THE QUANTITY SURVEYOR

Volume 65 | No. 1 & 2 |2019|ISSN:116 -915X

JOURNAL OF THE NIGERIAN INSTITUTE OF QUANTITY SURVEYORS

THE

QUANTITYSURVEYOR

Volume 66 | No. 1 | 2020 | ISSN: 116 - 915XCost management | Procurement Management | Project Management

AIMS AND SCOPE

The Quantity Surveyor is published bi-annually (twice per year) including special issue(s) where necessary, through the Nigerian Institute of Quantity Surveyors.

The Quantity Surveyor publishes high quality - minimum of double - blind peer-reviewed research papers in the areas of Cost management; Cost information management; Construction economics; Construction project management; Design and construction management processes; Housing and infrastructure development; Stakeholders management; Project planning and project impact assessments; Procurement management; Management of construction companies; Industry development; Knowledge management in construction; Innovation in construction; Sustainable construction; Project financing; Current and emerging infrastructure issues in developing countries etc. as well as other relevant issues.

The goal of the journal is to broaden the knowledge of construction professionals and academicians by promoting access to quality information and providing valuable insight to construction-related information, research and ideas.

The Quantity Surveyor welcomes research or technical articles, which are published after proper peer-review process, and provided the author(s) adhere strictly to the guideline for publication.Copyright: © 2020, The Nigerian Institute of Quantity Surveyors

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The Quantity Surveyor

Chief Editor Prof. Deji R. OgunsemiDepartment of Quantity Surveying, Federal University of Technology Akure, NigeriaEmail: [email protected]

EditorDr. Ayodeji E. OkeDepartment of Quantity Surveying, Federal University of Technology Akure, NigeriaEmail: [email protected], [email protected]

Other Editorial Board Members

Prof. Henry A. Odeyinka Obafemi Awolowo University, Ile-Ife, Nigeria

Prof. Ahmed D. Ibrahim Ahmadu Bello University, Zaria, Nigeria

Prof. Yakubu Ibrahim Abubakar Tafawa Balewa University, Bauchi, Nigeria

Prof. Samuel I. J. Onwusonye Imo State University, Owerri, Nigeria

Prof. Uchenna O. Ajator Nnamdi Azikiwe University, Awka, Nigeria

Dr. Richard Kolawole Federal Polytechnic, Bauchi, Nigeria

Dr. Simon Eigbe Auchi Polytechnic, Auchi, Nigeria

Prof. Olukayode S. Oyediran University of Lagos, Akoka, Nigeria

Prof. Olubola Babalola Obafemi Awolowo University, Ile-Ife, Nigeria

Prof King N.O. Nyenke Rivers State University, Port-Harcourt, Nigeria

Prof. Yahaya M. Ibrahim Ahmadu Bello University, Zaria, Nigeria

Editorial Advisory Board

Prof. Abdul Rashidi Universiti Sains Malaysia

Prof. Charles Egbu University of East London, UK

Prof. George Ofori London South Bank University, UK

Prof. Godwin Jagboro Obafemi Awolowo University Ile-Ife, Nigeria

Prof. Hamman Tukur Sa'ad Ahmadu Bello University Zaria, Nigeria

Prof. Joseph Afolayan Anchor University Lagos, Nigeria

Prof. Kabir Bala Ahmadu Bello University Zaria, Nigeria

Prof. Martin Skitmore Queensland University of Technology Sydney, Australia

Prof. Paul Olomolaiye University of the West of England Bristol, UK

Prof. T. C. Mogbo Enugu State University of Science and Technology, Enugu, Nigeria

Prof. Theo Haupt Mangosuthu University of Technology Durban, South Africa

Prof. Julius Fasakin Federal University of Technology Akure, Nigeria

Prof. Stephen Ogunlana Heriot-Watt University Edinburgh, UK

Support Staff

Ms. Lauretta GerardNigerian Institute of Quantity Surveyors House No 84, 4th Avenue, Gwarinpa, Abuja, Nigeria

The Quantity SurveyorISSN: 116-915X © 2020 The Nigerian Institute of Quantity Surveyors

http://journal.niqs.org.ng

The Quantity Surveyor

VOLUME 66 NUMBER 1 MARCH 2020 ISSN 116-915X

CONTENTS 4 EDITORIAL

PAPERS6-22 Jonathan Zishim Danjuma, Ahmed Doko Ibrahim, and Peter Gangas

Chindo A comparative analysis of factors affecting contractors' mark-up

decision based on selected project and organisational characteristics

23-30 Olubunmi Comfort Ade-Ojo and Joseph Aderemi Akinola Problems associated with plant and equipment hiring in Ondo State

Nigeria

31-42 Muhammad Abdullahi, Tsaku Joseph Ombugadu, Ahmed Doko Ibrahim, Yahaya Makarfi Ibrahim and Peter Gangas Chindo

IFCs' Capabilities for supporting quantity take-off of building works using BESMM 4

43-59 Chukwuemeka Patrick Ogbu and Vera Braiye Ebiminor Relationship between bill of quantities errors and construction

disputes: A multivariate analysis

60-67 Usman Sulaiman Jibril, Baba Adama Kolo, and Peter Gangas Chindo Assessment of project manager's roles in management of construction

projects in Nigeria

68-81 Chukwuemeka Patrick Ogbu and Monday Omogiate Imafidon Criteria for selection of consultants for tertiary institution

construction projects in Nigeria

82-96 Solomon Olusola Babatunde, Tolulope Esther Adeleye and Adedayo Opeyemi Adekunle

