ACTA Structilia · Acta Structilia 2018:25(1) Tydskrif vir die fisiese en ontwikkelingswetenskappe...

Vol 25 No 1 2018 http://dx.doi.org/10.18820/24150487

Tydskrif vir die fisiese en ontwikkelingswetenskappe

Journal for the physical and development sciences

ACTA

Structilia

http://dx.doi.org/10.18820/24150487

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http://dx.doi.org/10.18820/24150487/as25i1




Acta Structilia2018:25(1)Tydskrif vir die fisiese en ontwikkelingswetenskappe

Acta Structilia is ’n Suid-Afrikaanse geakkrediteerde tydskrif, wat publikasie geleenthede bied vir onafhanklik gerefereerde artikels deur plaaslike en buitelandse navorsers op die terreine van die fisiese en ontwikkelingswetenskappe. Elke gekeurde artikel word as sodanig aangedui. Die redaksie oorweeg Afrikaanse of Engelse artikels oor onderwerpe binne studie velde soos: argitektuur, stads- en streekbeplanning, bourekenkunde, konstruksie- en projekbestuur, bou-ekonomie, ingenieurswese, die eiendomsbedryf en die ontwikkelingsveld rondom gemeenskapsbouprojekte. Acta Structilia verskyn twee keer per jaar onder die vaandel van die Universiteit van die Vrystaat. Die tydskrif word gelewer aan die betrokke navorsingsinstansies, Suider-Afrikaanse universiteite met bogemelde navorsings-departemente, Suid-Afrikaanse navorsingsbiblioteke, geselekteerde buitelandse instansies en intekenaars. Menings en kritiek in die tydskrif is dié van die outeur(s). Publikasie daarvan is nie ’n aanvaarding dat die Redaksie of die Universiteit van die Vrystaat verantwoordelikheid daarvoor aanvaar nie.

Intekengeld:

Suid-Afrika: R100 per kopieInternasionaal: VSA$40 per kopie

Journal for the physical and development sciences

Acta Structilia is a South African accredited journal for independently adjudicated research articles on any topic in the field of the physical and development sciences. Each peer refereed article is indicated as such in the journal. The editorial staff considers articles in English and Afrikaans, written from any responsible point of view on subjects in any applicable field of scholarship, i.e. architecture, urban and regional planning, quantity surveying, construction management and project management, building economy, engineering and property or community development. Acta Structilia is published biannually by the University of the Free State. The journal is forwarded to all relevant research units and universities, Southern African research libraries, selected research institutions and libraries abroad, and to subscribers. Views and opinions expressed in this journal are those of the author(s). Publication thereof does not indicate that the Editorial Staff or the University of the Free State accept responsibility for it.

Subscription fees:

South Africa: R100 per copyInternational: US$40 per copy

Redaksie • Editorial Staff

Redakteur • Editor-in-Chief Prof. K Kajimo-Shakantu (Department of QuantitySurveying and Construction Management, University of the Free State, South Africa)

Adjunkredakteur • Deputy Editors Dr MM Campbell (Department of Town and Regional Planning, University of the Free State, South Africa)

Mr HB Pretorius (Department of Architecture, University of the Free State, South Africa)

Assistentredakteur • Assistant Editor Mrs AE Beukes (Department of Quantity Surveying and Construction Management, University of the Free State, South Africa)

Redaksionele • Raad Editorial board

Dr K Agyekum (Department of Building Technology, Kwame Nkrumah University of Science and Technology, Ghana)Mr T Ayalew (Department of Construction Management, Addis Ababa University, Ethiopia)Prof. G Crafford (Department of Quantity Surveying, Nelson Mandela University, South Africa)Dr G di Castri (Italian Institute of Chartered Engineers, Milan, Italy) Dr A Elkhalifia (Department of Construction Management and Economics, University of Khartoum, Sudan)Dr JA Fapohunda (Department of Construction Management and Quantity Surveying, Cape Peninsula University of Technology, South Africa)Prof. TC Haupt (Faculty of Engineering, Mangosuthu University of Technology, South Africa)Mrs E Hefer (Department of Construction Management and Quantity Surveying, Durban University of Technology, South Africa)Dr R Jimoh (Department of Building, Federal University of Technology, Minna, Nigeria)Mr C Kabuka (Director of Legal, Compliance and Regulatory, IHS Zambia Limited, Zambia)Mr A Kerin (President, Slovenian Project Management Association, Slovenia)Prof. K London (Property Construction & Project Management, RMIT University, Australia)Emer Prof. G McLachlan (Architect, Port Elizabeth, South Africa) Prof. K Michell (Deparment of Construction Economics and Management, University of Cape Town, South Africa)Mr I Moss (Department of Construction Management and Quantity Surveying, Walter Sisulu University of Technology, South Africa)Dr S Mukiibi (Department of Architecture and planning, Makerere University, Uganda)Mr C Musonda (Chairman Sherwood Greene Properties, Zambia)Prof. G Ofori (School of the Built Environment and Architecture, London South Bank University, London, United Kingdom)Mr MA Oladapo (Chief Executive, Murty International Limited, Nigeria)Dr S Ramabodu (QS-online Quantity Surveyors, Bloemfontein, South Africa)Dr I Saidu (Department of Quantity Surveying, Federal University of Technology, Minna, Nigeria)Prof. JJ Smallwood (Department of Construction Management, Nelson Mandela University, South Africa)Dr P Smith (Program Director of Construction project Management in the School of Building at University of Technology Sydney, Australia)Prof. J Tookey (Department of the Built Environment, AUT University, New Zealand)Mr K Trusler (EduTech Director, The Association of South African Quantity Surveyors, South Africa)Mr B van den Heever (Bert van den Heever Quantity Surveyors and Project Managers, South Africa)Prof. C Vosloo (Department of Architecture, University of Johannesburg, South Africa)Prof. BG Zulch (Department of Construction Economics, University of Pretoria, South Africa)

Acta Structilia Jaargang 25 Volume

Nommer 1 Number Junie 2018 June

Inhoud • Contents

Navorsingsartikels • Research articles

An exploratory factor analysis of risk Bérenger Renault 1 management practices: A study among Justus Agumba small and medium contractors in Gauteng Nazeem Ansary

An assessment of the causes, cost effects Oluwaseun Dosumu 40 and solutions to design-error-induced Clinton Aigbavboa variations on selected building projects in Nigeria

Successful transformational change in revenue Ric Amansure 71 management among beneficiary communities Chris Adendorff of South African renewable energy construction companies

A construction project management Michelle Burger 98 knowledge model: The type and level Benita Zulch of knowledge required

Assessment of housing quality in Ibeju-Lekki Funmilayo Adedire 126 peri-urban settlement, Lagos State, Nigeria Michael Adegbile

Oorsigsartikels • Review articles

Construction project management Hendri du Plessis 152 through building contracts, a South African Pierre Oosthuizen perspective

Boekresensie • Book review

Facilities Management Practice by Nico Janse van 182 A.C. Hauptfleisch, 2017. 1st edition. Rensburg Pretoria: South Africa: Career Excel Academy

Inligting aan outeurs • Information for authors 183

The South African Council for the Quantity Surveying Profession endorsesActa Structilia

The South African Council for the Quantity Surveying Profession (SACQSP) has simplified the submission and assessment of Continuining Professional Development (CPD) requirements of registered persons. CPD submission now requires disclosure of the number of hours invested meaningfully in activities in two main categories. Category 1 activities are those arranged or presented by or to ‘external’ organisatins such as participation in conferences, congresses, workshops or seminars, presentation of lectures, external examination for academic programmes, publication of articles in journals or magazines, other similar activities. Category 2 activities are less formal ‘internal’ activities such as in-house training or seminars, small group discussions, self-study of journals, magazines, articles on web pages, etc.

To assist registered persons with access to journal articles related to quantity surveying and, more generally, built environment issues, the SACQSP at its meeting in March 2007 adopted a recommendation to endorse the journal, Acta Structilia, which publishes quality, peer-reviewed articles and is accredited by the Department of Education.

Council encourages registered persons to peruse Acta Structilia and similar peer-reviewed journals as one of the alternative options to accumulate CPD credits in Category 2 activities. For a limited period, Council will encourage the circulation of Acta Structilia to registered persons.

Professor RN NkadoPresident

Royal Institution of Chartered Surveyors (RICS) supports Acta Structilia

Royal Institution of Chartered Surveyors (RICS) supports the aims and objectives of Acta Structilia and welcomes the efforts being made to improve our knowledge and understanding of the built environment, particularly in an African context.

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An exploratory factor analysis of risk management practices: A study among small and medium contractors in Gauteng

Peer reviewed and revised

*The authors declared no conflict of interest for this article or title.

AbstractRisk management (RM) is acknowledged as a key activity in project management in the pursuit to deliver successful construction projects. However, these projects are associated with various risks, which often jeopardise project performance, especially among small and medium construction enterprises (SMEs). Risk management practices (RMPs) have been developed, in order to curtail project risks. Nevertheless, there is no consensus on the practices that constitute RM for SME projects. Therefore, the main purpose of this research is to determine the RMPs that can be tailored for construction SMEs to manage risk in their projects, in order to achieve project success. An extensive review of relevant literature on RMPs was conducted and used to develop a structured questionnaire posted to construction SMEs who were conveniently sampled in the Gauteng province of South Africa. The empirical findings established nine RMPs that were reliable and valid for managing risk in projects undertaken by construction SMEs, namely organizational environment; defining project objectives; resource requirements; risk measurement; risk identification; risk assessment; communication approach and evaluation; risk response and action planning, as well as monitoring and review. It is important to note that the study was not conducted across South Africa; hence, the findings cannot be generalized. Despite the delimitation, the researchers recommend that these practices are for risk management in construction projects undertaken by SMEs in South Africa.

Bérenger Renault

Mr Bérenger Y. Renault, Department of Construction Management and Quantity Surveying, University of Johannesburg, Johannesburg, South Africa. Phone: +27 73 101 6707, email: <[email protected]>

Justus Agumba

Dr Justus N. Agumba, Department of Construction Management and Quantity Surveying, Durban University of Technology, Durban, South Africa. Phone: +27 31 373 2466, email: <[email protected]>

Nazeem Ansary

Mr Nazeem Ansary, Department of Construction Management and Quantity Surveying, University of Johannesburg, Johannesburg, South Africa. Phone: +27 11 559 6056, email: <[email protected]>

DOI: http://dx.doi.org/10.18820/24150487/as25i1.1ISSN: 1023-0564e-ISSN: 2415-0487Acta Structilia 2018 25(1): 1-39© UV/UFS

mailto:[email protected]




http://dx.doi.org/10.18820/24150487/as25i1.1



Acta Structilia 2018: 25(1)

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Keywords: Factor analysis, risk management practices, small and medium enterprises, South AfricaRisikobestuur (RB) word erken as ’n sleutelaktiwiteit in projekbestuur in die strewe om suksesvolle konstruksieprojekte te lewer. Hierdie projekte word egter geassosieer met verskeie risiko’s wat projekprestasie dikwels in gevaar stel, veral onder klein en medium konstruksie-ondernemings (KMO’s). Risikobestuurspraktyke (RBP) is ontwikkel om projekrisiko’s te beperk. Tog is daar geen konsensus oor die praktyke wat RB vir KMO-projekte uitmaak nie. Die hoofdoel van hierdie navorsing is dus om die RBP te bepaal wat aangepas kan word vir konstruksie-KMO’s om risiko in hul projekte te bestuur ten einde projeksukses te behaal. ’n Uitgebreide literatuurstudie oor RBP is gedoen en gebruik om ’n gestruktureerde vraelys te ontwikkel wat aan konstruksie-KMO’s in die Gauteng provinsie van Suid-Afrika gepos is. Die empiriese bevindinge het nege RBP opgestel wat betroubaar en geldig was vir die bestuur van risikos in projekte wat deur konstruksie-KMO’s onderneem is, naamlik organisatoriese omgewing; definisie van projekdoelwitte; hulpbronvereistes; risiko-meting; risiko-identifikasie; risikobepaling; kommunikasiebenadering en evaluering; risikoreaksie en aksiebeplanning, sowel as monitering en hersiening. Dit is belangrik om daarop te let dat die studie nie oor die hele Suid-Afrika uitgevoer is nie; daarom kan die bevindings nie veralgemeen word nie. Ten spyte van die beperking, beveel die navorsers aan dat hierdie praktyke is wat vir risikobestuur in konstruksieprojekte deur KMO’s in Suid-Afrika onderneem moet word.Sleutelwoorde: Faktoranalise, klein en medium ondernemings, risikobestuurs-praktyke, Suid-Afrika

1. IntroductionThe construction industry (CI) is one of the largest employers globally. It employs approximately 7% of the global work force or 180 million people and it is predicted to account for approximately 13% of the Global Domestic Product (GDP) by 2020 (Nieuwenkamp, 2016). In South Africa (SA), the CI employed 1 395 000 people (formal and informal sectors), contributing 3.9% to national GDP (StatsSA, 2017). Despite its economic contribution, a construction project is well acknowledged as the riskiest project to execute because of the complexity of its activities, operating environment, and processes involved prior to and during project execution (Gao, Sung & Zhang, 2013). The complexity of its activities and the risk environment lead to poor project performance, especially among small and medium construction enterprises (SMEs), whose contribution to the economy is substantial. This contribution has been recognised in many countries (Mutezo, 2013: 157; Abor & Quartey, 2010: 223; Ellegaard, 2008: 428) and especially in African countries such as South Africa and Nigeria, where they contribute 51% and 57% to national GDP (Kalane, 2015: 15). In Nigeria, SMEs have contributed approximately 48% of the national GDP in the last five years (Aroloye, 2017). As such, the South African government utilizes SMEs to attain three main objectives, namely poverty alleviation, job creation opportunities,

Renault, Agumba & Ansary • An exploratory factor analysis ...

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and promoting economic growth (Leboea, 2017: 39). To buttress this statement, Mutezo (2013: 155) stated that SMEs are often regarded as the backbone of the economy and the main driver of economic growth in the country (Falkner & Hiebl, 2015: 131).

Regardless of the noted economic significance, it is estimated that many SMEs in South Africa fail to go past the end of their second year of business establishment (Marcelino, Pérez-Ezcurdia, Echeverría Lazcano & Villanueva, 2014: 332; Cant & Wiid, 2013: 710). Perera (2016) supported this statement by arguing that many SMEs do not survive beyond their first five years of business establishment and that eight out of ten SMEs fail every year. Studies have revealed that many SMEs fail, due to a number of factors, which include, but are not restricted to the lack of access to finance (Boone & Kurtz, 2006; Ramlee & Bernma, 2013; Brown & Lee, 2014) and lack of appropriate management skills (Olawale & Garwe, 2010: 731). However, Rostami, Sommerville, Wong & Lee’s (2015: 98) study revealed that 80% of SMEs failures are as a result of management failure. It was indicated that there is a necessity to improve corporate governance and the link to risk management (RM). In performing their activities, SMEs face many risks that are often similar to those of large enterprises. SMEs, however, tend to experience more risks than large enterprises, and the risk of not delivering the project within its set target is higher in SMEs than in large enterprises (Rostami et al., 2015: 98). As a result of high exposure to risk and failure, investors and banks have become hesitant about funding SMEs (Ellegaard, 2008: 429; Kraus, Rigtering, Hughes & Hosman, 2012: 161).

Risk management practices (RMP) have been developed in order to curtail project risks. However, RM is still not widespread among construction SMEs. Even though it is not a new concept, it has lately become a growing priority in any construction project management (Jurgensen, Duijm & Troen, 2010: 1040). RM in construction refers to a process that consists of identifying, assessing, and planning actions to deal with potential risks that may influence the successful achievement of project objectives (Kraus et al., 2012: 161). The inability of SMEs’ owners to apply the RM process has contributed in RM becoming one of the factors that leads to lowering the sustainability of SMEs (Falkner et al., 2015:130). RM can help SMEs to efficiently deal with negative occurrences that could jeopardize the successful achievement of project objectives. However, Marcelino-Sádaba et al.’s (2014: 332) study reported that many SMEs do not or not adequately apply RMPs, mostly because they cannot afford to rededicate resources due to their constraints. Lack of RM strategies in place also remains to be a common trend among SMEs amidst


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many risks, a factor that could be closely linked to the high failure rate (Nunes, Viveiros & Serrasqueiro, 2012: 453). According to Gao et al. (2013: 683), knowledge on the risk management strategies applied by SMEs remains scanty, especially in less developed economies. Furthermore, Gunasekaran, Rai & Griffin (2011: 5494) point out that the lack of adoption and implementation of mitigative strategies in SMEs projects have resulted in many projects not achieving set objectives.

Chihuri & Pretorious (2010: 65) postulated that, in South Africa, risk management was also not widely used among both small and large firms and that there was a lack of actual adoption and implementation of RM practices. Yaacob (2015: 496) argues that scientific effort among researchers to investigate issues on RMPs is inadequate and emphasises that research on RMP of SMEs is minimal compared to SMEs’ critical contribution to the economy. In order to overcome project failures, Cooke-Davis (2002: 188) established that project success is highly dependent upon the implementation of RMPs. Rounds & Segner (2011: 104) described it as one of the most capable areas and critical procedures that help complete projects successfully. Furthermore, Imbeah & Guikama (2009: 778) argued that RMPs are closely aligned with overall project performance.

The scarcity of scientific research on RMPs and poor project perfor-mance highlight, the need to determine RMPs that construction SMEs can use to improve their project performance. Furthermore, although many studies have been conducted on RM among SMEs, the plethora of studies lack consensus of the RMPs to be used by construction SMEs. The purpose of this study is, therefore, to determine the reliable and valid RM practices tailored for construction SMEs projects, using exploratory factor analysis.

2. Risk management in SMEsA study conducted by Gao et al. (2013: 684) indicated that formal RM frameworks are designed for large enterprises, and that the frameworks are too complicated and pricey for SMEs to adopt. According to Blanc-Alquier & Lagasse-Tignol (2006: 18) and Gao et al. (2013: 684), SMEs lack RM knowledge, skills and capability. SMEs’ owner managers are so knowledgeable about their ventures and are commonly not able to identify all the risk elements that have an impact on their business activities (Smit & Watkins, 2012: 6326). These statements are supported by Sullivan-Taylor & Branicki (2011: 5565) and Gunasekaran et al. (2011: 5498) who believe that implementing formal RM process is not feasible because of SMEs’ restricted resources.


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Contrarily, Corvellec (2009: 288) argued that organizations might implicitly implement RM. RM is embedded in daily management activities and business processes. Organizations do not openly state that they are addressing risks and implementing RM. Nevertheless, they are addressing risks encountered by their organizations in an effective manner. Poba-Nzaou, Raymond & Fabi (2014: 488) concurred with the study. They revealed that SMEs’ RM practices are informal, unstructured, and instinctive. However, they still effectively address management risks. Poba-Nzaou, Raymond & Fabi (2014: 488) interpret this as SMEs demonstrating RM capability.

Establishing risk initiatives for construction SMEs is critical to the success of their projects. SMEs’ failure is often due to high levels of non-application of RM processes, unmanaged risks and worst-case scenarios, and the inability to manage risks. However, Ekwere (2016: 32) notes that the objective of RM is not to prevent risk-taking, but to ascertain that risk is taken with a clear understanding and knowledge to enable its measurement and mitigation with an organization. SMEs are also found to have backward-looking perspectives as opposed to a transformed and forward-looking approach that promotes continuous improvement (Ching & Colombo, 2014: 77). According to Watt (2007: 26), SME senior managers should consider the following steps in their RM processes: establish the SMEs’ risk strategy; determine the risk appetite; identify and assess the risk, and prioritize and manage the risk.

Having an understanding of the RM process surrounding the organization is useless if inadequate RM initiatives are applied. Owners and managers of construction SMEs need to take RM as a process that utilizes internal controls as measures to mitigate and control risk pertaining to their organizations. Hence, owners and managers in SMEs need to be conversant with risk identification and analysis, in order to manage risks from a diverse range of sources (Schultz, 2001). Schultz’s statement is complemented by Smit & Watkins (2012: 6328) who stipulate that SMEs that incorporate RM are better equipped to exploit resources pertaining to their organizations, thus enabling SMEs to convert an expenditure activity into an activity that can yield a positive return (Hsu, Lien & Chen, 2013). According to Napp (2011: 34), risk occurrence can be a danger to SMEs in continuity; it is of paramount importance that SMEs focus and try to implement comprehensive RM. The main outcome of RM is to reduce the number of threats that materialize into problems and to minimize the effect of those that do occur (Hillson, 2009). Taking the above into consideration, it is clear that RM is of paramount importance. If RM is


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managed effectively and efficiently, it can help businesses become more cost effective.

2.1 Identified risk management practices

There was no particular study with similar factors and the measures that deemed to influence project outcome. The extensive literature review suggested nine theoretical RM practices that SMEs could use to manage their projects in order to achieve successful project delivery. These practices are discussed in detail in this section.

2.1.1 Organizational environment

According to the Institute of Risk Management (IRM, 2002), the internal environment influences an organization in adopting a comprehensive and collaborative approach to risk and, therefore, impacts positively on the outcome of the project. In addition, it influences management decision-making to achieve the right balance of risk and opportunity. Likewise, the external environment evaluates the strategic alignment of an organization’s RM and its external operating environment (IRM, 2002). Smit (2012: 67) indicated that understanding the organizational environment of risk ensures that all organizational stakeholders understand their responsibilities and accountabilities, as well as identify possible weak areas that may influence the project from achieving its objectives. As stakeholders play a crucial role in the success of any project, scholars studying the construction sector (Olander & Landin, 2005: 323; El-Gohary, Osman & Ei-Diraby, 2006: 597; Bosher, Dainty, Carrillo, Glass & Price, 2007: 165; Momeni, Hamidizade & Nouraei, 2015: 416) established that stakeholder involvement has undeniable impacts on project outcomes. Furthermore, in exploring the effect of organizational environment, top management involvement, and stakeholder’s involvement on the success of a project, Basu, Hartono, Lederer & Sethi (2002: 516) observed that these factors were considerably related to project success. From the discussion, it can be suggested that understanding the organizational environment is an important practice of RM and project success.

