
APPELT, S. & GALINDO-RUEDA, F. 2016. Measuring the link between public procurement and innovation.
ARGOTE, L. & INGRAM, P. 2000. Knowledge transfer: A basis for competitive advantage in firms. Organizational behavior and human decision processes, 82, 150-169.
ARROWSMITH, S. 1998. National and international perspectives on the regulation of public procurement: harmony or conflict? Public procurement: global revolution, 3.
ATKINSON, R. 1999. Project management: cost, time and quality, two best guesses and a phenomenon, its time to accept other success criteria. International journal of project management, 17, 337-342.
ATTARAN, M. & ATTARAN, S. 2002. Catch the wave of e-procurement. Industrial Management-Chicago Then Atlanta-, 16-21.
AUSTRALIAN PROCUREMENT & CONSTRUCTION COUNCIL 2002. Procurement Guide. Australia: Australian Procurement & Construction Council.
AUSTRALIAN PROCUREMENT & CONSTRUCTION COUNCIL 2013. Procurement of construction products A guide to achieving compliance. Australia: Australian Procurement & Construction Council.
BABALOLA, M. T., STOUTEN, J., EUWEMA, M. C. & OVADJE, F. 2016. The relation between ethical leadership and workplace conflicts: The mediating role of employee resolution efficacy. Journal of Management, 0149206316638163.
BABBIE, E. 2015. The practice of social research, Nelson Education. BAGOZZI, R. P. & YI, Y. 1988. On the evaluation of structural equation models. Journal of
the academy of marketing science, 16, 74-94. BARON, R. M. & KENNY, D. A. 1986. The moderator–mediator variable distinction in social
psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology, 51, 1173.
BARRATT, H. & KIRWAN, M. 2009. Confounding, interactions, methods for assessment of effect modification. HealthKnowledge.
BARTLE, J. R. & KOROSEC, R. L. 2003. A review of state procurement and contracting. Journal of Public Procurement, 3, 192.
BASHEKA & BISANGABASAIJA, E. 2010. Determinants of unethical public procurement in local government systems of Uganda: A case study. International Journal of Procurement Management, 3, 91-104.
BASHEKA & MUGABIRA, M. I. Measuring professionalism variables and their implication to procurement outcomes in Uganda. The 3rd International Public Procurement Conference Proceedings, 2008.
BASHEKA, OLUKA, P. N. & MUGURUSI, G. 2012. Adopting new approaches for public procurement efficiency: Critical success factors (CSFs) for the implementation of e-procurement in Uganda's public sector. International Journal of Procurement Management, 5, 712-732.
BECKER, K. F. 2004. The informal economy: Fact finding study, Sida. BECKER, S., BRYMAN, A. & FERGUSON, H. 2012. Understanding research for social
policy and social work: themes, methods and approaches, Policy Press.
211
BELTRÁN-MARTÍN, I., ROCA-PUIG, V., ESCRIG-TENA, A. & BOU-LLUSAR, J. C. 2008. Human resource flexibility as a mediating variable between high performance work systems and performance. Journal of Management, 34, 1009-1044.
BLOUNT, C., BENNETT, R. & SMITH, M. L. 2017. Managing sensitive habitats adjacent to the Port Botany expansion. Australasian Coasts & Ports 2017: Working with Nature, 123.
BOER, MATTHIAS, MARTIN , M. P. & ROGER , C. V. 2014. Making a meaningful contribution to theory Harry Boer Matthias Holweg Martin Kilduff Mark Pagell Roger Schmenner Chris Voss. Management, 35, 1231-1252.
BOER & TELGEN, J. 1998. Purchasing practice in Dutch municipalities. International Journal of Purchasing and Materials Management, 34, 31-36.
BOGIATZIS, A., ASADA, H. & RAHUMAN, M. R. H. 2018. Sustainable finance for inclusive growth in Thailand.
BOLIN, J. H. 2014. Hayes, Andrew F.(2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression‐Based Approach. New York, NY: The Guilford Press. Journal of Educational Measurement, 51, 335-337.
BONTIS, N., BOOKER, L. D. & SERENKO, A. 2007. The mediating effect of organizational reputation on customer loyalty and service recommendation in the banking industry. Management decision, 45, 1426-1445.
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, 885-901.
BRAMMER, S., JACKSON, G. & MATTEN, D. 2012. Corporate social responsibility and institutional theory: New perspectives on private governance. Socio-economic review, 10, 3-28.
BRAUN, P. 2003. Strict compliance versus commercial reality: the practical application of EC public procurement law to the UK's Private Finance Initiative. European Law Journal, 9, 575-598.
BREAUX, D. M., MUNYON, T. P., HOCHWARTER, W. A. & FERRIS, G. R. 2009. Politics as a moderator of the accountability—job satisfaction relationship: Evidence across three studies. Journal of Management, 35, 307-326.
BROWN, J. & LOOSEMORE, M. 2015. Behavioural factors influencing corrupt action in the Australian construction industry. Engineering, Construction and Architectural Management, 22, 372-389.
BROWN, T. L. & POTOSKI, M. 2003. Managing contract performance: A transaction costs approach. Journal of Policy analysis and Management, 22, 275-297.
BROWNE, M. W. & CUDECK, R. 1989. Single sample cross-validation indices for covariance structures. Multivariate Behavioral Research, 24, 445-455.
BRUTON, G. D., AHLSTROM, D. & LI, H. L. 2010. Institutional theory and entrepreneurship: where are we now and where do we need to move in the future? Entrepreneurship theory and practice, 34, 421-440.
BRYMAN 2004. Qualitative research on leadership: A critical but appreciative review. The Leadership Quarterly, 15, 729-769.
BRYMAN & BELL, E. 2007. Business research strategies. Business research methods. BRYMAN & BELL, E. 2011. Business research methods. 3 uppl. Malmö: Liber AB. BRYMAN & CRAMER, D. 1997. Concepts and their measurement. Quantitative data
analysis, with SPSS for Windows. CARR, A. S. & SMELTZER, L. R. 2000. An empirical study of the relationships among
purchasing skills and strategic purchasing, financial performance, and supplier responsiveness. Journal of Supply Chain Management, 36, 40.
212
CARR, I. & SUNDARAM, J. 2016. International Trade Law Statutes and Conventions 2016-2018, Routledge.
CARRIÓN, G. C., NITZL, C. & ROLDÁN, J. L. 2017. Mediation analyses in partial least squares structural equation modeling: guidelines and empirical examples. Partial Least Squares Path Modeling. Springer.
CHAN & CHAN, A. P. 2004. Key performance indicators for measuring construction success. Benchmarking: an international journal, 11, 203-221.
CHAN, A. P. & OWUSU, E. K. 2017. Corruption forms in the construction industry: Literature review. Journal of Construction Engineering and Management, 143, 04017057.
CHAN, A. P., SCOTT, D. & LAM, E. W. 2002. Framework of success criteria for design/build projects. Journal of management in engineering, 18, 120-128.
CHAN, A. P. C., DARKO, A., OLANIPEKUN, A. O. & AMEYAW, E. E. 2018. Critical barriers to green building technologies adoption in developing countries: The case of Ghana. Journal of cleaner production, 172, 1067-1079.
CHANDRAN 2004. Research methods: A quantitative approach with illustrations from Christian ministries, Daystar University.
CHANDRAN, MUN, J., CHOI, K., CHEN, J., HAMILTON, A., NAGARAJ, A. & MCPHERSON, D. 2003. A method for in-vivo analysis for regional arterial wall material property alterations with atherosclerosis: preliminary results. Medical engineering & physics, 25, 289-298.
CHEAH, J.-H., SARSTEDT, M., RINGLE, C. M., RAMAYAH, T. & TING, H. 2018. Convergent validity assessment of formatively measured constructs in PLS-SEM: on using single-item versus multi-item measures in redundancy analyses. International Journal of Contemporary Hospitality Management, 30, 3192-3210.
CHEN, C. W. & SO, M. K. 2006. On a threshold heteroscedastic model. International Journal of Forecasting, 22, 73-89.
CHENG, W., APPOLLONI, A., D'AMATO, A. & ZHU, Q. 2018. Green Public Procurement, missing concepts and future trends–A critical review. Journal of cleaner production, 176, 770-784.
CHEUNG, G. W. & LAU, R. S. 2008. Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11, 296-325.
CHI, C. S. & NICOLE JAVERNICK‐WILL, A. 2011. Institutional effects on project arrangement: high‐speed rail projects in China and Taiwan. Construction Management and Economics, 29, 595-611.
CHIAPPORI, P.-A. & SALANIÉ, B. 2002. Testing contract theory: A survey of some recent work.
CHILESHE, N., RAMEEZDEEN, R., HOSSEINI, M. R., MARTEK, I., LI, H. X. & PANJEHBASHI-AGHDAM, P. 2018. Factors driving the implementation of reverse logistics: A quantified model for the construction industry. Waste management, 79, 48-57.
CHIN, W. W. 1998. The partial least squares approach to structural equation modeling. Modern methods for business research, 295, 295-336.
CHIN, W. W. 2010. How to write up and report PLS analyses. Handbook of partial least squares. Springer.
CHITENGI, H. S. 2018. Regulations and housing informality in African cities: appropriating regulatory frameworks to factors that influence resilience. Housing and Society, 45, 14-41.
CHURCHILL, G. A. & IACOBUCCI, D. 2002. Test Bank and Transparency Masters to Accompany Marketing Research: Methodological Foundations, Harcourt College Pub.
213
CLARK-CARTER, D. 2009. Quantitative Psychological Research: The Complete Student's Companion: The Complete Student's Companion, Psychology Press.
COLLIN, J. 2002. Measuring the success of building projects–improved project delivery initiatives. Report for the Queensland Department of Public Works, Australia.
CORNALBA, C. & GIUDICI, P. 2004. Statistical models for operational risk management. Physica A: Statistical Mechanics and its applications, 338, 166-172.
CORNISH, K. & MUGOVA, A. 2014. Improving access to finance for small- and medium-sized enterprises in the road sector: The CrossRoads Guarantee Fund in Uganda. Enterprise Development and Microfinance, 25, 135-149.
CULLEN, K. L., FAN, J. & LIU, C. 2014. Employee popularity mediates the relationship between political skill and workplace interpersonal mistreatment. Journal of Management, 40, 1760-1778.
CZARNITZKI, D., HÜNERMUND, P. & MOSHGBAR, N. 2018. Public procurement as policy instrument for innovation.
DAILY MONITOR. 5th November 2016. Entebbe ExpressWay cost inflated by SHs55b'. Daily Monitor.https://www.monitor.co.ug/News/National/-Entebbe-Expressway-cost-inflated-by-Shs55b-/688334-3440480-nf4oc8/index.html.
DAILY MONITOR. 12th March 2019. Contractors decry corrupt officials. Daily Monitor.https://www.monitor.co.ug/News/National/Contractors-decry-corrupt-officials-Iganga-District-PPDA/688334-5020172-2axjsk/index.html.
DAILY MONITOR. 24th October 2016. UNRA in another SHs500b pay scan. Daily Monitor.https://www.monitor.co.ug/News/National/UNRA-roads--Shs500b--scam/688334-3426156-format-xhtml-imspqkz/index.html.
DAILY MONITOR. 29th August 2016. RDCs warn Chinese firm on delayed works. Daily Monitor.https://www.monitor.co.ug/News/National/RDCs-warn-Chinese-firm-on-delayed-works/688334-3361094-format-xhtml-unu9tgz/index.html.
DAINTY, A. 2008. Chapter One Methodological pluralism in construction management research.
DARKO, A., CHAN, A. P., OWUSU-MANU, D.-G. & AMEYAW, E. E. 2017. Drivers for implementing green building technologies: An international survey of experts. Journal of cleaner production, 145, 386-394.
DAVIS, KEYS, L. K., CHEN, I. J. & PETERSON, P. L. 2004. Collaborative product development in an R&D environment.
DAVIS, SCHOORMAN, F. D. & DONALDSON, L. 1997. Toward a stewardship theory of management. Academy of Management review, 22, 20-47.
DAVIS, P., GAJENDRAN, T., VAUGHAN, J. & OWI, T. 2016. Assessing construction innovation: theoretical and practical perspectives. Construction Economics and Building, 16, 104-115.
DE JONG, A., SONG, M. & SONG, L. Z. 2013. How lead founder personality affects new venture performance: The mediating role of team conflict. Journal of Management, 39, 1825-1854.
DECAROLIS, F., GIUFFRIDA, L. M., IOSSA, E., MOLLISI, V. & SPAGNOLO, G. 2018. Bureaucratic Competence and Procurement Outcomes. National Bureau of Economic Research.
DENG, X. W., YUHONG, ZHANG, Q. H., JUDY XIYE & CUI, J. 2014. Analysis of fraud risk in public construction projects in China. Public Money & Management, 34, 51-58.
DIAMANTOPOULOS, A. & SIGUAW, J. A. 2006. Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British Journal of Management, 17, 263-282.
214
DIMAGGIO, P. J. & POWELL, W. W. 1991. The new institutionalism in organizational analysis, University of Chicago Press Chicago, IL.
DIMAGGIO, P. J. & POWELL, W. W. 2000. The iron cage revisited institutional isomorphism and collective rationality in organizational fields. Economics Meets Sociology in Strategic Management. Emerald Group Publishing Limited.
DIMAGGIO, P. J. & POWELL, W. W. 2015. The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields [1983]. Contemporary sociological theory, 175.
DOANE, D. P. & SEWARD, L. E. 2011. Measuring skewness: a forgotten statistic. Journal of Statistics Education, 19, 1-18.
DOLOI, H., IYER, K. C. & SAWHNEY, A. 2011. Structural equation model for assessing impacts of contractor's performance on project success. International Journal of Project Management, 29, 687-695.
DONAHUE, J. D. 1989. The privatization decision: Public ends, private means, Basic Books. DONALDSON, L. & DAVIS, J. H. 1991. Stewardship theory or agency theory: CEO
governance and shareholder returns. Australian Journal of management, 16, 49-64. DUFFY, J. 2000. Measuring customer capital. Strategy & Leadership, 28, 10-15. DURAKU, A. 2018. Public Expenditures Through Public Procurement. European Journal of
Engineering and Formal Sciences, 3, 40-49. DVIR, D. & LECHLER, T. 2004. Plans are nothing, changing plans is everything: the impact
of changes on project success. Research policy, 33, 1-15. EBERHARD, A. 2007. Infrastructure regulation in developing countries: an exploration of
hybrid and transitional models. Public-Private Infrastructure Advisory Facility, World Bank, Working Paper.
EECKHOUT, J. & MUNSHI, K. 2005. Mitigating Regulatory Inefficiency: The Non-market Response to Financial Regulation in India. unpublished paper.
EISENHARDT, K. M. 1989. Agency theory: An assessment and review. Academy of management review, 14, 57-74.
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, 269-280.
ESTACHE, A. 2006. PPI partnerships vs. PPI divorces in LDCs. Review of Industrial Organization, 29, 3-26.
ESTACHE, A. & IIMI, A. 2009. Joint bidding, governance and public procurement costs: A case of road projects. Annals of Public and Cooperative Economics, 80, 393-429.
EYAA, S. & OLUKA, P. N. 2011. Explaining non-compliance in public procurement in Uganda. International Journal of Business and Social Science, 2.
FAIRCHILD, A. J. & MCQUILLIN, S. D. 2010. Evaluating mediation and moderation effects in school psychology: A presentation of methods and review of current practice. Journal of school psychology, 48, 53-84.
FALK, R. F. & MILLER, N. B. 1992. A primer for soft modeling, University of Akron Press. FARAWAY, J. J. 2002. Practical regression and ANOVA using R. University of Bath. FARIDI, A. S. & EL‐SAYEGH, S. M. 2006. Significant factors causing delay in the UAE
construction industry. Construction Management and Economics, 24, 1167-1176. FARSHCHIAN, M. M., HERAVI, G. & ABOURIZK, S. 2017. Optimizing the Owner’s
Scenarios for Budget Allocation in a Portfolio of Projects Using Agent-Based Simulation. Journal of Construction Engineering and Management, 143, 04017022.
FAYEZI, S., WILDING, RICHARD, WAGNER, B., O'LOUGHLIN, A. & ZUTSHI, A. 2012. Agency theory and supply chain management: a structured literature review. Supply chain management: an international journal, 17, 556-570.
215
FELLOWS, R. & LIU, A. M. 2012. Managing organizational interfaces in engineering construction projects: addressing fragmentation and boundary issues across multiple interfaces. Construction management and economics, 30, 653-671.
FERBER, R. 1980. Readings in the analysis of survey data, Amer Marketing Assn. FIELD, A. 2013. Discovering statistics using IBM SPSS statistics, Sage. FLYVBJERG, B. 2016. The fallacy of beneficial ignorance: A test of Hirschman’s hiding hand.
World Development, 84, 176-189. FLYVBJERG, B., HOLM, M. S. & BUHL, S. 2002. Underestimating costs in public works
projects: Error or lie? Journal of the American planning association, 68, 279-295. FLYVBJERG, B., SKAMRIS HOLM, M. K. & BUHL, S. L. 2003. How common and how
large are cost overruns in transport infrastructure projects? Transport reviews, 23, 71-88.