Assessment of barriers and measures to improve BIM based detailed cost estimating in quantity surveying practices

97-103 Olufisayo Adewumi Adedokun, Fidelis Ojuoluwa Rufus and Isaac Olaniyi Aje

Indications of stress among the quantity surveyors



The Quantity Surveyor (March, 2020) 66, 4

Editorial

The Nigerian construction industry like most developing countries, is governed by a competitive business environment driven by the lowest cost mentality. Therefore, any contractor who must remain in business within the industry must be determined and use optimal bid mark-ups low enough to win the job, at the same time high enough to provide the minimum expected profit. To help contractors decide on the optimum mark-up to insert in their bids in Nigeria, Danjuma, Ibrahim and

Chindo examined and uncovered the factors affecting contractors' mark-up decisions in Nigeria through a comparative analysis of factors affecting contractors' mark-up decision based on selected project and organisational characteristics. Their study is relevant to construction industry players as it provides knowledge on how project and organisational characteristics affect factors affecting contractors' mark-up decision, therefore creating a better ground for improvements in tendering practices. This improvement in tendering practice in Nigeria has the potential to enhance the construction industry's performance. Ade-Ojo and Akinola assessed the problems associated with plant and equipment's hiring in Ondo State, Nigeria. They indicated the major problems associated with plant and equipment hiring for construction works, and concluded that inability of hiring firms to keep and maintain plant and equipment in a working condition contributed to the problem of project delivery in Nigeria. They recommended proper project planning and good assessment of plant and equipment to be hired by contracting organization in order to prevent time overrun. In Nigeria, the Building and Engineering Standard Method of Measurement (BESMM 4) is currently the standard for measurement of construction works but, till date an assessment of how well IFCs data schema supports the measurement of construction works using the BESMM 4 provisions is not known. Therefore, the capabilities of IFC for supporting quantity take-off of Building works using BESMM 4 was investigated by Abdullahi, Ombugadu, Ibrahim, Ibrahim, and Chindo. They concluded that software and BIM platform based on the current IFC4 Add 1 data schema are not adequate for quantity take-off of building works using BESMM 4 standard. The output of their study will avail schema developers and software vendors with the information requirement for schema extensions that capture the local requirement for cost estimating in the Nigerian construction industry. Bills of quantities (BoQs) doubtlessly remain the most preferred cost management instrument in construction procurements globally. However, BoQ errors has the potential to cause construction disputes. Ogbu and Ebiminor exposed the sources of BoQ errors and the relationship between BoQ errors and construction disputes. Based on their findings, they made recommendations on how best to address professional incompetence and mistakes in the preparation of BoQs. This paper offers insights into the relationship between errors in BoQs and construction disputes. Jibril, Kolo and Chindo acknowledged that lack of understanding of roles and responsibilities of construction practitioners (CPs) as one of the factors leading to ineffectiveness in teamwork within the construction industry. They appraised the roles of a project manager (PM) in the management of construction project and established that on a project where a PM is appointed, none among the roles and responsibilities of PM identified is fully undertaken by the PM. They concluded that there is a conflict amongst construction practitioners on the role of a PM. They suggested that CPs should improve their knowledge on the specific role of PM in construction projects and the attendant responsibilities that comes with such role. Almost all tertiary institutions' new construction projects in Nigeria have consultants. In spite of this, majority of these projects in the institutions underperform due to poor management as a result of flaws in the selection of consultants. The order of priority of the criteria for the selection of consultants for public tertiary institution construction projects in Edo and Delta States was ascertained by Ogbu and Imafidon. The output of their study will assist tertiary institutions on what to prioritise in the criteria used in selecting construction consultant for their projects. It will also expose consultants to the key qualifying criteria for successful bidding in the institutions. They recommended that the use of ICT and location of firm/proximity to the site should be among the criteria for the selection of construction consultants for tertiary institution projects. Babatunde, Adeleye and Adekunle examined the barriers to the implementation of building information modelling (BIM) based detailed cost estimating in quantity surveying practice; and evaluated the measures to improve its adoption within Nigerian quantity surveying firms. They presented the relative importance of the identified barriers and measures to improve BIM adoption. Their findings will help to ameliorate the barriers hindering the adoption of BIM based detailed cost estimating among quantity surveyors; thereby improving the reliability of the detailed cost estimating. Furthermore, their findings will positively inform the decisions of construction stakeholders, particularly quantity surveyors to formulate strategies to adopt the full implementation of BIM in their practices. Today's workforce is experiencing stress in epidemic proportions as illness and absenteeism cannot be overemphasized at all levels. Therefore, Adedokun, Rufus and Aje appraised the indications of stress among Quantity Surveyors with a view to enhance productivity while also improving stress management. They uncovered the most evident indications of stress and the major sub factors of these indications of stress. They further reported the significant sub factors of the indications of stress and made recommendations on how to curb factors that could trigger stress among employees.