2.1.2 Defining project objectives

According to Goetz (2010), unclearly defined objectives lead the project into overruns, personality clashes, unhappy clients, and missed milestones. Defining project objectives aids in aligning the organization whereby the project objectives are clearly visible and understood, hence positive and negative risks in achieving the objectives are identified and understood, and risk responses


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are aligned (Boubala, 2010: 14). In support of this statement, Goetz (2010) and Beleiu, Crisan & Nistor (2015: 64) added that keeping project objectives in the vanguard of every project assures that the project and the team are in sync during the course of the project’s life cycle. They deduced that clearly defined objectives will enable the project’s successful result. It can thus be suggested that defining project objectives is imperative practice for RM.

2.1.3 Resource requirements

RM resources are important in a project, as they enable RM perfor-mance of the project to be achieved (Oztas & Okmen, 2005: 1246; El-Sayeh, 2008: 435). Muthuramalingam (2008: 5) established that availability of resources was a good predictor of RM performance, thus contributing to a successful completion of the project. Haughey (2014: 2-3) concluded that RM resources influenced project success. Scheid (2011) stated that a project’s resources need to be considered, in order to keep on track with successful outcomes. Manfredi & Auletta (2013) concurred with Scheid (2011) who indicated that the availability of resources had an impact on the decrease of cost overruns in projects.

2.1.4 Risk measurement

Smit (2012: 71-72) indicated that defining and documenting the risk measurement of a project was crucial to its success. He observed that risk measurement influences the outcome of the project in defining the risk measurement criteria to be used (e.g., classification system of high, medium, or low); defining risk materiality (when risk is important), and determining the level of acceptable risk and risk time frame applicable to risk impact and risk probability (i.e., when risk is expected to occur, e.g., next month, next year, and so on). Phoya (2012: 28) declared that, in order to successfully achieve project objectives, a project team has to define a classification rule set (risk measurement) for each impact type that is relevant. The author further stipulated that risk measurement can detect the key influences on project outcome and allow the effects of uncertainty to be determined. Karimi, Mousavi, Mousavi & Hosseini (2010: 9108) indicated that, when risk measurement is used, it reduces risk impact on the project regarding schedule, budget, and quality. Goossens & Van-Gelder (2002) demonstrated that risk measurement, being one of the activities of RM, influenced project success and project performance.


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2.1.5 Risk identification

The results of Al-Shibly, Louzi & Hiassat (2013: 22) indicated that risk identification influenced project success. Similarly, Ewer & Mustafa (2008: 1-6) observed that some authors (Martins, 2006: 56; De Bakker, Boonstra & Wortmann, 2011: 78; Grote & Moss, 2008: 88-89) inferred that, when management involvement increases in risk identification, the risk of unclear or misunderstood scope seems to lessen and improve project performance and, hence, influence positively a project’s outcome. A study conducted by De Bakker et al. (2011: 78) stipulates that risk identification contributes to project success. They also inferred that the interaction through discussion between project members during risk identification has a positive impact on the perceived success of the project.

2.1.6 Risk assessment

Roque & De Carvalho (2013: 102) established that risk assessment activity makes a greater significant impact on the success of the project. The results indicated that adopting risk assessment has a substantial positive impact on the project success, as project staff are able to take actions to mitigate the occurrence of risks to a greater extent. Al-Shibly et al. (2013: 34) tested the relationship between risk assessment and planned budget. The authors established that there was an impact of risk assessment on project planned budget. Furthermore, Smit (2012: 83), Zeng & Smith (2007: 594), El-Sayegh (2008: 433) and Abu Mousa (2005: 18-19) affirmed the influence of risk assessment on the successful completion of a project. They reported that assessing uncertainties during the project, making use of the RM strategies, and understanding the business environment, significantly impact on project outcome.

By assessing risk, managers can distinguish between acceptable and unacceptable risk events, thus enabling them to capture and process information to assist them in the development of a risk management strategy (Oztas & Okmen, 2005: 1248; Nieto-Morote & Ruz, 2011: 226; Karimi et al., 2010: 9107). Likewise, Naidoo (2012: 24), indicated that risk assessment once performed, improved project objectives, accurate schedule, improved communication between relevant parties, and hence increased the likelihood of project success.

2.1.7 Risk response and action planning

Al-Rousan, Sulaiman & Salam (2010: 6-7) argued that there is no such thing as a project without risks and problems. The authors added that, if a project is successful, then it is not successful, because


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there were no risks and problems, but because appropriate responses were developed which led to successful completion of the project. Kutsch & Hall’s (2005: 596) studies established that project performance can be improved by developing mitigating measures that positively influence risk response for project success. Gajewska & Ropel (2011: 32) and Alberto & Timur (2013: 72) stated that risk response and action planning influence project success. The latter authors established that, when conducted, risk response will change the risk profile through the project life cycle, and risk exposure will diminish. Omphile (2011: 52) and Aimable (2015: 9-10) established that risk response activities are strongly linked to the success of construction projects. Omphile (2011: 52) further indicated that the impact of responding to a risk may make sense in the short term by saving design costs, allowing the team to meet schedule. Moreover, Baccarini, Salm & Love (2004: 288) indicated that one of the documented keys to project success is mitigating the influence of potential project risks to improve the chance of project success.

2.1.8 Communication

Aulich (2013: 96) indicated that communication between project head and management is crucial to the success of construction projects. This is generally influenced by the principal agent relationship between the parties and the contract type chosen (Kelkar, 2011: 112). Naidoo (2012: 29) showed that a balance between formal and informal communication between project manager and other stakeholders reduces mistrust and conflict of interest. Likewise, Zulch (2012: 54) opined that communication influenced project success. The author further established that managers spend approximately 90% of their working time engaged in some form of communication, be it meetings, writing emails, reading reports, or talking to project stakeholders. Therefore, communication in construction provides a positive contribution to projects, by improving the motivation of project members and the effectiveness of the performance (Aulich, 2013: 96). De Bakker et al. (2011: 83) stipulated that, in situations where risks are not shared openly, the positively communicative effect may not occur, hence, stifling the success of a project.

2.1.9 Monitoring, review and continuous improvement

A study by Prabhakar (2008: 8-9) pointed out that monitoring, review and continuous improvement influenced project success. Likewise, Papke-Shields, Beise & Quan (2010: 659) also asserted that the likelihood of achieving project success seemed to be enhanced by other factors, by regularly monitoring the project progress.


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In addition, Hwang & Lim (2013: 209) and Kamau & Mohamed (2015: 84) established that project monitoring and review allow management to verify that the control actions that were applied are efficacious in order to achieve project success. If control actions are found to be ineffective, these should be revised, or new control actions be implemented, thus enabling continuous improvement in future projects (DEAT, 2006: 8). Rezakhani (2012: 19) indicated that project monitoring and continuous improvement is even more critical than planning in achieving project success. Likewise, many researchers (Spikin, 2013: 104-105; Chin, 2012: 42 indicated that one of the elements of the project management methodology whose main aim is to achieve project success is monitoring project progress.

3. ResearchThe purpose of this research was to determine the RMPs that can be tailored for construction SMEs to manage risk in their projects, in order to achieve project success. A quantitative research design was adopted. This type of design allows for the use of structured questionnaire surveys, enabling researchers to generalise their findings from a sample of a population (Creswell, 1994). In the questionnaire, nine risk management practices (constructs), consis-ting of 42 measures, were extracted and set as the variables of risk management practices SMEs should follow (Netemeyer, Bearden & Sharma, 2003). Exploratory factor analysis (EFA) was used to assess these measured variables in terms of their validity and reliability. EFA is a type of technique that analyses the unidimensionality (characteristics) of each of the defined risk management practices (original variables), in order to reduce it to a common score (smaller number of factors) by examining relationships among these quantitative factors (Pallant, 2013: 192; Rossoni, Engelbert & Bellegard, 2016: 200). Several factor analysis methods are available, but principle component analysis (PCA) was used, because the Eigenvalues could be extracted, which explains whether the factors tested had or had not a noticeable effect on people’s responses to the variables in the original test (analysed construct) (Rossoni et al., 2016: 201; Yang, Shen & Ho, 2009: 163-164; Pallant, 2013: 192).

3.1 Sampling method and size

A list obtained from the CIDB register of contractors containing 548 addresses of SMEs forms the population for the study. A total of 225 participants registered with the CIDB, but located in the city of Johannesburg Metropolitan Municipality, city of Tshwane


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Metropolitan Municipality, Ekurhuleni Metropolitan Municipality, and the West Rand District Municipality, was conveniently sampled from this list, because they were easiest to access (Etikan, Musa & Alkassim, 2016: 2). The sample size used the general Rule of Thumb method. Van Voorhis & Morgan (2007: 34) recommend 10 participants per measurement; 20 participants should be added for each independent variable. With nine factors (constructs), the sample size was 9 x 20 = 180, but 45 additional participants were added, resulting in a total sample of 180 + 45 = 225. The sample size table by Krejcie & Morgan (1970: 608) recommends a sample size for a population of 500 as 217. This recommendation validates the sample size of 225 as efficient for the population of 548.

3.2 Response rate

From the 225 original questionnaires, 181 completed ones were returned, resulting in a high response rate of 96%. According to Moyo & Crafford (2010: 68), contemporary built-environment survey response rates range from 7% to 40%, in general.

3.3 Data collection

A structured questionnaire survey was distributed to 187 SMEs in South Africa, using the drop-and-collect method and electronic email from July to September 2016. Topics on risk management practices used in the questionnaire were extracted from reviews of the literature, resulting in the formulation of a questionnaire divided into two sections. Section one on respondent’s profile obtained personal information on current position and years of experience in business, gender, education qualification, risk management responsibility. It also obtained the company profile information, which included location of the business and type of contractor. Section two sets questions on nine risk management practices consisting of 42 measures. The respondents were required to indicate their level of agreement, in practice, with these measures defining the risk management practices. The data from these measurements forms the variables used in the EFA, which tested the validity and reliability of the factors. To reduce the respondent’s bias, closed-ended questions were preferred for section two (Akintoye & Main, 2007: 601).


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3.4 Data analysis and interpretation of findings

The Statistical Package for Social Science (SPSS) version 23 was used to determine the factor analysability of the risk management practices, using inferential statistics (Pallant, 2013).

To rank which of the nine risk management practices consisting of 42 measures were practice, the measures were rated on a five-point Likert scale. Likert-type or frequency scales use fixed choice response formats and are designed to measure attitudes or opinions (Bowling, 1997). The following scale measurement was used regarding mean scores, where 1 = Strongly disagree (≥ 1.00 ≤ and <1.80), 2 = Disagree (≥ 1.81 and ≤ 2.60), 3 = Neutral (≥ 2.61 and ≤ 3.40), 4 = Agree (≥3.41 and ≤ 4.20), and 5 = Strongly agree (≥4.21 and ≤ 5.00).

For analysis of the internal reliability of the factors in the questions on risk management practices, Cronbach’s alpha values were tested (Kolbehdori & Sobhiyah, 2014: 347; Wahab, Ayodele & Moody, 2010: 67). Tavakol & Dennick (2011: 54-55) and Yount (2006) suggested that the acceptable values of Cronbach’s alpha would range from 0.70 to 0.95. In the current study, a cut-off value of 0.70 was adopted. Furthermore, the optimal inter-item correlations mean (factor loadings) should range from 0.2 to 0.4, in order for the factor to be reliable (Pallant, 2013: 134). However, in this study, a value of 0.3 and above was adopted.

To confirm whether the data from the measurements was sufficient for factor analysis (test the validity), the Kaiser-Meyer-Olkin (KMO) test (Lorenzo-Seva, Timmerman & Kiers, 2011) and the Bartlett’s sphericity test (Hair, Black, Babin, Andersen & Taham, 2006: 110) were performed. In the KMO test, as the values of the test vary from 0 to 1, values above 0.7 are recommended as being desirable for applying EFA (Hair et al., 2006) and a statistically significant Bartlett test (p < 0.05) indicates that sufficient correlations exist between the variables to continue with the analysis (Hair et al., 2006: 110; Pallant, 2013: 190).

For factor extraction, Principal Components Analysis (PCA) was used to summarise most of the information into a minimum number of factors, by concentrating the explanatory power on the first factor (find the principal components of data) (Rossoni et al., 2016: 102). In PCA, when the number of variables (measures) is between 20 and 50, it is more reliable to use Eigenvalues to extract factors, as it makes interpretation simpler (Johnson & Wichern, 2007). The highest Eigenvalues in the data is, therefore, the principal components in the


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data, which are retained to form a set of few new variables (less than the original variables started with in the analysis).

3.5 Limitation(s) of the study

It is important to note that the study was not conducted across South Africa; hence, the findings cannot be generalised.

4. Results

4.1 Respondents’ profile

The first part of the questionnaire comprised questions relative to the demographic profile of the respondents, the people in the best position to indicate their level of agreement in practice with the measures defining the risk management practices. Table 1 shows the professions of the respondents. These include owner, owner-manager, manager, and project manager. It is obvious that the majority (87.6%) of the respondents were either owners or managers of their enterprise, male (81.8%), and had either Matriculation (22.7%) or a Certificate (20.4%); 43.1% of respondents had 10 years’ or less experience in construction.

Table 1: Respondents’ profile

Position Frequency Percentage (%)

Owner 56 30.9

Owner-manager 40 22.1

Manager 28 15.5

Project manager 31 17.1

Other 26 14.4

181 100.0

Gender Frequency Percentage

Male 148 81.8

Female 33 18.2

181 100.0


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Risk management responsibility Frequency Percentage (%)

Top management 108 59.6

Operation manager 15 8.3

Organization collective effort 11 6.1

Project manager 13 7.2

Owner 29 16.0

The risk task team 5 2.8

181 100.0

Highest education qualification Frequency Percentage (%)

Doctorate degree 3 1.7

Master’s degree 11 6.1

Honours/BTech/BSc 27 14.9

HND/Diploma 29 16.0

Certificate 37 20.4

Matriculation 41 22.7

Basic schooling 26 14.4

No qualification 5 2.8

179 100.0

Years of experience in construction Frequency Percentage (%)

1-5 years 30 16.6

6-10 years 48 26.5

11-15 years 29 16.0

16-20 years 22 12.2

21-25 years 7 3.9

26-30 years 14 7.7

31-35 years 7 3.9

Over 36 years 9 5.0

166 100.0


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4.2 SMEs’ profile

Table 2 shows the emerging contractors’ distribution according to the nature of their business. It further shows the frequency results of the municipality, in which their business was based. It is evident that the majority of SMEs were either subcontractors (37.6%) or general contractors (31.5%), and operated mostly in Johannesburg (41.4%) and Tshwane (30.9%) Metropolitan Municipalities.

Table 2: SMCEs’ profile

Type of contractor Frequency Percentage (%)

General contractor 57 31.5

Subcontractor 68 37.6

Civil contractor 12 6.6

Specialist contractor 32 17.7

Home building contractor 9 5.0

178 100.0

Municipality Frequency Percentage (%)

City of Johannesburg MM 75 41.4

City of Tshwane MM 56 30.9

Ekurhuleni MM 19 10.5

West Rand DM 30 16.6

180 100.0

4.3 Risk management practices

Table 3 ranks the mean scores to show which of the nine risk management factors were applied in practice in SMEs.

Table 3: Ranking of risk management factors

Risk management factor (N=181) (1 = strongly disagree ….. 5 = strongly agree) MS Rank

Risk response and action planning 4.00 1Communication 3.94 2Risk assessment 3.38 3Monitoring, review, and continuous improvement 3.29 4Risk identification 3.27 5Resource requirement 3.23 6Risk measurement 3.04 7Defining project objectives 2.98 8Organizational environment 2.68 9


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Organizational environment with a MS of 2.68 is the least practised factor within SMEs. Risk response and action planning with the highest score of MS of 4.00 was perceived to be commonly practised by SMEs.

4.4 Exploratory factor analysis results

The nine risk management factors were subjected to EFA to assess their validity and reliability. The results report the suitability of the data to be analysed, factor extraction and rotation, and interpretation.

4.4.1 Exploratory factor analysis for organizational environment

In Table 4, four measures defined organizational environment practice. The result posited that Cronbach’s alpha was greater than 0.70 at 0.889, indicating acceptable internal reliability, as recommended by Hair et al. (2006: 102). The Kaiser-Meyer-Olkin (KMO) of 0.740 with Bartlett’s Test of Sphericity of p<0.000, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as suggested by Pallant (2013:190). These results suggest that factor analysis could be conducted with the data.

Table 4: Organizational environment

Kaiser-Meyer-Olkin value = 0.740 Bartlett’s Test of Sphericity value = 0.00

Eigenvalue 3.073% of variance 76.831 Cronbach’s alpha 0.889

Item MeasureCronbach level after deletion

Factor loading

OE1 I/We identify and assess the internal environment factors 0.862 0.878

OE2 I/We identify and assess the external environment factors 0.810 0.943

OE3I/We use the organization business information system to document the internal and external environment

0.838 0.912

OE4I/We understand the internal environment, which concerns all factors influencing the manner in which firms manage risks

0.918 0.762

The four measures (OE1, OE2, OE3, OE4) expected to define the organizational environment practice attained factor loadings greater than 0.762, as reported in Table 4. These were greater than the recommended value of 0.40, as suggested by Hair et al. (2006: 128) and Pallant (2013: 200). An Eigenvalue greater than 3.073


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was established in this factor; this explained 76.831% of the variance in the data. Therefore, sufficient evidence of convergent validity was provided for this construct. It can, therefore, be indicated that this risk management practice is reliable and valid to measure the risk management practices in construction SMEs’ projects.

4.4.2 Exploratory factor analysis for defining project objectives

In Table 5, four measures (DO1, DO2, DO3, DO4) defined the risk management construct of defining project objectives. The findings indicate that the Cronbach’s alpha was greater than 0.70 at 0.842, indicating acceptable internal reliability, as recommended by Hair et al. (2006: 102). The Kaiser-Meyer-Olkin (KMO) of 0.819 with Bartlett’s Test of Sphericity of p<0.000, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as suggested by Pallant (2013: 190). These results suggest that factor analysis could be conducted with the data.

Table 5: Defining project objectives




Factor loading

DO1 I/We define the organizational focus, e.g., organizational objectives and strategy 0.934 0.877

DO2 I/We define the objectives and methodology of the risk management process 0.903 0.940

DO3I/We determine how the responsibility and accountability for the risk management process can be defined

0.923 0.900

DO4 I/We determine how the effectiveness of the risk management process can be assessed 0.897 0.947

The factor loadings for all practices were greater than 0.877, as reported in Table 5. These were greater than the recommended value of 0.40, as suggested by Hair et al. (2006: 128). An Eigenvalue greater than 3.079 was established in this factor, which explains 61.557% of the variance in the data. Therefore, sufficient evidence of convergent validity was provided for this construct. It can be inferred that defining project objectives is a reliable and valid practice of RM for construction SMEs’ projects.


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4.4.3 Exploratory factor analysis for resource requirement

In Table 6, it is evident that there were five measures defining resource requirement. The result indicates that the Cronbach’s alpha was greater than 0.70 at 0.901, indicating acceptable internal reliability, as indicated by Hair et al. (2006: 102). The Kaiser-Meyer-Olkin (KMO) of 0.778 with Bartlett’s Test of Sphericity of p<0.000, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as suggested by Pallant (2013: 190). These results suggest that factor analysis could be conducted with the data.

Table 6: Resource requirement




Factor loading

RR1 I/We consider personnel availability and know-how 0.858 0.906

RR2 I/We consider time requirement in terms of scheduling risk meetings/workshops 0.889 0.822

RR3I/We consider information system requirement in identifying risks, implementing controls and follow-up activities

0.877 0.850

RR4I/We consider risk communication mechanism, e.g., informal discussions, company newsletter.

0.890 0.814

RR5 I/We consider technology requirements, e.g., use of spreadsheets, risk profile 0.879 0.852

The factor loadings for all practices were greater than 0.814, as reported in Table 6. These were greater than the recommended value of 0.40, as suggested by Hair et al. (2006: 128). An Eigenvalue greater than 3.606 was established in this factor, which explains 72.126% of the variance in the data. Therefore, sufficient evidence of convergent validity was provided for this construct. It can, therefore, be indicated that resource requirement is a reliable and valid RM practice for construction SMEs’ projects.


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4.4.4 Exploratory factor analysis for risk measurement

Table 7 shows the five measures defining risk measurement. The result indicates that the Cronbach’s alpha was greater than 0.70 at 0.935, indicating acceptable internal reliability (Hair et al., 2006: 102). The Kaiser-Meyer-Olkin (KMO) of 0.837 with Bartlett’s Test of Sphericity of p<0.000, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as suggested by Pallant (2013: 190). These results suggest that factor analysis could be conducted with the data.

Table 7: Risk measurement




Loading factor

RM1 I/We define the risk measurement criteria to be used, e.g., high/medium/low 0.933 0.841

RM2 I/We define risk materiality, i.e., when risk is important 0.925 0.873

RM3I/We define risk time frame applicable to risk impact and risk probability, i.e., when risk is expected to occur

0.922 0.887

RM4I/We clarify risk terminology, i.e., use of terms such as impact, consequence, probability/likelihood

0.907 0.941

RM5 I/We determine the level of acceptable risk, i.e., the risk tolerance level of the firm 0.913 0.920

All five variables (RM1, RM2, RM3, RM4, RM5) expected to measure risk measurement loaded together on this factor. The factor loadings for all variables were greater than 0.841, as reported in Table 7. These were greater than the recommended value of 0.40, as suggested by Hair et al. (2006: 128). An Eigenvalue greater than 3.985 was established in this factor, which explains 79.700% of the variance in the data. Therefore, sufficient evidence of convergent validity was provided for this construct. The reliability values were also above the recommended value of 0.70, as considered by Hair et al. (2006: 102). It can be posited that risk measurement is a reliable and valid RM practice for construction SMEs’ projects.


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4.4.5 Exploratory factor analysis for risk identification

Table 8 indicates that there were four measures of risk identification. The Cronbach’s alpha for risk identification was greater than 0.70 at 0.825, indicating acceptable internal reliability, as suggested by Hair et al. (2006: 102). The Kaiser-Meyer-Olkin (KMO) of 0.712 with Bartlett’s Test of Sphericity of p<0.000, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as recommended by Pallant (2013: 190). These results suggest that factor analysis could be conducted with the data.