FOFIE, O. 2016. Transparency and Accountability in the Public Sector, A Case of Effective Regulatory Governance for Financial Reporting in Developing Economies. World of Accounting Science, 18.
FORD, B. 2011. Overruns add millions to the cost of state road projects. New England National Centre for Investigative Reporting.
FOROUGHI, B., MOHAMMAD SHAH, K. A., RAMAYAH, T. & IRANMANESH, M. 2019. The effects of peripheral service quality on spectators’ emotions and behavioural intentions. International Journal of Sports Marketing and Sponsorship.
FORZA, C. 2002. Survey research in operations management: a process-based perspective. International journal of operations & production management, 22, 152-194.
FRADKOV, M. 2004. State procurement to reach 40% of 2004 budget expenses. The Russia Journal Daily.[On-line]. Available at http://www. russiajournal. com. news/cnewswire. shtml.
FRAZIER, P. A., TIX, A. P. & BARRON, K. E. 2004. Testing moderator and mediator effects in counseling psychology research. Journal of counseling psychology, 51, 115.
FREEMAN, D. M., HALVERSON, M., LEWIS, S. & FIELY-FISHER, B. 2006. Project management for complex construction projects by monitoring subcontractors in real time. Google Patents.
FREEZE, R. D. & RASCHKE, R. L. An Assessment of Formative and Reflective Constructs in IS Research. ECIS, 2007. 1481-1492.
FREY, B. S. 1993. Does monitoring increase work effort? The rivalry with trust and loyalty. Economic Inquiry, 31, 663-670.
FRØYSTAD, M., HEGGSTAD, K. K. & FJELDSTAD, O.-H. 2010. Linking procurement and political economy. UK Department for International Development and the World Bank Institute.
FURNEAUX, C. W., BROWN, K. A., ALLAN, D., MCCONVILLE, S., MCFALLAN, S., LONDON, K. & BURGESS, J. 2006. Client capabilities and capital works procurement policies: A comparative analysis of Australian jurisdictions. Brown, K., K. Hampson and P. Brandon. Clients Driving Construction Innovation: Moving Ideas into Practice. Brisbane: Cooperative Research Centre for Construction Innovation, Icon. Net Pty Ltd, 62-71.
GAMBO, N., SAID, I. & ISMAIL, R. 2016. Influences of Cost Factors Affecting Technical Performance of Local Government Projects in Nigeria: A Partial Least Square-Structural Equation Modeling (PLS-SEM) Approach. Journal of Construction in Developing Countries, 21.
GAN, F. & KOEHLER, K. 1990. Goodness-of-Fit Tests Based on P-P Probability Plots. Technometrics, 32, 289-303.
216
GARCIA, R. & KANDEMIR, D. 2006. An illustration of modeling moderating variables in cross-national studies. International Marketing Review, 23, 371-389.
GEELS, F. W. 2004. From sectoral systems of innovation to socio-technical systems: Insights about dynamics and change from sociology and institutional theory. Research policy, 33, 897-920.
GEFEN, D. & STRAUB, D. 2005. A practical guide to factorial validity using PLS-Graph: Tutorial and annotated example. Communications of the Association for Information systems, 16, 5.
GEFEN, D., STRAUB, D. & BOUDREAU, M.-C. 2000. Structural equation modeling and regression: Guidelines for research practice. Communications of the association for information systems, 4, 7.
GELDERMAN, GHIJSEN, P. & SCHOONEN, J. 2010. Explaining Non‐Compliance with European Union Procurement Directives: A Multidisciplinary Perspective. JCMS: Journal of Common Market Studies, 48, 243-264.
GELDERMAN, GHIJSEN, P. W. T. & BRUGMAN, M. J. 2006. Public procurement and EU tendering directives-explaining non-compliance. International Journal of Public Sector Management, 19, 702-714.
GELDERMAN, C. J., SEMEIJN, J. & VLUGGEN, R. 2017. Development of sustainability in public sector procurement. Public Money & Management, 37, 435-442.
GEORGE, D. & MALLERY, P. 2016. IBM SPSS statistics 23 step by step: A simple guide and reference, Routledge.
GIROUD, S., GRANDJEAN, A., JAHNS, F., COBUCCIO, L., CASTIONI, J., GRASSET, N., SARTORI, C. & SARAGA, M. 2018. The «Osler» group: a new opportunity to think about «becoming a physician». Revue medicale suisse, 14, 2104.
GLEDSON, B., WILLIAMS, D. & LITTLEMORE, M. 2018. Construction Planning Efficiency and Delivery Time Performance: Analysing Failure in Task-Level ‘Hit Rates’.
GOLDEN, M. & PICCI, L. 2006. 16 Corruption and the management of public works in Italy. International handbook on the economics of corruption, 457.
GÖTZ, O., LIEHR-GOBBERS, K. & KRAFFT, M. 2010. Evaluation of structural equation models using the partial least squares (PLS) approach. Handbook of partial least squares. Springer.
GREENWOOD, R. & HININGS, C. R. 1988. Organizational design types, tracks and the dynamics of strategic change. Organization studies, 9, 293-316.
GREENWOOD, R. & HININGS, C. R. 1996. Understanding radical organizational change: Bringing together the old and the new institutionalism. Academy of management review, 21, 1022-1054.
GREWAL, R., COTE, J. A. & BAUMGARTNER, H. 2004. Multicollinearity and measurement error in structural equation models: Implications for theory testing. Marketing Science, 23, 519-529.
GROVE, S. K., BURNS, N. & GRAY, J. R. 2014. Understanding nursing research: Building an evidence-based practice, Elsevier Health Sciences.
GUDIENĖ, N., BANAITIS, A. & BANAITIENĖ, N. 2013. Evaluation of critical success factors for construction projects–an empirical study in Lithuania. International journal of strategic property management, 17, 21-31.
GUNNINGHAM, N. & KAGAN, R. A. 2005. Regulation and business behavior*. Law & Policy, 27, 213-218.
GUPTA, S. 2002. Research methodology and statistical techniques, Deep and Deep Publications.
217
HAIR & BLACK 2009. BJ, & Anderson, RE (2010). Multivariate data analysis: A global perspective. Upper Saddle River: Pearson Education.
HAIR, HAIR, J., HOLLINGSWORTH, C. L., HOLLINGSWORTH, C. L., RANDOLPH, A. B., RANDOLPH, A. B., CHONG, A. Y. L. & CHONG, A. Y. L. 2017. An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117, 442-458.
HAIR, HULT, G. T. M., RINGLE, C. & SARSTEDT, M. 2016. A primer on partial least squares structural equation modeling (PLS-SEM), Sage Publications.
HAIR, RINGLE, C. M. & SARSTEDT, M. 2011. PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19, 139-152.
HAIR, SARSTEDT, M., HOPKINS, L. & KUPPELWIESER, V. G. 2014. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26, 106-121.
HAIR, SARSTEDT, M., PIEPER, T. M. & RINGLE, C. M. 2012a. The use of partial least squares structural equation modeling in strategic management research: a review of past practices and recommendations for future applications. Long range planning, 45, 320-340.
HAIR, SARSTEDT, M., RINGLE, C. M. & MENA, J. A. 2012b. An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the academy of marketing science, 40, 414-433.
HAIR, J. F., SARSTEDT, M. & RINGLE, C. M. 2019. Rethinking some of the rethinking of partial least squares. European Journal of Marketing, 53, 566-584.
HANSEN, C. P., RUTT, R. & ACHEAMPONG, E. 2018. ‘Experimental’or business as usual? Implementing the European Union Forest Law Enforcement, Governance and Trade (FLEGT) Voluntary Partnership Agreement in Ghana. Forest Policy and Economics, 96, 75-82.
HANSON, D. N. 2006. Causes of Client Dissatisfaction in the South African Building Industry and Ways of Improvement: the Contractors’perspectives. Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg.
HARTLEY, R. 2009. Fighting corruption in the Australian construction industry: The national code of practice. Leadership and Management in Engineering, 9, 131-135.
HAYES, A. F. 2009. Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication monographs, 76, 408-420.
HAYES, A. F. 2012. Process: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. University of Kansas, KS.
HAYES, A. F. & PREACHER, K. J. 2014. Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67, 451-470.
HAYES, A. F. & ROCKWOOD, N. J. 2017. Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour Research and Therapy, 98, 39-57.
HAYES, A. F. & SCHARKOW, M. 2013. The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological science, 24, 1918-1927.
HE, Q., LUO, L., HU, Y. & CHAN, A. P. 2015. Measuring the complexity of mega construction projects in China—A fuzzy analytic network process analysis. International Journal of Project Management, 33, 549-563.
HEATH, J. & NORMAN, W. 2004. Stakeholder theory, corporate governance and public management: what can the history of state-run enterprises teach us in the post-Enron era? Journal of business ethics, 53, 247-265.
218
HELSBY, R. & KAIZER, A. 2005. PricewaterhouseCoopers–Economic crime survey 2003. HEMSTRÖM, K., GUSTAVSSON, L. & MAHAPATRA, K. 2017. The sociotechnical regime
and Swedish contractor perceptions of structural frames. Construction Management and Economics, 35, 184-195.
HENSELER, J. 2010. On the convergence of the partial least squares path modeling algorithm. Computational statistics, 25, 107-120.
HENSELER, J., DIJKSTRA, T. K., SARSTEDT, M., RINGLE, C. M., DIAMANTOPOULOS, A., STRAUB, D. W., KETCHEN, D. J., HAIR, J. F., HULT, G. T. M. & CALANTONE, R. J. 2014. Common beliefs and reality about PLS: comments on Rönkkö and Evermann (2013)| NOVA. The University of Newcastle's Digital Repository.
HENSELER, J., RINGLE, C. M. & SINKOVICS, R. R. 2009. The use of partial least squares path modeling in international marketing. New challenges to international marketing. Emerald Group Publishing Limited.
HILLEBRAND, B., NIJHOLT, J. J. & NIJSSEN, E. J. 2011. Exploring CRM effectiveness: an institutional theory perspective. Journal of the Academy of Marketing Science, 39, 592-608.
HILLIER, D., GRINBLATT, M. & TITMAN, S. 2011. Financial markets and corporate strategy, McGraw Hill.
HU, L. T. & BENTLER, P. M. 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6, 1-55.
HUNJA, R. R. 2003. Obstacles to public procurement reform in developing countries. Public Procurement: The Continuing Revolution, Kluwer Law International, 13-22.
HUNT, K. A., MENTZER, J. T. & DANES, J. E. 1987. The effect of power sources on compliance in a channel of distribution: a causal model. Journal of Business Research, 15, 377-395.
HUSSAIN, S., FANGWEI, Z. & ALI, Z. 2019. Examining Influence of Construction Projects’ Quality Factors on Client Satisfaction Using Partial Least Squares Structural Equation Modeling. Journal of Construction Engineering and Management, 145, 05019006.
HWANG, B.-G., ZHAO, X. & ONG, S. Y. 2014. Value management in Singaporean building projects: Implementation status, critical success factors, and risk factors. Journal of Management in Engineering, 31, 04014094.
HWANG, B. G., ZHAO, X., SEE, Y. L. & ZHONG, Y. 2015. Addressing risks in green retrofit projects: The case of Singapore. Project Management Journal, 46, 76-89.
HWANG, H., SARSTEDT, M., CHEAH, J. H. & RINGLE, C. M. 2019. A concept analysis of methodological research on composite-based structural equation modeling: bridging PLSPM and GSCA. Behaviormetrika, 1-23.
IKA, L. A. 2018. Beneficial or Detrimental Ignorance: The Straw Man Fallacy of Flyvbjerg’s Test of Hirschman’s Hiding Hand. World Development, 103, 369-382.
ISAAC, S. & NAVON, R. 2014. Can project monitoring and control be fully automated? Construction management and economics, 32, 495-505.
JAMES, L. R., MULAIK, S. A. & BRETT, J. M. 2006. A tale of two methods. Organizational research methods, 9, 233-244.
JARI, A. J. & BHANGALE, P. 2013. To study critical factors necessary for a successful construction project. International Journal of Innovative Technology and Exploring Engineering, 2, 331-335.
JARVIS, C. B., MACKENZIE, S. B. & PODSAKOFF, P. M. 2003. A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of consumer research, 30, 199-218.
219
JHA, K. & MISRA, S. 2007. Ranking and classification of construction coordination activities in Indian projects. Construction Management and Economics, 25, 409-421.
JONDEAU, E. & ROCKINGER, M. 2003. Conditional volatility, skewness, and kurtosis: existence, persistence, and comovements. Journal of Economic dynamics and Control, 27, 1699-1737.
JOSE, P. E. 2013. MedGraph-I: A programme to graphically depict mediation among three variables. Victoria University of Wellington New Zealand
JU, C. & ROWLINSON, S. 2014. Institutional determinants of construction safety
management strategies of contractors in Hong Kong. Construction management and economics, 32, 725-736.
KAGIOGLOU, M., COOPER, R., AOUAD, G. & SEXTON, M. 2000. Rethinking construction: the generic design and construction process protocol. Engineering, construction and architectural management, 7, 141-153.
KAJEVSKA, A. M. 2018. A foe of democracy, gender and sexual equality in Macedonia: The worrisome role of the party VMRO-DPMNE. Politics and Governance, 6, 55-66.
KAKITAHI, ALINAITWE, H. L., ANNE & MONE, S. H., THEOC 2016. Impact of construction-related rework on selected Ugandan public projects. Journal of Engineering, Design and Technology, 14.
KAKITAHI, ALINAITWE, H. M., LANDIN, A. & MUDAAKI, S. P. 2015. A study of non-compliance with quality requirements in Uganda. Proceedings of Institution of Civil Engineers: Management, Procurement and Law, 168, 22-42.
KAKITAHI, LANDIN, A. & ALINAITWE, H. M. 2013. An exploratory study of rework causality in Uganda. Construction Innovation, 13, 266-280.
KAKWEZI, D. & NYEKO, P. 2010. Procurement Processes and Performance: Efficiency and Effectiveness of the procurement function. Retrieved April, 3, 2011.
KALIBA, C., MUYA, M. & MUMBA, K. 2009. Cost escalation and schedule delays in road construction projects in Zambia. International Journal of Project Management, 27, 522-531.
KALINZI, C. 2014. Level of professionalism in public procurement: A survey of selected districts in Uganda. Net Journal of Business Management, 2, 1-7.
KALUARACHCHI, Y. D. & JONES, K. 2007. Monitoring of a strategic partnering process: the Amphion experience. Construction Management and Economics, 25, 1053-1061.
KAPLIŃSKI, O. 2018. Innovative solutions in construction industry. Review of 2016–2018 events and trends. Engineering Structures and Technologies, 10, 27-33.
KASSEL, D. S. 2008. Performance, accountability, and the debate over rules. Public Administration Review, 68, 241-252.
KAUFMAN, A. S. & KAUFMAN, N. L. 2004. Kaufman brief intelligence test, Wiley Online Library.
KAUPPI, K. & VAN RAAIJ, E. M. 2015. Opportunism and honest incompetence—seeking explanations for noncompliance in public procurement. Journal of Public Administration Research and Theory, 25, 953-979.
KENNY 2007. Construction, corruption, and developing countries. World Bank Policy Research Working Paper.
KERLINGER, F. & LEE, H. 2000. Foundations of Behavioral Research: Wadsworth, Thomson Learning. Northridge, CA.
KIAMA, G. P. 2014. Factors affecting implementation of public procurement act in SACCO societies in Kenya. International Journal of Academic Research in Business and Social Sciences, 4, 169.
220
KIM, S.-Y. & HUYNH, T.-A. 2008. Improving project management performance of large contractors using benchmarking approach. International Journal of Project Management, 26, 758-769.
KINGSFORD OWUSU, E. & CHAN, A. P. 2018. Barriers Affecting Effective Application of Anticorruption Measures in Infrastructure Projects: Disparities between Developed and Developing Countries. Journal of Management in Engineering, 35, 04018056.
KLINE, R. B. 2015. Principles and practice of structural equation modeling, Guilford publications.
KLING, R. Taxpayers are fighting back: Transparency and accountability does not mean inefficiency. Proceedings from the 3rd International Public Procurement Conference, Amsterdam, The Netherlands, August, 2008. 28-30.
KNIGHT, A. & RUDDOCK, L. 2009. Advanced research methods in the built environment, John Wiley & Sons.
KOCK, N. & HADAYA, P. 2018. Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28, 227-261.
KOG, Y. C. & LOH, P. K. 2011. Critical success factors for different components of construction projects. Journal of Construction Engineering and Management, 138, 520-528.
KONDRA, A. Z. & HININGS, C. R. 1998. Organizational diversity and change in institutional theory. Organization studies, 19, 743-767.
KOTHARI, C. R. 2004. Research methodology: Methods and techniques, New Age International.
KRAMBIA-KAPARDIS, M. 2019. Financial Compliance, Springer. KRASIKOVA, D. V., GREEN, S. G. & LEBRETON, J. M. 2013. Destructive leadership: A
theoretical review, integration, and future research agenda. Journal of Management, 39, 1308-1338.