Relationship between bill of quantities errors and construction disputes: A multivariate analysis

1 2Chukwuemeka Patrick Ogbu * and Vera Braiye Ebiminor

1 & 2 Department of Quantity Surveying, University of Benin, Nigeria * - E-mail address of Corresponding Author: [email protected]

Abstract

Bills of quantities (BoQs) doubtlessly remain the most preferred cost management instrument in construction procurements globally. Inadvertently, however, the potential of BoQ errors to cause construction disputes is largely ignored in literature. This study determined the sources of BoQ errors and the relationship between BoQ errors and construction disputes. Data were gathered by opinion survey of construction professionals and contractors in Edo State, Nigeria. The multivariate techniques of factor analysis, canonical correlation and logistic regression were used in the analyses. It was found that the sources of BoQ errors can be summarised as designer's competence, BoQ compiler's competence, designer's mistakes and BoQ compiler's mistakes. Apart from designer's mistakes, all the factors were found to be significantly related to the types of errors actually found in BoQs. The BoQ errors that lead to disputes were identified as inaccurate quantities, inadequate unit rates, and measuring mechanical and electrical works as provisional sums. To address professional incompetence and mistakes in the preparation of BoQs, government should insist that only drawings and BoQs that are sealed by the appropriate professionals are acceptable for the award of public contracts, and construction professionals should ensure that they carefully scrutinize works done by their junior staff before such works are sent out for use in construction procurement. The paper offers insights into the relationship between errors in BoQs and construction disputes.

Keywords: Bill of quantities, bill of engineering measurement and evaluation, construction disputes, construction errors, professional competence

Introduction

In the construction industry, a contractual relationship is difficult to contrive without proper documentation. Although this is generally accepted as true, adequate research attention has not been given to the connection between documentation errors and the often-observed adversarial relationship between parties to a construction contract (Meng, 2012; Pesämaa, Eriksson, & Hair, 2009). Nevertheless, a number of studies have inquired into documentation errors in construction projects (Dosumu & Aigbavboa, 2017; Dosumu, 2018; Dosumu and Adenuga, 2013). Although BoQs have been in use for more than 300 years, they have come under serious criticisms recently over the reliability of their contents (Davis, Love and Buccarini, 2009). The insidious implications of this on construction contract disputes are little researched. Most construction projects in developing countries are based on the design-bid-build procurement method in which the BoQs play a prominent role. Given the adversarial relationship that frequently ensue from this procurement route, it is pertinent that BoQ errors that lead to disputes in construction projects are fully understood (Kong & Gray, 2006; Regan, Love & Jim, 2015). Ho and Tsui (2010) observed that despite the provision for correction of BoQ errors in most forms of contract, the errors still lead to disputes. In practice, the disputes sometimes outweigh the advantages of use of BoQs in construction projects (Davis et al., 2009). Some authors think that errors still exist in most BoQs irrespective of the use of standard methods of measurement in their preparation, and the industry experience of BoQ compilers. Despite these observable deficiencies of BoQs, it is still in dominant use in developing countries (Ogbu, Asuquo & Oyoh, 2012). BoQ errors' contributions to the adversarial relationship between clients and contractors is largely overlooked in literature. In Nigeria particularly, the use of BoQs faces challenges from two main points. First, the introduction of the Bill of Engineering Measurement and Evaluation (BEME) as a rival to the classical BoQ creates confusion for users as to the contents and characteristics of the BoQ. While the BEME does not enjoy an international status, and has no standard method of preparation, it often substitutes the BoQ in public sector capital intensive infrastructural projects (Nwannekanma, 2019; Osubor, 2017). BEMEs, being unstandardized, are usually difficult to interpret and lead to dispute-vulnerable contracts. For the purpose of this study, however, BoQs are

The Quantity Surveyor (March, 2020) 66, 43-59



assumed to mean the same thing as BEMEs. Secondly, the standard method of measurement of construction works in Nigeria has under gone rapid improvements in recent years. Since 1988 when the first standard method of measurement (SMM1) was introduced, Nigeria has had SMM1 (second impression) (1996), Building and Engineering Standard Method of Measurement (BESMM2) (2002), BESMM3 (2008), BESMM4 (2015) and currently, BESMM4 revised edition (2017). This rapidly changing basis of construction measurement leads to confusion which can result in BoQ errors and disputes. Over the years, researchers have been inquisitive about the sources of errors in construction contract documents, especially, BoQs. Jalam, Gambo, Dahiru and Aliyu (2018) researched on the severity of errors in BoQs for public projects in Nigeria and revealed that errors mainly arise from lack of risk analysis and wrong assumptions. However, a generally accepted definition of error hardly exits (Lopez, Love, Edwards, & Davis 2010). While Rooney, Heuvel and Lorenzo (2002) defined error as any human action that exceeds the tolerance defined by the system with which the human interacts, Love and Josephson (2004), defined it as a deviation from what is intended that is caused by human action. In this work, BoQ errors are regarded as mistakes, slips or lapses in BoQs (Mollo, Emuze & Smallwood, 2018). Dosumu and Iyagba (2013) appraised the factors responsible for errors in Nigerian construction contract documents and found that consultant, management and client factors are mainly responsible for the errors, although consultant related errors were found to be the most important source. Dosumu and Adenuga (2013) observed that the major causes of BoQ errors are lack of adequate documentation, poor communication between professional, and client and negligence of the professional. Gunathilaka and Senevirathne (2013) discussed the common errors that are made in preparing and pricing BOQ in the Sri Lankan construction industry. Incorrect quantities, irrelevant preliminary items, unnecessary specifications, insufficient information in descriptions, omissions and discrepancies between drawings and the BOQ are the common BoQ errors detected by the study. Dosumu, Idoro and Onukwube (2017) researched on the causes of errors in construction contract documents in southwestern Nigeria and highlighted similar errors to those found in earlier studies. Most previous studies investigated contract documents as a whole, while only a few focused solely on BoQs (e.g. Jalam et al. 2018; Ho & Tsui, 2010; Gunathilaka & Senevirathne, 2013). However, the relationship between BoQ errors and construction disputes seems uninvestigated. Secondly, the sources of BoQ errors and the types of BoQ errors were not separated despite the observations by Dosumu, (2018) that errors are different from their sources. Adequate understanding of the sources of BoQ errors is required in order to minimise BoQ errors. Existing studies have not sufficiently investigated the domains of BoQ error sources, and their linkages to the types of errors found in most BoQs. Furthermore, it is argued here that the significance of BoQ errors lies in whether they influence project performance. Normally, where an error exists, two things are possible: the parties may accept the existence of the error and choose to make necessary compensations. On the contrary, a dispute may emanate from the error and lead to a negative project outcome. The later scenario is poorly investigated in literature. Consequently, this study focuses on the contributions of BoQ errors to construction contract disputes in the Nigerian construction industry with a view to minimizing disputes occasioned by BoQ errors. The research objectives are to: (1) determine the relationship between sources of BoQ errors and types of BoQ errors, and; (2) determine the relationship between BoQ errors and construction contract disputes.