Table 8: Risk identification


Eige value 2.642% of variance 65.628 Cronbach’s alpha 0.825


Factor loading

RI1 I/We develop risk information database, e.g., information gathering, risk history database 0.779 0.818

RI2 I/We identify how and why risk arises 0.764 0.839

RI3I/We conduct present and future risk identification, e.g., develop risk register information quality, management techniques

0.741 0.861

RI4 I/We use physical inspection to identify the risk 0.830 0.725

All four measures (RI1, RI2, RI3, RI4) expected to define risk iden-tification loaded together on this factor. The factor loadings for all practices were greater than 0.741, as reported in Table 8. These were greater than the recommended value of 0.40, as suggested by Hair et al. (2006: 128). An Eigenvalue greater than 2.642 was established in this factor, which explained 66.057% of the variance in the data. Therefore, sufficient evidence of convergent validity was provided for this construct. The reliability values were also above the recommended value of 0.70, as considered by Hair et al. (2006: 102). The results infer that risk identification is a reliable and valid RM practice for construction SMEs’ projects.

4.4.6 Exploratory factor analysis for risk assessment

Table 9 shows the five measures explaining risk measurement. The result stipulates that the Cronbach’s alpha was greater than 0.70 at 0.908, indicating acceptable internal reliability (Hair et al., 2006:


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102). The Kaiser-Meyer-Olkin (KMO) of 0.849 with Bartlett’s Test of Sphericity of p<0.000, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as suggested by Pallant (2013: 190). These results suggest that factor analysis could be conducted with the data.

Table 9: Risk assessment




Factor loading

RA1 I/We determine the risk cause, risk duration, risk volatility 0.890 0.850

RA2I/We determine the probability of the risk occurring, the impact, classification consistency, i.e., high/medium/low

0.892 0.843

RA3I/We establish the risk profile, e.g., high probability/high impact, high probability/low impact

0.871 0907

RA4I/We assess risks by quantitative analysis methods, e.g., probability, sensitivity, scenario, simulation analysis

0.875 0.899

RA5I/We assess risks by qualitative analysis methods, e.g., direct judgement, comparing option, descriptive analysis

0.908 0.777

All five variables (RA1, RA2, RA3, RA4, RA5) expected to measure risk measurement loaded together on this component. The factor loadings for all variables were greater than 0.777, as indicated in Table 9. These were greater than the recommended value of 0.40, as suggested by Hair et al. (2006: 128). An Eigenvalue greater than 3.669 was established in this factor, which explains 73.379% of the variance in the data. Therefore, sufficient evidence of convergent validity was provided for this construct. The reliability values were also above the recommended value of 0.70, as considered by Hair et al. (2006: 102). It can be postulated that risk assessment is a reliable and valid RM practice for construction SMEs’ projects.

4.4.7 Exploratory factor analysis for risk response and action planning

Table 10 indicates the six measures of risk response and action planning. The Cronbach’s alpha of the construct was greater than 0.70 at 0.864, indicating acceptable internal reliability, as


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recommended by Hair et al. (2006: 102). The Kaiser-Meyer-Olkin (KMO) of 0.796 with Bartlett’s Test of Sphericity of p<0.000 were also obtained, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as suggested by Pallant (2013: 190). These results suggest that exploratory factor analysis could be conducted with the data.

Table 10: Risk response and action planning


Eigenvalue 2.041; 1.451% of variance 34.021; 24.177 Cronbach’s alpha 0.864


Factor loading

Factor loading

RP1 I/We identify risk treatment options by avoiding risk 0.952 0.276 -0.699

RP2 I/We identify risk treatment options by mitigating risk 0.944 0.368 0.657

RP3 I/We identify risk treatment options by retaining risk 0.86 0.742 -0.292

RP4 I/We identify risk treatment options by transferring risk 0.812 0.696 0.127

RP5 I/We predefine actions to counter the identified project risks 0.940 0.516 0.582

RP6 I/We prepare and implement risk action plan 0.922 0.727 -0.302

The exploratory factor analysis using principal component analysis extracted two components. The results revealed that three of the measures (RP3, RP4, RP6) strongly loaded on the first component renamed “risk action plan” and the other three measures (RP1, RP2, RP5) loaded on the second component renamed “risk response”. The factor loadings were greater than 0.40, as reported in Table 10, therefore acceptable measures of the factors (Hair et al. 2006: 128; Pallant, 2013: 200). An Eigenvalue of “risk action plan” greater than 2.041 was established in this component, which explained 34.021% of the variance in the data. An Eigenvalue of “risk response” greater than 1.451 was established in this component, which explained 24.177% of the variance in the data. Therefore, sufficient evidence of convergent validity was provided for these two constructs. It can, therefore, be indicated that risk action plan and risk response are risk management practices that are reliable and valid to measure the RM practices in construction SMEs’ projects.


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4.4.8 Exploratory factor analysis for communication

Table 11 indicates the four measures of communication. The Cronbach’s alpha of the construct was greater than 0.70 at 0.841, indicating acceptable internal reliability, as recommended by Hair et al. (2006: 102). The Kaiser-Meyer-Olkin (KMO) of 0.735 with Bartlett’s Test of Sphericity of p<0.000, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as suggested by Pallant (2013: 190). These results suggest that exploratory factor analysis could be conducted with the data.

Table 11: Communication




Factor loading

Factor loading

C1I/We establish a communication process for interactive (two-way) consultation with stakeholders

0.856 0.796 -0.040

C2I/We establish a communication process for two-way consultation with external stakeholders

0.843 0.743 -0.547

C3I/We establish a crisis communication strategy facilitating immediate information exchange

0.765 0.641 0.159

C4 I/We develop a communication evaluation mechanism 0.786 0.387 0.870

The exploratory factor analysis using principal component analysis extracted two components. The results revealed that three of the measures (C1, C2, C3) strongly loaded on the first component renamed “communication approach” and only one measure (C4) loaded on the second component renamed “communication evaluation”. The factor loadings were greater than 0.40, as reported in Table 11, therefore acceptable measures of the factors (Hair et al. 2006: 128; Pallant, 2013: 200). However, the rule of thumb suggests that a factor cannot be measured by one variable. Therefore, based on this suggestion, the two components were combined and the communication practice was renamed “communication approach and evaluation”. An Eigenvalue greater than 1.745 for “communication approach” was established in this first component, which explained 43.617% of the variance in the data. The second


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component named “communication evaluation” attained an Eigenvalue of 1.083 and explained 27.0635 of the variance in the data. The renaming of the RM practice suggests that sufficient evidence of convergent validity was provided for this construct. It can, therefore, be indicated that this risk management practice is reliable and valid to measure the risk management practices in construction SMEs’ projects.

4.4.9 Exploratory factor analysis for monitoring, review, and continuous improvement

From Table 12, it is evident that the five measures of monitoring, review and continuous improvement attained acceptable internal reliability. The Cronbach’s alpha was greater than 0.70 at 0.892, as recommended by Hair et al. (2006: 102). The Kaiser-Meyer-Olkin (KMO) of 0.802 with Bartlett’s Test of Sphericity of p<0.000, indicating consistency with the recommended KMO cut off value of 0.60 and Bartlett’s Test of Sphericity of p<0.05, as suggested by Pallant (2013: 190). These results indicate that factor analysis could be conducted with the data.

Table 12: Monitoring, review, and continuous improvement




Factor loading

MR1 I/We assign responsibility for monitoring and review actions 0.876 0.830

MR2 I/We identify and select monitoring and review techniques 0.850 0.912

MR3I/We assess control effectiveness, measured in terms of meeting departmental/organizational objectives

0.890 0.777

MR4 I/We do control enhancement by revising ineffective controls identified 0.877 0.826

MR5 I/We report the new results from monitoring and review activities 0.868 0.856

All five measures (MR1, MR2, MR3, MR4, MR5) expected to define the monitoring, review, and continuous improvement of risk management practice attained factor loadings greater than 0.800, as reported in Table 12. The loadings were greater than the recommended value


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of 0.40, as suggested by Hair et al. (2006: 128) and Pallant (2013: 200). An Eigenvalue greater than 3.540 was established in this factor, which explains 70.796% of the variance in the data. Therefore, sufficient evidence of convergent validity was provided for this construct. It can, therefore, be indicated that this risk management practice is reliable and valid to measure the risk management practices in construction SMEs’ projects.

5. Discussion of the results

5.1 Organizational environment

The results found that four measures defined organizational environment practice of RM. This suggests that the four measures, empirically tested, strongly congregated on this practice. Hence, the result supported its theoretical conceptualization. In order for the organizational environment practice of RM to be demonstrated, four activities must be evinced, namely identify and assess the internal environment factors; identify and assess the external environment factors; use the organization business information system to document the internal and external environment, and understand the internal environment, which concerns all factors influencing the manner in which firms manage risks. These measures strongly congregated in defining organizational environment practice. Furthermore, the empirical finding inferred that the organizational environment practice of RM was reliable and valid. Previous studies by Smit (2012: 62), Olander & Landin (2005: 324), El-Gohary et al. (2006: 596), Bosher et al. (2007: 167), and Momeni et al. (2015: 418) are in line with this finding. It can be suggested that understanding the organizational environment is an important practice of RM and project success.

5.2 Defining project objectives

Defining project objectives practice of RM was defined by four measures. The result was supported by the theoretical construction of this construct. The empirical finding established that the practice was reliable and valid. The following measures defined this practice: define the organizational focus (e.g., organizational objectives and strategy); define the objectives and methodology of the RM process; determine how the responsibility and accountability for the RM process can be defined, and determine how the effectiveness of the RM process can be assessed. The finding is also supported by the argument of Goetz (2010) that vaguely defined objectives,


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without objectives, leads the project into overruns, personality clashes, missed milestones, and unhappy clients. Furthermore, defining project objectives helps align the organization, whereby the project objectives are clear and understood. In addition, the positive and negative risks in achieving the objectives are identified and understood, and risk responses are aligned (Boubala, 2010: 88).

5.3 Resource requirements

The resource requirement practice of RM was reliable and valid. Therefore, it can be used to manage the risks of projects involving construction SMEs. The measures of this RM practice congregated strongly on this practice; hence, construct validity was achieved. These measures were: personnel availability and their knowledge base; consider time requirement in terms of scheduling risk meetings/workshops; consider information system requirements in identifying risks; implement controls and follow-up activities; consider risk communication mechanism (e.g., informal discussions, company newsletter), and consider technology requirements (e.g., use of spreadsheets, and risk profile). Haughey (2014: 2-3), Manfredi & Auletta (2013), Scheid (2011), and Muthuramalingam (2008: 4) support this finding, as the availability of resources was a good predictor of RM performance, thus contributing to successful completion of the project.

5.4 Risk measurement

The five measures of risk measurement practice identified in the literature congregated strongly on this practice after empirical testing; hence, construct validity was achieved. These measures were: define the risk measurement criteria to be used (e.g., high/medium/low; define risk materiality (i.e., when risk is important); define risk time frame applicable to risk impact and risk probability (i.e., when risk is expected to occur); clarify risk terminology (i.e., use of terms such as impact, consequence, probability/likelihood), and determine the level of acceptable risk (i.e., the risk tolerance level of the firm). Furthermore, this practice of RM was reliable and valid. Therefore, it can be used to manage the risks of projects involving construction SMEs. In line with this finding, Smit (2012: 68) established that defining and documenting the risk measurement of a project was crucial to its success. Smit (2012: 68) observed that risk measurement influences the outcome of the project in defining the risk measurement criteria to be used (e.g., classification system of high, medium or low); defining risk materiality (when risk is important), and in determining the level of acceptable risk and risk


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time frame applicable to risk impact and risk probability (i.e., when risk is expected to occur: next month, next year, and so on). Karimi et al. (2010: 9108) indicated that, when risk measurement is used, it reduces risk impact on the project regarding schedule, budget, and quality. Goossens & Van-Gelder (2002) demonstrated that risk measurement, being one of the activities of RM, influenced project success and project performance.

5.5 Risk identification

The risk identification practice of RM was reliable and valid. Therefore, it can be used to manage the risks of projects involving construction SMEs. The results are supported by Al-shibly et al. (2013: 26) and De Bakker et al. (2011: 82) who inferred that, when management involvement increases in risk identification, the risk of unclear or misunderstood scope seems to lessen and improve project performance and, hence, influence positively project outcome. Further, the four measures of RM practice identified in the literature review congregated strongly on this practice; hence, construct validity was achieved. In order to ensure that risk identification is practised in the SMEs’ construction projects, the following four activities must manifest as per the empirical findings: develop risk information database (e.g., information gathering, risk history database); identify how and why risks arise; conduct present and future risk identification (e.g., develop risk register information quality, management techniques), and physical inspection to identify the risk.

5.6 Risk assessment

The current findings posit that five activities must be practised for risk assessment practice to be evinced in the construction projects of SMEs. The following activities defined risk assessment practice as they empirically congregated strongly on it: determine the risk cause, risk duration, and risk volatility; determine the probability of the risk occurring, the impact, and classification consistency (i.e., high/medium/low); establish the risk profile (e.g., high probability/high impact, high probability/low impact); assess risks by quantitative analysis methods (e.g., probability, sensitivity, scenario, simulation analysis), and assess risks by qualitative analysis methods (e.g., direct judgement, comparing option, descriptive analysis). Furthermore, the risk assessment practice was empirically deemed to be reliable and valid, and is supported by the findings of Roque & De Carvalho (2013: 101), Al-Shibly et al. (2013: 33), Smit (2012: 78); Zeng & Smith


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(2007: 593), El-Sayegh (2008: 433), and Abu Mousa (2005: 20) as a RM practice to influence the successful delivery of construction projects.

5.7 Risk action plan

The findings stipulated that risk response and planning of RM practice was empirically represented by two practices. This result did not support the theoretical conceptualized risk response and planning practice. The results revealed that the renamed first practice (i.e., risk action plan) was defined by three of the measures i.e., risk treatment options by retaining risk, identify risk treatment options by transferring risk, and prepare and implement risk action plan, congregated strongly on the renamed practice of risk action plan. It can further be inferred that risk action plan is a reliable and valid RM practice for managing construction SMEs’ projects.

5.8 Risk response

The findings on risk response and planning of RM practice were empirically represented by two practices. As discussed earlier, this result did not support the theoretical conceptualized practice. The results revealed that the other three measures i.e. identify risk treatment options by avoiding risk, risk treatment options by mitigating risk, and predefine actions to counter the identified project risks, congregated strongly on the renamed RM practice of risk response. It can be inferred that this RM practice was valid and reliable. This finding is supported by the findings of Omphile (2011: 54) and Aimable (2015: 9-10) who established that risk response activities are strongly linked to the success of construction projects as an individual RM practice. However, Gajewska & Ropel (2011: 32) contrast this finding, as their RM practice combined risk response and action planning.

5.9 Communication approach and evaluation

The findings stipulated that communication as a RM practice was empirically represented by two practices. This was not in line with its theoretical conceptualization despite the evidence of two empirical practices manifesting. The first practice was renamed “communication approach” and was measured by three activities. The second practice was renamed “communication evaluation” and was measured by one variable. However, the rule of thumb suggests that a factor cannot be measured by one variable. Therefore, based on this rule of thumb, the two components were combined, and the communication practice was renamed “communication approach and evaluation”. The essence of


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retaining the measures was informed by the sufficient evidence of convergent validity in each of the two renamed constructs. It can, therefore, be indicated that this RM practice is reliable and valid to measure the RM practices in construction SMEs’ projects. Partially, the finding and argument are supported in the studies of Aulich (2013: 97), Kelkar (2011: 102), and Zulch (2012: 51-52). De Bakker et al. (2011: 83) stipulated that, in situations where risks are not shared openly, the positively communicative effect may not occur, thus stifling the success of a project.

5.10 Monitoring, review and continuous improvement

Monitoring, review and continuous improvement practice of RM empirically supported its conceptual theory. This practice was valid and reliable as a practice of RM. This finding corroborates with the studies of Prabhakar (2008: 7), Papke-Shields et al. (2010: 658), Hwang & Lim (2013: 206), and Kamau & Mohamed (2015: 90). Rezakhani (2012: 19) indicated that project monitoring and conti-nuous improvement are crucial to planning in achieving project success. In addition, the following five theoretical activities that were deemed to evince this practice empirically converged strongly on this RM practice: assign responsibility for monitoring and review actions; identify and select monitoring and review techniques; assess control effectiveness, measured in terms of meeting departmental/organizational objectives; undertake control enhancement by revising ineffective controls identified, and report the new results from monitoring and review activities.

6. Conclusion The empirical investigation of RM practice deduced and helped better understand the difference in the conceptualised RM practice and the empirically extracted RM practices. The empirical investigation inferred that 10 and not nine practices are reliable and valid to be used by construction SMEs. These RM practices are: organizational environment; defining project objective, resource requirements, risk measurement, risk identification, risk assessment, communication approach and evaluation, risk response, action planning, and monitoring, review and continuous improvement. The researchers suggest that the SMEs should be made aware of these RM practices and be trained in their implementation.


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7. Further areas of researchThe researchers recommend that these reliable and valid RM practices can be used to successfully manage risks in construction projects undertaken by SMEs in South Africa. However, to justify these statements, these RM practices should be validated in a national study to ensure that they positively influence the successful delivery of construction projects. Furthermore, further research can be undertaken to justify the manifestation of two RM practices on each of the risk response and planning practice, and communication practice.

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An assessment of the causes, cost effects and solutions to design-error-induced variations on selected building projects in Nigeria


*The authors declared no conflict of interest for the article or title.

AbstractDesign errors and variations are inherently part of many construction projects and require deliberate effort to combat. The literature reviewed indicates that empirical studies of the cost effect of design-error-induced variations are scarce. This study investigates the causes of variation on building projects, the frequent design errors that lead to variation, the effects of design error on variation cost, and solutions to design-error-induced variation in design documents. A mixed methods research (interviews and 30 case study building projects) was used to collect the necessary data for the study. Interviews were conducted with 25 construction professionals to obtain information on the causes of variation on building projects and solutions to design-error-induced variation on building construction projects. Thirty documents including valuation breakdowns and variation/change order documents were obtained by convenience sampling technique and used for the extraction of design errors leading to variations and their associated costs. The data was analysed with frequencies and percentages. The study found that poor working drawing and lack of coordination among design documents are the major causes of variation. Errors in design calculations and wrong descriptions in specifications are prominent design errors that led to variation. Design errors account for roughly 36% of the variation cost of building projects. Structural and architectural drawings contain the largest number of errors among design documents, but electrical and mechanical documents have

Oluwaseun Dosumu

Dr Oluwaseun S. Dosumu, Department of Construction Management and Quantity Surveying, University of Johannesburg, Johannesburg, South Africa / Department of Building, University of Lagos, Nigeria. Phone: +27640476921 or 2348038825534, email: <[email protected]>

Clinton Aigbavboa

Prof. Clinton Aigbavboa, Department of Construction Management and Quantity Surveying, University of Johannesburg, Johannesburg, South Africa. Phone: +27 78 795 8231, email: <[email protected]>








Dosumu & Aigbavboa • An assessment of the causes, cost effects ...

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the highest contribution to variation cost. The study concluded that variation costs could be minimized if government policies, aimed at ensuring proper contract documentation, were put in place, and construction professionals were limited to their core roles on construction projects. Rechecking of design documents prior to use, knowledge sharing, and use of computer programs were among the recommended solutions to design-error-induced variation in project documents.Keywords: Construction projects, cost of error, design documents, design error, variation cost, valuation documents

AbstrakOntwerpfoute en -variasies vorm inherent deel van baie konstruksieprojekte wat doelbewuste pogings verg om te bestry. Die literatuuroorsig dui daarop dat empiriese studies van die koste-effek van ontwerpfout-geïnduseerde variasie skaars is. Daarom ondersoek hierdie studie die oorsake van ontwerpfout-geïnduseerde variasie, hul effekte op variasiekoste en oplossings vir ontwerpfoute in ontwerpdokumente. Die studie is uitgevoer op geselekteerde bouprojekte in Nigerië. Die gemengde metode van onderhoud- en 30 gevallestudie-bouprojekte is aangeneem in die versameling van die nodige data vir die studie. Onderhoud is met 25 konstruksiekenners gevoer om inligting te verkry oor die oorsake van variasie en oplossings om foute van boukonstruksieprojekte te ontwerp. Dertig dokumente wat insluit waardasie-afbreekpunte en variasie-/veranderingsopdragdokumente is verkry deur die gemaksbepalingstegniek en gebruik vir die onttrekking van ontwerpfoute wat lei tot variasies en hul verwante koste. Die data is geanaliseer met frekwensies, somme en persentasies. Die studie het bevind dat swak werktekening en gebrek aan koördinasie onder ontwerpdokumente die hoofoorsake van variasie is. Foute in ontwerpberekeninge en verkeerde beskrywing in spesifikasies is die prominente ontwerpfoute wat tot variasie gelei het. Ontwerpfoute verteenwoordig tot 36% van die variasiekoste van bouprojekte. Strukturele en argitektoniese tekeninge bevat die meeste foute onder ontwerpdokumente, maar elektriese en meganiese dokumente maak die grootste bydrae tot variasiekoste. Die studie het tot die gevolgtrekking gekom dat variasiekoste in ’n groot mate tot ’n minimum beperk kan word indien regeringsbeleid om behoorlike kontrakdokumentasie te verseker, ingestel word en professionele persone beperk word om die werk van ander professionele persone te doen. Herontwerp van ontwerpdokumente voor gebruik, kennisdeling en gebruik van rekenaarprogramme is onder die aanbevole oplossings om foute van projekdokumente te ontwerp.Sleutelwoorde: Konstruksieprojekte, koste van foute, ontwerpdokumente, ontwerpfout, variasie, waardasie dokumente

1. IntroductionConstruction is, by nature, complex and uncertain. Unlike the manufacturing and other sectors of the economy, the design and production activities of construction projects are usually separate functions. That is, the design and construction of a building are two separate functions performed by different parties working independently (Juliana, Ramirez & Larkin, 2005). However, these


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parties (contractors and consultants) have different interests in building projects. For instance, while the client wants value for money, the contractor wants to maximize profit. These interests normally lead to design error as a major source of variation, as claimed by Asamaoh & Offei-Nyako (2013).