KREJCIE, R. V. & MORGAN, D. W. 1970. Table for determining sample size from a given population. Educational and Psychological Measurement, 30, 607-610.
KULP, S. L., RANDALL, T., BRANDYBERRY, G. & POTTS, K. 2006. Using organizational control mechanisms to enhance procurement efficiency: how GlaxoSmithKline improved the effectiveness of e-procurement. Interfaces, 36, 209-219.
KUMAR, AAKER, D. A. & DAY, G. S. 2002. Essentials of marketing research, John Wiley & Sons.
KUMAR, SCHEER, L. K. & STEENKAMP, J.-B. E. 1998. Interdependence, punitive capability, and the reciprocation of punitive actions in channel relationships. Journal of Marketing Research, 225-235.
KUMAR, D. S. & PURANI, K. 2018. Model specification issues in PLS-SEM: Illustrating linear and non-linear models in hospitality services context. Journal of Hospitality and Tourism Technology, 9, 338-353.
LAM, E. W., CHAN, A. P. & CHAN, D. W. 2008. Determinants of successful design-build projects. Journal of Construction Engineering and management, 134, 333-341.
LAN, G. Z., RILEY, L. & CAYER, N. J. 2005. How can local government become an employer of choice for technical professionals? Lessons and experiences from the city of Phoenix. Review of Public Personnel Administration, 25, 225-242.
LANGSTON, C. 2014. Construction efficiency: A tale of two developed countries. Engineering, Construction and Architectural Management, 21, 320-335.
LAPIDUS, A. A. & YVES, N. Integrated Quality Index of Organizational and Technological Solutions for Implementation of Burundian Capital Master Plan. Materials Science Forum, 2018. Trans Tech Publ, 1295-1300.
221
LARMOUR, P. 2007. Administrative theory, interpersonal relations and anti corruption practice in Papua New Guinea.
LAWRENCE, T. B. & ROBINSON, S. L. 2007. Ain't misbehavin: Workplace deviance as organizational resistance. Journal of Management, 33, 378-394.
LE, Y., SHAN, M., CHAN, A. P. & HU, Y. 2014a. Investigating the causal relationships between causes of and vulnerabilities to corruption in the Chinese public construction sector. Journal of construction engineering and management, 140, 05014007.
LE, Y., SHAN, M., CHAN, A. P. & HU, Y. 2014b. Overview of corruption research in construction. Journal of management in engineering, 30, 02514001.
LELAND, H. E. 1998. Agency costs, risk management, and capital structure. The Journal of Finance, 53, 1213-1243.
LENGWILER, Y. & WOLFSTETTER, E. 2006. Corruption in procurement auctions. Available at SSRN 874705.
LI, H., XU, L. C. & ZOU, H. F. 2000. Corruption, income distribution, and growth. Economics & Politics, 12, 155-182.
LIKERT, R. 1932. A technique for the measurement of attitudes. Archives of psychology. LIM, C. & MOHAMED, M. Z. 1999. Criteria of project success: an exploratory re-
examination. International journal of project management, 17, 243-248. LISA, I. 2010. Compliance culture. A conceptual framework. Journal of management and
organization, 19, 702-714. LITTLE, R. J. & RUBIN, D. B. 2002. Wiley series in probability and statistics. Statistical
Analysis with Missing Data, Second Edition, 383-389. LIU, J., ZHAO, X. & YAN, P. 2016. Risk paths in international construction projects: Case
study from Chinese contractors. Journal of Construction Engineering and Management, 142, 05016002.
LOGAN, M. S. 2000. Using agency theory to design successful outsourcing relationships. The International Journal of Logistics Management, 11, 21-32.
LOOSEMORE, M. & MALOUF, N. 2019. Safety training and positive safety attitude formation in the Australian construction industry. Safety Science, 113, 233-243.
LOVE 2002. Influence of project type and procurement method on rework costs in building construction projects. Journal of Construction Engineering and Management, 128, 18-29.
LOVE, ACKERMANN, F., TEO, P. & MORRISON, J. 2015a. From individual to collective learning: A conceptual learning framework for enacting rework prevention. Journal of Construction Engineering and Management, 141, 05015009.
LOVE, DOMINIC, A.-D. & ZAHIR IRANI 2016a. cost overrun in transportation infrastructure projects: Sowing the seeds for a probabilistic theory of causation. Elsevier, 11.
LOVE, EDWARDS, D. J., WATSON, H. & DAVIS, P. 2010. Rework in civil infrastructure projects: Determination of cost predictors. Journal of Construction Engineering and Management, 136, 275-282.
LOVE, GUNASEKARAN, A. & LI, H. 1998. Concurrent engineering: a strategy for procuring construction projects. International Journal of Project Management, 16, 375-383.
LOVE, HAYNES, N., SOHAL, A., CHAN, A. & TAM, C. 2002. Key Construction Management Skills for Future Success. Monash University. Faculty of Business and Economics. Working Paper 49/02.
LOVE & SMITH, J. 2016. Toward Error Management in Construction: Moving beyond a Zero Vision. Journal of Construction Engineering and Management, 04016058.
222
LOVE, SMITH, J., SIMPSON, I., REGAN, M. & OLATUNJI, O. 2015b. Understanding the landscape of overruns in transport infrastructure projects. Environment and Planning B: Planning and Design, 42, 490-509.
LOVE, VELI, S., DAVIS, P., TEO, P. & MORRISON, J. 2016b. See the Difference in a Precast Facility: Changing Mindsets with an Experiential Safety Program. Journal of Construction Engineering and Management, 05016021.
LOVE, P. & SMITH, J. 2019. Unpacking the ambiguity of rework in construction: making sense of the literature. Civil Engineering and Environmental Systems, 1-24.
LOVE , P. D., SING MICHAEL C.P, LAVAGNON IKA & SIDNEY NEWTON 2019. The Cost Performance of Transportation Projects: The Fallacy of the Planning Fallacy Account. Transportation Research Part A: Policy and Practice, 1-40.
LOVE, P. E., AHIAGA-DAGBUI, D., WELDE, M. & ODECK, J. 2017. Light rail transit cost performance: Opportunities for future-proofing. Transportation Research Part A: Policy and Practice, 100, 27-39.
LOVE, P. E. & AHIAGA-DAGBUI, D. D. 2018. Debunking fake news in a post-truth era: The plausible untruths of cost underestimation in transport infrastructure projects. Transportation Research Part A: Policy and Practice, 113, 357-368.
LOVE, P. E., AHIAGA-DAGBUI, D. D., SMITH, S. D., SING, M. C.-P. & TOKEDE, O. 2018a. Cost profiling of water infrastructure projects. Journal of Infrastructure Systems, 24, 04018023.
LOVE, P. E., IKA, L. A., LOCATELLI, G. & AHIAGA-DAGBUI, D. D. 2018b. Future-proofing ‘Next Generation’infrastructure assets. Frontiers of engineering management, 5, 1-4.
LOVE, P. E., SMITH, J., SIMPSON, I., REGAN, M. & OLATUNJI, O. 2015c. Understanding the landscape of overruns in transport infrastructure projects. Environment and Planning B: Planning and Design, 42, 490-509.
MACKINNON, D. P., LOCKWOOD, C. M., HOFFMAN, J. M., WEST, S. G. & SHEETS, V. 2002. A comparison of methods to test mediation and other intervening variable effects. Psychological methods, 7, 83.
MAHMOOD, S. A. I. 2010. Public procurement and corruption in Bangladesh confronting the challenges and opportunities. Journal of public administration and policy research, 2, 103.
MALHOTRA, N. & PETERSON, M. 2006. Basic Marketing Research,. International Edition. Pearson Education, Inc. Upper Saddle River, NJ.
MARK, S., PHILIP, L. & ADRIAN, T. 2009. Research methods for business students. Harlow: Prentice Hall.
MARNEWICK, C., ERASMUS, W. & NAZEER, J. 2018. The symbiosis between information system project complexity and information system project success, AOSIS.
MARTIN, G. P., WISEMAN, R. M. & GOMEZ-MEJIA, L. R. 2016. The interactive effect of monitoring and incentive alignment on agency costs. Journal of Management, 0149206316678453.
MATHIEU, J. E. & TAYLOR, S. R. 2006. Clarifying conditions and decision points for mediational type inferences in organizational behavior. Journal of Organizational Behavior, 27, 1031-1056.
MAWENYA, A. 2008. Preventing corruption in Africa. Occasional paper, South African Institute of International Affairs (SAIIA), Johannesburg.
MBABAZI, KARUHANGA & MAURICE, M. 2015. Compliance and Service delivery ; Case of Local Government procurement Units in Uganda.
MCDANIEL, C. & GATES, R. 2010. Marketing research with SPSS. Hoboken. New Jersey: John Wiley & Sons.
223
MCNUTT, P. A. & ROSSI, C. L. 2010. Compliance: an over-looked business strategy. International Journal of Social Economics, 37, 816-831.
MEHMETOGLU, M. 2004. Quantitative or qualitative? A content analysis of Nordic research in tourism and hospitality. Scandinavian Journal of Hospitality and Tourism, 4, 176-190.
MEMON, M., CHEAH, J., RAMAYAH, T., TING, H. & CHUAH, F. 2018. Mediation Analysis Issues and Recommendations. Journal of Applied Structural Equation Modeling, 2, 1-9.
MEMON, M., TING, H., RAMAYAH, T., CHUAH, F. & CHEAH, J. 2017. A review of the methodological misconceptions and guidelines related to the application of structural equation modeling: A Malaysian scenario. Journal of applied structural equation modeling, 1, 1-13.
MENTZER, J. T., STANK, T. P. & ESPER, T. L. 2008. Supply chain management and its relationship to logistics, marketing, production, and operations management. Journal of Business Logistics, 29, 31-46.
MIGOSI, J. A., OMBUKI, C. N., OMBUKI, K. N. & EVUSA, Z. 2013. Determinants of non-compliance of public procurement regulations in Kenyan secondary schools.
MILLER, T. L., DEL CARMEN TRIANA, M., REUTZEL, C. R. & TREVIS CERTO, S. 2007. Mediation in strategic management research: Conceptual beginnings, current application, and future recommendations. Research methodology in strategy and management. Emerald Group Publishing Limited.
MIN, S. & MENTZER, J. T. 2004. Developing and measuring supply chain management concepts. Journal of business logistics, 25, 63-99.
MINISTRY OF FINANCE , P. A. E. D. 2013. Background to budget 2013/14. Kampala,Uganda: Ministry of Finance ,Planning and Economic Development.https://finance.go.ug/budget.
MINISTRY OF WORKS & TRANSPORT 2013. Annual Sector Performance Report 2012/2013. Kampala Uganda: Ministry of Works & Transport.https://www.works.go.ug/wp-content/uploads/2016/03/Final-Draft-ASP-2012-13.pdf.
MINISTRY OF WORKS AND TRANSPORT 2012. Annual Sector Performance Report 2011-12. Kampala Uganda: Ministry of Works & Transport.https://www.works.go.ug/wp-content/uploads/2016/03/Final-Draft-ASP-15-09-12.pdf.
MINISTRY OF WORKS AND TRANSPORT 2014. Annual Performance Report 2013/2014.
. Kampala Uganda: Ministry of Works and Transport.https://works.go.ug/wp-content/uploads/2015/08/Annual-Works-and-Transport-Sector-Performance-Report-For-Financial-Year-2013-14.pdf.
MINISTRY OF WORKS AND TRANSPORT 2015. Annual sector performance report 2014/2015. Kampala Uganda: Ministry of Woerks and Transport.https://www.works.go.ug/wp-content/uploads/2016/03/Final-MoWT-ASPR-Report-2014-15.pdf.
MITCHELL, T. R. & JAMES, L. R. 2001. Building better theory: Time and the specification of when things happen. Academy of Management Review, 26, 530-547.
MOJTAHEDI, MOUSAVI, S. & AMINIAN, A. 2009. A non-parametric statistical approach for analyzing risk factor data in risk management process. Journal of Appled Science, 9, 113-120.
MOJTAHEDI & OO, B. L. 2017. The impact of stakeholder attributes on performance of disaster recovery projects: The case of transport infrastructure. International Journal of Project Management, 35, 841-852.
224
MUGENDA, M. & MUGENDA, A. 2003. Research Methods in Education: Quantitative and Qualitative Approach, Nairobi. Acts press.
MULLER, D., JUDD, C. M. & YZERBYT, V. Y. 2005. When moderation is mediated and mediation is moderated. Journal of personality and social psychology, 89, 852.
MÜLLER, R. 2009. Project Governance (Fundamentals of project management), Ashgate Publishing Group.
MÜLLER, T., SCHUBERTH, F. & HENSELER, J. 2018. PLS path modeling–a confirmatory approach to study tourism technology and tourist behavior. Journal of Hospitality and Tourism Technology, 9, 249-266.
MUNYASYA, B. & CHILESHE, N. 2018. Towards Sustainable Infrastructure Development: Drivers, Barriers, Strategies, and Coping Mechanisms. Sustainability, 10, 4341.
MURTAGH, N., ACHKAR, L. & ROBERTS, A. 2018. The role of building control surveyors and their power in promoting sustainable construction. Construction Management and Economics, 36, 363-374.
MWAKIBINGA & BUVIK, A. 2013. An empirical analysis of coercive means of enforcing compliance in public procurement. Journal of Public Procurement, 13, 243.
NADIOPE, M. 2005. Effects of contract management methods of donor funded projects on construction in Uganda. Unpublished.
NAOUM, S. G. 1998. Dissertation Research & Writing for Construction Students, Oxford , UK, Bulter Worth Heinemann.
NAVON, R. 2005. Automated project performance control of construction projects. Automation in Construction, 14, 467-476.
NEW VISION. 4th August 2017. Katosi road scan, Kagina cuations Chinese contractors, UNRA faulted over Entebbe Expressway delays. New Vision.https://www.newvision.co.ug/new_vision/news/1459448/entebbe-expressway-unra-faulted-delayed-compensation.
NEW VISION. 20th October 2016. UNRA queried over sh300b contract Kanoni-Ssembabule-Villa maria road. New Vision.https://www.google.com.au/search?q=New+Vision,+20th+October+2016.+UNRA+queried+over+sh300b+contract+Kanoni-Ssembabule-Villa+maria+road.&rlz=1C1GGRV_enAU787AU787&tbm=isch&tbo=u&source=univ&sa=X&ved=2ahUKEwier7nhiYPfAhUBeisKHR3ADIQQ7Al6BAgFEA0&biw=1920&bih=920., p.1.
NEW VISION. 28th July 2016. 24 billion lost in Mukono road project. New Vision.http://accu.or.ug/sh24b-lost-in-mukono-road-project/, p.1.
NEWAZ, M. T., DAVIS, P., JEFFERIES, M. & PILLAY, M. Role of Psychological Contract to Influence Safety Behaviour at Construction Sites. International Conference on Applied Human Factors and Ergonomics, 2018. Springer, 545-555.
NEWBOLD, P. & AGIAKLOGLOU, C. 1991. Looking for evolving growth rates and cycles in British industrial production, 1700-1913. Journal of the Royal Statistical Society. Series A (Statistics in Society), 341-348.
NG, S. T., PALANEESWARAN, E. & KUMARASWAMY, M. M. 2002. A dynamic e-Reporting system for contractor's performance appraisal. Advances in Engineering Software, 33, 339-349.
NITZL, C., ROLDAN, J. L. & CEPEDA, G. 2016. Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Industrial management & data systems, 116, 1849-1864.
NORRMAN, A. 2008. Supply chain risk-sharing contracts from a buyers' perspective: content and experiences. International Journal of Procurement Management, 1, 371-393.
225
NORTH, D. C. 1993. Institutional change: a framework of analysis. Institutional change: Theory and empirical findings, 35-46.
NORTH, D. C. 2016. Institutions and economic theory. The American Economist, 61, 72-76. NSANGANZELU 2015. procurement practices and financial performance of district councils
in Tanzania Sky journal of Business Administration and Management, 3(4), 032-047. NTAYI, BYABASHAIJA, EYAA, N. & MULIIRA 2010a. Social cohesion, groupthink and
ethical behavior of public procurement officers. Journal of public procurement, 10, 68. NTAYI & EYAA, S. 2009. Supply Chain Swiftness in a Developing Country: The Case of
Uganda Small and Medium Sized Enterprises, E-Journal of Business and Economic Issues, Vol. IV, No. I. PPDA (2011-2014).
NTAYI, NGOBOKA, P. & KAKOOZA, C. S. 2013. Moral Schemas and Corruption in Ugandan Public Procurement. Journal of Business Ethics, 112, 417-436.
NTAYI, ROOKS, EYAA & QIAN 2010b. Perceived Project Value, Opportunistic Behavior, Interorganizational Cooperation, and Contractor Performance. Journal of African Business, 11, 124-141.
OBANDA, W. 2010. Fighting corruption in tactical procurement. Unpublished PHD dissertation. University of Twente.
OBICCI, P. A. 2015. Conflict of interest on public procurement management in Uganda. ODECK, J. 2004. Cost overruns in road construction—what are their sizes and determinants?