Hypotheses of the studyH : There is no significant relationship between the source of BoQ errors and the types of errors found in BoQs.o1

H : There is no significant relationship between BoQ errors and the incidence of construction dispute. o2

Construction dispute

The construction industry is complex, fragmented, and dispute-prone by nature (Oladapo & Onabanjo, 2009). Construction disputes can occur at the design or construction phase of a project. Disputes vary, but they are commonly inimical to the project objectives, and ruinous to working relationships amongst project participants (Farooqui, Azhar & Umer, 2014). Disputes arise where a party in a construction contract is alleged to have extended his interests beyond the boundary set by the terms of the contract, or has denied the other party's interest contrary to the contract (Ogbu, 2017). According to Kumaraswamy (1997), a construction dispute is a situation where an assertion made by one party is rejected by the other, and the rejection is not accepted in return. Disputes lead to negative consequences including: prolongation of projects (Ellis & Baiden, 2008), time and cost overruns, diminution of respect between parties, breakdown in cooperation (Ade-Ojo & Babalola, 2013; Mukaka, Aigbavboa & Thwala, 2014) poor project performance, loss of company reputation, loss of profit, loss of professional reputation, rework, relocation cost for men, equipment and materials, and project abandonment (Agu 2015; Love et al, 2007; Idowu & Hungbo, 2017). In addition to these negative consequences, construction

44 Ogbu and Ebiminor

disputes are primarily expensive and time wasting, not only to the immediate projects, but to the entire economy as well. Immediate resolution of disputes is critical to the attainment of the project objectives (Shin, 2000). Consequently, it is ideal to ensure that contract documents, especially, BOQs, are error-free, and useful for settlement of disputes. The connectedness between BoQ errors and disputes is little discussed in literature. As observed by Ramonu, et al. (2018), understanding the conditions that lead to construction disputes will aid mitigative efforts to avoid or reduce disputes in construction procurement processes.

Sources of BoQ errors

Extant literature attributes BoQ errors to different sources. While Adnan, Nawawi, Akhir, Supardi and Chong (2011), Dosumu (2018) and Juszczyk, Kozik, Lesniak, Plebankiewicz and Zima, (2014) regard poor design and management experience as an origin of BoQ errors, other scholars like Sinclair, Artin., and Mulford, (2002), Gunathilaka and Senevirathne (2013) and Dosumu and Iyagba (2013) consider poor communication among the consultants as another origin of BoQ errors. Inadequate communication between the quantity surveyor and the project designers (architects and engineers) will possible lead to inaccurate assumptions, and eventually manifest as BoQ errors. Every contract document is reflected by the BoQ in one way or the other because the BoQ captures the financial essence of all contract documents. Resultantly, errors in other contract documents result in error(s) in the BoQ. Adnan et al. (2011) and Gunathilaka and Senevirathne (2013) opined that BoQ errors occur during measurement, compilation of descriptions from drawings and specifications, squaring dimensions, and abstracting. It is argued in this study that the different sources of BoQ errors result in different types of BoQ errors. A BoQ error is different from its source (Dosumu, 2018). For instance, poorly written specifications can lead to errors in description, and dimensional errors in drawings will likely result in wrong quantities. There are hardly any attempts in literature to group the sources of BoQ errors. Generally, however, some authors have grouped project errors into: practice, task, circumstance, organisation, system, industry and tool related factors (Busby & Hughes 2004; Love, et al., 2009). In the view of Chapman (1991), design errors can be observational, conceptual/mapping, conventional, measurement and keyboard related in origin. These opinions were not specifically directed at BoQs. Juszczyk et al. (2014) categorized BoQ errors into formal and calculation errors, the categorization was not based on empirical data. A consensus does not exist in literature as to the taxonomy of all human errors, which implies a need to develop a taxonomy of errors for individual subject matters (Dosumu, 2018; Reason, 1995). The present study intends to develop a taxonomy of BoQ error sources, and to determine how these sources relate with the BoQ errors themselves. Identifying the underlying causes of BoQ errors will help to develop error management practices by BoQ compilers (Love, et al. 2009). Types of errors commonly found in BoQs include incorrect quantities (Adnan et al. 2011; Razali et al. 2014; Dosumu et al. 2017) and irrelevant preliminary items (Hurd, 2007; Dosumu & Adenuga, 2013; Jalam et al. 2018). It is presently unclear in literature which sources of errors account for most of the errors found in BoQs. This study hypothesizes that the sources of BoQ errors are related to the types of BoQ errors. Conceptually, the elimination of BoQ error sources will ultimately lead to a reduction in the BoQ errors themselves.