Variation is any deviation from an agreed, well-defined scope and schedule of construction projects after issuance of variation order (Osman, Omran & Foo, 2009: 142; Alaryan, Emadelbeltagi, Elshahat & Dawood, 2014: 1). Furthermore, while Love, Edwards and Irani (2008: 234) defined errors as unintended deviations from correct and acceptable practice that are avoidable, Dosumu & Adenuga (2013: 677) noted that error entails different meanings and usages depending on how it is conceptualized across different fields of study. With these assertions, design error may be defined as preventable deviations from acceptable standards of practice during the design of construction projects.

Many projects in developing countries suffer from slipped milestone, cost and time overrun, due to variation in construction projects (Ubani, Nwachukwu & Nwokonkwo, 2010: 141). Muhammad, Keyvanfar, Abd-Majid, Shafaghat, Magana & Dankaka (2015: 91) revealed that variation occurs in all types of projects. Muhammad et al. (2015: 96) noted three prominent sources of variation: design error and omission account for 65% of variation; design changes account for 30% of variation, and other reasons account for only 5% of variation. To buttress this position, Diekmann and Nelson (1995) affirmed that variation has a 65% likelihood of being caused by design error. Therefore, it can be argued that there is a strong connection between design error and variation. It is on this basis that this study investigates the causes of variation, frequent design errors that lead to variation, cost effects of design errors on variation, and solutions to design-error-induced variation in building projects.

Researchers, including Love & Josephson, 2004; Mohammed, 2007; Long, 2011; Love, Edwards, Han & Goh, 2011; Dosumu & Adenuga, 2013; Dosumu, Idoro & Onukwube, 2017, have worked on the causes, effects and remedies of error in construction documents. Studies have also been conducted on variation and variation orders (Anees, Mohamed & Razek, 2013; Desai, Pitroda & Bhavsar, 2015). Other studies (Al-Dubaisi, 2000; Aljishi & Almarzouq, 2008; Zawawi, Azman & Kamar, 2010) were conducted to affirm that design error is the major source of variation on construction projects. However, there is a paucity of studies investigating the extent to which design errors affect variation cost of construction projects. Without identifying the


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design errors that have large contributions to variation cost, it may be difficult to reduce the total cost of variation and invariably cost overrun of construction projects.

2. Literature reviewVariation is a change or any modification to the contractual guidance provided to the contractor by the owner or consultants (Ismail, Pourrostam, Soleymanzadeh & Ghouyounchizad, 2012: 4969). Changes including changes to plans, specifications or any other contract documents occur after the award of the initial contract or after work might have commenced. The changes may be due to various reasons such as inadequate design, change in design, and misinterpretation of drawings leading to construction error (Memon, Rahmon & Abul-Hasan, 2014: 4495). Similarly, variation order is a formal document that is used to modify an original contractual agreement. It becomes part of the project’s documents (Alaryan et al., 2014: 2).

Osman et al (2009: 143) and Muhammad et al. (2015: 92) classified variation, according to their causes, as design errors and omission (65%), design changes (30%), and unforeseen conditions (5%). Fisk (1997) stated that the two basic types of variation are direct and constructive changes. Direct changes occur when a client instructs the contractor to perform works that are not specified in the contract document or makes additions to the original scope of work. Constructive changes are informal acts or modifications to a contract, due to an act or failure to act. Juszczyk, Kozik, Lesniak, Plebankiewicz & Zima (2014: 285) analysed the errors committed in design and classified them based on error group, person responsible for the error, and place of error in designs.

Variation has been an inherent part of construction projects and usually arises due to the causes attributed to the different stakeholders involved in project execution (Alaryan et al., 2014: 1). Variation is usually regularized by the issuance of a variation order. Various causes of variation have been identified in construction projects and the enormity of these causes indicates that variation is part of construction projects and cuts across various stakeholders (Sunday, 2010: 101). Ibn-Homaid, Eldosouky & Al-Ghamdi (2011: 36) revealed that consultants are mostly responsible for variation order. The reason for this assertion is not known. Oladapo’s (2007) study on the significance of variation as a cause of cost and time overruns revealed that changes in specification and scope initiated by clients and consultants are the most frequent causes of variation.


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Other causes of variation include inadequate details of working drawings, change in schedule (Memon et al., 2014: 4495); change in scope (CII, 1990); poor workmanship; client’s financial problem; change in specification, and design complexity (Mohammad, Che Ani, Rakmat & Yusof, 2010: 75). Alaryan et al. (2014: 1) noted that error and omission in design are the main elements of variation, even though there are main causes such as safety consideration, weather conditions, new government regulations, poor planning by contractor, technology changes, and changes in work procedures, among others. Al-Dubaisi (2000) and Zawawi et al. (2010) revealed that errors and omission in design are the sources of variation.

Asamaoh & Offei-Nyako (2013: 23) stated that design complexity, change in specification, and lack of knowledge are part of the causes of design errors that lead to variation. Muhammad et al. (2015: 93) revealed that impediment to prompt decision-making process, poor workmanship, lack of strategic planning, change in design, non-compliance of design with government regulation, aesthetics, cost, inadequate project objectives, mistake, and plan error are the causes of variation which originated from design error.

Researchers (Jawad, Abdulkader & Ali, 2009; Keane, Sertyesilisik & Ross, 2012; Olsen, Killingsworth & Page, 2012) on the effect of variation in construction projects indicated that changes during construction will affect project performance. Osman et al. (2009: 144-145) affirmed that the potential effects of variation on construction projects are increase in project cost, additional payment for contractor, increase in overhead expenses, completion schedule delay, as well as rework and demolition. Increase in project cost and time are the two main effects of variation, according to Aljishi & Almarzouq (2008). It can be deduced from the literature reviewed for this study that design error is a major cause of variation. In order to reduce variation, design error needs to be diminished to the barest minimum.

In addressing the conventional methods of reducing variation, it was suggested that error prevention should be viewed as a continuous process rather than a product of certain activities or behaviours, as it involves people, organisations and project systems (Love, Lopez, Edwards & Goh, 2012: 108). Love, Lopez & Kim (2014: 813, 815, 817) noted that people-related error management includes cognition, behaviour, motivation and learning; organisational error management includes quality, culture and training, and project-related error management includes the use of integrated procurement methods, Building Information Modeling (BIM) and Computer-Aided Design (CAD). Other methods of managing


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design errors include specialists’ involvement in design planning and processing of construction works, preparation of detailed design, provision of elaborate project brief, day-to-day management of the project (Ismail et al., 2012: 4971), reports among client, consultant and contractors, establishment of oversight committee, and budgetary allocations (Asamaoh & Offei-Nyako, 2013: 24).

Table 1 summarizes the classifications of design-error-induced variations based on their causes, effects and solutions, as discussed in the literature review of this study.

Table 1: Classification of design-error-induced variations based on their causes, effects and solutions

Classification Causes Effects Solutions(Alaryan et al., 2014; Osman et al., 2009; Fisk, 1997)

(Muhammad et al., 2015; Memmon et al., 2014; Alaryan et al., 2014; Asamaoh & Offei-Nyako, 2013; Mohammad et al., 2010; CII, 1990; Oladapo, 2007)

(Keane et al., 2012; Olsen et al., 2012; Osman et al., 2009; Jawad et al., 2009; Aljishi & Almarzong, 2008)

(Love et al., 2014; Asamaoh & Offei-Nyako, 2013; Love et al., 2012; Ismail et al., 2012)

Design error and omission

Inadequate details in drawings, lack of knowledge, inadequate project objectives, and design complexity

Completion schedule delay, and increased project cost

Viewing error prevention as a continuous process, organisations and project systems cognition, motivation and learning; quality control, culture and training, use of integrated procurement methods, Building Information Modeling (BIM), Computer-Aided Design (CAD), specialists’ involvement in design planning, preparation of detailed designs, elaborate project brief, day-to-day management of the project, establishment of oversight committee, and budgeting allocations


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Classification Causes Effects SolutionsDesign changes

Change in schedule, change in scope, clients’ financial problems, change in specifications, safety consideration, poor planning, technology change, slow decision-making process, non-compliance of design with government regulation, aesthetics, and cost

Additional payment for contractors, rework, demolition, completion schedule delay, increased overhead expenses, rework, and demolition

Quality control, culture and training, Building Information Modeling (BIM), Computer-Aided Design (CAD), specialist involvement in design planning, detailed design, and elaborate project brief

Unforeseen conditions

Poor workmanship, government regulations, and weather conditions

Increased overhead expenses, and completion schedule delay

Motivation and learning

3. Research methodologyThis study addressed the causes of design-error-induced variation on building projects, the frequent design errors that lead to variation, the effects of design error on variation cost, and solutions to design-error-induced variation in design documents. The study used a mixed methods design, in which qualitative and quantitative data are collected in parallel, analysed separately, and then merged (Creswell, 2005). In this study, valuation and variation documents from 30 selected case studies of building projects were used to build the theory of human error in designs, predicting that design-induced-errors will negatively affect the variation cost of building projects in Nigeria. The interviews explored causes of and solutions to design-error-induced variation from construction professionals in Nigeria. The reason for collecting both quantitative and qualitative data is to elaborate on specific findings from the breakdown of the valuation and variation documents, such as similar causes of design errors and variation suggested from respondents’ groups (Creswell, 2005; Creswell & Plano-Clark, 2007).


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Twenty-five construction professionals, consisting of builders, architects, engineers and project managers, were interviewed on the causes of design-error-induced variation and the ways in which design-error-induced variation in construction projects may be minimized. The construction professionals were selected through the stratified sampling technique. The stratification was done according to the respective professional bodies (Nigerian Institute of Building, Nigerian Institute of Architects, Nigeria Society of Engineers, and Institute of Project managers) in the Nigerian built environment. The number of professionals interviewed appears to be small, but the validity of the information supplied was inherent in their wealth of experience on the subject matter and the number of years they have spent in the construction industry. The minimum qualification for corporate membership of professional bodies in the Nigerian built environment is first degree (BSc/BTech/BEng); thus, the minimum qualification of the respondents was BSc/BTech/BEng. Further informal interrogation indicated that the respondents had a minimum of 7 years’ work experience in the construction industry.

The case studies selected for the study consisted of building projects that were completed between 2014 and 2016, and that had valuation/variation documents. However, due to the confidentiality of the type of information that was sought, it was necessary to select the building projects to be used for the study based on convenience and availability of the required information. Therefore, 30 case study building projects were selected by non-probabilistic convenience sampling technique and used as the source of data for this study (Etikan, Musa & Alkassim, 2016: 2).

3.2 Data collection

The design-error mitigation topics used in the interview survey were extracted from reviews of the literature. In addition, the myriads of design-error-induced variations discovered in the case study projects prompted the researchers to interview professionals on how the problems may be solved. The interview survey contained one closed-ended and two open-ended questions. Respondents were asked to indicate their role on building construction projects. The options were: (a) Architect; (b) Builder; (c) Engineer (Structural, Mechanical, Electrical), and (d) Project manager. Respondents were asked to mention the top causes of design-error-induced variation in building projects and briefly discuss ways in which design-error-induced variation in construction projects may be minimized. Email


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messages were sent to respondents via the addresses obtained from the professional bodies, requesting them to grant an interview based on the questions raised in the accompanied interview template, or to reply to the questions in the template, provided they had completed a building project in the past two years and such buildings were not bungalows. A bungalow is a building that is limited to having only a ground floor level. Bungalows do not usually have structural, mechanical and electrical drawings (in Nigeria), which are the major documents investigated in this study. Hence, bungalows were excluded from the study. Professionals who did not meet the stated criteria were not expected to reply to the email invitations; they were automatically disqualified. While 10 of the respondents replied via email by completing the accompanied interview template, 15 respondents granted interviews to the researcher. Further information was requested from those who replied using emails, where clarity was deemed necessary.

For the case studies, the building projects were selected across Nigeria, including commercial, residential and special purpose projects. The selection criteria of the case study projects included suitability of the project for the study (must not be a bungalow), in order to ensure that all case study projects must have all the necessary design documents, valuation/variation documents, and be completed between 2014 and 2016) and the willingness of the custodian of the required documents to release them for the study. It was ensured that projects used for the study were completed between 2014 and 2016 so that recent information could be collected for the study. A breakdown of valuation documents and variation order documents of the selected building projects were examined, in order to determine the design errors that led to variations, and their associated costs and effects on total variation cost of building projects. The valuation and variation documents were obtained from the quantity surveyors of consulting and contracting firms that executed the selected projects. The information extracted from the documents included general information on the types of building projects, design errors that led to variation, cost of each design error, and total variation costs of the building projects.


Using the Excel software program, the responses on causes of design-error-induced variation, the specific design errors that led to variation as well as the responses on the solutions to design-error-induced variation were subjected to content analysis prior to tabulation. Content analysis is a technique that relies on coding and


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categorizing the data (Stemler, 2001: 137). Once the responses from the interview results were analysed, the causes of variation, specific design errors, as well as the solutions were coded and categorized based on frequency of occurrence.

Since the data collected from valuation and variation documents for the study were mostly related to cost and frequency, they were analysed with sums, frequencies and percentages. To interpret the findings, the following formula was used to calculate the effect of design error on variation cost:

Variation cost (%) = Design error costTotal variation cost

X 100

4. FindingsThis section shows the findings from the analysis and interpretation of the data collected for this study. Tables 2 to 5 show the general information of the case study projects used for the study. Table 6 shows the causes of variation in construction projects. Tables 7 to 8 indicate the frequent design errors that led to variation in the case study projects. Table 9 shows the description of design errors that led to variation on building projects. Tables 10 and 11 show the effects of design error on the variation cost of construction projects. Table 12 presents the data analysis from the report of interviews conducted with construction professionals on the solutions to design-error-induced variation in construction projects.

4.1 General information regarding the type of case study building projects

Table 2 shows the procurement methods used for the building projects investigated in the study.

Table 2: Procurement method used for building projects

Procurement method Frequency Percentage (%)

Traditional 18 60.0

Design and build 12 40.0

Total 30 100.0

Of the projects, 60% were procured traditionally, whereas 40% were procured through management methods (design and build). This indicates that the majority of the projects were procured using traditional methods. Traditional procurement method separates the design from the construction process; a client appoints a main


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contractor on the basis of competitive or single-stage tendering. Tendering is a process whereby contractors are invited to bid for construction projects based on a competitive fee.

Table 3 shows the types of building projects investigated in the study.

Table 3: Types of building projects investigated

Type of building project(in terms of use) Frequency Percentage (%)

Residential 15 50.0

Commercial 8 26.7

Special purpose 7 23.3

Total 30 100.0

Residential building projects were 50%, commercial buildings, 26.7%, and special-purpose building projects, 23.3%. Special-purpose buildings are buildings with special construction materials and unique designs that restrict its use to what it was built for (that is, they may not be easily converted for other purposes). They are usually single-purpose buildings and include churches, mosques, recreational buildings, theatres, and so on.

Table 4 indicates the sector to which the building projects clients belong.

Table 4: Sector to which building projects clients belong

Type of building project client Frequency Percentage (%)

Private 23 76.7

Government 7 23.3

Total 30 100.0

Projects belonging to private clients were 76.7% and projects owned by government (federal and state) were 23.3%.

Table 5 shows the different contract sums under which the building projects are categorized.

Table 5: Contract sum of building projectsContract sum (=N=) Frequency Percentage (%)Below 100 million 15 50.0100-500 million 10 33.3Above 500 million 5 16.7Total 30 100.0


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The number of building projects with contract sums above N500 million Naira were 16.7%; 33.3% of the projects cost between N100 million and N500 million Naira, and 50% were below N100 million Naira. It is worth noting that all (100%) the projects investigated were multi-storey buildings.

4.2 Causes of variation in construction projects

Table 6 indicates the result of the interviews conducted with professionals on the causes of variation in construction projects. Once the contents of the interview results were analysed, 15 causes of variation were identified and tabulated as shown. The frequency represents the number of respondents who mentioned the identified causes, and the percentage represents the fraction of the individual frequency to the total frequency of occurrence of the variation. It is important to mention that some of the causes identified by the respondents may be taken as design errors, on the one hand, and they may, however, equally be regarded as causes of variation, on the other.

Table 6: Causes of variation in construction projects

Causes of variation Frequency Percentage (%) Rank

Poor working drawings 24 13.3 1

Lack of coordination during design 20 11.1 2

Change in scope of work by clients 19 10.5 3

Omissions in design 18 9.9 4

Design error 18 9.9 4

Inadequate project objectives 16 8.8 6

Mistakes 15 8.3 7

Inexperience of designers 14 7.7 8

Owner’s financial difficulties 12 6.6 9

Difficult site condition 6 3.3 10

Design complexities 6 3.3 10

Incorrect assumptions 4 2.2 12

Aesthetics 4 2.2 12

Technology changes 3 1.7 14

Fatigue 2 1.2 15

Total 181 100


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Poor working drawing (13.3%) was the most rated cause of variation on construction projects, followed by lack of coordination during design (11.1%), change in scope of work by clients (10.5%), design errors (9.9%), omissions in design (9.9%), inadequate project objectives (8.8%), mistakes (8.3%), inexperience of designers (7.7%), owner’s financial difficulties (6.6%), design complexities (3.3%), difficult site conditions (3.3%), aesthetics (2.2%), incorrect assumptions (2.2%), technology changes (1.7%), and fatigue (1.2%), respectively. Many of the causes of variation identified in the study were more design related; this is consistent with the claims made in the literature reviewed in this study. To elaborate on this finding, a breakdown of valuation/variation documents from the construction buildings of this study was done to examine specific design errors that led to variation in construction projects (see Table 7). It was also important to examine the frequency of occurrence of design errors according to the types of errors identified (see Table 8) and to describe the design errors that led to variation on building projects (see Table 9).

Table 7 indicates the design errors that led to variation on construction projects according to the breakdown of valuation/variation documents examined. The frequencies, types of design errors and their descriptions were also obtained from the documents. Due to space, Table 7 presents only the frequencies of design error on construction projects and their corresponding percentages based on design documents and total number of design errors identified; other details are presented in Table 9.

Table 7: Design errors that led to variation based on design documents

Types of errors FrequencyTotal error per

document (%)

Total design

error (%)Rank

Structural drawings

Wrong/inadequate description in specification 6 11.5 4.5 7

Error in design calculation 34 65.4 25.8 1

Omission of details 12 23.1 9.0 5

Total 52 100.0 39.3

Architectural drawings

Absence of specification 6 15.0 4.5 7

Dimensional error 16 40.0 12.1 2


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Types of errors FrequencyTotal error per

document (%)

Total design

error (%)Rank



Total 40 100.0 30.3

Electrical drawings




Total 22 100.0 16.7

Mechanical drawings

Omission of specification 6 33.3 4.5 7


Wrong description 8 44.4 6.1 6

Total 18 100.0 13.7

Total of totals 132 100

A total of 132 errors were found in architectural drawings (40), structural drawings (52), electrical drawings (22), and mechanical drawings (18), respectively. These figures translate to 30.3%, 39.3%, 16.7%, and 13.7% for the design documents, respectively. Table 7 shows further that the frequency of occurrence of design errors in valuation documents based on design documents were in the order of structural drawings (39.3%), architectural drawings (30.3%), electrical drawings (16.7%), and mechanical drawings (13.7%), respectively. This shows that, if variations are to be greatly reduced, more attention needs to be paid to structural and architectural drawings (69.6%) during their preparation, in order to reduce the frequency of error occurrence.

Aside from consideration based on design documents, errors in structural design calculations (25.8%) showed the highest design error that led to variation, followed by dimensional errors in architectural drawings (12.1%), wrong descriptions in electrical specifications (12.1%), wrong descriptions in electrical specifications (10.6%), omission of details in structural drawings (9%), wrong description in mechanical drawings (6.1%), absence of mechanical specification (4.5%), absence of architectural specification (4.5%), wrong/


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inadequate description in structural specifications (4.5%), omission of details in electrical specifications (4.5%), errors in mechanical design calculations (3.1%), omission of details in architectural specifications (1.6%), and error in electrical design calculations (1.6%), respectively.

Table 8 presents the frequency of occurrence of design errors accor-ding to the types of errors identified.

Table 8: Design errors that led to variation in construction projects based on type of error

Type of error Frequency Percentage (%) Rank

Wrong/inadequate descriptions in specifications 44 33.3 1

Errors in design calculations 40 30.3 2

Omission of details in specification 20 15.2 3

Dimensional errors in architectural drawings 16 12.1 4

Absence of specifications 12 9.1 5

Total error 132 100

Out of the 132 design errors discovered in the design documents of construction projects, 44 (33%) were wrong/inadequate description in specifications, 40 (30.3%) were errors in design calculations, 20 (15.2%) were omission of details in specifications, 16 (12.1%) were dimensional errors in architectural drawing, and 12 (9.1%) were complete absence of specifications. This shows that errors in design documents of building projects are mostly characterized by wrong/inadequate description in specifications, errors in design calculations, omission of details in specifications, and dimensional errors.

Table 8 also indicates that specification-related errors accounted for 57.6% of the total errors leading to variation in construction projects. This implies that many problems are yet to be solved in the specifications of construction drawings. These problems include provision of clear and detailed specifications for materials, and correct and adequate description of specification, among others. In addition, errors in design calculations constituted 30.3% of the total errors leading to variation in construction documents. In Nigeria, at present, many civil/structural engineers do not use Computer-Aided Designs (CAD) software for their designs; yet they mostly do not carry out manual calculations before providing for numbers and sizes of reinforcement required as main and distribution reinforcement bars of construction projects. They only rely on residual knowledge of seemingly similar projects that have been designed at some point.


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Table 9 presents the design errors that were extracted from the valuation breakdown of investigated building projects and their descriptions on how they led to variations in those construction projects. It is clear from Table 9 that all the design documents were characterized by one or other error. Therefore, there is an urgent need to improvise means of preparing design documents that are near error free.