Transport policy, 11, 43-53. ODHIAMBO, W. & KAMAU, P. 2003. Public Procurement: Lessons from Kenya, Tanzania
and Uganda,
OECD Development Centre Working Papers 208, OECD Publishing. OGUNLANA, S. O., LI, H. & SUKHERA, F. A. 2003. System dynamics approach to exploring
performance enhancement in a construction organization. Journal of construction engineering and management, 129, 528-536.
OJO, E. & GBADEBO, A. 2014. An assessment of non-compliance with procurement proceedings in procurement of works in Nigeria. International Journal of Economic and Business Management, 2, 25-34.
OKEAHALAM, C. C. 2004. Corporate governance and disclosure in Africa: Issues and challenges. Journal of Financial Regulation and compliance, 12, 359-370.
OLANDER, S. 2007. Stakeholder impact analysis in construction project management. Construction Management and Economics, 25, 277-287.
OLIVER, C. 1991. Strategic responses to institutional processes. Academy of management review, 16, 145-179.
OLKEN, B. A. 2005. Monitoring corruption: evidence from a field experiment in Indonesia. National Bureau of Economic Research.
OLUKA, P. N. & BASHEKA, B. C. 2014. Determinants and constraints to effective procurement contract management in uganda: A practitioner's perspective. International Journal of Logistics Systems and Management, 17, 104-124.
ONYEMA. 2011. Challenges, prospects of public procurement practices Guardian Newspaper.
OPPENHEIM, A. N. 1992. Questionnaire design. Interviewing and Attitude measurement, 2. OSEI-TUTU, BADU, E. & OWUSU-MANU, D. 2010. Exploring corruption practices in
public procurement of infrastructural projects in Ghana. International Journal of Managing Projects in Business, 3, 236-256.
OSEI-TUTU, MENSDAH, S. & AMEYA, C. The level of compliance with the public procurement Act (Act 663) in Ghana. Management and Innovation for a Sustainable
226
Built Environment MISBE 2011, Amsterdam, The Netherlands, June 20-23, 2011, 2011. CIB, Working Commissions W55, W65, W89, W112; ENHR and AESP.
OSLAND, O. & STRAND, A. 2010. The politics and institutions of project approval-a critical-constructive comment on the theory of strategic misrepresentation. EJTIR, 1.
OTHMAN, I., HASHIM, Z., MOHAMAD, H. & NAPIAH, M. The Framework for Effective Human Resource Management at Construction Site. MATEC Web of Conferences, 2018. EDP Sciences, 02002.
OWUSU, E. K., CHAN, A. P. & SHAN, M. 2017. Causal factors of corruption in construction project management: an overview. Science and engineering ethics, 1-31.
PACHNOU, D. 2005a. Bidder’s Use of Mechanism to Enforce EC Procurement. PPLR. PACHNOU, D. 2005b. Factors Influencing Bidder’s Recourse to the European Commission to
Enforce Procurement Law. PPLR. PAPADONIKOLAKI, E. 2018. Loosely coupled systems of innovation: Aligning BIM
adoption with implementation in Dutch construction. Journal of Management in Engineering, 34, 05018009.
PARK, Y.-I. & PAPADOPOULOU, T. C. 2012. Causes of cost overruns in transport infrastructure projects in Asia: their significance and relationship with project size. Built Environment Project and Asset Management, 2, 195-216.
PARKER, C. & NIELSEN, V. L. 2017. Compliance: 14 questions. Regulatory theory: Foundations and applications, 217-232.
PAULSON JR, B. C. & FONDAHL, J. W. 1983. Craft Jurisdiction Impact on Construction. Journal of Construction Engineering and Management, 109, 369-386.
PAYAN, J. M. & MCFARLAND, R. G. 2005. Decomposing influence strategies: Argument structure and dependence as determinants of the effectiveness of influence strategies in gaining channel member compliance. Journal of Marketing, 69, 66-79.
PEGNATO, J. A. 2003. Assessing federal procurement reform: Has the procurement pendulum stopped swinging? Journal of public Procurement, 3, 145.
PEPRAH, J. A. 2015. Trajectories of Maverick Buying in the District Assemblies in Ghana. European Centre for Research Training and Development UK.
PHENG, L. S. & CHUAN, Q. T. 2006. Environmental factors and work performance of project managers in the construction industry. International journal of project management, 24, 24-37.
PIERCE, J. R. 2015. Reexamining the Cost of Corporate Criminal Prosecutions. Journal of Management, 0149206315594845.
PINTO. 1986. Project implementation: a determination of its critical success factors, moderators and their relative importance across the project life cycle. University of Pittsburgh.
PINTO & MANTEL, S. J. 1990. The causes of project failure. IEEE transactions on engineering management, 37, 269-276.
PITARIU, A. H. & PLOYHART, R. E. 2010. Explaining change: Theorizing and testing dynamic mediated longitudinal relationships. Journal of Management, 36, 405-429.
PPDA AUTHORITY 2003. Disposal of Public Assets Act.(2003). In: AUTHORITY.HTTPS://WWW.PPDA.GO.UG/DOWNLOAD/PPDA_ACT/PPDA_ACT/PPDA_ACT-2003.PDF, P. (ed.) Printed by UPPC, Entebbe, by Order of the Government.
PPDA AUTHORITY 2007. Disposal of Public Assets Authority.(2006). Procurement and Disposal Compliance Check Report of National Social Security Fund.
PPDA AUTHORITY 2008. Workshop on challenges facing construction sector in Uganda. Kampala,Uganda: PPDA Authority.http://docplayer.net/40154255-Workshop-on-challenges-facing-the-construction-sector-in-uganda.html.
227
PPDA AUTHORITY 2009a. Annual Performance Report. Kampala Uganda: PPDA Authority.https://www.ppda.go.ug/download/ppda_annual_reports/ppda_annual_reports/PPDA-Annual-Report-2008-9.pdf.
PPDA AUTHORITY 2009b. Second Public Procurement Integrity Survey. Kampala Uganda: PPDA Authority.https://www.scribd.com/document/306142813/PPDA-2nd-integrity-survey-pdf.
PPDA AUTHORITY 2012. training and capacity building strategy plan 2012-2014. Kampala, Uganda: PPDA Authority.https://www.ppra.go.tz/index.php/2012-11-29-10-53.../capacity-building-strategy.
PPDA AUTHORITY 2014. Investigation into alleged irregularity. Kampala Uganda: PPDA Authority.https://www.ppda.go.ug/download/investigations/investigations/financial_year__2013-14/UNRA-INVESTIGATION-MUKONO-KATOSI-NYENGA-ROAD.pdf.
PPDA AUTHORITY 2016. Third Public procurement Integrity Survey. Kampala Uganda: PPDA Authority.https://www.ppda.go.ug/download/corporate_reports/corporate_reports/PPDA-3rd-Integrity-Survey-Report-.pdf.
PRAYAS ENERGY GROUP 2002. Bujagali power purchase Agreement. By Prayas, Energy Group, Pune, India for International Rivers Network International Rivers Network 1847 Berkeley Way Berkeley, CA 94703, USA.
PREACHER, K. J. & HAYES, A. F. 2004. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior research methods, 36, 717-731.
PREACHER, K. J. & LEONARDELLI, G. J. 2001. Calculation for the Sobel test. Retrieved January, 20, 2009.
PRENCIPE, A. & TELL, F. 2001. Inter-project learning: processes and outcomes of knowledge codification in project-based firms. Research policy, 30, 1373-1394.
PREUSS, L. & WALKER, H. 2011. Psychological barriers in the road to sustainable development: evidence from public sector procurement. Public Administration, 89, 493-521.
QIN, X., MO, Y. & JING, L. 2016. Risk perceptions of the life-cycle of green buildings in China. Journal of Cleaner Production, 126, 148-158.
RAAIJMAKERS, Q. A. 2000. Adolescents’midpoint Responses on Likert-Type Scale Items: Neutral or Missing Values? International Journal of Public Opinion Research, 12, 209-217.
RAFFERTY, M. & TONER, P. 2018. Thinking like Capital markets–Financialisation of the Australian Construction Industry. Construction Management and Economics, 1-13.
RAJAB, M. & EYDGAHI, A. 2019. Evaluating the explanatory power of theoretical frameworks on intention to comply with information security policies in higher education. Computers & Security, 80, 211-223.
RASOOLIMANESH, S. M., MD NOOR, S., SCHUBERTH, F. & JAAFAR, M. 2019. Investigating the effects of tourist engagement on satisfaction and loyalty. The Service Industries Journal, 1-16.
RASOOLIMANESH, S. M., RINGLE, C. M., JAAFAR, M. & RAMAYAH, T. 2017. Urban vs. rural destinations: Residents’ perceptions, community participation and support for tourism development. Tourism Management, 60, 147-158.
RED PEPPER. 3rd November 2016. UNRA Pays new Chinese ghost contractors. Red Pepper.https://www.google.com.au/search?q=RED+PEPPER.+3rd+November+2016.+UNRA+Pays+new+Chinese+ghost+contractors.+Red+Pepper&rlz=1C1GGRV_enAU787AU787&tbm=isch&tbo=u&source=univ&sa=X&ved=2ahUKEwjv04vw-YffAhXbZCsKHSQGDwcQ7Al6BAgEEA0&biw=1920&bih=969.
228
RED PEPPER. 2018. Corruption Delayed Kanungu Road- Museveni. Red Pepper, 22 December 2018.
RED PEPPER. 21st October 2016. Parliament orders audit into UNRA contractors. Red Pepper.https://www.google.com.au/search?q=RED+PEPPER.+21st+October+2016.+Parliament+orders+audit+into+UNRA+contractors.+Red+Pepper&rlz=1C1GGRV_enAU787AU787&tbm=isch&tbo=u&source=univ&sa=X&ved=2ahUKEwiZ-qiq-YffAhVYbysKHe3ABHUQ7Al6BAgEEA0&biw=1920&bih=969.
REEVES, E. 2008. The practice of contracting in public private partnerships: transaction costs and relational contracting in the Irish schools sector. Public Administration, 86, 969-986.
REICHELSTEIN, S. 1992. Constructing incentive schemes for government contracts: An application of agency theory. Accounting Review, 712-731.
RENDON, R. G. 2010. Critical success factors in government contract management. RINGLE, WENDE, S. & BECKER, J.-M. 2015a. SmartPLS 3. Boenningstedt: SmartPLS
GmbH, http://www. smartpls. com. RINGLE, WENDE, S. & BECKER, J. 2015b. SmartPLS. Boenningstedt, Germany: SmartPLS
GmbH. RINGLE, C. M., SARSTEDT, M., MITCHELL, R. & GUDERGAN, S. P. 2018. Partial least
squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 1-27.
RIZK, R., SOBH, D., YASSIN, A. A. A. & HAMZEH, F. 2018. Studying the Mindset of Corruption in the Construction Industry-A Lean Perspective.
ROBINSON, H. S. & SCOTT, J. 2009. Service delivery and performance monitoring in PFI/PPP projects. Construction Management and Economics, 27, 181-197.
ROBSON, C. 2002. Real world research. 2nd. Edition. Blackwell Publishing. Malden. ROBSON, C. & MCCARTAN, K. 2016. Real world research, John Wiley & Sons. ROGATI, K. 2004. Uganda Country Procurement Assessment Report (CPAR, 2004). Main
Report, June. ROGERSON, C. 2018. Local Economic Development in the Changing World: The Experience
of Southern Africa, Routledge. ROKKAN, A. I. & BUVIK, A. 2003. Inter-firm cooperation and the problem of free riding
behavior: An empirical study of voluntary retail chains. Journal of Purchasing and Supply Management, 9, 247-256.
ROKKAN, A. I. & BUVIK, A. 2009. The threat-based influence strategy and monitoring arrangements in voluntary retail chains: the conflict and control effects. International Journal of Procurement Management, 2, 79-92.
ROSS, S. A. 1973. The economic theory of agency: The principal's problem. The American Economic Review, 63, 134-139.
RUBIN, A. & BABBIE, E. R. 2012. Brooks/Cole Empowerment Series: Essential research methods for social work, Cengage Learning.
RUDDOCK, L. & LOPES, J. 2006. The construction sector and economic development: the ‘Bon curve’. Construction Management and Economics, 24, 717-723.
RUNESON, G. & SKITMORE, M. 1999. Tendering theory revisited. Construction Management & Economics, 17, 285-296.
RUTHERFORD, M. A., BUCHHOLTZ, A. K. & BROWN, J. A. 2007. Examining the relationships between monitoring and incentives in corporate governance. Journal of Management Studies, 44, 414-430.
RWELAMIRA, P. 1999. Quality and Efficiency of the African Construction Industries; Where Do We Go From Here? CIB REPORT, 120-129.
229
SAAM, N. J. 2007. Asymmetry in information versus asymmetry in power: Implicit assumptions of agency theory? The Journal of Socio-Economics, 36, 825-840.
SADEH, A., DVIR, D. & SHENHAR, A. 2000. The role of contract type in the success of R&D defense projects under increasing uncertainty. Project Management Journal, 31, 14-22.
SAMARAWEERA, A., SENARATNE, S. & SANDANAYAKE, Y. 2018. Nature of construction project cultures in the public sector: case studies in Sri Lanka. Built Environment Project and Asset Management, 8, 557-568.
SANTOSH, G. 2007. Research methodology and statistical techniques. Deep & Deep Publications Pvt. Ltd. New Delhi.
SARSTEDT, M. & CHEAH, J.-H. 2019. Partial least squares structural equation modeling using SmartPLS: a software review. Journal of Marketing Analytics, 1-7.
SARSTEDT, M., HAIR JR, J. F., CHEAH, J.-H., BECKER, J.-M. & RINGLE, C. M. 2019a. How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal (AMJ).
SARSTEDT, M., RINGLE, C. M., CHEAH, J.-H., TING, H., MOISESCU, O. I. & RADOMIR, L. 2019b. Structural model robustness checks in PLS-SEM. Tourism Economics, 1354816618823921.
SATTARI, M. T., YUREKLI, K. & PAL, M. 2012. Performance evaluation of artificial neural network approaches in forecasting reservoir inflow. Applied Mathematical Modelling, 36, 2649-2657.
SAUNDERS, M. N. 2012. Choosing research participants. Qualitative organizational research: Core methods and current challenges, 35-52.
SAWYER, S. 2005. Resampling data: Using a statistical jackknife. Washington University: Washington.
SCARABOTO, D. & FISCHER, E. 2012. Frustrated fatshionistas: An institutional theory perspective on consumer quests for greater choice in mainstream markets. Journal of Consumer Research, 39, 1234-1257.
SCHAMBERGER, T., SCHUBERTH, F., HENSELER, J. & DIJKSTRA, T. K. 2019. Robust partial least squares path modeling. Behaviormetrika, 1-28.
SCHAPPER, P. R., MALTA, J. N. V. & GILBERT, D. L. 2006. An analytical framework for the management and reform of public procurement. Journal of public procurement, 6, 1.
SCHEER, L. K. & STERN, L. W. 1992. The effect of influence type and performance outcomes on attitude toward the influencer. Journal of Marketing Research, 128-142.
SCOTT 1983. The organization of societal sector. Organizational environments: Ritual and rationality, 129-153.
SCOTT 1995. Institutions and organizations. Foundations for organizational science. London: A Sage Publication Series.
SCOTT 2005. Institutional theory: Contributing to a theoretical research program. Great minds in management: The process of theory development, 460-485.
SCOTT 2013. Institutions and organizations: Ideas, interests, and identities, Sage Publications.
SCOTTI, R., CARDELLI, P., BALDISSARA, P. & MONACO, C. 2011. Clinical fitting of CAD/CAM zirconia single crowns generated from digital intraoral impressions based on active wavefront sampling. Elsevier.
SEKARAN, U. 2006. Research methods for business: A skill building approach, John Wiley & Sons.
SEKARAN, U. & BOUGIE, R. 2010. Research methods for business: A skill building approach. Research methods for business: A skill building approach. Wiley.
230
SEKARAN, U. & BOUGIE, R. 2016. Research methods for business: A skill building approach, John Wiley & Sons.
SHABAN, S. S. A. 2008. Factors affecting the performance of construction projects in the Gaza Strip. Gaza Strip: Islamic University of Gaza.
SHAN, M., LE, Y., CHAN, A. P. & HU, Y. 2020a. Corruption in the Public Construction Sector.
SHAN, M., LE, Y., CHAN, A. P. & HU, Y. 2020b. Underlying Factors of Corruption in the Public Construction Sector. Corruption in the Public Construction Sector. Springer.
SHAN, M., LE, Y., YIU, K. T., CHAN, A. P. & HU, Y. 2017. Investigating the underlying factors of corruption in the public construction sector: Evidence from China. Science and engineering ethics, 23, 1643-1666.
SHAVER, J. M. 2005. Testing for mediating variables in management research: Concerns, implications, and alternative strategies. Journal of management, 31, 330-353.
SHIVAMBU, X. & THWALA, W. D. Assessment of the Delays in the Delivery of Public Sector Projects in South Africa. International Conference on Intelligent Human Systems Integration, 2019. Springer, 902-908.