BoQ errors and construction disputes

Nigeria is notedly lagging behind in terms of critical construction manpower due to problems in her tertiary and vocational education systems (Ofor, 2001). Ultimately, the dearth of construction manpower reduces the quality of outputs from the construction industry, including those of documents like the BoQ used in procurement and contract administration in the country. It is hypothesized that this situation is partly responsible for the incidences of dispute in construction procurement. Most authors attribute disputes to violations of expressed contract terms. Ramonu et al., (2018) noted that disputes arise from breach of contract, however, they also added inadequate procurement, inadequate brief, and poor communication. Ogbu (2017) identified corruption, lack of capacity on the side of the consultants or contractors, impacts of the economic and social environments, insufficient time for completion of project documentation prior to award, variations and lack of capacity sometime lead to construction disputes. Aiyewalehinmi and Nkumah (2019) opined that disputes are traceable to payment delays, defect, professional negligence, variation, extension of time, poor quality of work, unfamiliarity with local condition, poor project scope definition and poor communication. Cakmak and Cakmak (2013) classified causes of disputes depending on their nature into: design team related, contract related, human organization problem related, owner related contractor related, project related and external factors related causes. Clearly, previous studies have not adequately investigated the connectedness between errors in contract BoQs and construction disputes. This study argues that, howsoever they arise, disputes mostly end up in financial claims that can only be settled by reference to the BoQ. Dinu, Olteanu and Soveja, (2017) noted correctly that someone must pay for such

Relationship between bill of quantities errors and construction disputes: A multivariate analysis 45

errors. If the risk of occurrence of disputes were properly considered in the preparation of BoQs, they will be easily resolved without unbearable liabilities on either side of the contract. Otherwise, disputes will worsen leading to outright project failure. The opportunistic behaviour of contractors dictates that BoQs should be error-proof to avoid disputes. For instance, concrete is usually measured in m3. If the BoQ compiler mistakenly enters square metres (m2) in the unit column for concrete in the BoQ, the contractor, though being aware of this typographical error, may go ahead to give the correct rate for concrete per cubic metre (m3), but will later claim that his rate reflected the unit in the BoQ which is m2. The contractor's opportunistic behavior in this regard can lead to a financial dispute. Another example is where a BoQ item (say tiles) was insufficiently described, and an opportunistic contractor decided to buy a lower grade of tiles even when the unit rate could cover for a higher grade. Attempts to deny or reduce such claims can lead to disagreements that will put the project to a halt. These BoQ error-dispute relationships are presently poorly understood. Understanding these relationships will lead to a reduction in expensive and time-consuming construction disputes which tend to increase with increasing complexity of projects (Raji, 2017).

Research methodology

For this study, BoQ error sources and types of BoQ errors identified in previous studies were first listed during a rigorous literature review. The identified sources and errors were carefully considered by three senior quantity surveying academics for validity and appropriateness for inclusion in the study questionnaire. This process led to the clarification and merger of some of the factors. The study questionnaire sought the respondents' opinions on the frequency of sources of BoQ and types of BoQ errors pertaining to recently completed projects. Also, they were requested to indicate whether or not a dispute occurred in the project of reference. Contractors, builders, quantity surveyors, architects and engineers in Edo State Nigeria were the study population. These professionals and contractors prepare and use BoQs in the administration of construction contracts, and will be knowledgeable of BoQ errors, their sources and the disputes arising from the errors. The respective professional bodies supplied their memberships (the average number of members that attend meetings regularly) in Edo State as shown in Table 1. The construction contractors (n=61) covered by the study were those that are registered with the Edo State Public Procurement Agency. Using the Yamane (1964) formula for a finite population (equation 1), the sample size for the study was obtained as 241.

Where: n = sample size, N = population size (608), e = coefficient of confidence or margin of error or allowable error or level of significance (0.05). Questionnaires were administered conveniently on members of the sample that were accessible at the time of the study. In the end, 123 (51% response rate) useful copies of the questionnaire were returned and used in the analysis. Similar studies also had response rates within this range (Aibinu & Jagboro, 2002; Dosumu & Adenuga, 2013).

Methods of data analysis

Factor analysisFactor analysis is a data reduction technique that helps to obtain uncorrelated factors that account for most of the variances in a set of data (Fellows & Liu, 2015; Iyer & Jha, 2005). The technique was used in this study to reduce the sources of BoQ errors to a fewer number of factors. Before factor analysis, the data was tested for factorability. For a good factor analysis, the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy should be ≥0.6 and Bartlett's test of sampling sphericity should be significant at α=0.05 (p ˂ 0.05) (Fellows & Liu, 2015; Field 2005). The number of factors was decided based on eigen value of ≥1. Only variables with loadings of ≥0.6


were considered to have loaded significantly on each of the factors (Leung et al. 2005).