Table 9: Description of design errors that led to variation on building projects

Types of building Design errors Description of design errors as stated in valuation

breakdowns of investigated building projects

Residential buildings

Omission of detail on structural drawing.Omission of details on electrical drawing.Omission of specification on mechanical drawing.Absence of specification on architectural drawing.Inadequate specification on structural drawing.Wrong description of specification on structural drawing.Wrong description of specification on architectural drawing.Wrong description of specification on electrical drawing.Wrong description of specification on mechanical drawing.Dimensional errors on architectural drawing.Dimensional errors on structural drawing.Error in structural design calculation.

Omission of 2.8 tons of reinforcement in beams.Absence of specification on architectural drawing.Inadequate specification of retaining wall on structural drawing.Omission of specification of soil and storm uPVC pipes on mechanical drawing.Dimensional error leading to extension of wall on architectural drawing.Dimensional error leading to increment in window dimensions on architectural drawing.Wrong description of bar marks and changing it from Y6 to Y12 on structural drawing.Addition of reinforcement on first-floor slab top and bottom on structural drawing.Dimensional error on architectural and structural drawings, which later led to extension of roof.Omission of garden light on electrical drawing.Error in mechanical drawing, which led to removal of already installed pipes.Omission of electrical fittings, which include fire alarm, internal and external lighting fittings, telephone systems, sub-main cables, and so on.Omission of mechanical appliances, which include air conditioner, plumbing fittings, and so on.Omission of columns on ground floor.Dimensional error on slab, which led to extension of slab.Omission of some details on roof from initial design, which led to re-design of the roof.Error in roof slab, which led to redesign of roof slab.Wrong description of floor tiles.Extension of window sizes, due to dimensional error.Wrong description of electrical cables.Wrong description of plumbing and mechanical fittings.


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breakdowns of investigated building projectsAbsence of roof gutters on architectural drawing.Extension of living room, due to dimensional error.Extension of slab along circular column, due to dimensional error.Omission of beams on ground-floor slab.Extension of beam 20 to grid line 5A.Omission of columns on ground-floor slab.Extension of ground beam, due to dimensional error.Omission of columns on ground-floor slab.Reduction of beam height, due to wrong description.Increment of beam height connecting to isolated column.Introduction of column, due to omission.Introduction of beam, due to omission.Inadequate specification of door type.Wrong description of paving stone.Introduction of Cantilever beam from column C33 & C27 first-floor layout beam.Introduction of RC roof gutter to replace original aluminium roof gutter.Introduction of column C33 & 27 on first-floor slab layout.Introduction of new roof floor beam (Beam 15A).Additional reinforcement to roof beam and slab.Introduction of columns.Addition of beams.Additional reinforcement on roof slab.Relocation of pipes at various locations.Removal of floor screed in maid’s room and replacing with floor tiles.Breaking of wall on gridline two for bedroom 2.Reduction of swimming pool finish level from 1650mm to 1500mm.Relocation of water heater and switches in various areas in the utility building.Demolition of staircase.Increased thickness of external concrete skirting of the main building to conceal pipes.


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breakdowns of investigated building projects

Commer-cial buildings

Wrong description of specification on mechanical drawing.Wrong description of specification on electrical drawing.Wrong description of specification on architectural drawing.Wrong description of specification on mechanical drawing.Absence of specification on electrical drawing.Omission of details on mechanical drawing.Error on structural design drawing.Error on electrical drawing

Extension of wall due to error on architectural and structural drawings.Wrong description on mechanical drawing, which led to removal of duct and relocating it on another spot.Relocating water supply riser on gridline (4, B).Relocation to shaft between gridlines (1, 2) and B on the ground-floor ceiling level.SWP riser on gridline (4, B).Relocation to shaft between gridlines (1, 2) and B on the ground-floor ceiling level.Omission of male and female toilets of 1st, 2nd and 3rd floors and fixing installation between gridlines (3, 5).Redesign of duct, due to design error on mechanical drawings.Relocation of lighting points on electrical drawing.Absence of CCTV, TV, normal and UPS power points on electrical drawing.Relocation of points for light switches, water heater, hand dryers, shaver sockets, normal and UPS power points, due to wrong description of specification on electrical drawing.Redesigning of roof trusses, due to errors on drawing.Redesigning of electrical drawings, due to issues encountered during construction.Wrong specification of drainage pipes and coupling.Wrong description of distribution board to accommodate pumps.

Special-purpose projects

Error in structural design calculation.

Design error in structural calculation.Absence of specifications.

4.3 Cost-effect of design error on variation cost of building projects

Table 10 shows the cost effects of design errors on variation and total cost of building projects based on design documents.


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Table 10: Effects of design errors on variation cost of building projects based on design documents

Types of errors Cost of error (=N=)

Effect on document’s

total (%)

Effect on total cost of

error (%)

Effect on total variation cost (%)

Rank

Electrical drawingsOmission of details in specifications 26,475,763.86 20.9 10.6 3

Wrong description in specification 15,183,882.82 12.0 6.2 6

Error in design calculation 85,158,591.04 67.1 34.1 1

Total 126,818,237.71 100.0 50.9 18.3

Mechanical drawingsAbsence of specification 23,342,763.68 46.3 9.4 5


Wrong description in specifications 12,167,522.98 24.1 4.9 8

Total 50,441,338.72 100.0 20.3 7.3Structural drawingsWrong/inadequate description in specification

831,880.00 2.2 0.3 12


Omission of details 3,330,131.66 8.9 1.3 10Total 37,588,383.72 100.0 15.0 5.4Architectural drawingsAbsence of specification 453,810.00 1.4 0.2 13

Dimensional error 5,332,677.76 15.4 2.1 9Wrong/inadequate description in specification

25,759,565.16 74.4 10.3 4

Omission of details in specifications 3,060,000 8.8 1.2 11

Total 34,606,052.92 100.0 13.8 5.0Impact of design error on variation cost (%)

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Total cost of error = N249,454,013.07Total variation cost of investigated projects = N692,723,179.98

According to design documents, electrical drawings had the highest cost effect on total variation cost (50.9%), followed by mechanical


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drawings (20.3%), structural drawings (15%), and architectural drawings (13.8%), respectively. Individually however, errors in electrical design calculations (34.1%) had the highest effect on total cost of error, followed by error in electrical design calculation (13.4%), omission of details in specifications (10.6%), wrong/inadequate description in specification (10.3%), absence of specification (9.4%), wrong description in electrical specification (6.1%), and error in mechanical design calculation (6%), among others.

Table 10 also indicates that, when design error costs were compared with the total cost of variation (= 692,723,179.98), electrical drawings contributed 18.3% to total variation cost, mechanical drawings contributed 7.3%, structural drawings contributed 5.4%,d and architectural drawings contributed 5%, respectively, to total variation cost of the building projects investigated in this study. In summary, if the works of services engineers (electrical and mechanical engineering works) are correct, 25.6% of the 36% variation cost could be saved.

Table 11 presents the effect of design error on total cost of error and variation cost based on types of errors.

Table 11: Effects of design errors on variation cost based on types of error

Types of error Cost of errorEffect of error on total error cost

(%)

Effect of error costs on total

variation cost (%)Rank

Errors in design calculations 133,526,015.16 53.5 19.3 1

Wrong/inadequate descriptions in specifications

53,942,850.96 21.6 7.8 2

Omission of details in specification 32,865, 895.52 13.2 4.7 3

Absence of specifications 23,796,573.68 9.5 3.4 4

Dimensional errors in architectural drawings 5,332,677.76 2.2 0.8 5

Total cost of error 249,454,013.08 100 36

Total variation cost of investigated projects = N692,723,179.98

Errors in design calculations (53.5%) had the highest effect on total cost of errors. This was followed by wrong/inadequate description in specifications (21.6%), omission of details in specifications


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(13.2%), absence of specifications (9.5%), and dimensional error in architectural drawings (2.2%), respectively.

This result shows that there is the need to reduce errors in design calculations to the barest minimum, in order to reduce variation cost. There is also the need to improve specification-related issues that accounted for approximately 44.3% of the types of errors leading to variation. This shows that specification-related issues and errors in design calculation account for approximately 97.8% of the total design error cost leading to variation. This is revealing, as it shows that specifications and calculations are the greatest issues of design errors and variation cost on building projects.

Furthermore, errors in design calculations contributed approximately 53.5% to the total cost of design errors, and errors in electrical design calculations alone took 34.1% (see Table 9). The problem with electrical design in Nigeria may be as a result of building services’ works being executed by mechanical and electrical engineers who have hardly any or no knowledge about building construction processes. In view of this, the Nigerian Institution of Building (NIOB), the Council of Registered Builders of Nigeria (CORBON) and the academia in the built environment have been clamouring and encouraging builders to specialise in building services rather than in the saturated construction management, construction technology, and building maintenance.

In addition, Table 11 shows the impact of design error costs on total variation cost of building projects investigated. Errors in design calculation had 19.8%, wrong/inadequate description in specifications had 7.8%, omissions of details in specifications had 4.7%, absence of specifications had 3.4%, and dimensional errors in architectural drawings had 0.8%. The total contribution of design errors to variation cost, according to the investigation in this study, is 36%. That represents the probable net effect of design errors on variation cost of building projects.

4.4 Solutions to design-error-induced variation in building projects

Based on the classification in Table 1, the content analysis method was adopted to categorize measures for minimizing design-error-induced variation in building projects so that variation costs can be drastically reduced. The main points from the interview results were tabulated. Table 12 shows the suggested measures as well as brief explanations of how the measures can be practised.


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Table 12: Measures and explanations for minimizing design-error-induced variation in building projects

Classification Suggested measure(s) Explanation

Design error and omission

Visitation to site before designing

Many designs are produced on the assumption that construction sites are of levelled topography and, as such, designs are produced based on that assumption. This unethical practice should be avoided, as it has caused a great deal of design problems leading to litigations, delays, cost overrun, and wastages, among others.

Proper planning There should be proper planning and assessment of clients’ brief before project design commences.

Contractors’ representatives are important

Contractor’s representatives should be represented during the design process of building projects. An interviewee noted that the presence of a builder in the design build-up is of no little importance, as issues of discrepancies in contract documents, buildability and maintainability, methodologies, work programming, health and safety, quality management and building production management would be articulated before the final design is produced. This means errors and their potentials would be pointed out early enough and this would save a great deal of time and cost for the client.

Use of computer programs

It was suggested that the use of computer programs, software and applications that are available across different disciplines in the built environment should be used for the design of construction documents.

Pay adequate attention to details

This will improve concentration on projects, reduce oversight problems and negligence on the part of designers. The phrase used by one of the respondents is that designers must take design of building projects as ‘their baby’. For this to happen, it was noted that clients must be willing to pay adequately for design jobs.

Design changes

Clients to give more time for designs

This suggestion was believed to be a major way forward if it is religiously followed. Respondents noted that many clients are not aware of the tasks ahead for a project to be well designed. Attempts to explain to clients mostly fail, because many of them lack sufficient education on how building projects are prosecuted. This condition is aggravated when clients believe that they are the financiers of projects and can always engage the services of another designer if a designer fails to abide by the time allocated. This condition is further compounded, as many designers who have been out of job for some time are willing to take up those jobs with a view that problems emanating from the designs will be solved one way or another during the project.

Construction professionals and their roles

Professionals should not only have adequate understanding of the project to be executed, but also understand the roles to be played.

Knowledge sharing

There should be a forum for sharing knowledge on the experience of various building projects so that it can be useful for future projects. This is based on the learning curve theory.

Professionals should have checklists from a collective data bank that can be used for future projects

This suggestion is like that of knowledge sharing. However, the difference is that, in this case, there is a recognized co-ordination point where other designers can furnish themselves with relevant information concerning the type of project to be executed.


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Further discussions with professionals indicate that these suggestions will be mostly successful when adopted multilaterally rather than unilaterally.

5. Discussion of findingsThis study investigated the causes of variation, design errors that lead to variation, effects and solutions to design-error-induced variation on building projects.

5.1 Causes of variation and design errors in construction projects

The findings of the study show that the main causes of design-error-induced variation are poor working drawings, lack of coordination during designs, change in scope of work by clients, omission in designs, inadequate project objectives, mistakes, inexperience of designers, and owners’ financial difficulties. These results are consistent with the existing body of knowledge in the fields of poor working drawing (Mohammad et al., 2010; Ismail, et al., 2012; Asamaoh & Offei-Nyako, 2013; Memmon et al., 2014; Mohammad et al., 2015: 93-94); change in scope of work by clients (CII, 1990); omission in design error (Al-Dubaisi, 2000; Zawawi et al., 2010; Alaryan et al., 2014); inadequate project objectives (Ismail et al., 2012; Mohammad et al., 2015: 95); mistakes (Mohammad et al., 2015; 93); inexperience of designers (Asamaoh & Offei-Nyako, 2013: 22), and owners’ financial difficulties (Mohammad et al., 2010: 78).

The results of this study further indicate that errors in structural and architectural drawings constitute approximately 70% of the total design errors that led to variation in the projects investigated. This shows that, if structural engineers and architects can do something drastic about their designs, roughly 70% of design-induced variation could be eliminated. While Muhammad et al. (2015) noted that design for aesthetics is a cause of errors in design documents (mostly architectural drawings), experience shows that civil engineers are used to design for reinforcement of construction projects, instead of structural engineers. This is inconsistent with the ethics of construction professional practice and needs to be mitigated.

The findings of the study further indicate that errors in structural design calculations, dimensional errors in architectural drawings and wrong/inadequate description in specifications are the most occurring design errors in the documents studied. In Nigeria, for instance, there is no clear difference between civil and structural engineers by practice. However, professional structural engineers are statutorily


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charged with the responsibility of reinforcement designs for all kinds of construction works, whereas civil engineers are simply constructors of engineering projects. Besides, many reinforcement designers base their designs on residual knowledge and make provisions for reinforcements without doing any loading calculations. The result of many of these design practices is over-reinforcement of buildings that could be as dangerous as under-reinforcement. This practice has been found culpable for many cases of building collapses occurring in developing countries following investigations by concerned organisations such as government and professional institutions.

In addition, wrong/inadequate description in specifications and omission of details could lead to delay and cost overrun, which could be due to late reply to Request for Information (RFI), change in scope of work, and clarifications to drawings and specifications. In general, the findings of the study indicate that wrong/inadequate description in specification and errors in design calculations were jointly responsible for approximately 64% of design errors in project documents. Thus, deliberate efforts to improve on the descriptions of design specifications and calculations could lead to a reduction of over half of the total design errors leading to variation in building projects. In addition, it is cause for concern to discover that some large building projects investigated were being constructed without any specifications. This is not only unprofessional, but also dangerous to the cost, time, quality and safety of the building and occupants of such projects. It could also pose risks of buildings collapsing.

5.2 Cost-effect of design error on variation cost of building projects

Much of the literature investigated in this study did not consider the effects of variation on construction projects in quantitative terms. Hence, comparison with the results of this study may be difficult. This study found that electrical and mechanical drawings constitute approximately 71% of the total cost of error in design documents and roughly 26% of the variation cost of building projects. This shows that, even though structural and architectural drawings contain the most number of errors in design documents, those of electrical and mechanical drawings (services) have the most cost effects on variation when compared with other documents. This means that attention must be paid to services drawings if considerable reduction of design error and variation costs are to be achieved. In Nigeria, for example, mechanical and electrical engineers are still responsible for the electrical, plumbing and other services in buildings. The problem is that many of them are not trained building


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services engineers and this could be a major cause of the problem with services documents discovered in this study. Therefore, young and upcoming builders need to be encouraged to shift focus from construction management and construction technology to building services.

5.3 Solutions to design-error-induced variation in building projects

Lastly, the interview of experts revealed that design error variation can be reduced by rechecking designed documents before presenting them for use, using computer programs rather than manual calculations and designs, knowledge sharing among designers, use of competent designers, clients giving more time to designers, site visitation before designing, having design checklists, paying adequate attention to details, proper planning and assessment of clients’ briefs, good understanding of projects and the roles to be played, and representation of contractor in the design phase of building projects. Comparing these suggestions with previous studies indicates that they agree with Love et al. (2014) in respect of learning, use of Computer-Aided Designs (CAD) and Building Information Modelling (BIM). The learning corresponds with knowledge sharing among designers and CAD/BIM corresponds with the use of computer programs. The result also agrees with Asamaoh & Offei-Nyako (2013) in respect of reports among consultants and use of oversight committee for designs. Reports among designers goes with knowledge sharing among designers and use of oversight committees goes with rechecking design documents by the committees before presenting them for use. The result of Ismail et al. (2012) is consistent with the representation of contractors in the design phase of building projects, as mentioned by the respondents in this study.

It is important to state that one of the suggestions of Love et al. (2014) is the adoption of the Integrated Procurement Method (IDP). Even though many developing countries such as Nigeria know all about the procurement method, professionals are still reluctant to adopt the method. The reason for this may be multivariate, ranging from the adoption of computer programs such as BIM to the fear of running out of business for unknown reasons. It is important to clarify that the IDP is adopted on some projects. Many of the construction stakeholders, however, still vest their interests in the traditional procurement method, as is evident in the projects investigated for this study. Therefore, more campaigns and enlightenment may be required to ensure that the IDP is embraced in the construction


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industry. It is also important to mention that the campaign for sustainable design and construction is hinged on the adoption of IDP, as all the professionals must simultaneously meet and brainstorm on the success of the project.

6. ConclusionsBased on the findings of this study, it was concluded that poor working drawings, lack of coordination during designs, change in the scope of work by clients, omission in designs, inadequate project objectives, mistakes, use of inexperienced designers, and owners’ financial difficulties are the main causes of design-error-induced variation. In addition, structural and architectural drawings contain the highest number of errors in design documents of building projects. In these documents (structural and architectural drawings), errors in structural design calculations, dimensional errors in architectural drawings, wrong/inadequate description in specifications, and omission of details were the most implicated.

Furthermore, electrical and mechanical drawings (drawings of services engineers) contained fewer errors in comparison with structural and architectural drawings; they had the most cost effect on variation cost. The most implicated errors in these documents (electrical and mechanical drawings) were errors in design calculations, wrong/inadequate description in specifications, omission of details in specifications, and absence of specifications. Lastly, the suggested methods of minimizing design-error-induced variation were rechecking of documents before use, use of computer programs, knowledge sharing, use of competent designers, giving more time to designers, site visitation before designing, having design checklists, paying attention to design details, proper planning and assessment of clients’ brief, understanding projects and the roles to be played, and engaging the contractor’s representative during the design phase.

7. RecommendationsAll electrical, mechanical and structural design calculations should be verified by dedicated government authorities before proceeding to the site for construction. Hence, legislation towards achieving this feat is recommended. Furthermore, it appears that not much can be done about the current professionals preparing electrical and mechanical design documents, because there are hardly any building services professionals. In view of this, government and higher institutions are advised to sponsor staff in the building profession on


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building services training. Many schools in Europe and universities in Hong Kong, in particular, are engaging in services trainings and researches including Heating Ventilation and Air Conditioning (HVAC). The Nigerian construction industry and the academia can tap into this wealth of knowledge and experience.

Moreover, all design organisations should be advised to establish quality control departments to verify all designs. Appropriate sanctions should be prescribed for defaulters. In addition, only structural engineers should be allowed to carry out structural designs and detailing. Civil engineers should be stripped from performing that function, as it is outside their professional roles. Structural engineers are trained people who design the reinforcement details of structural construction works. Civil engineers are generally trained construction managers on civil engineering works such as stadium, dams, roads, and so on.

In addition, if any meaningful improvement is to be made on errors in design calculations, government policies or other means should compel structural engineers to use the recommended software to calculate the numbers and sizes of reinforcement required for structural designs. This will prevent the perennial problem of over- and underdesigning that could result in recurrent building collapses. It is important to note that this recommendation is also applicable to other construction documents (architectural, electrical, and mechanical engineers) investigated in this study. Lastly, since designers pay more attention to drawings than specifications, this study recommends that designs with specification-related issues be regarded as incomplete and not be used for construction works until all specifications issues are settled.

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Successful transformational change in revenue management among beneficiary communities of South African renewable energy construction companies


*The authors declared no conflict of interest for this title or article.