SHROUT, P. E. & BOLGER, N. 2002. Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychological methods, 7, 422-445.
SHU HUI, W., OTHMAN, R. O., NORMAH, ABDUL RAHMAN, R. & HUSNA HARON, N. 2011. Procurement issues in Malaysia. International Journal of Public Sector Management, 24, 567-593.
SIDWELL, A., KENNEDY, R. & CHAN, A. 2002. Re-engineering the construction delivery process-report and case studies. Construction Industry Institute.
SIGNOR, R., LOVE, P., OLATUNJI, O., VALLIM, J. & RAUPP, A. 2017. Collusive bidding in Brazilian infrastructure projects. Proceedings of the Institution of Civil Engineers: Forensic Engineering, 170, 113-123.
SIGNOR, R., LOVE, P. E. & OLATUNJI, O. 2016a. Determining overpricing in Brazilian infrastructure projects: A forensic approach. Journal of Construction Engineering and Management, 142, 06016001.
SIGNOR, R., LOVE, P. E., OLATUNJI, O., MARCHIORI, F. F. & GRIPP, W. G. 2016b. A probabilistic method for forensic cost estimating of infrastructure projects. Applied Mathematical Modelling, 40, 9197-9211.
SIGNOR, R., LOVE, P. E., VALLIM, J. J. B., RAUPP, A. B. & OLATUNJI, O. 2019. It’s Not Collusion Unless You Get Caught: The Case of ‘Operation Car Wash’and Unearthing of a Cartel.
SINESILASSIE, E. G., TRIPATHI, K. K., TABISH, S. Z. S. & JHA, K. N. 2019. Modeling success factors for public construction projects with the SEM approach: engineer’s perspective. Engineering, Construction and Architectural Management.
SMOLDERS, J. & SHER, W. 2016. A Study of the Causation of Distressed Projects. SNYDER, C. S. 2013. A User's Manual to the PMBOK Guide, John Wiley & Sons. SOBEL, M. E. 1982. Asymptotic confidence intervals for indirect effects in structural equation
models. Sociological methodology, 13, 290-312. SOHAIL, M. & CAVILL, S. 2008. Accountability to prevent corruption in construction
projects. Journal of Construction Engineering and Management, 134, 729-738. SØREIDE, T. 2002. Corruption in public procurement. Causes, consequences and cures, Chr.
Michelsen Intitute. SPARROW, M. K. 2000. The Regulatory Craft: Controlling Risks, Solving Problems, and
Managing Problems. Washington, DC: Brookings Institution Press. STANSBURY, N. 2003. Anti-corruption initiative in the construction and engineering
industry. Transparency International (UK).
231
STOPHER, P. 2012. Collecting, managing, and assessing data using sample surveys, Cambridge University Press.
STYHRE, A. 2011. In the circuit of credibility: construction workers and the norms of ‘a good job’. Construction Management and Economics, 29, 199-209.
SU, Z.-X., WRIGHT, P. M. & ULRICH, M. D. 2018. Going beyond the SHRM paradigm: Examining four approaches to governing employees. Journal of Management, 44, 1598-1619.
SUTINEN, J. G. & KUPERAN, K. 1999. A socio-economic theory of regulatory compliance. International journal of social economics, 26, 174-193.
SUTRISNA, M., COOPER-COOKE, B., GOULDING, J. & EZCAN, V. 2018. Investigating the cost of offsite construction housing in Western Australia. International Journal of Housing Markets and Analysis.
SUTTON, R. I. & STAW, B. M. 1995. What theory is not. Administrative science quarterly, 371-384.
SWART, J. & HARCUP, J. 2013. ‘If I learn do we learn?’: The link between executive coaching and organizational learning. Management Learning, 44, 337-354.
SWEIS, R. B., S. M. & BISHARAT, L. S., G. J. 2014. Factors affecting contractor performance on public construction projects. Life Science Journal, 11, 28-39.
TABASSI, A. A., RAMLI, M., ROUFECHAEI, K. M. & TABASI, A. A. 2014. Team development and performance in construction design teams: an assessment of a hierarchical model with mediating effect of compensation. Construction Management and Economics, 32, 932-949.
TABISH, S. Z. S. & JHA, K. N. 2011. Identification and evaluation of success factors for public construction projects. Construction Management & Economics, 29, 809-823.
TABISH, S. Z. S. & JHA, K. N. 2015. Point of View Success factors for safety performance in public construction projects. Indian Concrete Journal, 89, 58-72.
TAYEH, B. A., AL HALLAQ, K., ALALOUL, W. S. & KUHAIL, A. R. 2018. Factors Affecting the Success of Construction Projects in Gaza Strip. The Open Civil Engineering Journal, 12.
TAYLOR, A. M. 2002. A century of purchasing-power parity. Review of economics and statistics, 84, 139-150.
TENDER, N. & ENTERPRISES, D. 2016. Institute Of Certified Public Accountants Of Kenya Tender Document For The Provision Of Cleaning And Garbage Collection.
TERRILL, M. & DANKS, L. 2016. Cost Overruns in Transportation Infrastructure Projects. A Grattan Institute, Melbourne, Victoria, Australia.
THAI, K. V. 2001. Public procurement re-examined. Journal of public procurement, 1, 9. THAI, K. V. 2008a. International handbook of public procurement, CRC Press. THAI, K. V. Measuring losses to public procurement corruption: The Uganda Case. 3rd
International Public Procurement Conference Proceedings,(August 28-30), 2008b. Citeseer.
THAI, K. V. 2010. Thai, 2010. Challenges in Public Procurement. Journal of Public Procurement, 1, 9-50.
TOPCHIY, D., SHATROVA, A. & YURGAYTIS, A. Integrated construction supervision as a tool to reduce the developer’s risks when implementing new and redevelopment projects. MATEC Web of Conferences, 2018. EDP Sciences, 05032.
TRACEY, D. & JOHANNESSON, M. 2008. Pride and prejudice: The human side of incentive theory. The American Economic Review, 98, 990-1008.
TREPTE, P.-A. 2004. Regulating Procurement. Understanding the ends and means of public procurement regulation.
232
TRIONFETTI, F. 2000. Discriminatory public procurement and international trade. The World Economy, 23, 57-76.
TUKAMUHABWA, B. R. 2012. Antecedents and consequences of public procurement non-compliance behavior. Journal of Economics and Behavioral Studies, 4, 34-46.
TURLEY, L. & PERERA, O. 2014. Implementing sustainable public procurement in South Africa: Where to start. International Institute of Sustainable Development. Retrieved April, 12, 2015.
UDECHUKWU, I. I. 2009. Correctional officer turnover: Of Maslow's needs hierarchy and Herzberg's motivation theory. Public Personnel Management, 38, 69-82.
UGANDA NATIONAL ROAD AUTHORITY 2014. End of year performance worshop. Kampala Uganda: Uganda National Roads Authority.https://www.unra.go.ug/en/welcome.
UGANDA NATIONAL ROAD AUTHORITY 2018. UNRA Performance Report for the Financial Year 2017-18. Kampala: Uganda National Roads Authority.https://www.unra.go.ug/en/notices/UNRA-NOTICES-11.
UGANDA NATIONAL ROADS AUTHORITY 2013. Annual performance report. Kampala, Uganda: UNRA.https://www.unra.go.ug/en/downloads/UNRA-Annual-Performance-Report-2011-12.
UGANDA ROAD FUND 2014. Monitoring & Evaluation Road Maintenance Performance. Kampala Uganda: Uganda Road Fund.http://roadfund.ug/research-surveys/monitoring-evaluation/.
UGANDA ROAD FUND 2015. Road Maintenance Monitoring Final Report Urban Authorities
Kampala,Uganda: Uganda Road Fund.http://demo.omnitech.co.ug/urf/wp-content/uploads/2018/03/URF-Annual-Report-FY-2013-14.pdf.
UM, K.-H. & KIM, S.-M. 2018. Collaboration and opportunism as mediators of the relationship between NPD project uncertainty and NPD project performance. International Journal of Project Management, 36, 659-672.
URBACH, N. & AHLEMANN, F. 2010. Structural equation modeling in information systems research using partial least squares. JITTA: Journal of Information Technology Theory and Application, 11, 5.
VAN SLYKE, D. M. 2007. Agents or stewards: Using theory to understand the government-nonprofit social service contracting relationship. Journal of Public Administration Research and Theory, 17, 157-187.
VAN SNELLENBERG, T. & VAN DE PEPPEL, R. 2002. Perspectives on compliance: non‐compliance with environmental licences in the Netherlands. European Environment, 12, 131-148.
VENKATESH, R., KOHLI, A. K. & ZALTMAN, G. 1995. Influence strategies in buying centers. The Journal of Marketing, 71-82.
VERDEAUX, J.-J. 2003. Public procurement in the European Union and in the United States: a comparative study. Public contract law journal, 713-738.
VOLINTIRU, C. & OLIVAS OSUNA, J. J. 2018. Preventing corruption at local and regional level in South Mediterranean countries.
WACHTER, K. 2003. Rethinking Maslow's needs. Journal of Family and Consumer Sciences, 95, 68.
WALFISH, S. 2006. A review of statistical outlier methods. Pharmaceutical technology, 30, 82.
WALKER & LLOYD-WALKER, M. B. 2015. Collaborative project procurement arrangements.
233
WALL, J. & AHMED, V. 2008. Use of a simulation game in delivering blended lifelong learning in the construction industry–Opportunities and Challenges. Computers & Education, 50, 1383-1393.
WATSON, T. 2002. Professions and Professionalism-Should We Jump Off the Bandwagon, Better to Study Where It Is Going? International Studies of Management & Organization, 32, 93-105.
WHETTEN, D. A. 1989. What constitutes a theoretical contribution? Academy of management review, 14, 490-495.
WHITE, D. & FORTUNE, J. 2002. Current practice in project management—An empirical study. International journal of project management, 20, 1-11.
WIRICK, D. W. The Challenges of Public‐Sector Project Management and the Coming Storm. Public-Sector Project Management: Meeting the Challenges and Achieving Results, 2009. Wiley Online Library, 1-15.
WITTIG, W. 1999. Building Value through Procurement: A Focus on Africa. Paper presented to the 9th International Anti-Corruption Conference.[On-line].
WITTING, W. 2005. Linking islands of integrity to promote good governance in public procurement: Issues for considerations. Fighting Corruption and Promoting Integrity in Public Procurement, 109-14.
WONG, K. K.-K. 2013. Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24, 1-32.
WOO, S., CHANG, C.-K., LEE, S. & CHO, C.-S. 2019. Comparison of Efficiency and Satisfaction Level on Different Construction Management Methods for Public Construction Projects in Korea. KSCE Journal of Civil Engineering, 1-9.
WOOD, M. & ROSS-KERR, J. 2011. Basic Steps in Planning Nursing Research from Question to Proposal. 2011. Sudbury, MA: Jones & Bartlett Publishers.
WORSHAM, J., EISNER, M. A. & RINGQUIST, E. J. 1997. Assessing the assumptions: A critical analysis of agency theory. Administration & Society, 28, 419-440.
WRIGHT, P., MUKHERJI, A. & KROLL, M. J. 2001. A reexamination of agency theory assumptions: extensions and extrapolations. The Journal of Socio-Economics, 30, 413-429.
XIAO, H. & PROVERBS, D. 2003. Factors influencing contractor performance: an international investigation. Engineering, Construction and Architectural Management, 10, 322-332.
YIN, R. K. 2003. Case study research design and methods third edition. Applied social research methods series, 5.
YIN, R. K. 2006. Mixed methods research: Are the methods genuinely integrated or merely parallel? Research in the Schools, 13.
ZADAWA, A. N., HUSSIN, A. A. & OSMADI, A. 2015. Determinants Of Compliance With Public Procurement Guidelines In The Nigerian Construction Industry. Jurnal Teknologi, 75.
ZADAWA, A. N., HUSSIN, A. A. & OSMADI, A. 2018a. The Mediating Effects Of Awareness On The Relationship Between Procurement Manual Compliance’s Barriers And Cost Performance Of Construction Projects. Planning Malaysia Journal, 16.
ZADAWA, A. N., HUSSIN, A. A. & OSMADI, A. 2018b. Mediating Effects of Enforcement on Public Procurement Guidelines' Compliance Barriers and Cost Performance of Construction Projects in Nigerian Federal Universities: A Process Macro Approach. Journal of Construction in Developing Countries, 23, 81-102.
ZHANG, B., LE, Y., XIA, B. & SKITMORE, M. 2016. Causes of business-to-government corruption in the tendering process in China. Journal of Management in Engineering, 33, 05016022.
234
ZHAO, X., LYNCH JR, J. G. & CHEN, Q. 2010. Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of consumer research, 37, 197-206.
ZHOU, C., LUO, H., FANG, W., WEI, R. & DING, L. 2019. Cyber-physical-system-based safety monitoring for blind hoisting with the internet of things: A case study. Automation in Construction, 97, 138-150.
ZOLFANI, S. H., POURHOSSEIN, M., YAZDANI, M. & ZAVADSKAS, E. K. 2018. Evaluating construction projects of hotels based on environmental sustainability with MCDM framework. Alexandria engineering journal, 57, 357-365.
ZSIDISIN, G. A. & ELLRAM, L. M. 2003. An agency theory investigation of supply risk m anagement. Journal of supply chain management, 39, 15-27.
ZSIDISIN, G. A. & SMITH, M. E. 2005. Managing supply risk with early supplier involvement: a case study and research propositions. Journal of supply chain management, 41, 44-57.
ZSIDISIN*, G. A., MELNYK, S. A. & RAGATZ, G. L. 2005. An institutional theory perspective of business continuity planning for purchasing and supply management. International journal of production research, 43, 3401-3420.
ZUBCIC, J. & SIMS, R. 2011. Examining the link between enforcement activity and corporate compliance by Australian companies and the implications for regulators. International Journal of Law and Management, 53, 299-308.
235
APPENDICES Appendix A. Exchange rate (As at 21/11/2016)
1 UGX = 0.00038 AU$, 1 US$ = 1.360 AU$, 1Tsh = 0.00062 AU$ and 1ksh = 0.013 AU$.
Appendix B. Publications
Extracted papers from the thesis for publication in peer reviewed journal
1. Compliance within a regulatory framework in implementing public road construction
projects: Journal of Construction Economics and Building.(Published already)
2. Success factors for implementing Uganda’s public road construction projects:
International Journal of Construction Management. (Published already)
3. Compliance mediating role within road construction regulatory framework: Journal of
Public Procurement. (Accepted for publication)
Published refereed journal articles
1. Compliance within a regulatory framework in implementing public road construction
projects: Journal of Construction Economics and Building.
2. Success factors for implementing Uganda’s public road construction projects:
International Journal of Construction Management.
3. Lean manufacturing and profitability of manufacturing firms in Uganda: European
Journal of Business and Management.
4. Outsourcing practices and profitability levels of manufacturing firms in Uganda:
European Journal of Business and Management.
5. Risk management and profitability of manufacturing firms in Uganda: Industrial
Engineering Letters.
6. Testing for volatility and market efficiency of Uganda securities exchange: Journal of
Research in Business, Economics and Management.
236
Appendix C. Questionnaire
Dear respondent
This questionnaire is to collect data on an on-going PhD study at University of Newcastle, Faculty of Engineering and Built Environment, School of Architecture and Built Environment, Australia.
The study is on compliance and regulatory framework in public procurement road construction projects in Uganda. You are selected to participate in this study as one of the respondents.
Please allow approximately twenty (20) minutes of your time to complete the questionnaire. Your answers will be treated with utmost confidentiality. Note that information provided here is only for academic purpose and will be confidential. Please rate/indicate/tick () appropriately your response in respect to level of agreement with the statements below:
A. Familiarity with regulatory framework 1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly
Agree 1 2 3 4 5
F1 The procurement regulatory framework is written in the way that is easily understood.
F2 In road project implementation, familiarity with the procurement regulatory framework is the basic requirement for staff.
F3 In road project implementation, only those familiar with the regulatory framework carry out procurement tasks.
F4 I frequently participate in training programs that aims to increase my familiarity with the regulatory framework.
F5 I am familiar with the public procurement regulatory framework in road construction projects.
F6 I have worked on similar road construction projects for a long time.
F7 I am familiar with road construction implementation processes.
F8 I have intimate understanding of road construction implementation strategies.
237
F9 Inadequate knowledge with the regulatory framework negatively affects compliance in road construction projects.
F10 Road construction project implementation team have limited access to information to carry out their work.
F11 I can interpret all sections of the regulatory framework on road construction projects.
F12 I have sufficient knowledge about the objectives of established regulatory framework.
F13 Only staff with appropriate academic qualifications work on applicable road construction projects.
F14 Procurement officers and contract committee members should have knowledge on procedures for project implementation.
F15 I have been made awareness of the regulatory framework governing the project implementation.
B. Monitoring activities
1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree 1 2 3 4 5
M1 There are regular reports on activities/targets achieved on road construction projects.
M2 Key road project implementation targets are reported on regular intervals.
M3 I provide extensive information regarding project procurement practices to my supervisors.
M4 There are frequent inspections to check whether I record project progress activities on time.