Canonical correlation

The canonical correlation was used to analyse the relationship between the two sets of variables. The method was chosen because both the dependent and independent variables (the factors obtained through factor analysis) are more than one. Secondly, it allows for the use of data in the ordinal scale (Hair, et al. 1998), and reduces the possibility of committing Type I error (Sherry & Henson, 2005). In a practical situation, projects are faced with many sources of BoQ errors, and the errors in a BoQ are usually more than one. Canonical correlation accommodates this complexity in which ≥2 dependent and ≥2 independent variables interact simultaneously (Thompson, 1990). A cut-off value of ≥0.30 was used to determine the significance of the canonical structure loading (rs) of the variables following the recommendations of Crum, Lund and van Auken (1987) and Munro (2005). To test the stability of the canonical correlation model, the processes recommended by Laessig and Duckett (1979) and Wiggins and Pincus (1989) were adopted. The stability of the model was tested by removing the predictor variables with rs ≤0.30 and repeating the canonical correlation. Variables with canonical commonality of ≤50% were considered to have insignificant contribution to the canonical model.

Logistic regression

Logistic regression was used to determine the relationship between BoQ errors and the incidences of disputes. It assumes that the relationship between the dichotomous dependent variable (dispute in this case) and an independent variable can be represented by a logistic distribution. It can be used to test the hypothesis about the relationship between categorical outcomes and a set of categorical or non-categorical predictors (Peng, Lee, & Ingersoll, 2002). Projects in which disputes occurred were coded 1 while those in which there were no disputes were coded 2. For the purposes of this study, a dispute was defined as a situation where a claim made by a party was denied by the other party resulting in up to 60 days delay of the project (whether or not formal dispute resolution mechanisms such as adjudication, arbitration or litigation were resorted to).

Findings and discussion

Factor AnalysisThe KMO test yielded a value of 0.944, while Bartlestt's test was significant at α=0.05 (p<0.05), which meant that the data were factorable. Based on the eigenvalue of 1 and a view of the scree plot (Figure 1), the factor analysis yielded 4 factors (see Table 2).



Factor 1 was named BoQ Compiler's Competence factor on the account of high loading of variables related to the competence of the BoQ maker such as reuse of old BoQ, lack of awareness of changes in standards, assumption of output of crew members based on past experience, among others. This factor accounted for most (32.356%) of the variance in the sources of BoQ errors. Similarly, factor 2 was christened designer's competence factor due to the high loading of design and management experience, errors in design/calculations, wrong specification/omission of specification, among others. Factor 2 explains 30.391% of the variance in the sources of BoQ errors. The third factor had high loadings in variables related to BoQ compilers' mistakes such as use of wrong unit of measurement, inadequate information on actual items of temporary works, allocating resources incorrectly, etc. Factor 4 likewise had high loadings in variables related to designer's mistakes including: carelessness and negligence of project consultant, incompleteness/contradiction of information, lack of planning and inspection of project site before design, lack of clarity and legibility and lack of consistency between drawings and specification. Factors 3 and 4 were named BoQ compiler's mistakes and designer's mistakes factors respectively.

Relationship between Sources of BoQ errors and types of error in BoQs

Table 3 shows the relationship between the 4 factors obtained by factors analysis and the 16 BoQ errors. The result shows that all the canonical roots are significant. To exemplify, for canonical root 1, Wilk's ʎ=0.000, F (64, 241.08) = 60.139, p˂0.001. However, canonical root 4 was disregarded due to the low canonical structure loadings (rs) (≤0.3) in all of its criterion variables.

The result in Table 3 means that a significant relationship exists between the error-sources (the 4 factors) and errors in BoQs. Therefore, H is rejected.o1


Table 4 presents the standardized coefficients (coeff), canonical structure loadings (rs), canonical correlation coefficients (Rc2), redundancies (Rd) and commonalities (h2) of the 3 canonical roots with at least one criterion (dependent) variables ≥0.30. It can be seen from Table 4 that the canonical commonality (h2) (which indicates the overall importance of a variable in a canonical correlation model) for designer's mistakes is below average (33.33%). This suggests that the factor contributes very little to the relationship between the two sets of variables. The canonical correlation analysis was, therefore, repeated while omitting the designer's mistakes. This second analysis tests the stability of the loadings obtained in the first analysis.


Table 3: Canonical correlations

Roots Correlations Eigenvalue Wilks Statistics F Num D.F Denom Sig.

5.720 1.080

4.967

5.000


Table 5 shows the results obtained when the designer's mistakes (factor 4) was omitted. Overall, the canonical correlation between the two sets of variables remained high. However, the Rd, which is the mean of the squared coefficient of multiple correlation between each variable in one set and all the variables in the other set were small for canonical roots 2 (4.3%) and 3 (1.6%). For canonical root 1, it was reasonably high (79.2%). This implies that as a whole, canonical roots 2 and 3 cannot be meaningfully interpreted (Dattalo, 2014). However, relationships between individual variables within these canonical roots are meaningful. For instance, canonical roots 2 reveals that dimensional errors (Y5) and item repetition in the BoQ (Y10) (criterion variables) are mostly caused by designer's competence and BoQ compiler's mistakes (predictors). Note that only variables that loaded significantly in both canonical correlations (Tables 4 and 5) were considered stable and worthy of interpretation. Canonical root 3 points to the relationship between bill compiler's competence and mistakes (predictors) and wrong assumptions in the BoQ (Y8). Predominantly, wrong assumptions in the BoQ emanate from the bill compiler either due to lack of competence or due to mistakes. The canonical loadings of all the criterion and predictor variables are significant in canonical root 1. The Rc2 and the Rd also have high values (Rc2=98.21%, Rd=79.2%). This is an indication that the predictors are related to the criterion variables. Thus, designer's competence (rs=-0.706) is the strongest predictor of errors in BoQ followed by BoQ compiler's competence (rs=-0.635) and lastly by BoQ complier's mistakes (rs=-0.315).