AbstractTransformational change is the second of three sub-models that resulted from the splitting of the original model following the data analysis as part of a thesis entitled A theoretical model for successful management of revenue for beneficiary communities of renewable energy companies in South Africa. The sub-model provides specific guidance for project managers dealing with transformational change in communities to stakeholders, industry experts and community development practitioners in the renewable energy sector. The aim of the research was to promote a localised understanding of education, social interaction, social cohesion, infrastructure improvement and sharing to ensure success in managing the revenue for beneficiary community projects by renewable energy construction companies. A literature review of relevant literature on transfor mational change factors was conducted and used to develop a structured questionnaire distributed to national and international popu lation of project management practitioners who were conveniently sampled in South Africa. Using an electronic measuring instrument, the empirical findings established four factors that were reliable and valid for transformational change in communities, namely education, infrastructure development, human develop-ment, and change management. Using these factors and construc ting a path diagram of

Ric Amansure

Dr Ric Amansure, Department of Developmental Studies, Nelson Mandela University, PO Box 77000, Port Elizabeth 6031, South Africa. Phone: +27 41 5860421, email: <[email protected]>

Chris Adendorff

Prof. Chris Adendorff, Department of Developmental Studies, Nelson Mandela University, PO Box 77000, Port Elizabeth 6031, South Africa. Phone: 0027 41 5860421, email: <[email protected]>








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the indepen dent variables (education, infrastructure develop ment, human development, change management) and subsequent intervening (good governance) and dependent variables (perceived success of revenue management), appropriate hypotheses were developed to test the model. The hypotheses were analysed and tested empirically using Structural Equation Modelling (SEM). Determinants were identified as elements of transformational change that influence the success of revenue management for beneficiary communities for South African renewable energy companies. These included the use of education, infrastructure development, human development, change management, and good governance. Keywords: Beneficiary communities, community development, economic development, green energy, renewable energy, revenue management, socio-economic development, project management, transformational change

AbstrakTransformatoriese verandering is die tweede van drie submodelle wat voortspruit uit die opbreking van die oorspronklike model na die data-analise as deel van ’n proefskrif getiteld A theoretical model for successful management of revenue for beneficiary communities of renewable energy companies in South Africa. Die submodel bied spesifieke leiding aan projekbestuurders wat handel oor transformasieverandering binne gemeenskappe aan belanghebbendes, kundiges in die bedryf en gemeenskapsontwikkelingspraktisyns in die hernu-bare energie sektor. Die doel van die navorsing was om ’n gelokaliseerde begrip van onderwys, sosiale interaksie, sosiale samehorigheid, verbetering van infrastruktuur en deel te bevorder om sukses te behaal in die bestuur van die inkomste vir begunstigde gemeenskapsprojekte deur hernubare energie konstruksiemaatskappye. ’n Literatuurstudie van relevante literatuur oor transformasieveranderingsfaktore is gedoen en gebruik om ’n gestruktureerde vraelys te ontwikkel wat aan nasionale en internasionale populasie van projekbestuurspraktisyns in Suid-Afrika versprei is. Met behulp van ’n elektroniese meetinstrument het die empiriese bevindinge vier transformasiefaktore gevind wat betroubaar en geldig was vir transformasieverandering in gemeen-skappe, naamlik onderwys, infrastruktuurontwikkeling, menslike ontwikkeling, en veranderingsbestuur. Met behulp van hierdie faktore en die konstruksie van ’n vloeidiagram van die onafhanklike veranderlikes (onderwys, infrastruktuurontwikkeling, menslike ontwikkeling, en veranderingsbestuur) en die daaropvolgende tussenliggende (goeie bestuur) en afhanklike veran-derlikes (waargeneme sukses van inkomstebestuur) is toepaslike hipoteses ontwikkel om die model te toets. Die hipoteses is empiries geanaliseer met behulp van strukturele vergelyking modellering (SEM). Determinante is geïdentifiseer as elemente van transformasieverandering wat die sukses van inkomstebestuur vir begunstigde gemeenskappe vir Suid-Afrikaanse hernubare energie maatskappye beïnvloed. Dit sluit in die gebruik van onderwys, infrastruktuurontwikkeling, menslike ontwikkeling, veranderingsbestuur, en goeie bestuur.Sleutelwoorde: Begunstigde gemeenskappe, ekonomiese ontwikkeling, gemeen-skapsontwikkeling, groen energie, hernubare energie, inkomstebestuur, projekbestuur en transformasieverandering, sosio-ekonomiese ontwikkeling

Amansure & Adendorff • Successful transformational change ...

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1. IntroductionAs mentioned in a previous article entitled The success of multi-sector participation in the management of revenue for beneficiary communities of South African renewable energy companies – sub-model A (Amansure & Adendorff, 2017: 63-75), one of the main benefits to be derived from the industry is not being achieved, owing to ineffective project management of revenue for beneficiary communities in the renewable energy sector in South Africa.

Beneficiary communities refers to those communities that must receive socio-economic development benefits from the renewable energy companies located in the area surrounding the renewable energy farm. This investigation focuses on the second sub-model of a comprehensive model to explain transformational change in the perceived success of the management of revenue for beneficiary communities. This is of paramount importance to project managers, especially those operating in the renewable energy sector in South Africa as part of the Renewable Energy Independent Power Producers Procurement Programme (REIPPPP).

The comprehensive model consists of three sub-models (in effect, three sets of independent variables), namely multi-sector participation, transformational change (addressed in this article), and sustainable initiatives (Amansure, 2016). Owing to the limited sample size, the entire matrix of responses in this study could not be subjected to a single exploratory factor analysis and was consequently split into the three sub-models. In order to promote a localised understanding of transformational change to ensure success in managing the revenue for beneficiary community projects by renewable energy construction companies, the factors (variables) that influence the success of revenue management solutions for the renewable energy sector in South Africa were investigated and a theoretical business process model was developed for the perceived success of this revenue management. To test the proposed model, appropriate hypotheses were proposed and tested, and a path diagram of relationships between the independent variables and the dependent variable was constructed and measured. Based on the results of the statistical analysis, the organisational and social variables that will ensure transformational change were identified.


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2. Literature review Sub-model – Transformational change (see Figure 1)

Change without transformation is simply window-dressing (Amansure, 2016). Transformation is about changing the way people view themselves – self-potential; how people view others around them — collective potential, and how people view the world around them (including the natural environment) — sustainable potential (Amansure, 2016). Transformation involves education, social interaction, social cohesion, infrastructure improvement, and sharing. Therefore, every kind of participation referred to in Sub-model – Multi-sector participation) must complement Sub-model – Transformational change and have a deliberate component of knowledge (education) and skills transfer so that beneficiary communities can take ownership of, and be responsible for growth and development.

INDEPENDENT VARIABLES INTERVENING VARIABLE DEPENDENT VARIABLE

+H16

+H1

+H14

+H11

+H1

+H10

+H9

+H1

+H8

+H1

+H12

+H1

+H13

+H1

+H15

+H1

Figure 1: Proposed theoretical Sub-model – Transformational change

To understand the elements in the proposed model, it is important to introduce the factors relating to transformational change that directly influence the perceived success of revenue management for beneficiary communities. These factors form the independent variables used in the measuring instrument. Two of the variables, education and infrastructure development, will be loaded together to form a factor labelled “developmental benefits”. The independent variables associated with this sub-model include developmental benefits, human development and the intervening variable of good governance, measured against the dependent variable: Perceived


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success of revenue management for beneficiary communities. This model alludes to a transformational approach to managing revenue for beneficiary communities.

2.1 Independent variables

2.1.1 Independent variable: Education

The development of a model for managing revenue for beneficiary communities must include the benefits of access to quality education for the rural poor, in order to address illiteracy in rural communities (Atchoarena & Gasperini, 2003). The renewable energy sector should be informed about the best methodology to follow when engaging with these communities to ensure that outcomes are positive and meaningful. In this model, “education” refers to formal and informal education and training in the form of learnerships, mentorships, further education and training, educational support, and resourcing to increase the success of revenue management for beneficiary communities. This will improve the socio-economic circumstances of members of beneficiary communities, enabling them to access the mainstream economy and contribute to local and national economic growth.

2.1.2 Independent variable: Infrastructure development

There are still challenges in infrastructure development in South Africa that must be addressed, especially in rural areas, before the country can reach its infrastructure goals. Some of the challenges include funding of infrastructure projects, slow approval processes for projects, and skills shortages in carrying out the actual work. However, there are also opportunities in investing and developing infrastructure, namely job creation, social development, economic efficiency, and skills development (Gauteng Province Provincial Treasury, 2012: 1). The unique relationship between the renewable energy sector, government and the community must be approached with caution. In this model, “infrastructure development” refers to the physical systems of a renewable energy company or beneficiary community, such as buildings, transportation, communication, sewage, water, and electrical systems that can contribute to successful revenue management, thereby contributing to increased economic growth. Infrastructure governance is also an integral part of this variable.


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2.1.3 Independent variable: Human development

In 2010, the United Nations Development Programme (UNDP) reported that South Africa’s human development index (HDI) rose from 0.587 to 0.601 between 2005 and 2010 (HDR, 2010: 145). South Africa falls into the medium human development category, with a ranking of 110 out of 169 countries (HDR, 2010: 149). United Nations (UN) documents emphasise that “human development” is measured by life expectancy, adult literacy, access to all three levels of education, as well as people’s average income that is a necessary condition to their freedom of choice. In a broader sense, the notion of human development incorporates all aspects of individuals’ well-being, from their health status and capabilities to their economic and political freedom (Munene, 2012). In this model, “human development” refers to the increase of capabilities and opportunities that will ensure successful revenue management for beneficiary communities; to improvement in the quality of life and life expectancy of community members in beneficiary communities; to improvement of human capabilities such as improved health, knowledge and skills, and the use people make of the acquired capabilities for leisure, productive purposes or being active in cultural, social and political affairs in beneficiary communities.

2.1.4 Independent variable: Change management

The Department of Energy (DoE) sets the rules for the disbursement of revenue by renewable energy companies (Eberhard & Naude, 2017). These companies lack the experience and skills to deal with the often complex beneficiary communities that must benefit from funds spent on Socio-Economic Development (SED) and Enterprise Development (ED) (Tait, Wlokas & Garside, 2013). Trying to meet the obligations of the DoE has brought about sudden changes (such as large amounts of revenue inflow) in the beneficiary communities that fall within the geographic radius of the SED and ED obligations of multiple renewable energy facilities. Unless these changes are managed correctly and systematically, it threatens to unbalance and have a negative long-term effect on the socio-economic growth of the beneficiary communities. In this model, “change management” refers to all the participants, methodologies and activities that will contribute to the success of revenue management for beneficiary communities in a transformational and sustainable manner. This will promote human development, socio-economic development, creativity, and innovation with a view to assisting in closing the poverty gap where it exists.


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2.2 Intervening variable: Good governance

Corporate governance is a system of procedures and rules laid down by a company for its efficient and ethical functioning to achieve its mission, conforming to both public policy and law of government and the acceptable, ethical standards of society, resulting in equitable and just distribution/delivery of its benefits to all stakeholders and to society at large (Colley, Doyle, Logan & Stettinius, 2004). Good governance has also been covered extensively by the King Commissions Report of the past few years (The Institute of Directors in Southern Africa, 2016). The code views good governance essentially as being effective, ethical leadership (The Institute of Directors in Southern Africa, 2016: 20). The application of sound governance principles to managing revenue for beneficiary communities in the renewable energy sector in South Africa addresses issues of the mismanagement and misappropriation of funding in the short, medium and long term, as well as deterring incidences of fraud and corruption. In this model, “good governance” refers to the influence of good governance practices, the relationship with the identified variables, and the perceived success of revenue management for beneficiary communities in South Africa. This includes good governance infrastructure, processes, policies, systems, and procedures.

2.3 Dependent variable: Perceived success of revenue management for beneficiary communities

In this model, “the perceived success of revenue management for beneficiary communities” is defined as the degree to which the proposed revenue management model results in an increase in the quality and sustainability of benefits to beneficiary communities in the short, medium and long term, thus resulting in transformational socio-economic development that will reduce poverty and increase job creation and overall economic development of the country.

The primary objective of Sub-model – Transformational change was to guide stakeholders, enterprises and consultants in the renewable energy sector towards a pro-active, effective and relevant decision-making process, in order to achieve transformation success in revenue management for the beneficiary communities. Using proposed Sub-model – Transformational change as a guide and constructing a path diagram of the dependent variable and subsequent independent and intervening variables, appropriate hypotheses were developed. Table 1 shows the hypotheses considered to be tested for Sub-model – Transformational change.


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Table 1: Hypothesis for Sub-model – Transformational change

Hypothesis Definition

H8 There is a positive relationship between education and the perceived success of revenue management for beneficiary communities of South African renewable energy companies.

H9 There is a positive relationship between infrastructure development and the perceived success of revenue management for beneficiary communities of South African renewable energy companies.

H10 There is a positive relationship between human development and the perceived success of revenue management for beneficiary communities of South African renewable energy companies.

H11 There is a positive relationship between change management and the perceived success of revenue management for beneficiary communities of South African renewable energy companies

H12 There is a positive relationship between education and good governance.

H13 There is a positive relationship between infrastructure development and good governance.

H14 There is a positive relationship between human development and good governance.

H15 There is a positive relationship between change management and good governance.

H16 There is a positive relationship between good governance structures and the perceived success of revenue management.

3. Research methodology For this research study, a positivistic research paradigm was adopted within which to identify the organisational and social variables that will ensure transformational change of revenue management among beneficiary communities of South African renewable energy construction companies. The positivist paradigm asserts that real events can be observed empirically and explained with logical analysis (Aliyu, Bello, Kasim & Martin, 2014: 83). The positivistic paradigm is also known as the quantitative, objectivist, scientific, experimentalist or traditionalist research paradigm (Collis & Hussey, 2003). This paradigm allows for quantitative research design which allows for the use of structured questionnaire surveys, enabling researchers to generalise their findings from a sample of a population (Creswell, 1994). In the questionnaire, transformational change, items expected to measure the factors of education, infrastructure development, human development, and good governance were extracted and set as the variables that will ensure transformational change (Creswell, 2005). Exploratory factor analysis (EFA) was used


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to assess these measured variables in terms of their validity and reliability. It is a type of technique that analyses the unidimensionality (characteristics) of each of the defined transformational change items (original variables), in order to reduce it to a common score (smaller number of factors) by examining relationships among these quantitative factors (Pallant, 2013: 192; Rossoni, Engelbert & Bellegard, 2016: 200). Several factor analysis methods are available, but Principal Axis Factoring (PAF) was used, because it analyses not only correlations, but also covariances, and the Eigenvalues could be extracted which explains whether the factors tested had or had not a noticeable effect on people’s responses to the variables in the original test (analysed construct) (Rossoni et al., 2016: 201; Pallant, 2013:192; Youngblut, 1993: 123). Structural Equation Modelling (SEM) was used to test the significance of the causal relationships hypothesized between the variables that influence good governance. SEM is a technique that uses path analysis to test factor analysis and hypotheses in the same analysis (Gefen, Straub & Boudreau, 2000: 5).


It is very difficult to ascertain the overall research population size, but the composition of the population that was targeted for this research study included practitioners from various renewable energy sectors, governmental institutions, non-governmental institutions, renewable energy researchers, community development specialists, and academics. Snowball sampling was used, because this method is appropriate when the members of a special population are difficult to locate (Babbie & Mouton, 2001). As the snowball sampling progressed, databases were received from interested parties within the renewable energy community and economic development sector, resulting ultimately in 219 participating respondents.

3.2 Data collection

A self-administered questionnaire was developed and distributed to 219 respondents using electronic email from 1 July to 30 September 2016. The questionnaires were collated online, using an Excel-based spreadsheet, and then downloaded by the researcher for analysis.

Topics on transformational change of revenue management used in the questionnaire were extracted from reviews of the literature, resulting in the formulation of a questionnaire divided into two sections. Section one on respondent’s profile obtained personal information on age, gender, level of education, experience in


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community development, and connection with the renewable energy sector. Section two sets 60 questions on factors influencing revenue management for beneficiary communities in the renewable energy sector in South Africa. The respondents were required to indicate their level of agreement with these statements. The data from these measurements forms the variables used in the exploratory factor analysis, which tested the validity and reliability of the factors. To reduce the respondent’s bias, closed-ended questions were preferred for section two (Akintoye & Main, 2007: 601).


Prior to the implementation of SEM, IBM Statistical Product and Service Solutions 23 (SPSS 23) for Windows was used to determine the factor analysability of the measured constructs incorporated in the theoretical model (Pallant, 2013).

To rank which of the transformational change items were expected to measure the factors of education, infrastructure development, human development, and good governance, the measures were rated on a seven-point Likert scale. Likert-type or frequency scales use fixed choice response formats and are designed to measure attitudes or opinions (Simon & Goes, 2013: online). The following scale measurement was used regarding mean scores, where 1 = strongly disagree (≥ 1.00 ≤ and <1.80); 2 = disagree (≥ 1.81 and ≤ 2.60); 3 = somewhat/slightly disagree (≥ 2.61 and ≤ 3.40); 4 = neither agree nor disagree (neutral) (≥ 2.61 and ≤ 3.40); 5 = somewhat/slightly agree (≥ 3.41 and ≤ 4.20); 6 = agree (≥ 2.61 and ≤ 3.40), and 7 = strongly agree (≥ 4.21 and ≤ 5.00).

For the analysis of the internal reliability of the factors in the questions on transformational change, Cronbach’s alpha values were tested during the exploratory factor analysis (Kolbehdori & Sobhiyah, 2014: 347; Nunnally & Bernstein 1994; Wahab, Ayodele & Moody, 2010: 67). Tavakol and Dennick (2011: 54-55) and Yount (2006) suggested that the acceptable values of Cronbach’s alpha would range from 0.70 to 0.95. In the current study, a Cronbach’s alpha co-efficient of greater than 0.70 is used to indicate that a factor is reliable. Furthermore, the optimal inter-item correlations mean (factor loadings) should range from 0.2 to 0.4, in order for the factor to be reliable (Pallant, 2013: 134). However, in this study, a value of 0.3 and above was adopted.

To confirm whether the data from the measurements was sufficient for factor analysis (test the validity and factor analysability of the data), the Kaiser-Meyer-Olkin (KMO) test (Lorenzo-Seva, Timmerman


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& Kiers, 2011: 343) and the Bartlett’s sphericity (Hair, Black, Babin, Andersen & Taham, 2006: 110) tests were performed. In the KMO test, as the values of the test vary from 0 to 1, values above 0.7 are recommended as being desirable for applying EFA (Hair et al., 2006). A statistically significant Bartlett test (p < 0.05) indicates that sufficient correlations exist between the variables to continue with the analysis (Hair et al., 2006: 110; Pallant, 2013: 190). Eigenvalues are used to explain the variance captured by the factor. Eigenvalues greater than 1 are considered significant, whereas factors with Eigenvalues less than 1 are considered insignificant and are discarded (Hair et al., 2010). In this study, in exceptional cases, factors with Eigenvalues lower than 1 were considered for retention provided that the factors (and items) could be interpreted.

In determining the number of factors to extract, Principal Axis Factoring (PAF) was used to find the underlying factors related to the 60 questionnaire items based on correlations and on covariances, where the first factor accounts for as much common variance as possible (Burton & Mazerolle, 2011: 28; Fabrigar, Wegener, MacCallum & Strahan, 1999: 277). In PAF, when the number of variables (items) is between 20 and 60, it is more reliable to use Eigenvalues to extract factors, as it makes interpretation simpler (Johnson & Wichern, 2007). To clarify and simplify the results of the factor analysis, Oblique Rotation (direct quartimin) was used to examine factor/item loadings and to reveal any correlation between these factors (Costello & Osborne, 2005: 3).

Structural Equation Modelling (SEM) was used to test the significance of the causal relationships hypothesized between the variables that influence good governance. The LISREL software application (v 8.8) was used to test the relationships among the factors that influence the perceived success of the management of revenue.

3.4 Limitations

The research was limited to the field of global and regional generation of electrical power by renewable energy.

4. FindingsThe significant relationships identified in the study and the recom-mendations about how these determinants can be addressed are presented and discussed in Tables 1-5.


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4.1 Empirical results of Sub-model – Transformational change

For Sub-model – Transformational change, labelled “Transformational change”, PAF with an Oblique Rotation (Oblimin with Kaiser Normalisation) was used as the extraction and rotation method. Bartlett’s Test of Sphericity returned a KMO value of 0.93 (p < 0.00), indicating that the data were suitable for factor analysis.

In Sub-model – Transformational change, items expected to measure the factors of education, infrastructure development, human development, and good governance were assessed for discriminant validity by means of an exploratory factor analysis. Initially, the number of factors to be extracted was not specified, but the Eigenvalues suggested a total of three factors to be used as the independent variables. The final solution was reached through an iterative process of deleting items that did not demonstrate sufficient discriminant validity, and re-running the exploratory factor analysis until all the remaining items loaded to a significant extent (p > 0.4), with no cross-loadings (i.e., loaded on only one factor). All items with loadings < 0.4 were deleted. The independent variables were analysed first and the following results were obtained:

Table 1: Rotated factor loadings: Sub-model – Transformational change

VariableFactor 1

Developmental benefits

Factor 2Human development

Factor 3Good governance

ED5 0.822* -0.032 -0.009

ID5 0.813* 0.020 -0.212

ED3 0.768* 0.051 0.054

ID4 0.746* 0.025 0.106

ED4 0.709* 0.041 0.136

ID2 0.673* 0.024 0.184

ED2 0.602* -0038 0.194

ID3 0.551* 0.009 0.276

ID1 0.533* 0.011 0.233

ED1 0.462* 0.011 0.289

HD4 -0.097 0.895* 0.004

HD3 0.025 0.853* -0.084

HD2 -0.041 0.744* 0.033

HD1 0.168 0.678* -0.131


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VariableFactor 1

Developmental benefits

Factor 2Human development

Factor 3Good governance

HD5 -0.038 0.528* 0.143

GG3 0.162 -0.009 0.732*

GG1 -0.009 0.012 0.702*

GG4 0.205 0.05 0.658*

* = significant loadings (p ≥ 0.4); ED = Education; HD = Human deve-lopment; ID = Infrastructure development; GG = Good governance

Table 1 indicates that a total of 20 items, including three independent variables and one intervening variable, were grouped into three factors, which explained 65.24% of the variance in the data. The intervening variables were then analysed using the same procedure of factor analysis.

4.1.1 Factor 1: Dependent variable – developmental benefits

All five items expected to measure the construct of education and infrastructure development loaded together on the same factor. Consequently, based on the results of the factor analysis, this construct was redefined and renamed “developmental benefits”.

In this study, “developmental benefits” are operationally defined as the benefits that the beneficiary community can derive from formal and informal education, training in the form of learnerships, mentorships, further education and training, educational support, and resourcing. Benefits also include the development of physical systems such as buildings, transportation, communication, sewage, water, and electricity pertinent to the construction phase that will improve the socio-economic circumstances of the beneficiary communities.

Developmental benefits explained 45.01% of the variance in the data, with an Eigenvalue of 9.00, as reported in Table 1. All factor loadings exceeded 0.4 and were thus regarded as significant, providing sufficient evidence of discriminant validity of the construct. The Cronbach’s alpha co-efficient of 0.93 for developmental benefits suggests that the instrument used to measure this construct was reliable.


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4.1.2 Factor 2: Independent variable – human development

All five of the items that were expected to measure the construct of human development loaded together on one factor. Human development explained 14.60% of the variance in the data, with an Eigenvalue of 2.92, as reported in Table 1. All factor loadings exceeded 0.4 and were thus regarded as significant, providing sufficient evidence of discriminant validity of the construct. The Cronbach’s alpha co-efficient of 0.856 for human development suggests that the instrument used to measure this construct was reliable.

The operationalization of human development, as described in Section 2, remained unchanged.

4.1.3 Factor 3: Intervening variable – good governance

All five of the items that were expected to measure the construct of good governance loaded together on one factor, as expected. Good governance explained 5.64% of the variance in the data, with an Eigenvalue of 1.13, as reported in Table 1. All factor loadings exceeded 0.4 and were thus regarded as significant, providing sufficient evidence of discriminant validity of the construct. The Cronbach’s alpha co-efficient of 0.88 for good governance suggests that the instrument used to measure this construct was reliable.