M5 Road construction projects are supervised by a contracts committee.
M6 I am frequently asked to report on my activities.
M7 I always receive directives on how to carry out road project implementation.
M8 I am assessed based on reported project implementation performance.
M9 Project performance reports are verified through physical on site evaluations.
M10 Management monitors the extent road implementation activities are progressing in line with regulatory framework.
238
M11 There are frequent inspections to determine whether I comply with regulatory framework.
M12 There are frequent inspections to determine whether the project is implemented within established regulatory framework.
M13 There are frequent inspections to determine whether I ensure timely completion of the road construction project.
M14 There are frequent inspections to determine whether I apply proper storage methods to prevent damage of road construction materials.
M15 There are frequent inspections to determine whether I apply proper storage methods to prevent theft of road construction materials.
M16 There are frequent inspections to determine whether any variations in project implementation is approved by relevant authorities.
C. Professionalism 1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly
Agree 1 2 3 4 5
PR1 I am always under pressure to deviate from road project implementation process.
PR2 Procurement officers are guided by professional code in performing procurement tasks.
PR3 Staff undertaking road construction project exercise high level of professional integrity.
PR4 I regularly participate in procurement training programs aimed at increasing my professional behavior.
PR5 The level of professionalism amongst project team affects positively on compliance with regulatory framework.
PR6 The level of professionalism amongst project team affects negatively on compliance with regulatory framework.
PR7 Pressure from interested parties on road construction projects influence my compliance with public procurement regulatory framework.
PR8 As long as my objectives are achieved, I am less concerned about complying with public procurement regulatory framework.
PR9 Training program conducted is related to public procurement process in general.
PR10 Training program conducted is related to road construction implementation process and procedures.
PR11 There is training on each particular road construction project being undertaken.
239
PR12 Despite experience, procurement staff must have awareness workshops on public procurement.
PR13 Staff on road implementation have appropriate competence to handle compliance processes.
PR14 Public procurement staff on road construction project lack proper training to comply with implementation procedures.
PR15 Implementation team on road construction is knowledgeable in dealing with their respective tasks during construction process.
PR16 I regularly participate in training programs aimed at increasing my procurement knowledge.
PR17 Training in a timely manner is provided to staff on the road construction projects.
PR18 Road construction team exercise professional judgement in decision making during construction process.
PR19 Road construction staff have practical experience in road construction.
PR20 Staff on the road construction project have required expertise.
PR21 Staff undertaking road construction projects exercise high level of confidentiality.
PR22 Confidentiality is enforced by team throughout project implementation.
PR23 Public procurement officers ought to have certified professional training like CIPS.
PR24 Staff hold appropriate qualifications required by their professional bodies e.g. IPPU, CIPS, Building & Construction association etc.
D. Sanctions
1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree
1 2 3 4 5
S1 There is penalty for non-compliance with regulatory framework.
S2 I am concerned that my specific benefits will discontinue for non-compliance.
S3 Uganda National Roads Authority (UNRA) enforce proportional and timely administrative sanction e.g. warnings, suspension, disqualification, dismissal and fines on errant officers.
240
S4 Sanctions are effected immediately after a violation of the regulatory framework is detected.
S5 UNRA punishes contractors when they don’t meet specifications during road construction.
S6 UNRA punishes contractors when they don’t follow the regulatory framework during road construction.
S7 Contractors are penalized without any warning for non-compliance.
S8 Sanctions are implemented in secret.
S9 Sanctions with negative consequences are imposed on contractors who fail to meet their obligations.
S10 It is an organizational policy to take action with negative consequences on staff who fail to meet their obligations.
S11 I am sanctioned for not complying with the regulatory framework.
S12 I am provided reasons for implemented penalties.
S13 All stipulated sanctions are known by staff involved in road construction projects.
S14 Failure to comply with public procurement process on road construction will attract retaliation from authorities.
S15 Stipulated penalties in public procurement regulatory framework provide fear of violating it.
S16 I weigh benefits against possible negative outcomes of complying with the regulatory framework.
E. Perceived inefficiency of Public Procurement Regulatory Framework
1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree
1 2 3 4 5
PI1 There is ban on negotiations between contractor and UNRA team during road construction.
PI2 There is ban on contract extension beyond agreed schedule.
PI3 There is ban on excluding underperforming contractors in road construction.
PI4 I need legal assistance during project implementation of road construction process.
241
F. Contractor resistance
1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree 1 2 3 4 5
CR1 Contractors are ready to take action against bad decision to achieve compliance.
CR2 Contractor’s knowledge on procurement process helps in controlling public officers from making bad decisions.
CR3 Public officers fear to be exposed by contractors if they don’t follow the correct procurement procedures.
G. Compliance with regulatory framework
1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree 1 2 3 4 5
CP1 Road construction projects are implemented without proper authority.
CP2 Road construction projects are not delivered on time.
CP3 Road implementation transactions are not recorded on time.
CP4 There is always damage or loss of road construction materials during project implementation.
CP5 Road implementation transactions are paid through invoices as per Government policy.
CP6 Road implementation transactions are paid through imprest as per Government policy.
CP7 Adherence to organizational specific directives entails breach of public procurement regulatory framework.
CP8 Particular road construction projects are given conflicting objectives.
CP9 Road construction procedures match with applied public procurement regulatory framework.
CP10 It is easy to achieve road construction project objectives without complying with public procurement regulatory framework.
CP11 I comply with public procurement regulatory framework during road construction project implementation.
242
H. Project success 1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree 1 2 3 4 5
PS1 Road construction projects are implemented in accordance to specifications.
PS2 Road construction projects are completed within schedule.
PS3 Road construction projects are completed within budget.
PS4 Compliance with public procurement regulatory framework leads to public road project success.
243
THANK YOU FOR YOUR CO-OPERATION.
I. Background information
Please fill in or use a tick ( ) to indicate your response where applicable.
1 Your Organization’s Name
MoWT UNRA URF PPDA Contractor
2 Highest education PhD
Master’s degree Bachelor’s degree Diploma Secondary school Primary school Others (please specify) ………………………………………………...
3 Professional training (e.g.)
CIPS CILT ACCA CPA Others (please specify)
….…………………….………
4 Indicate your gender. Female Male
5 Tick the age range which represents you. Below 30
31-40 41-50 Above 50
6 What is your title/position in this organization?
7 How many years have you been working in your current position?
Number of years
8 How many years have you been working in this organization? Number of years
9 How many employees work for this department? Number of employees
10a Are you a registered member of any professional body? Yes No
10b If Yes, name the professional body to which you are registered and category of your membership.
244
Appendix D. RESEARCH PERMIT: HUMAN RESEARCH ETHICS COMMITTEE
Notification of Expedited Approval
To Chief Investigator or Project Supervisor: Professor Peter Davis
Cc Co-investigators / Research Students: Mr. Noah Mwelu, Dr Yongjian Ke
Re Protocol: COMPLIANCE AND REGULATORY FRAMEWORK IN PUBLIC
PROCUREMENT ROAD CONSTRUCTION PROJECTS BY UGANDA NATIONAL
ROAD AUTHORITY
Date: 24-Apr-2017
Reference No: H-2017-0056
Date of Initial Approval: 24-Apr-2017
Thank you for your Response to Conditional Approval (minor amendments) submission to the
Human Research Ethics Committee (HREC) seeking approval in relation to the above protocol.
Your submission was considered under Expedited review by the Ethics Administrator.
I am pleased to advise that the decision on your submission is Approved effective 24-Apr-2017.
In approving this protocol, the Human Research Ethics Committee (HREC) is of the opinion
that the project complies with the provisions contained in the National Statement on Ethical
Conduct in Human Research, 2007, and the requirements within this University relating to
human research.
Approval will remain valid subject to the submission, and satisfactory assessment, of annual
progress reports. If the approval of an External HREC has been "noted" the approval period
is as determined by that HREC.
The full Committee will be asked to ratify this decision at its next scheduled meeting. A formal
Certificate of Approval will be available upon request. Your approval number is H-2017-0056.
If the research requires the use of an Information Statement, ensure this number is inserted
at the relevant point in the Complaints paragraph prior to distribution to potential
participants You may then proceed with the research.
245
Conditions of Approval
This approval has been granted subject to you complying with the requirements for Monitoring
of Progress, Reporting of Adverse Events, and Variations to the Approved Protocol as detailed
below.
PLEASE NOTE:
In the case where the HREC has "noted" the approval of an External HREC, progress reports
and reports of adverse events are to be submitted to the External HREC only. In the case of
Variations to the approved protocol, or a Renewal of approval, you will apply to the External
HREC for approval in the first instance and then Register that approval with the University's
HREC.
Monitoring of Progress
Other than above, the University is obliged to monitor the progress of research projects
involving human participants to ensure that they are conducted according to the protocol as
approved by the HREC. A progress report is required on an annual basis. Continuation of your
HREC approval for this project is conditional upon receipt, and satisfactory assessment, of
annual progress reports. You will be advised when a report is due.
Reporting of Adverse Events
1. It is the responsibility of the person first named on this Approval Advice to report
adverse events.
2. Adverse events, however minor, must be recorded by the investigator as observed by the
investigator or as volunteered by a participant in the research. Full details are to be
documented, whether or not the investigator, or his/her deputies, consider the event to
be related to the research substance or procedure.
3. Serious or unforeseen adverse events that occur during the research or within six (6)
months of completion of the research, must be reported by the person first named on the
Approval Advice to the (HREC) by way of the Adverse Event Report form (via RIMS at
https://rims.newcastle.edu.au/login.asp) within 72 hours of the occurrence of the event
or the investigator receiving advice of the event.
4. Serious adverse events are defined as:
246
Causing death, life threatening or serious disability. Causing or prolonging hospitalisation.
Overdoses, cancers, congenital abnormalities, tissue damage, whether or not they are judged
to be caused by the investigational agent or procedure.
Causing psycho-social and/or financial harm. This covers everything from perceived invasion
of privacy, breach of confidentiality, or the diminution of social reputation, to the creation of
psychological fears and trauma.
Any other event which might affect the continued ethical acceptability of the project.
5. Reports of adverse events must include: Participant's study identification number; date
of birth;
date of entry into the study; treatment arm (if applicable); date of event;
details of event;
the investigator's opinion as to whether the event is related to the research procedures; and
action taken in response to the event.
6. Adverse events which do not fall within the definition of serious or unexpected, including
those reported from other sites involved in the research, are to be reported in detail at
the time of the annual progress report to the HREC.
Variations to approved protocol
If you wish to change, or deviate from, the approved protocol, you will need to submit an
Application for Variation to Approved Human Research (via RIMS at
https://rims.newcastle.edu.au/login.asp). Variations may include, but are not limited to,
changes or additions to investigators, study design, study population, number of participants,
methods of recruitment, or participant information/consent documentation. Variations must
be approved by the (HREC) before they are implemented except when Registering an
approval of a variation from an external HREC which has been designated the lead HREC, in
which case you may proceed as soon as you receive an acknowledgement of your Registration.
Linkage of ethics approval to a new Grant
HREC approvals cannot be assigned to a new grant or award (ie those that were not identified
on the application for ethics approval) without confirmation of the approval from the Human
Research Ethics Officer on behalf of the HREC.
247
Best wishes for a successful project.
Associate Professor Helen Warren-Forward
Chair, Human Research Ethics Committee
For communications and enquiries:
Human Research Ethics Administration
Research & Innovation Services Research Integrity Unit
NIER, Block C
The University of Newcastle Callaghan NSW 2308
T +61 2 492 17894
RIMS website - https://RIMS.newcastle.edu.au/login.asp
Linked University of Newcastle administered funding:
Funding body Funding project title First named
investigator
Grant Ref
248
Appendix E. Consent Forms
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
Compliance and regulatory framework in public procurement road construction
projects by Uganda national road authority
Document Version 1; Dated 18 June 2017
Dear Professor Mark Rubarenzya,
It is with great pleasure that I write to you after the email introduction from our University student and ambassador, Noah Mwelu. In the first instance, I would like to apologise for not responding sooner to your queries arising from your meeting with Noah on 15 June 2017. However, I am sure you will appreciate there are matters that I am required to assess and check when our University students are working remotely from campus in Australia and questions arise.
The survey that is being carried out by Noah is not focused only on UNRA, but a broad cross section of the road construction industry in Uganda. This may be observed with reference to the questionnaire that identifies five strata (please see Page7 of the proposal).
UNRA is believed to be a key respondent because it is core in implementing national road projects and it is crucial to the structure of national roads construction and management. It is the implementing authority for national roads that account for the highest percentage of the road network in Uganda. (please see page 3, 7 and 31 of the proposal).
Whilst the questionnaire is designed to obtain information about that which currently happens, Noah’s overall research question is focused on obtaining benefits for the Ugandan economy, via its procurement and project delivery processes driven by individual companies that work within your regulatory frameworks. In particular I expect that the outcomes of this research will be helpful in developing new policy and governance processes.
This study will establish compliance factors and their impact on road construction performance to devise appropriate means for successful performance (mitigation strategies). This will also enable stakeholders to identify areas for performance improvements hence, successful delivery of road construction projects that achieve value for money.
It is my obligation and as per University of Newcastle research ethics to treat all responses with utmost confidentiality. Only aggregated and anonymous data that will be described in Noah’s thesis document. Therefore, any outputs and all research papers arising from this work will also be treated in the same confidential way. No individual organisations will be identified in any way.
Professor Peter Davis School of Architecture and Built Environment Faculty of Engineering and Built Environment University of Newcastle [email protected]
Noah Mwelu School of Architecture and Built Environment Faculty of Engineering and Built Environment University of Newcastle +61469881060/[email protected]
270
Given the above, Noah is appreciative of your assistance in obtaining a good response of around one hundred and two UNRA staff in the Directorate of Procurement, Directorate of Legal, Directorate of Planning, Human Resource department, Monitoring and evaluation, Finance and Administration and Project managers’ works.
At your request, I have attached the following documents;
A PDF copy of the questionnaire that will be distributed to your staff
A PDF copy of the University of Newcastle approved organisational consent form
A PDF copy of Noah’s research proposal that indicates the necessity of UNRA participating toenable a good research outcome.
Yours Sincerely,
Peter Davis Chair of Construction Management Tel +61 2 4985 4315Fax +61 2 4921 6913Mob +61(0) 418 925 343
EMAILS FROM HEAD OF RESEARCH AND DEVELOPMENT UGANDA NATIONAL ROADS AUTHORITY
[email protected] Fri 6/16/2017, 10:53 PM Dear Noah,
I am yet to hear from Peter but at least you are familiar with the process of requesting for information from a public institution. When you have all the requisite information then you can write again to the Executive Director with your complete requests. My office is beneath that of the ED.
Kind regards,
Dr. MARK HENRY RUBARENZYA │Head - Research and Development Directorate of Network Planning and Engineering │Uganda National Roads Authority Plot 3-5 New Port Bell Road, UAP Nakawa business park Block C & D P.O.Box 28487 Kampala, Uganda Office: +256312233340 │ Mobile: +256 782 163508 http://www.unra.go.ug/ Twitter:@UNRA_UG Facebook:UNRApage
UNRA - Connecting Uganda
271
NOTE: This e-mail message is subject to the UNRA Email Disclaimer @ https://www.unra.go.ug/index.php/131-uncategorised/509-disclaimer [email protected] Wed 6/14/2017, 11:46 PMNoah Mwelu;[email protected];[email protected] Inbox You forwarded this message on 6/15/2017 8:05 PM Dear Noah, following on our phone conversation this afternoon, I invite you to a meeting in UNRA on 15 June 2017 at 11:00am. The subject of the meeting will be your letter dated 12 June 2017, in which you indicate the selection of UNRA to participate in a study that you are undertaking on 'Compliance and regulatory framework in public procurement road construction projects in Uganda'. Kind regards, Dr. MARK HENRY RUBARENZYA │Head - Research and Development Directorate of Network Planning and Engineering │Uganda National Roads Authority Plot 3-5 New Port Bell Road, UAP Nakawa business park Block C & D P.O.Box 28487 Kampala, Uganda Office: +256312233340 │ Mobile: +256 782 163508 http://www.unra.go.ug/ Twitter:@UNRA_UG Facebook:UNRApage UNRA - Connecting Uganda NOTE: This e-mail message is subject to the UNRA Email Disclaimer @ https://www.unra.go.ug/index.php/131-uncategorised/509-disclaimer NOTE: This e-mail message is subject to the UNRA Email Disclaimer @ https://www.unra.go.ug/index.php/131-uncategorised/509-disclaimer
272
Appendix F. Outer Loadings
Indicato
rs
Original Sample
(O)
Sample Mean
(M)
Standard Deviation
(STDEV)
T Statistics
(|O/STDEV|)
P
Values
CP1 0.895 0.892 0.018 49.922 0.000
CP10 0.727 0.721 0.056 12.964 0.000
CP2 0.663 0.664 0.073 9.065 0.000
CP3 0.719 0.720 0.064 11.222 0.000
CR1 0.856 0.854 0.044 19.255 0.000
CR2 0.779 0.774 0.064 12.226 0.000
F1 0.746 0.741 0.063 11.885 0.000
F13 0.675 0.669 0.072 9.389 0.000
F3 0.818 0.815 0.041 19.934 0.000
M13 0.597 0.590 0.092 6.515 0.000
M14 0.858 0.856 0.033 26.044 0.000
M15 0.820 0.818 0.041 20.125 0.000
M4 0.675 0.674 0.054 12.602 0.000
PI1 0.730 0.724 0.069 10.614 0.000
PI2 0.845 0.845 0.029 29.381 0.000
PI3 0.742 0.740 0.054 13.825 0.000
PR18 0.682 0.679 0.055 12.433 0.000
PR19 0.686 0.682 0.062 11.036 0.000
PR20 0.714 0.710 0.054 13.237 0.000
PR21 0.791 0.790 0.032 24.654 0.000
273
PR3 0.690 0.690 0.057 12.200 0.000
PS1 0.728 0.726 0.049 14.941 0.000
PS2 0.883 0.884 0.017 50.781 0.000
PS3 0.858 0.857 0.027 31.667 0.000
S7 0.812 0.809 0.043 19.055 0.000
S8 0.862 0.861 0.030 28.486 0.000
S9 0.569 0.557 0.106 5.369 0.000
274
Appendix G.