Stability Test

The data set was split into 2 and canonical correlation was carried out on 62 of the cases. The resulting canonical structure loadings were correlated with the loadings obtained in Table 4. The Pearson correlation coefficients were 0.949 (p=0.000), 0.465 (p=0.045) and -0.56 (p=0.013) for canonical roots 1, 2 and 3 respectively, which indicates that the loadings are related. Hence, the model can be adjudged stable.

Relationship between types of boq error and construction disputes

This test was carried out to determine the influence of the types of BoQ errors on the incidence of construction dispute. The inferential goodness of fit test of the model yielded a χ2 (16) = 51.514 (P<0.05) as presented in Table 6. This tests the null hypothesis that adding the types of BoQ error variables to the model did not significantly increased its ability to predict the incidence of construction dispute. The result shows that Ho2 should be rejected, and it is concluded that a significant relationship exists between types of BoQ errors and construction disputes. The measures of pseudo-R2 (Cox & Snell R square and Nagelkerke R square) suggest that the strength of the relationship as being between 34% and 45.7%. It should be noted, however, that these indices of goodness of fit are not the same as the coefficient of determination (R2) in multiple regression analysis in terms of the ability to measure the variance in the dependent variable explained by the independent variables (Peng, Lee & Ingersoll, 2002). The results further showed that, overall, 79% of the data were correctly classified by the discriminant analysis. Further examination of the classification table (Table 7) shows that both the dispute (81.9%) and no-dispute (75%) incidences were reasonably accurately predicted.

The detailed logistic regression model is shown in Table 8. The column Exp (B) shows the odds of the independent variables. At α=5%, only 3 of the independent variables have significant influences construction disputes. The variables are inaccurate quantities (Y2), Inadequate unit rates (Y9), and measuring mechanical and electrical works as provisional sums (Y16). The odds of the other variables are not significantly different from zero, and were therefore not interpreted. Thus, a unit rise in inaccurate quantities, increases the chance of construction dispute by 0.079, all other variables remaining constant. For Y9 and Y16, the increases are 9.527 and 36.136 respectively. Overall, this result indicates that use of provisional sums for mechanical and electrical services are the worst causes of construction disputes emanating from the BoQ. It also shows that although disputes could emanate from inaccurate quantities, their impact on the chances of construction disputes in a project is rather low.


aEstimation terminated at iteration number 20 because maximum iterations has been reached. Final solution cannot be found

Discussion of findings

The study found that BoQ error pathogens can be classified under BoQ compiler's competence, designer's competence, BoQ compiler's mistakes and designer's mistakes. This corroborates Dosumu, Idoro and Onukwube's (2017) observation that most errors in projects are consultant-related.

BoQ compiler's competence

Incidences of quackery in the Nigerian construction industry is already a known problem (Olusegun, et al. 2011). This study's result possibly points to quackery because reuse of old BoQ, lack of awareness of changes in standards and violation of codes, laws and regulations in contact documents loaded significantly. Quacks may be professionals of other built environment professions usurping the quantity surveyors' roles (Osubor, 2017), pupil quantity surveyors undertaking jobs for which they are ill-trained, or complete non-professionals undertaking quantity surveying tasks for pecuniary reasons. Although Jimoh, et al. (2016) submitted that projects supervised by professionals and non-professionals do not differ, however, that is not the case with BoQs prepared by professionals and non-professionals, where the incompetence of the BoQ compiler is considered a significant source of error.

Designer's competence

This factor was underpinned by high loadings in design and management experience, errors in design/calculations, wrong specification/omission of specification among others. Dosumu and Aigbavboa (2017) found that errors in design calculations and wrong/inadequate descriptions in specifications accounted for most of the cost of errors in projects. Project designers are usually either engineers or architects. In practice, design professionals often usurp one another's roles. Examples include where purely mechanical designs are undertaken by civil or electrical engineers being the primary consultants for a project. Sometimes, critical designs are left to pupil engineers without proper oversight by their experienced principals. This usually results in the loss of important details, and tend to compromise the BoQ compiler's ability to produce an accurate BoQ. This agrees with previous studies that errors in contract documents are traceable to consultant's experience (Dosumu and Iyagba, 2013), and lack of design reviews (Dosumu & Iyagba, 2013; Love, Edwards & Han, 2011)

BoQ compiler's mistakesUse of wrong unit of measurement, inadequate information on actual items of temporary works, allocating resources incorrectly for the project, incorrect use of computer device or software among others loaded significantly in this factor. These variables fall under the knowledge/rule-based mistakes identified by Reason (1995), Love et al. (2009) and Lopez et al. (2010). A mistake can be related to execution or evaluation of work


(Lopez et al. 2010). It applies where a person does not actually know what is required, but he executes what he knows (what he thinks is right) without achieving the expected outcome (Busby & Hughes, 2004; Reason, 1995). These mistakes likely arise from information overload and workplace stress to which BoQ compilers are subjected during procurement (Love et al. 2009). Additionally, the results support the findings of Hamma-Adama, Kouider, and Salman (2018) on the low level of competence in the use of specialised BIM software for BoQ preparation in the Nigerian construction industry which contributes to mistakes in BoQ compilation.