The operationalization of good governance, as described in Section 2, remained unchanged.

4.2 Reformulation of the hypotheses and the revised theoretical model

Sub-model – Transformational change (Transformational change) was constructed using a separate path diagram depicting the causal relationships between the antecedent variable of developmental benefits and human development and the intervening variable of good governance and the dependent variable of perceived success of revenue management (Figure 2).


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+H8a

+H1

+H6

+H1

+H7

+H8

+H1

+H8b

Figure 2: Path diagram of causal relationships: Revised theoretical model (Sub-model – Transformational change)

Two variables, namely education and infrastructure development, loaded together to form a factor labelled “developmental benefits” (DEVB). The independent variable of change management was removed from the proposed theoretical model because its discriminant validity could not be confirmed by the exploratory factor analysis.

After the reliability and discriminant validity of all the variables remaining in the empirical model had been confirmed, the statistical technique of SEM was used to test the series of relationships of the revised model in Figure 2.

Table 2: Reformulated hypotheses for Sub-model – Transfor-mational change

Reformulated hypotheses

Sub-model - Transformational change – Transformational change

H6 There is a positive relationship between developmental benefits and the perceived success of revenue management.

H7 There is a positive relationship between human development and the perceived success of revenue management.

H8 There is a positive relationship between good governance and the perceived success of revenue management.

H8a There is a positive relationship between developmental benefits and good governance.

H8b There is a positive relationship between human development and good governance.


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4.3 Assessment of fit

Before the SEM analysis was carried out, an assessment of the multivariate normality of the data was conducted. The following hypotheses were formulated for this purpose:

H0: The data are normally distributed.

Ha: The data are not normally distributed.

The null hypothesis and the alternative hypothesis, as formulated above, were evaluated by assessing the skewness and the kurtosis of the data, while the Chi- square (x2) value was used to determine the relevant p-value. The results of the test of multivariate normality of the relationship between the independent and intervening variables are presented as follows.

4.3.1 The measurement and structural models for Sub-model – Transformational change (intervening variable of good governance)

Table 3 shows the fit indices for Sub-model – Transformational change, which assess the relationship between the independent variables of developmental benefits and human development and good governance.

Table 3: Fit indices for the measurement and structural models for Sub-model – Transformational change – intervening variable

Fit indices for the measurement and structural models for Sub-model – Transformational changeRelationship between the independent and intervening variables (good governance)

Item Measurement model Structural model

Sample size 219 219

Degrees of freedom 269 271

Satorra-Bentler scaled Chi-square 466.463 (p = 0.00)

471.228 (p = 0.00)

SBx2 / Degrees of freedom 1.73 1.74

Root Mean Square Error of Approximation (RMSEA) 0.0580 0.0582

90% confidence interval for RMSEA (0.0491; 0.0668) (0.0493; 0.0669)

Expected Cross-validation Index (ECVI) 2.654 2.657


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4.3.1.i Measurement model

The goodness-of-fit indices for the measurement model illustrated in Figure 3 are reported in Table 3. The Satorra-Bentler x2 divided by the degrees of freedom is 1.73, which is lower than the acceptable value of 2 and indicates a good fit. The RMSEA (0.0580) is less than 0.06 and indicates a close fit (Hu & Bentler, 1999, while the 90% confidence interval for RMSEA (0.0668) is less than 0.08 and is considered to be in the upper limit of the confidence level (MacCullum, Browne & Sugawara, 1996). These fit indices all provide evidence of a model with a reasonable fit. Consequently, the null hypothesis, that the data fit the model perfectly, must be rejected. However, although the data do not fit the model perfectly, the data can be described as having a close fit.

4.3.1.ii Structural model

The Satorra-Bentler x2 to degrees of freedom ratio is 1.74, which is lower than 2. Values lower than 2 indicate a good fit (Politis, 2003). The RMSEA (0.0582) is less than 0.06 and indicates a very close fit (Hu & Bentler, 1991), while the upper limit of the 90% confidence interval for RMSEA (0.0669) is less than 0.08 (Roberts, Stephen & Ilardi, 2003). These fit indices all provide evidence of a model with a good fit. Consequently, the null hypothesis, that the data fit the model perfectly, must be rejected. However, although the data do not fit the model perfectly, the data can be described as having a good fit.

4.3.2 The measurement and structural models for Sub-model – Transformational change (dependent variable of perceived success of revenue management)

Table 4 shows the fit indices for Sub-model – Transformational change, which assess the relationship between the independent variables of developmental benefits and human development, and dependent variable of perceived success of revenue management.


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Table 4: Fit indices for the measurement and structural models for Sub-model – Transformational change – dependent variable

Fit indices for the measurement and structural models for Sub-model – Transformational changeRelationship between the independent and dependent variables (perceived success)

Item Measurement model

Structural model

Sample size 219 219

Degrees of freedom 167 167

Satorra-Bentler scaled Chi-square x2 279.470 (p = 0.00)

279.470 (p = 0.00)

SBx2 / Degrees of freedom 1.67 1.67

Root Mean Square Error of Approximation (RMSEA) 0.0556 0.0556

90% confidence interval for (RMSEA) (0.0439; 0.0668)

(0.0439; 0.0668)

Expected Cross-Validation Index (ECVI) 1.676 1.676

4.3.2.i Measurement model

The ratio x2 to degrees of freedom is 1.67, which is significantly lower than 2. A value of lower than 2 is an indication of a good fit. The RMSEA (0.0556) is within the reasonable fit range of 0.05-0.08, while the upper limit of the 90% confidence interval for RMSEA (0.0668) is less than 0.08. These indices all provide evidence of a model with a reasonable fit. Consequently, the null hypothesis, that the data fit the model perfectly, must be rejected. However, although the data do not fit the model perfectly, the data can be described as having a reasonable or acceptable fit.

4.3.2.ii Structural model

The Satorra-Bentler x2 divided by the degrees of freedom is 1.67, which is lower than 2 and indicates a good fit (Politis, 2003). The RMSEA (0.0556) is less than 0.06 and indicates a good fit (Hu & Bentler, 1991), while the upper limit of the 90% confidence interval for RMSEA (0.0668) is less than 0.08, which is in the upper limit of the confidence level and indicates a good fit (Roberts et al., 2003). These fit indices all provide evidence of a model with a good fit. Consequently, the null hypothesis, that the data fit the model perfectly, must be rejected. However, although the data does not fit the model perfectly, the data can be described as having a good fit.


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4.4 Structural and measurement model

Figure 3 illustrates the structural estimation for Sub-model – Transfor-mational change.


+H8b Path co-efficient = 0.01 N.S.

t=0.27

Path co-efficient = 0.02 +H7 N.S.

t=0.43

Path co-efficient = 0.84 +H6 p<0.001

t=5.18

Path co-efficient = 0.93 p<0.001 t=6.38

+H8a Path co-efficient = 0.88 p<0.001

t=3.99

Sub-

Mod

el B

+H8

Figure 3: Structural estimation for Sub-model – Transformational change (including t-values) where N.S. = non-significant

4.5 Empirical results: hypotheses testing

In the ensuing sections, the various steps of SEM are applied to Sub-model – Transformational change (Figure 3) to evaluate whether the various hypotheses associated with this sub-model should be accepted or rejected.

4.5.1 Developmental benefits and the perceived success of revenue management

H6: There is a positive relationship between developmental benefits and the perceived success of revenue management.

Since various academics and practitioners suggested that the use of developmental benefits would improve the perceived success of revenue management, Hypothesis 6 was assessed. Figure 3 shows that developmental benefits are positively related to the perceived success of revenue management for beneficiary communities (point estimate = 0.84, p < 0.001, t = 5.18), with 0.01% level of significance. Hypothesis 6 was thus accepted. Hypothesis 6 confirms that, when renewable energy companies incorporate developmental benefit projects such as education and infrastructure development into the socio-economic development approach, they will have a


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positive impact on the revenue management for the company’s beneficiaries. This empirical result concurs with previous research recorded in literature by Halina, Wilson & Zarsky (2007), Dutton (2004), and Nyahuye (2012).

4.5.2 Human development and the perceived success of revenue management

H7: There is a positive relationship between human development and the perceived success of revenue management.

The empirical results of this study revealed that human development does not have a significant influence on the perceived success of revenue management for beneficiary communities of South African renewable energy companies (point estimate = -0.02, p > 0.00, t = 0.43). Therefore, Hypothesis 7 was rejected.

4.5.3 Good governance and perceived success of revenue management

H8: There is a positive relationship between good governance and the perceived success of revenue management.

Various sources, both academically and practically oriented, have suggested that the use of good governance practices can improve the perceived success of the revenue management of renewable energy companies. It was against this background that Hypothesis 8 was assessed. The results recorded in Figure 3 confirm that the use of good governance practices is positively related to the perceived success of revenue management for beneficiary communities (point estimate = 0.93, p < 0.001, t = 6.38), with a 0.1% level of significance. Hypothesis 8 was thus accepted. Hypothesis 8 proposes that, when good governance measures are implemented, this will result in an improvement in the integrity of revenue management for beneficiary communities. This empirical result is supported by previous research recorded in literature by Jonker & De Witte (2006); Walker & Mokoena (2011); Engelbrecht (2009); Erasmus (2014); Johnston (2009); Boyce, Griffith & King (2007), and Rossouw (2012).

4.5.4 Developmental benefits and good governance

H8a: There is a positive relationship between developmental benefits and good governance.

Various sources, both academically and practically oriented, have suggested that developmental benefits can improve the perceived success of the revenue management of renewable energy companies. Hypothesis 8a was assessed against this background.


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Figure 3 shows that developmental benefits are positively related to the intervening variable of good governance (point estimate = 0.88, p < 0.001, t = 3.99), with 0.1% level of significance. Hypothesis 8a was thus accepted. This hypothesis suggests that, when renewable energy companies consider the implementation of developmentally beneficial projects (education and infrastructure development), this will improve the company’s approach of good governance towards beneficiary revenue management. This empirical result confirms previous research recorded in literature by Agenor (2013); Dorel, Rasa & Olga (2015); Boateng (2012); Fourie (2006), and the Economic Commission for Africa (2013).

4.5.5 Human development and good governance

H8b: There is a positive relationship between human development and good governance.

The empirical results of this study revealed that human development does not have a significant influence on good governance (point estimate = -0.01, p > 0.00, t = -0.27), which is contrary to what was proposed in hypothesis 8b. Therefore, Hypothesis 8b was rejected.

Table 5: Summary of all the Sub-model – Transformational change hypotheses

Summary of all the Sub-model – Transformational change hypotheses

H6There is a positive relationship between developmental benefits and the perceived success of revenue management.

Supported

H7There is a positive relationship between human development and the perceived success of revenue management.

Not supported

H8 There is a positive relationship between good governance and the perceived success of revenue management. Supported

H8a There is a positive relationship between developmental benefits and good governance. Supported

H8b There is a positive relationship between human development and good governance. Not supported

5. ConclusionThe independent variables associated with this sub-model include developmental benefits and human development, and the inter vening variable was good governance, which alludes to a transformational approach to revenue management for beneficiary


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communities. Therefore, every kind of participation referred to in sub-model A (multi-sector participation) must complement Sub-model – Transformational change and have a deliberate component of knowledge (education) and skills transfer so that beneficiary communities can take ownership of, and be responsible for growth and development.

There must be greater participation on the part of government and the IPPs during the implementation of community projects to ensure that outcomes for the beneficiary communities are transformational in nature. The role of the intervening variable, good governance, must also form an integral part of project management to ensure that transformational change benefits the beneficiary community at all times and in every possible way. Project management, especially during the construction phase, must include activities such as:

• Addressing human development needs as a priority.• Prior to construction of the renewable energy facility, gain

baseline knowledge and insight regarding the educational and infrastructural needs of the beneficiary communities (including engagement with the community at grassroots level).

• Scenario forecasting.• Appointing internal and external service providers.• Forming possible PPPs or collaborating with other IPPs.• Managing finances and financial transactions.• Monitoring, evaluating and reporting all activities.• Include policies and procedures in all project management

processes.It is now known from the most recent literature available (DoE, 2015) that the quantum of the socio-economic development, enterprise development and community trust to be spent over the next 20 to 25 years in South Africa in the renewable energy sector as part of the REIPPP Program is over R50 billion. The renewable energy sector has the opportunity to use these funds to make a transformational change in the beneficiary communities and, ultimately, in the overall economy of South Africa.

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A construction project management knowledge model: The type and level of knowledge required



AbstractConstruction project managers come from diverse backgrounds and may, therefore, lack the knowledge set currently required in order to be competent and effective in practice. The aim of this article is to establish the National Qualifications Framework (NQF) level of each type of knowledge area required for a competent and effective construction project manager in South Africa. These levels of knowledge are important, in order to develop a proposed construction project management knowledge model to be used by the construction industry. A mixed methods research design was used, including structured questionnaires (n = 40), interviews (n = 10), and a single case study. The questionnaire survey, using close-ended questions measured on a 5-point Likert scale, tests the importance of and rated the NQF qualification levels of each knowledge type fit for project managers in the built environment. The rating assisted in knowing to what knowledge depth project managers need to be educated and trained. Interviews were conducted with 10 construction professionals to obtain their views on the importance of industry-specific know ledge of a construction project manager and to critically review the form of knowledge considered essential. The case study of a building project to the value of R35 million was used to gain understanding of the impact that industry-specific knowledge, or the lack thereof, may have on the successful completion of a project. Results showed that qualifications to gain industry-specific knowledge should at least be on NQF level 6; a qualification on NQF level 7 is recommended to gain adequate project manage ment knowledge (theory). These findings are important, as some construction project management courses in

Michelle Burger

Dr Michelle Burger, Lecturer, Department of Construction Economics, University of Pretoria, Private bag X20, Hatfield 0028, South Africa. Phone: 082 418 2833, email: <[email protected]>

Benita Zulch

Prof. Benita G. Zulch, HOD, Department of Construction Economics, University of Pretoria, Private bag X20, Hatfield 0028, South Africa. Phone: (012) 420-2581, email: <[email protected]>







Burger & Zulch • A construction project management knowledge ...

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South Africa are currently below NQF level 6. This may be contributing to industry not producing construction project managers with the required knowledge set. The proposed model outlines the adequate knowledge sets and level thereof that can be used when designing training and educational degrees for construction project managers. The proposed model could also be used in practice as a guideline for placing or promoting construction project managers. Keywords: Construction project management, knowledge model, type of knowledge, NQF knowledge level, South Africa

AbstrakKonstruksieprojekbestuurders kom van uiteenlopende agtergronde, en mag dus die kennisstel kort wat tans benodig word om vaardig en effektief in die praktyk te wees. Die doel van hierdie artikel is om die Nasionale Kwalifikasieraamwerk (NKR)-vlak van elke tipe kennisarea vas te stel wat benodig word vir ’n bevoegde en effektiewe bouprojekbestuurder in Suid-Afrika. Hierdie vlakke van kennis is belangrik om ’n voorgestelde konstruksieprojekbestuur-kennismodel te ontwikkel wat deur die konstruksiebedryf gebruik kan word. ’n Gemengde metodes navorsingsontwerp is gebruik, insluitend gestruktureerde vraelyste (n = 40), onderhoude (n = 10) en ’n enkele gevallestudie. Die vraelys-opname deur middel van geslote vrae het die belangrikheid van en gegradeerde NKR-vlakke van elke kennissoort geskik vir projekbestuurders in die beboude omgewing, gemeet op ’n 5-punt Likert-skaal. Die gradering het gehelp om te weet tot watter kennisdiepte projekbestuurders opgelei moet word. Onderhoude is gevoer met 10 konstruksiewerknemers om hul standpunte oor die belangrikheid van bedryfspesifieke kennis van ’n konstruksieprojekbestuurder te verkry en om die vorm van kennis wat noodsaaklik beskou word, krities te hersien. Die gevallestudie van ’n bouprojek ten bedrae van R35 miljoen is gebruik om begrip te kry van die impak wat bedryfspesifieke kennis, of die gebrek daarvan, op die sukses van ’n projek kan hê. Resultate het getoon dat kwalifikasies om bedryfskennis te verkry, ten minste op NKR-vlak 6 moet wees; ’n kwalifikasie op NKR-vlak 7 word aanbeveel om voldoende projekbestuurskennis (teorie) te verkry. Hierdie bevindings is belangrik aangesien sommige konstruksieprojekbestuurskursusse in Suid-Afrika tans laer as NKR-vlak 6 is. Dit kan bydra daartoe dat die industrie tans konstruksieprojekbestuurders sonder die vereiste kennisstel in diens neem. Die voorgestelde model beskryf die toereikende kennisstelle en vlak daarvan wat gebruik kan word by die ontwerp van opleidingskwalifikasies vir konstruksieprojekbestuurders. Die voorgestelde model kan ook in die praktyk gebruik word as riglyn om konstruksieprojekbestuurders te plaas of te bevorder.Sleutelwoorde: Konstruksieprojekbestuur, kennismodel, NKR-kennisvlak, tipe kennis, Suid-Afrika

1. IntroductionThe PMI Pulse of the Profession highlighted that the high cost of low performance resulted in organisations, globally, wasting US$122 billion for every US$1 billion spent on projects, due to poor project management. Organisations that use formal project management practices waste 13 times less money than organisations that do not (PMI, 2016).


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The built environment is project driven, and to meet organisational aims and reach higher profits, these projects need to be completed as efficiently as possible (Rad & Levin, 2006: 1; Trebilcock, 2007: 40). In the built environment, project management is used to produce better projects, and speed up the operational process (Morrison & Brown, 2004: 73-74). To manage projects successfully, organisations use project managers with the necessary knowledge about techniques that are used to ensure successful management of projects (Burke, 2013: 1-5; Chordas, 2008: 66-69; Kerzner, 2013: 2-10; PMI, 2016).

Organisations in the built environment rely heavily on the proficiency of construction project managers (Orr, 2004: 1). Therefore, project managers cannot merely rely on experience, but they need, not only adequate knowledge, but also the correct knowledge set, in order to be competent and effective in managing projects (Craig, 2005: 42). As the market place is highly competitive, organisations in the built environment will benefit in knowing what type of knowledge construction project managers require and to what level it should be (Peterson, 2008: 38-42).

A literature review identified some knowledge management models for project management (Piraquive, García & Crespo, 2015; Yeong & Lim, 2010; Handzic & Durmic, 2010), but a specific model for project managers in the construction industry may not exist.

A proposed construction project management knowledge model may fill the void for a model that can be used by construction project managers as a possible enhancement tool for improved project management knowledge sets. A literature study clarified the type of knowledge project managers should have, as well as the level thereof based on the NQF scope of knowledge classification. This clarification was important to highlight some elements within the knowledge areas as well as the NQF level of knowledge classification that may contribute to the design of the proposed model.

In order to determine the elements needed to design the model, a mixed methods research study design was used to test the importance of NQF levels of knowledge for project managers in the built environment from not important to critically important. Interviews with construction professionals determined their views on the importance of industry-specific knowledge of a construction project manager. The case study of a building project was used to gain understanding of the impact that industry-specific knowledge and experience may have on the success of a project.


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Based on the findings, the knowledge expected from project managers was grouped into NQF level 6 (technical knowledge) and NQF level 7 (project management knowledge theory), which together with knowledge gained through experience form the main basis of the proposed model.

2. Literature review

2.1 Type of knowledge

An effective project manager needs to have project management knowledge (Pacelli, 2004: 54; Sumner & Powell, 2013: 2; Udo & Koppensteiner, 2004); technical (industry) knowledge and experience (Kerzner, 2013: 9-1; Petterson, 1991: 99). A combination of these knowledge areas is essential, in order to effectively manage a project (Burger, Verster & Zulch, 2015: 69). To understand the importance of the type of knowledge within the proposed model, it is important to determine and define project management knowledge (theory), technical (industry) knowledge and experience that are considered in project management.

2.1.1 Project management knowledge (theory)

A successful project needs to be completed within time, cost and quality and according to the agreed upon scope. Some organisations fail to realise that having staff, time and money is not enough to ensure success. Some important factors to accomplish this are effective project planning, management, and control (Chordas, 2008: 66-69; Kerzner, 2013: 2-10). Having project management tools and techniques is important, in order to plan. Planning is important, in order to manage a project within time, cost, and quality parameters. By implication, integrated knowledge is required to have an understanding of, and an ability to apply and evaluate the key terms, concepts, facts, principles, rules and theories of project management to other fields, disciplines or practices (e.g., engineering) in the construction industry (Longman & Mullings, 2005: 5; Kerzner, 2013: 2-10). Project management is regulated by professional bodies, one of which is the Project Management Institute (PMI). The PMI has published a knowledge guide known as the PMBOK guide stipulating the key terms, concepts, facts, principles, and rules of project management areas.

The nine generic project management areas include integration, scope, time, cost, quality, human resources, communication, risk, and procurement. In addition to the nine PMBOK knowledge areas


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that are generic, the PMI have identified four additional areas known as the Construction Extension to the PMBOK that are industry specific, namely safety management, environmental management, claims management, and financial management (PMI, 2015; Burger et al., 2015: 53). The purpose of the Construction Extension is to improve the efficiency and effectiveness of the management of construction projects. The focus of this study is on NQF level qualifications. The 13 project management areas are only introduced and not discussed in this article.

2.1.2 Technical (industry) knowledge

A project manager must have detailed technical knowledge of the main areas of project management, in order to accurately understand and apply the key terms, concepts, facts, principles, rules, and theories of the technical industry requirements of the project so that business needs are addressed and satisfied (Cadle & Yeates, 2001: 358; Ashworth & Hogg, 2002: 381-384). Turk (2007: 25) states that project managers need to know what questions to ask and should be able to judge when they are not getting the full story. In order to do this, technical knowledge is required. This knowledge is also needed to evaluate technical concepts and solutions, assess risks and make trade-offs between cost, schedule and technical issues (Kerzner, 2013: 146-149). A blend of technical knowledge and project management knowledge is, therefore, required.