Table 1.3: Constructs regrouping
Category Major factors Sub-factors Comment Reference
Environmental factors
Compliance with Public procurement regulatory framework
Regulations
Laws
Rules
Policies
Procedures
Instructions
Public procurement regulatory framework will be a collective term for regulations, laws, rules, policies, procedures, directives and formal instructions used in this study to reflect compliance as our major dependent variable.
Note: Lack of compliance will encompass all issues including but not limited to procurement/project irregularities, corruption, unethical behaviours among others.
Gelderman et al. (2006), Eyaa & Oluka (2011), Mwakibinga & Buvik (2013), Agaba & Shipman (2007), Basheka & Sabiiti (2011), Golden & Picci (2006), Kulp et al (2006), Obanda (2010), Sutinen & Kuperan (1999), Fleisher (1991), Kauppi & Van Raaij (2015), Rokkan & Buvik (2008 & 2003), Rutherford, Buchholtz & Brown (2007), Tukamuhabwa (2012), Shu Hui et al (2011), Migosi, Ombki & Evusa (2013), Peprah (2015), Osei-Tutu et al. (2011), Boer & Telgen (1998), Zadawa et al. (2015), Karjalainen, Kemppainen & Van Raaij (2009), Payan & McFarland (2005), Keith, Jackson Jr & Crosby (1990), Venkatesh, Kohli & Zaltman (1995), Zubcic & Sims (2011), Adusei & Awunyo-Victor (2015), Ojo & Gbadebo (2014), Kakitahi et al. (2015), Chan & Owusu (2017), Shan et al, (2016), Owusu et al (2017).
Perceived inefficiency of regulatory framework
Weakness/loopholes
Clarity
Contradictions
This factor will be used in the study and it refers to stakeholder’s view on usefulness or effectives of regulatory framework in achieving intended objectives
Gelderman et al. (2006)
275
Category Major factors Sub-factors Comment Reference
Political interference External influence Influence by politicians, top management. This will be covered under professionalism
Adusei & Awunyo-Victor (2015), Ojo & Gbadebo (2014).
Organizational factors
Monitoring activities
Monitoring
Supervision
Coordination
Inspections
Audit
Monitoring activities will be used in this study and will collectively cover monitoring, supervision, inspections, audits and coordination.
Mwakibinga & Buvik (2013), Agaba & Shipman (2007), Golden & Picci (2006), Kulp et al (2006), Sutinen & Kuperan (1999), Fleisher (1991), Kauppi & Van Raaij (2015), Rokkan & Buvik (2008 & 2003), Rutherford, Buchholtz & Brown (2007), Van Slyke (2007), Peprah (2015), Boer & Telgen (1998), Adusei & Awunyo-Victor (2015), Bartle &Korosec (2003), Tabish & Jha (2015 & 2011), Ameyaw et al 2017.
Organizational incentives
Sanctions (Negative incentives) Sanctions will be used in this study and will cover punishments including penalties, demotion, dismissal, warning among others
Eyaa & Oluka (2011), Mwakibinga & Buvik (2013), Gelderman et al. (2010), Agaba & Shipman (2007), Rokkan & Buvik (2008 & 2003), Rutherford, Buchholtz & Brown (2007), Payan & McFarland (2005), Keith, Jackson Jr & Crosby (1990), Zubcic & Sims (2011), Ameyaw et al 2017, Chan & Owusu (2017).
Rewards (Positive incentives) Rewards will not be used in this study and involves promotion, recognition etc.
Fleisher (1991), Rutherford, Buchholtz & Brown (2007), Van Slyke (2007).Gelderman et al. (2006)
Institutional factors
Monitoring
Supervision
This factor will not be used in this study as it is reflected under monitoring activities and professionalism
Eyaa & Oluka (2011), Guy (2000)
276
Category Major factors Sub-factors Comment Reference
Influence peddling
Organizational pressure
Enforcement mechanism
Incentives
This is part of governance mechanism that will be enforced through sanctions
Gelderman et al. (2010), Braun’s (2003), Van Shellenberg &Van de peppel (2002)
Organizational size Number of staff
Complexity in controlling
Uncertainty of procurement orders management
This factor will not be used in the study and refers to size of an organization in relationship to procurement magnitude. It is left out because road construction is implemented by only one organization meaning that it will not be required to consider organizational size since we are not comparing with other competing firms in road construction project implementation.
Mwakibinga & Buvik (2013), Kulp et al. (2006), Langbein (2000), Ameyaw et al (2017), Chan & Owusu (2017).
Project factors Contractor’s resistance
Familiarity with regulatory framework
Report cases of non-compliance
Willingness to take action
Power of remedies
This factor will be used in this study and it refers to contractor’s knowledge of regulatory framework to help them resist public officer’s unethical decisions that are not in line with regulatory framework during project implementation
Gelderman et al. (2010 & 2006), Pachnou (2005), Braun’s (2003)
277
Category Major factors Sub-factors Comment Reference
Project success (Performance)
Cost
Quality
Time
Client satisfaction
Safety
Dispute occurrence
Scope clarity
Security
Weather
This factor will be used in this study as a final dependent variable. It will be a result of compliance with regulatory framework and will be measured through client’s satisfaction. client satisfaction is selected because it overrides other factors of quality, cost, time, safety among others (Dvir & lechler, 2004)
Neeraj Jha & Misra (2007), Chan & Chan (2004), Chan (2001), Atkinson (1999), Lim & Mohamed (1999), Mbabazi et al. (2015), Alinaitwe, Mwakali & Hansson (2007), Enshassi, Mohamed & Abushaban (2009), Ntayi, Rooks, Eyaa & Qian (2010), Kakwezi & Nyeko (2010), Basheka & Mugabira (2008). Atkinson (1999), Tabish & Jha (2015 & 2011), Dvir & Lechler (2004), Pinto & Mantel (1990), Bartle & Korosec (2003), Agaba & Shipman (2007), Rendon (20010), Iyer & Jha (2005), Jacobson & Ok choi (2008), Ameyaw et al 2017.
Contract management
Information sharing
Monitoring
Flexibility
Leadership/cooperation
Technical knowledge
This factor is the overall idea of project implementation. It will not stand on its own as it is being measured within factors of our study
Rendon (20010), Kakwezi & Nyeko (2010), Bartle & Korosec (2003), Agaba & Shipman (2007), Iyer & Jha (2005), Jacobson & Ok choi (2008), Ntayi, Rooks, Eyaa & Qian (2010), Tabish & Jha (2015 & 2011), Kingsford & Chan 2018, Ameyaw et al 2017.
278
Category Major factors Sub-factors Comment Reference
Record management
Record keeping This factor will not be used in this study as it is among items measured under compliance and monitoring activities
Mwakibinga & Buvik (2013), Basheka & Sabiiti (2011), Chan & Owusu (2017).
Individual factors
Familiarity with regulatory framework
Procurement knowledge
Clarity of regulatory framework & project scope
Familiarity with applications
This factor is selected for this study and it refers to one’s knowledge over regulatory framework, project scope and activities to be performed. It is beyond academic qualification and professionalism as a whole.
Gelderman et al, (2006), Eyaa & Oluka (2011), Mwakibinga & Buvik (2013), Migosi, Ombki & Evusa (2013), Peprah (2015), Boer & Telgen (1998), Zadawa et al (2015), Adusei & Awunyo-Victor (2015). Obanda (2010), Tukamuhabwa (2012),
Professionalism
Capacity building
Training
Skills
Experience
Qualifications
Procurement knowledge
Confidentiality
Integrity
Corruption
Professionalism will be used in this study and measured through competence, integrity, confidentiality and professional membership that summarizes all other professional sub-factors.
Eyaa & Oluka (2011), Mwakibinga & Buvik (2013), Agaba & Shipman (2007), Obanda (2010), Kaupi & Van Raaij (2015), Bartle & Korosec (2003), Tukamuhabwa (2012), Migosi, Ombki & Evusa (2013), Osei-Tutu et al (2011), Boer & Telgen (1998), Basheka & Mugabira (2008). Shu Hui et al (2011), Ntayi & Eyaa (2010), Ntayi et al. (2009), Peprah (2015), Zadawa et al (2015), Kakitahi et al. (2015), Kalubanga, Kakwezi & Kaise (2013), Ntayi, Rooks, Eyaa & Qian (2010), Thai (2008), Duperouzel (2003), Ntayi, Byabashaija, Eyaa, Ngoma & Muliira (2010), You (2005), Karjalainen, Kemppainen & Van Raaij (2009). Owusu & Chan (2017), le et al 2014, Zhang et al 2016, Kingsford & Chan (2018), Ameyaw et al( 2017), Chan & Owusu (2017).
279
Category Major factors Sub-factors Comment Reference
irregularities
Ethical code/behaviour
Professional membership,
conflict of interest
political interference
Perceived gain
Source: Researcher
280
Appendix H.
Table 3.1. Showing literature gap
Literature/Research Gap
Author Agency Theory
Quantitative/Cross-sectional
Compliance
Project success
Monitoring
Familiarity
Professionalism
Sanctions
Public procurement (Supplies & Service)
Construction projects
Road construction projects
Gelderman et al (2006)
Eyaa & Oluka, (2011)
Mwakibinga & Buvik, (2013)
Boer & Telgen, (1998)
Migosi, Ombki & Evusa (2013)
Peprah, (2015)
Tukamuhabwa, (2012)
Zadawa et al, (2015)
281
Literature/Research Gap
Author Agency Theory
Quantitative/Cross-sectional
Compliance
Project success
Monitoring
Familiarity
Professionalism
Sanctions
Public procurement (Supplies & Service)
Construction projects
Road construction projects
Adusei & Awunyo-Victor (2015)
Obanda, (2010)
Rokkan & Buvik (2009 & 2003)
Kulp et al, (2006)
Jha & Misra, (2007)
Dvir & Lechler (2004)
Lim & Mohamed, (1999)
Chan & Chan, (2004)
Atkinson, (1999)
282
Literature/Research Gap
Author Agency Theory
Quantitative/Cross-sectional
Compliance
Project success
Monitoring
Familiarity
Professionalism
Sanctions
Public procurement (Supplies & Service)
Construction projects
Road construction projects
Kakwezi & Nyeko, (2010)
Tabish & Jha, (2015)
Tadeo Mbabazi, (2015)
Ntayi, Rooks, Eyaa & Qian (2010)
Basheka & Mugabira, (2008)
Zubcic & Sims, (2011)
Source: Researcher
283
SNAPSHOT OF NOAH MWELU’S BIOGRAPHY
I was born on 8th February 1972 to Ms Naome Hilder Namono and Mr. Alfred Wabuswali. I was
born in the morning of that day in a cobweb kind of membrane. It was unusual birth that almost
took my life had it not been my Untie Joy Namasaba and Uncle Richard Mabonga who arrived
shortly after birth and cut the membrane to pull me out. I am told that reports reached my maternal
grandmother Efulasi Nakhumitsa on the evening of 7th February about a disturbing and expected
baby delivery by her daughter (Naome). As a concerned and responsible mother, my grandmother
sent Untie Joy and Uncle Richard on the bicycle early morning of 8th February with essential tools
for assistance. On arrival, they were shocked by an abnormal birth. Despite their age, they acted
very first by cutting the membrane to save my life. My grandmother had instructed my Untie and
Uncle to carry my mother on the bicycle and return her home (Grandmother’s). This was because
she anticipated better treatment and care of her daughter compared to my father’s place given the
prevailing situation. Accordingly, Uncle Richard carried my mother on the bicycle and Untie Joy
carried baby Noah and took us to my grandmother’s home which is approximately 8 Kilometres
away. My father had three wives. Among whom, my mother was the third.
From 8th February 1972, I stayed at my grandmother’s place with my mother. When I was
one year and two months old, my mother left me with my grandmother and she got married
elsewhere. It is from that time that my grandmother took full care of me solely. My grandmother
looked after me amidst numerous sickness and challenges that I encountered without any
assistance from my father. My mother would come visit us and go. Remarkably, I call my
grandmother “MUM” because I grew up with her biological children calling her MUM. So I got
used to that and up to now, I find it extremely hard to call her my grandmother. My mother is
the overall eldest child followed by Uncle Richard and Untie Joy is their last born. We are seven
children from my mother and all of us were taken care of by our grandmother. I am the third
born and eldest son in the family of four girls and three boys.
My grandmother was a British trained primary teacher specialized in infants and was
employed by the Government of Uganda. She retired in teaching services in 1980 before I
started schooling. Being a British trained specialist in infants, enabled her to bring us up in a
healthy and humble environment amidst poverty challenges as a single parents looking at her
biological children and grandchildren. She taught us all how to work and she never segregated
which work was for boys or girls. All of us were responsible of doing any house work including
gracing cattle, grinding millet flour on the grinding stone among other cores. This has really
helped me in doing all sorts of work for survival. My grandmother had reasonable farm land,
284
cattle, goats and chicken that she secured from her earnings as a teacher. It is from these animals
and chicken that she used to sale and pay our school fees and provide us with basics in life. My
grandmother was committed to educating her children and grandchildren. This is exemplified
with extending financial assistance to cater for education of her nieces and relatives. Uncle
Richard is an electrician by profession and Untie Joy is a medical nurse. However, my mother
dropped out of school when she was in primary six after giving birth to my eldest sister.
In 1980, I started subgrade school at Bumasikye Primary School under support of my
grandmother. In 1982, when I was in Primary three, I was sent by my grandmother to grace
cattle as a normal routine work on weekends. However, I was stubborn and went to play football
instead. When I came back in the late evening, my grandmother obviously wanted to punish me
for that. However, my mother who had visited us at the time motivated me to run away and she
took me to my fathers’ place. I had to change to another school near my fathers’ place. My
grandmother was furious about this move because she knew it was going to affect my future.
While at my father’s place, I was chased out of school several times because he was not paying
school fees. Most of the time, I was gracing his cattle which he never wanted to sell and pay my
school fees. The whole of 1982 was academically wasted. My grandmother learnt of the hard
times I was going through including sleeping in the neighbours and looking after cattle. She sent
someone to ask me return home (Grandmother’s). I returned and she took me back to
Bumasikye Primary School to continue with my studies. One important thing I will never forget
among my grandmother’s reprimands, “She used to tell me and my siblings that it is very hard
to enjoy staying comfortably in the place where you never grew up from”. This reprimand was
intendent to stop us from misbehaving with a hope that we shall go to our respective fathers.
This was really true because I tested it personally. My father would tell me during that short stay
with him that these cows are meant to pay dowry when I marry a wife but not school fees.
Another important thing I learnt from my grandmother, she used to tell us that the
education she is providing us, is a key to anything good and for our bright future. She would list
some of the benefits of education as; marrying a good wife, paying dowry, building a good
house, driving a car among others. I now see the reality of her words very fresh in my mind
whenever I go. My grandmother was able to educate me up to senior two when her animals she
used to sell and pay our school fees got finished. She remained surviving on her little pension
and farming. The pension was not enough to pay school fees nor would she sell her land that
was meant for her biological children. This was a turning point in my academic life. That was
the time I started doing all sorts of businesses and casual jobs to raise my school fees as well as
285
support my siblings. These included fetching and selling firewood, sugarcanes, local brew
(Malwa and Waragi), labouring in peoples’ gardens, drinking clubs/Joints and restaurants among
others. At times, I would take the local brew to my mother’s place to make and sale for me given
the stiff competition at my grandmother’s place. Uncle Richard and Untie Joy had their own
families they were respectively struggling for and would not meet my major educational burden.
However, they would on some occasions provide me with books, pens and clothing. My eldest
sister who later qualified as a primary teacher would also help me with scholastic materials and
at times top up my fees.