Designer's mistakes

This factor was underpinned by variables such as carelessness and negligence of project consultants, incompleteness/contradiction of information, lack of planning and inspection of project site before design among others. While Dosumu, Idoro and Onukwube (2017) found that carelessness and negligence are not important causes of errors in construction contract documents, most of the high loading variables in this analysis point to carelessness and negligence by the consultants. A plausible reason for this difference may be the dedication of this research to BoQ errors. Even where designer competence has been established as a fact, negligent actions like not inspecting the project site will still lead to unsuitable designs. Instances of such occur as a result of competitive professional fees (Lopez, et al. 2010), where the agreed fee is inadequate to motivate the consultant's wholehearted attention to the design task.

Relationship between sources of BoQ errors and types of BoQ error

Three canonical roots were discovered. In the first canonical root, with the exception of designer's mistake, the other 3 BoQ error sources (BoQ compiler's competence, Designer's competence and BoQ compiler's mistakes) are all significantly related to the types of BoQ errors. This supports the arguments of previous studies that manifest errors in contract documents owe their existence to latent error pathogens in the entire contract documentation process (Dosumu et al., 2017; Reason, 1995). However, designers' mistakes were found to have insignificant contribution to the entire canonical correlation model since its h2 was lower than the cutoff point (50%). Impliedly, BoQ errors relate more to the designer's competence than to his mistakes. Further, the overall relationships between the predictor and criterion variables observed in canonical roots 2 and 3 have low redundancies, and should be interpreted with caution. However, these canonical roots reveal that designer's competence and BoQ compiler's mistakes are related to dimensional errors (Y5) and item repetition in the BoQ (Y10) in canonical root 2, while BoQ compiler's competence and BoQ compilers mistakes are related to wrong assumptions in the BoQ in canonical root 3. Further studies are required to acceptably clarify these observations.

Relationship between types of BoQ error and construction disputes

The findings of this study are to the effect that the construction disputes emanating from the BoQ are usually related to inaccurate quantities (Y2) (Exp B=0.079), Inadequate unit rates (Y9) (Exp B=9.527), and measuring mechanical and electrical works as provisional sums (Y16) (Exp B=36.136). Basically, these three variables relate to disagreements over quantities and unit rates, since provisional sums imply that quantities are unknown or approximate at the time of contract. In the Nigerian public sector, BoQ quantities are mostly considered to be approximate, while the actual quantities to be paid for are determined after the work has been done (Federal Government of Nigeria, 2011; Federation Internationale Des Ingenieurs-Conseils (FIDIC), 2017). This presents challenges in that government projects are usually tied to budgets. When wrong quantities lead to variations in excess of the allowed contingency sums, the procuring entities run into disputes with the contractors. On the other hand, even when a firm-quantities conditions of contract such as the Nigerian Construction Industry Standard Form (Nigerian Institute of Quantity Surveyors, 2018) is used, disagreements over quantities is not entirely circumvented. In such cases, inaccurate BoQ quantities are treated as variations when discovered, which leaves the disadvantaged party unhappy. This result extends the finding of Dosumu (2018) to the effect that under/over measurement of quantities leads to construction dispute. However, the effect on dispute is currently small as a result of the predominance of approximate quantities conditions of contract in the industry.

Conclusion and recommendation

Errors encountered in BoQs in the study area arise from designer's competence, BoQ compiler's competence and BoQ compiler's mistakes. Therefore, it is particularly important to ensure that contract documents originate from the right professionals if the BoQs will be error free. The government should strengthen policies aimed at ensuring that only drawings and BoQs that are sealed by the appropriate professionals are acceptable in all public


procurements. This will provide an example for the private sector to follow. Quackery should be eliminated as much as possible in the preparation of BoQs. BoQs prepared by trainee quantity surveyors should be carefully scrutinised by their principals to minimise BoQ errors. The results of this study imply that the blame for BoQ errors are not the BoQ compiler's alone, but the designer's incompetence could also be to blame. Arising from this, BoQ compilers should not refrain from asking questions bordering on the integrity of the designs they are working with. Likewise, design professionals should ensure that the best design information available are used as the basis for their designs. Preferably, professionals with design and management experience in the type of project being designed should be allowed to vet designs prior to final submission for BoQ preparation. BoQ-related disputes predominantly arise from inaccurate quantities, inadequate unit rates, and measuring mechanical and electrical works as provisional sums. Based on this finding, it is concluded that BoQ related disputes arise from disagreements over quantities, rates and provisional sums. Quantity surveyors should not only enhance their ability to measure all items in BoQs completely, they should also ask for sufficient time to do their work. Contractors should ensure that their unit rates not only reflect the cost of the resources required to execute each work item, but also that they reflect the difficulties and risks associated with such work items. Further studies should explore the overall contributions of incompetence and mistakes of consultants on the incidences of construction disputes in the Nigerian construction industry.

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