In 1991 after sitting Ordinary Secondary School Level Exams, I move to Kampala to stay
with Untie Joy hopping to join Advanced Level Secondary School. During that time, I got
opportunity to do casual jobs on construction sites and in manufacturing factories to buy myself
basics like beddings, shoes and clothes that I was lacking. The money earned was not enough
for tuition. Whereas Untie Joy was not able to pay my tuition, her place was another link point
in my life that I appreciate forever. In 1992, having excelled in Ordinary Level Secondary School
Exams, I was admitted in one of the good High Schools in Kampala but I could not join because
the tuition fees was high. In this High School, I was required to pay basic tuition fees amounting
to UGX320, 000 (AUD124) without other academic requirements. This was a lot of money at
that time. I explored numerous options to get that money but I failed. I finally resorted to going
to my father for help. I remembered my grandmother’s statements “Education is a key to
everything good in future”. Based on that statement, I decided to go and convince my father to
get for me this money on condition that I will pay my own dowry in future when I marry. This
was a major convincing point because previously whenever, I would go to him for help, he
would tell me to marry and he pays dowry using the cows he had. I travelled from Kampala to
the village to convince him. It was a difficulty trip since along the way, I was debating within
myself how I would win him to give me the UGX320, 000. Remember, I was not thinking about
the other academic requirements which would cost approximately UGX100, 000 (AUD39) nor
how I would pay fees for the other coming three academic terms of High School.
The following day after travelling to the village, I met my father and we talked. I explained
to him about the whole scenario surrounding UGX320, 000. I begged him to recue me on
condition that in future, I will pay dowry on my own. He told me, go to Uncle Richard in Nairobi
Kenya for assistance and I come back to him. I agreed and I thought he had understood the
magnitude of fees required. I sold my goat at my grandmother’s place that I was given by one
of my uncles as a gift during my circumcision. This was to get the transport to Nairobi to seek
286
assistance from Uncle Richard. Notably, I got this goat in 1988 when I was in senior one.
According to our culture, I was supposed to sell it immediately. However, I decided not to sell
and instead keep it to produce others so that I could sale for tuition fees. That plan worked for
me during my Ordinary Secondary School as a supplementary source of my fees. By the time I
was travelling to Nairobi, it was only the mother goat left. So I had to sell it and got transport.
Having sold the goat, I started the journey very early morning to Nairobi. However, being a
different country, I needed to convert Ugandan Shillings to Kenyan shillings. I converted the
money at Uganda-Kenya border. During that time in 1992, Kenya and Uganda had political
issues and crossing to Kenya was difficulty. Because of that tension, I was stopped by Kenyan
authorities at the border not to proceed to Nairobi unless I had a Passport. Surely, I did not
possess a passport and my school identity card was no longer allowed. It was late in the evening
when I returned to Ugandan side and tried to reconvert the Kenyan money to Ugandan money.
Part of the money was stolen by crazy money changers at the border. I cried and travelled back
to my grandmother’s place at night. My grandmother was shocked to hear me knocking on her
door at night because she believed I had succeeded travelling to Nairobi despite prevailing
border situation at that time. I slept and the following morning, I went back to my father.
On reaching my father, I explained what had happened and I could not reach Nairobi to
see Uncle Richard. My father told me Okay. He said that he cannot give me any of my allocation
for future dowry because there was no guaranty that I will not task him to pay dowry for me.
However, he promised to give me a piece of land on his own to sell and bail me out. I was very
happy and accepted knowing that the piece of land would fetch approximately UGX320, 000.
He took me to the Promised Land, shown me the boundaries and asked me to look for buyers.
By that time, I had never known the price of land. So I thought it would fetch money close to
what I had explained to him. The land was approximately 12 metres squared and with a very big
rock covering almost 8 square metres. He told me that the rock is money itself. During that time
and being deep in the village, people had not started building permanent houses that requires
crushing such rocks for building aggregates that one can sell to get money. I thanked him and
he himself called one of his neighbours to come and negotiate the price. I was dismayed and
automatically tears started rolling out of my eyes when the neighbour said that he can only give
me 2 ducks for that land. The neighbour was interested because he wanted to level his boundary.
Otherwise given the nature and size of the land, it was hard to get another buyer. When I had
of 2 ducks that is when I roughly understood the value of that piece of land my father was
offering me. I left in tears to my grandmother and told her what had transpired. With no option
left, the following day I went back to Kampala to stay with Untie Joy.
287
I missed school for two years. While at Auntie Joy’s place, Mr. Leo Iku used to come for
treatment in Auntie’s clinic that was operated in the same house we were staying. Mr. Leo Iku
asked me why I was not studying. I told him the tuition fees problems and he offered me a job
of a waitress in his Kyambogo Sports Club so that I can raise fees. In this job, he allowed me to
work in the evening on week days from 5.00Pm to late night (Past Midnight) on average and on
weekends or public holidays, from morning to late night. This job enabled me to start Advanced
Level (High School) from Modern Senior Secondary School that Uncle Perez Matanda together
with Auntie Joy secured a vacancy for me. I would study in the morning from 8.00Am to 5.00Pm
then report for work few minutes past 5.00Pm. It was a challenging job that would make me
doze in class because of short sleep at night. In the begging of that job, I encountered challenges
of knocking Auntie Joy past midnight to open for me. This caused problems with her husband
and I resorted to sleeping in her carport where she was raring her chicken for poultry business
since they had no car.
Having stayed with the chicken for more than three weeks, one Good Samaritan whom
I remember by only one name (Kenneth) working with President’s office and used drink from
Kyambogo Sports Club called me one evening and offered me accommodation in one of his
rooms on the boy’s quarters. I believe he might have seen me entering the carport housing
chicken and decided to offer me accommodation. My pay in return was to mow and clean his
compound whenever it was bushy and dirty. Kenneth’s offer greatly relieved me of
accommodation difficulties and was a starting point of being independent. Before completing
my Advanced level, Mr Leo Iku died in a motor accident at night while returning from
Angenuire Disco-Tech (A night Club). This was again a dilemma in my life since the business
was solely managed. Upon his death, his relative closed it and shared the proceeds. During that
time, I was in senior six and completing was a big problem financially. However, I gambled and
sat for the final qualifying exams to the University in 1996. Given prevailing challenges, my
performance was poor and I could not get limited Government admission slots in the
University. I gave up with education and looked for all sorts of jobs for survival.
In 1999, I married Dr Susan Watundu who by then had just finished her Higher Diploma
from Makerere University Business School (MUBS) on Government Scholarship. I knew Susan
way back in childhood since we are from the same village. However, in 1996 while at MUBS is
when I proposed and she told me to wait until she finished her studies. Finally after completing
her studies in 1998, we were able to officially marry on 22nd May 1999 amidst great poverty. In
formalising our marriage, I went to my father asking him for assistance. Surprisingly, he told me
288
that the remaining cows are for my step-mothers because they were bride prices for my step-
sisters and he does not own any. However, he gave me one calf. So out of the five cows I paid
dowry, the four were bought using my savings with Susan. This reminded me when my father
visited us one time in 1998 and he jokingly said since my to be daughter in-law is well educated,
she will pay dowry for herself. Indeed it was a reality. I wondered where are the cows he has
been promising to pay dowry while denying me school fees had gone. Given logistic issues, we
combined three functions (Introduction, Dowry and Wedding) in one and it was successful.
This function stressed me and Susan so much because of financial difficulties given our little
earnings. The stress was so much that I developed severe headache which lasted two weeks.
Whenever I think of our function, I always remember the severe headache. Remarkably, I thank
Dr Susan Watundu for accepting me the way I was with my poverty and academic status. Many
Ladies of her status then, prefer getting married to rich and educated men. I really feel honoured
for having secured such a powerful woman as my wife.
From 1996 to 2006, I did all sorts of casual jobs and businesses including working in
Coffee factories, selling soda, plastics, stationary, charcoal, bananas and cocoa. All these were
on short time basis as they were seasonal jobs and business losses respectively. Remarkably, in
all this gambling and survival for the fittest, I was able to save money and acquire tangible items.
In 2000, Susan upgraded for a Bachelor’s degree on Government sponsorship at Makerere
University. She later went back to Makerere University for her Master’s degree before going to
Dar Es-salaam University in the Republic of Tanzania for her PhD that she completed in 2015.
After completing her Higher Diploma through to PhD, Susan worked in various places and
doing all sorts of jobs ranging from low to average income earnings. With our little savings
collectively we were able to acquire land, buildings and educating our children. Concurrently,
with the motivation from Susan and Uncle Geoffrey Wepondi, I resumed my academic journey
by doing a Certificate in Strategic Procurement and Logistics Management from Makerere
University in 2006. In 2007, I sat for Special Qualifying Exams to Makerere University for a
Bachelors’ Degree in Procurement and Supply Chain Management. I passed and started my
Bachelor’s Degree on private sponsorship in 2007. During this time I was working with
Alphamat Consult Limited an affiliated company to Cambridge University Press United
Kingdom based in Kampala. I was studying in the evening while working during day time. I
completed this three years bachelor’s degree in 2010 and immediately enrolled for a Master’s
degree in Procurement and Supply Chain Management from Makerere University that I
completed in 2013. The salary earned from Alphamat enabled me to pay tuition fees for both
degrees as well as supporting my family.
289
In September 2012, I left Alphamat and joined Makerere University Business School. In
2013, Susan started her PhD at Dar Es-salaam University (Tanzania) that culminated into her
joining World Bank Washington (USA) before completing in 2015. During this time (2013-
2015), I was motivated by Susan’s PhD studies and I started applying for PhD scholarships.
Upon Susan’s PhD completion, by coincidence and God’s Grace, I luckily won a full
Scholarship from the Australian Government to study a PhD at the University of Newcastle
Australia. I enrolled for the PhD in Public Procurement for Construction Projects in 2016 and
hopefully finishing in 2019. From 1996 up to now, I and Susan have supported ourselves
socially, morally, educationally and materially amidst severe challenges. We have five daughters.
Two of whom (Lucky Mercy and Peace Joy) are joining University this year (2019) to study
Pharmacy and Medicine respectively. One (Talituleka Hope) is in secondary school, another one
(Blessed Malyamu) is joining secondary school next year (2020) and the last born (Mariza Susan)
is in lower primary school. These children have supported the family in various ways despite
their age.
“Education is a key to bright future”….this were my grandmother’s words to me. I
reemphasize her statement to everyone who can listen, care and learn from me together with
my wife. Accordingly, I take this opportunity to thank my maternal grandmother Efulasi
Nakhumitsa (R.I.P 2013) for her tremendous efforts and sowing an education seed into me that
I am reaping from. I thank various personalities and organizations that have come to my rescue
at various stages of life. Starting with my late grandmother (Ms Efulasi Nakhumitsa), my wife
(Dr Susan Watundu), my daughters (Lucky Mercy, Peace Joy, Talituleka Hope, Blessed Malyamu
and Mariza Susan), my mother (Naome Namono), my mother in-law (Malyamu Wambi), Uncles:
Richard Mabonga, Geoffrey Wepondi, Dayson Maswere, Richard Wambi, Perez Matanda,
Francis Waluya, Peter Khaukha, Eric Sakwa, Robert Sakwa, Titus Masete and family, Tsombe
Nampude and family, Yowasi Wanyera and family, Aunties: Joy Namasaba, Lonah Watela,
Connie Mlay, Debora Wanyenya, Sister Loy Lunyolo, all my teachers and lecturers (Primary,
Secondary and University) levels, Evangelist Christopher Besweri Kaswasbuli, The Government
of Uganda and Australia, Sisters and Brothers, Brother in-law (Simon Sakwa), Entire Church of
ISA MASIYA, Relatives, Friends and Neighbours. May the Almighty God Bless you all in the
name of our Lord ISA MASIYA. AMEN.
290
DEDICATION TO:
Noah Mwelu
1. “Born to suffer” The songs of people will tell me no for the cause of the
children………If they treat them right, children will have bright future and if they treat
them wrong, we shall have cause of war……If children grow up without
parents………..who will tell them this is right or wrong….. (Born to suffer, born to suffer
haaaaaah)X4 …… Without the mother, children suffering…Without the father, children
suffering… Without the parents, children suffering...… (Born to suffer)X4…They need
parental care….You can suffer if the mother does not care for you…You will suffer if
the father does not care for you…. (We were born to suffer)X4……… We were born to
suffer aaaahhhh…no, no, no, .noooh…Born to suffer… My mother didn’t tell me the
truth nor did my father tell me the truth, born to suffer aawooo,
aayaaahhh…awooyihhhh...Born to suffer... (Lucky Dube…R.I.P).
2. (On my own, on my own)X4….Struggling and Suffering...…..I have been waiting for the
years, for this time to happen……for this day to come…..I have learnt to believe in
myself and no body...Else ….I will face the future with pride…and do much as I
can……………Oh Thank you God …for helping me and making me what I am ,,,,,thank
you, thank you my grandma ,,,,thank you everyone who came to my rescue ,,,Thank you,
thank you my Lord (Lucky Dube…R.I.P).
Dr Susan Watundu (Super Girl)
I am happy to be here with you my Love……I never let you go away……I have a feeling that a
chance is a dream……….and if it is a dream, I will never be weaker to let it
go……Haaaa……After all these problems……Eheeeh…after all these problems I feel happy to
be with you and will never let you go……Baby I want you, Darling I want you………….I will
try to keep you cool as much as I can………(People bring confusion)X2…I feel like going
Heaven…Oh God come by myside..…Happy you my Love……..I still Love you as much as I
can my Dr Super Girl (Beloved Super Boy, Noah Mwelu).
My Beloved Daughters (Lucky Mercy, Peace Joy, Talituleka Hope, Blessed
Malyamu and Mariza Susan)
Education is a key to bright future………….In the fear of God, the Wisdom begins…….Always
sympathize and respect your parents…..See what we are going through…..Always love one
another……Avoid bad groups…..Genuine parents always wish their children the very best of
291
their lives…..There you are!!!!!!!!!!!!! All the Very the Best and Long Live my Beloved Daughters
(Daddy, Noah Mwelu).
My Fellow Parents
Being a father or mother is not all about just producing and abandoning children for others to
care on your behalf. If you want your children to treat and respect you as their earthly God,
endeavour to care for them by providing them what they need within your income or capabilities.
I love my parents, I have forgiven them and I have tried to provide them with what they deserve.
However, I have no kind words for what they did (If I keep quiet, people would not know the
truth). Hence, this is a learning point for others to reform. I refer to my grandmother as my
earthly God for the burden she carried (She carried a heavy grinding stone on her head on behalf
my biological parents). God Bless you my ‘Great MUM’ (R.I.P).
I thank and applaud those mothers and fathers who are tirelessly doing all they can for the good
and wellbeing of their children. I pity those who have run away from their responsibilities and
left the children and spouses suffering. “Responsibility defines one’s wealth but not being rich
materially” (Noah Mwelu).
The Wives, Husbands and Relatives
For those intending to marry, marriage should not be based on wealth and education but the way
you perceive someone whom you will stay with together for the rest of your life (True Love).
Otherwise if you base on wealth and education, then it is material love. If you work together to
acquire wealth, you will be more respected than if you got already made wealth. This so called
already made wealth is the source of men and their relatives mistreating women because they
believe that you have come to take away their wealth. Believe me, you will feel greatly honoured
and have control of your wealth that you have worked together. Off course I don’t side with men
who manipulate their wives by grabbing wealth acquired together or solely acquired by the wife.
I find it extremely difficult to say that I own any of our things. This is because I and Dr Susan
Watundu have worked together including our children to acquire what we have. Believe me, some
of the things we own, I have not contributed a coin. This serves as a lesson to husbands and
relatives who manipulate and mistreat women because of wealth to stop forthwith. You should
always remember that irrespective of women contribution to family wealth, genuine wives work
committedly for the well-being of their families. Just think of a husband passing on, who carries
the burden of bringing up the children left behind? If you truly love your son and his children,
then sincerely relatives should not mistreat and grab family properties. Women are not objects
292
that you own and sell like property. Hence, those mistreating wives because they paid dowry
should change that attitude of thinking they bought the wives. Furthermore, those who anticipate
material gain by marrying off their daughters should refrain from such cultures. This is because
in no way can the dowry paid be equated to the lives of human being.
I conclude by apologising to those who may feel offended with the message put forward
in this write-up and I invite you for discussions, comments and feedback. Thank you and God
bless you all.
With great pleasure from,
Noah Mwelu.
293
Noah with Dr Susan Watundu and the daughters
294
Noah with the Family
Noah attending FEBE three minute thesis competition
295
Family Photos: (Noah, Susan, Lucky, Peace, Hope, Blessed and Mariza)
296
From left: Head of Construction MGT, Supervisor & Chair of Construction MGT, Noah, VC & President,
PVC and Director HDR
Noah with PVC (FEBE), Prof Brett Ninness and HOS (SABE) Prof Sue Anne Ware
297
Hand shake by VC and President UON (Prof Alex Zelinsky)
298
Hand Shake with PVC FEBE (Prof Brett Ninness)
Hand Shake with Principal Supervisor and Chair of Construction Management (Prof Peter Davis)
299
Hand Shake with Head of Construction Management (Dr Kim Maud) and HDR Director (Prof Patrick Tang)
Noah with fellow PhD students
![Sustainable Regulatory Compliance[1]](https://img.pdfslide.us/doc/110x75/577cdd861a28ab9e78ad346d/sustainable-regulatory-compliance1.jpg)