The following technical knowledge areas are required: construction science, finance and cost, construction processes, and design processes (Burger et al., 2015: 22; SACPCMP, 2015). Each of these four areas contains knowledge subsections. Construction science includes understanding of structures, understanding of construction and building sciences, understanding construction and building finishes, and knowledge of building material. Finance and cost includes understanding financial processes and having knowledge of the cost of construction. Knowledge of construction processes includes site, plant and equipment, formwork systems, quality management, health and safety management, environmental management, organisational/management structures, general building sequences, general output and production factors, and basic knowledge of building trades. Knowledge of the design processes consists of sequence of design processes and time required for design processes.

The construction industry is unique, as it differs from, for example, the IT industry. Project management within the construction industry


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requires a specialised form of management. A construction project manager requires technical competencies, in order to effectively execute the work s/he needs to do (SACPCMP, 2015: Online).

2.1.3 Experience

Petterson (1991: 99) mentions that project managers need a solid basic experience in the relevant field. This is also supported by Sears, Sears & Clough (2008: 15) who state that the project manager needs certain attributes, in order to be successful. This includes a considerable background of experience and expertise. Experience alone will not suffice. In order to progress in a career, project managers need the combination of both experience and knowledge (Craig, 2005: 42).

Construction project managers thus need a blend of project manage-ment knowledge, technical knowledge, and experience in the field, in order to contribute to successful project management. The correct knowledge set will contribute to effective communication and trust in a project. These organisational elements are crucial for efficient and successful project management (Burger et al., 2015: 69).

2.2 Level of knowledge

In South Africa, all education and training qualifications need to be registered through the South African Qualifications Authority (SAQA) and given a certain National Qualifications Framework (NQF) rating scale level. These NQF rating scale level descriptors are used to indicate the type and level of knowledge required for a qualification from NQF level 1 to NQF level 10 (SAQA, 2015: Online). The lower level descriptors relate to artisan training and, from NQF level 5, the focus moves towards management type of knowledge. As the level of knowledge sets of project managers is tested, the focus of this study is on NQF level 5 to NQF level 9.

• NQF 5 (certificate).• NQF 6 (diploma level).• NQF 7 (first degree such as a BSc).• NQF 8 (Honours level).• NQF 9 (Master’s level).

For education and training qualifications in Construction Project Management, various project management courses, presented by different institutions in South Africa have been registered and received a certain NQF level. These courses range from a NQF level 5 (certificate) to a NQF level 9 (Master’s) (SAQA, 2015: Online). The


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NQF rating level indicates that the knowledge presented in the course is on an adequate level as expected for that course. An institution can offer a level 5 certificate programme. However, the SACPCMP requires a minimum of a level 8 for registration. Any lower NQF qualification will mean that the individual will need additional work experience or be required to write an entrance examination, in order to be registered as a professional construction project manager (SACPCMP, 2015: online).

Table 1 shows the scope of knowledge that is required for the various NQF levels defined by SAQA.

Table 1: NQF levels

NQF level Qualification Requirements

5 Certificate

Knowledge of the main areas of one or more fields, disciplines or practices, including an understanding of the key terms, concepts, facts, principles, rules, and theories of that field.

6 Diploma

Detailed knowledge of the main areas of one or more fields, disciplines or practices, including an understanding of, and an ability to apply the key terms, concepts, facts, principles, rules, and theories of that field, discipline or practice.

7 First degree such as a BSc

Integrated knowledge of the main areas of one or more fields, disciplines or practices, including an understanding of, and an ability to apply and evaluate the key terms, concepts, facts, principles, rules, and theories of that field, discipline or practice. Knowledge of an area or areas of specialisation and how that knowledge relates to other fields, disciplines or practices.

8 Honours

Knowledge of, and engagement in an area at the forefront of a field, discipline or practice. Furthermore, there is an understanding of the theories, research methodologies, methods and techniques relevant to the field, discipline or practice, and an understanding of how to apply this knowledge in a particular context.

9 Master’s

Specialist knowledge to enable engagement with, and critique of current research or practices. An advanced scholarship or research in a particular field, discipline or practice is present.

The above literature review introduces project management knowledge (theory), technical (industry) knowledge, and knowledge gained through experience in the field, as the three knowledge types considered to be important for construction project managers. Project management knowledge (theory) requires integrated knowledge of an area of specialisation. Table 1 shows that NQF level 7, defined by SAQA, demands integrated knowledge of an area or areas of specialisation and how that knowledge relates to


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other fields, disciplines or practices. Therefore, it can be suggested that the project manager’s knowledge, as an expert in project management, should be at an NQF level 7.

Technical (industry) knowledge requires detailed knowledge that can be applied to more than one field in the construction management industry. The NQF guide of knowledge classification in Table 1 shows clearly that, for construction project management qualifications, the NQF level should at least be on level 6, as detailed knowledge needs to be applied from more than one field.

The SACPCMP (2015: Online) requires a minimum of a level 8 to be registered as a professional construction project manager.

3. ResearchThis study addressed the importance of NQF qualification levels of knowledge for project managers as well as the importance of gaining knowledge through experience for construction project managers in the built environment. The validity and reliability of a study is important (Creswell, 2009: 202-203). It was, therefore, decided to use a mixed methods study design, in which qualitative and quantitative data are collected in parallel, analysed separately, and then merged (Creswell, 2005). In this study, a questionnaire survey (n = 40) was used to test the project management knowledge theory, which specifies that a sufficient level of construction project management knowledge will have a positive effect on project completion by construction managers in the built environment. The interviews (n = 10) and single case study explored the impact and the importance of industry-specific knowledge for construction project managers in the built environment. The reason for collecting both quantitative and qualitative data is to elaborate on specific findings from the questionnaire survey (quantitative data), such as similar opinions regarding the importance of NQF levels of knowledge as well as the importance of industry-specific knowledge suggested by the interview and case study (qualitative data) respondents’ groups (Creswell, 2005; Creswell & Plano-Clark, 2007).


A combined list of 87 built environment professionals was obtained from the personal business contact list of the researcher as well as from colleagues regarded by the researcher as professionals in the built industry. The list was stratified between those professionals involved in quantity surveying (17), project management (33),


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engineering (18), building contracting (8), architects (4), valuers (1), and built environment academics (6), which represent the sample size of the questionnaire survey.

For the interview survey, using the original business contact list, the researcher selected 10 experienced senior project management professionals who work/worked for over 10 years on large buildings projects (R100 million and more) within the built environment in South Africa. These professionals have qualifications on an NQF level 6.

According to the SACPCMP’s (2016: 24) annual report, there are approximately 1,585 professional construction project managers registered in South Africa. Using the sample size table recommended by Krejcie & Morgan (1970: 608), where a sample of 278 for a population of 1,000 is recommended, the sample sizes appear to be small, but the validity of the information supplied was inherent in their wealth of experience on the subject matter and the number of years they have spent in the construction industry.

A single case study of a building project to the value of R35 million was selected for the study. The reason for selecting the case study was the failure of the project, due to the limited previous built environment industry knowledge shown by the project manager who worked on the project. The project manager appointed on the project was registered as project manager and worked as a consultant for an engineering firm. He has a BCom qualification without any qualifications in the built environment. He has a few years’ work experience.

3.2 Data collection

Leedy & Ormrod’s (2010: 194) list of guidelines for compiling question-naires was followed. A structured questionnaire was distributed electronically via email to a total randomly selected sample of 87 construction-related professionals in South Africa. Responses were returned within a two-month period. The project management knowledge topics used in the questionnaire were extracted from reviews of the literature. Some questions were based on the PMBOK knowledge areas, while others were based on the technical knowledge areas for project managers in the built environment introduced by the SACPCMP. This resulted in the formulation of a questionnaire divided into two sections, namely respondent’s profile, and questions to determine whether the respondents think that it is important for a project manager to have industry-specific knowledge and to discover what form of knowledge they regard as essential for a project manager. Elements from the following main areas were


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tested: Experience in the built environment, project management knowledge, technical knowledge, and qualifications. To reduce the respondent’s bias, closed ended questions were preferred (Akintoye & Main, 2007: 601).

After the location city and addresses of the organisations were determined, interviews were planned, a date was set to meet, and the individual interviews were conducted with 10 professionals from built environment organisations in South Africa. Interviewees were asked to give their views on the importance of industry-specific knowledge of a construction project manager and to review the form of knowledge considered essential. Topics discussed included important knowledge types, industry-related knowledge required, and required qualification. Feedback from the qualitative research afforded an opportunity for respondents to elaborate on opinions, including experiences. All these discussions were recorded and used as the interview data. The interviews were conducted within two weeks.

For the case study, the quantity surveyor working on the project was questioned on his assessment of problems faced on the project. The quantity surveyor reported on specific incidences where the project manager’s lack of industry-specific knowledge as well as project-management knowledge affected the project. All the discussions and emails exchanged were noted. It was also determined that the data would be interpreted using specific categories including industry-related knowledge and project-management knowledge. This cross-sectional study was carried out only once (Schoonraad, 2003: 139).

3.3 Response rate

Forty completed questionnaires were returned, resulting in a response rate of 45%. According to Moyo & Crafford (2010: 68), contemporary built environment survey response rates range between 7% and 40%, in general. All of the ten interviewees invited to participate in the study took part in the interview discussions.

3.4 Data analysis and interpretation of findings towards the proposed model

For the questionnaire survey, a 5-point Likert scale was used to obtain the opinions of the respondents and to analyse the results. Likert scales need a minimum of two categories and a maximum of eight or nine (Neuman, 1997: 159; Leedy & Ormrod, 2010: 189). For the purpose of analysis and interpretation, the scale measurement between 1 and 5 was used. Likert-type or frequency scales are designed to


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measure attitudes or opinions. In this research, these ordinal scales measure levels of not important/very important. The scales were 1 = ‘not important’, 2 = ‘fairly important’, 3 = ‘important’, 4 = ‘very important’, and 5 = ‘critically important’. The data were captured using the SPSS program, upon which the findings were reviewed against the foregoing literature review. This was used in order to make deductions and increase the understanding of the required knowledge for project management in the built environment. In the quantitative research, the raw data was coded prior to starting the analysis. The codes were then entered into a statistical computer program SPSS and usable statistics were compiled.

All discussions during the interviews were recorded and used as the interview data. Using Microsoft Excel 2003®, the raw data was analysed and organised into conceptual themes under the categories important knowledge types, industry-related knowledge required, and required qualification for construction project managers. These categories were tabulated.

Using qualitative analysis, the research case study was discussed and the data organised into specific categories. The category industry-related knowledge was coded: Knowledge of construction science; Knowledge of financial cost factors; Knowledge of design processes, and Knowledge of construction processes. The category project management knowledge was coded: Integration, Scope, Trust, Communication, Time, and Cost. These categories and codes were tabulated.

3.5 Limitations

This study is limited to construction project managers within South Africa. In terms of the guidelines stipulating type of knowledge that project managers should have, this study focused on the nine PMBOK knowledge areas from the PMI PMBOK guide 4th edition 2008 and did not include the 5th edition, as the study was conducted prior to the release of the 5th edition. Therefore, the study was limited to the nine PMBOK knowledge areas and did not include stakeholder management as the tenth area.

4. ResultsThe findings from the analysis and interpretation of the data collected for this study are shown in Tables 2 to 13. Tables 2 and 3 – the respondents’ profile; Tables 4 and 5 – the type of knowledge needed for project managers; Table 6 – the importance of having


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project management knowledge (theory); Table 7 – the case study results of why the project failed, due to lack of project management knowledge; Table 8 – the importance of having technical (industry) management knowledge in the built environment; Table 9 – the interview and case study responses on the industry-related knowledge required for construction project managers; Tables 10 and 11 – the importance of gaining knowledge through experience, and Tables 12 and 13 – the level of knowledge (qualifications) required for project managers in the built environment.

4.1 Respondents’ profile

The first part of the interview survey and questionnaire survey contained questions on the demographic profile of the respondents who are in the best position to comment on the knowledge set that project managers should possess. Table 2 shows the professions of the respondents and Table 3 shows the years of experience in a profession as well as the respondent’s NQF qualification level.

Table 2: Professions of respondents

Profession of respondents

Questionnaire: Number of

respondents in the correlating

profession in column 1

%

Interview: Number of

respondents in the correlating

profession in column 1

%

Quantity surveying 3 7.5 2 20

Project management 21 52.5 3 30

Engineering 10 25 3 30

Building contracting 3 7.5 2 20

Architects 1 2.5 0 0

Valuers 1 2.5 0 0

Built environment academics 1 2.5 0 0

Total 40 10

Table 3: Respondents’ NQF qualification level and years of expe-rience in profession

ProfessionYears of

experience in profession Total

NQF qualification level of respondents in the profession

TotalQuestionnaire respondents 5-10 10-20 20+ 4 5 6 7 8 9 10

Quantity surveying 1 0 2 3 0 0 0 0 0 2 1 3


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ProfessionYears of

experience in profession Total

NQF qualification level of respondents in the profession

TotalQuestionnaire respondents 5-10 10-20 20+ 4 5 6 7 8 9 10

Project management 6 7 8 21 0 0 15 6 0 0 0 21

Engineering 2 4 4 10 0 0 0 10 0 0 0 10

Building contracting 1 2 0 3 1 0 2 0 0 0 0 3

Architects 0 1 0 1 0 0 0 1 0 0 0 1

Valuers 0 0 1 1 0 0 1 0 0 0 0 1

Built environment academics

0 0 1 1 0 0 0 0 0 0 1 1

Total%

1025

1435

1640

401

2.50

1845

1742.5

025

12.5

40

Interview survey

respondents5-10 10-20 20+ Total 4 5 6 7 8 9 10 Total

Quantity surveying 0 1 1 2 0 0 0 0 2 0 0 2

Project management 0 2 1 3 0 0 0 0 3 0 0 3

Engineering 0 1 2 3 0 0 0 0 3 0 0 3

Building contracting 0 2 0 2 0 0 0 0 3 0 0 2

Total%

06

604

4010 0 0 0 0

10100

0 0 10

Indicating first the questionnaire results and then the interview results, the majority of the responses (52.5%; 30%) and (25%; 30%) were received from project managers and engineers. The results show that (35%; 50%) of the professionals have over 10 years’ experience in their professions, of whom 40% from both respondents’ groups have 20 years or more experience. The interview survey respondents all had NQF level 8 qualifications and the questionnaire respondents’ NQF level of qualifications varied: 2.5% had NQF level 4; 45%, NQF level 6; 42%, NQF level 7; 5%, NQF 9, and 2.5%, NQF 10.

4.2 Type of knowledge needed

Based on the scale measurement used regarding mean scores, where 1 = ‘not important’, 2 = ‘fairly important’, 3 = ‘important’, 4 = ‘very important’, and 5 = ‘critically important’, the results in Table 4 show the mean scores for the importance levels of the


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type of knowledge which a construction project manager should have, as perceived by the respondents who participated in the questionnaire survey. Table 5 shows the tabulated responses from the interview survey.

Table 4: Questionnaire responses: Importance of knowledge types

Knowledge area

Questionnaire responses

1 = Not important 5 = Critically important

Average rating

1 2 3 4 5 Total

Work experience

Number of respondents 1 5 15 14 5 40

4.35Percentage of total 2.5 12.5 37.5 35 12.5 100

Project management knowledge


3.85Percentage of total 2.5 12.5 37.5 35 12.5 100

Technical knowledge


3.83Percentage of total 5 5 20 42.5 27.5 100

Table 5: Interview responses: Important knowledge types

Important knowledge

Industry-specific knowledge is essential.Knowledge of project management, the built environment and knowledge gained though experience are essential.Need project management knowledge plus industry-specific knowledge.Need to have knowledge and experience within the built environment.

The results in Table 4 show that Knowledge through work experience (Ms = 4.35) was rated very important; Project management knowledge (Ms = 3.85) and Technical (industry) knowledge (Ms = 3.83) were rated important. Tabulated responses in Table 5 show that all ten interviewees indicated that a construction project manager needs technical (industry) knowledge, project management (theory) knowledge, and experience.

4.2.1 Project management knowledge

The generic project management knowledge areas listed in the PMI as well as the additional extension to the Construction PMBOK areas were tested. Table 6 shows the weighted mean score averages for


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the 13 areas ranked according to the importance, as perceived by the respondents who participated in the questionnaire survey.

Table 6: Questionnaire responses: Importance of project manage-ment knowledge

PMBOKProject management knowledge

Response (N = 40)Average

mean score

Rank1 = not important ...... 5 = critically important

1 2 3 4 5

Project time management 0 0 7 22 11 4.10 1

Project cost management 0 0 11 16 13 4.05 2

Claims management (construction extension) 0 0 11 17 12 4.03 3

Project risk management 0 2 9 15 14 4.02 4

Project scope management 0 0 11 18 11 4.00 5

Financial management (construction extension) 2 0 9 17 12 3.93 6

Project human resources management 1 2 11 14 13 3.87 7

Project quality management 0 0 10 17 11 3.83 8

Project integration management 0 1 11 17 10 3.82 9

Project communication management 1 2 12 15 10 3.79 10

Occupational health and safety (construction extension) 1 3 12 15 9 3.70 11

Project procurement management 1 6 10 16 7 3.55 12

Environmental management (construction extension) 3 4 14 12 7 3.40 13

Total average 3.85

Areas that were rated very important, with mean scores of 4 and above, will be included in the proposed model. These areas are: Project time management (4.10); project cost management (4.05); project claims management (4.03); project risk management (4.02), and project scope management (4.00).

Areas that were rated as important will be included in the proposed model. These areas are: Project financial management (3.93); project human resources management (3.87); project quality management (3.83); project integration knowledge (3.82); project communication management (3.79); project occupation health


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and safety (3.70); project procurement management (3.55), and project environmental management (3.40).

With an Ms of 3.85, respondents view it important that project managers should have project management knowledge (theory). To gain theoretical project management knowledge, integrated knowledge and specialisation of the field is needed. A qualification on NQF level 7 (first degree such as a BSc) allows for integrated knowledge and specialisation of a field, discipline or practice.

Table 7 shows the tabulated responses from the case study of why the project failed, due to lack of project management knowledge.

Table 7: Case study results: Project management knowledgeProject

management knowledge

Reasons why the project failed

Integration

The project manager lacked integrated knowledgeThere was inefficient management of the projectFor example, the waterline had to be moved, and would amount to R500,000. The project manager did not understand the implications and actions involved in moving the line as the project manager did not have knowledge about costing and construction processes

Scope

The project manager could not check the project work of the consultants, as the project manager did not have the technical knowledge of the work required to do construction-related tasks, and he could, therefore, not determine whether it was complete or notThe project manager did not know this, due to the fact that he did not have knowledge of the scope of work

Trust

Lack of knowledge and inability to answer the client’s questions led to mistrust in the project managerHe did not instil trust among project team members, so they did not trust his expertise as project manager

Communication

Lack of knowledge led to miscommunication during the projectHe did not understand what the team members were saying and the implications of what they were sayingHe did not know what questions to ask and, therefore, asked the wrong questions

Time There were time delays, due to miscommunicationDue to his inadequate knowledge, he had to enquire about a lot of information that should have been part of his knowledge base

Cost

Time delays, as the result of insufficient knowledge, contributed to project cost increaseThe project manager did not understand the industry standard quantity surveying costing, as the project manager did not have knowledge about costingHe could not justify the cost and the reason for the cost


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The quantity surveyor who worked on the project is convinced that a large contributing factor in the eventual termination of the project was the project manager’s lack of project management knowledge.

4.2.2 Technical (industry) knowledge

Technical knowledge areas, as listed by the SACPCMP, were tested in terms of their importance in the built environment. Table 8 shows the mean scores for the importance levels of project manager technical (industry) management knowledge, as perceived by the respondents from the questionnaire survey.

Table 8: Questionnaire responses: Importance of technical (industry) management knowledge in the built environment

SACPCMP technical knowledge areas

Response (N = 40)

Average mean score Rank1 = not important .......

5 = critically important

1 2 3 4 5

Knowledge of financial cost factors 0 0 4 19 17 3.94 1

Knowledge of design processes 0 0 10 17 11 3.83 2

Knowledge of construction processes 0 2 11 17 9 3.80 3

Knowledge of construction science 0 4 12 16 8 3.72 4

Average 3.83

Rated as important, the following technical knowledge areas were identified as knowledge areas to be included in the proposed model: Knowledge of financial cost factors (Ms = 3.94); Knowledge of design processes (Ms = 3.83); Knowledge of construction processes (Ms = 3.80), and Knowledge of construction science (Ms = 3.72). With a weighted average of 3.83, supported by the results from the interviews and case study tabulated in Table 9, the findings show that having technical (industry) knowledge is important.


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Table 9: Interview and case study responses: Industry-related knowledge required

Industry-related knowledge required Interview responses Case study results: why the

project failed

Knowledge of construction science

Industry knowledge is most importantShould know the essentials of the industryNeeds to understand the processes relevant in the industry to understand what is going to be developed and builtNeeds project management knowledge plus industry-specific knowledge

Lacked knowledge in the fields of construction science and construction processesFor example, the project manager did not know what bending schedules were. His lack of industry-specific knowledge caused frustration among project team members and negatively affected the project

Knowledge of construction processes

Needs above average knowledge about the industry and an understanding of how various elements fit togetherHas to know and understand the process and systemsNeeds a different level of required knowledgeExperience is one of the essential knowledge components

The project manager did not understand the construction processes that had to take place. For example, the waterline had to be moved to a lower level. The project manager did not understand why it should be lower

Knowledge of design processes

Has to understand the processes involved in the industryHas to be familiar with the steps and processesHas to have knowledge of the roles and responsibilities of the parties involved in a building project

The project manager did not understand what the team members were saying and the implications of what they were saying. For example, the 300 trees that were to be planted on site cost substantially more than expected and took longer. The project manager did not know that the costs and time involved were more than merely the purchase price per tree and the planting thereof

Knowledge of financial cost factors

Has to understand the processes involved in cost and finances

The project manager did not have knowledge about costing. For example, the waterline had to be moved; this would amount to R500,000. The project manager did not understand why it costs so much


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The case study indicated that the project manager lacked knowledge. The consultants working on the project agreed that the project manager lacked knowledge in the fields of construction science, construction processes, design processes, and finance. Therefore, the project failed to be completed.

4.2.3 Knowledge through experience

Respondents rated the importance of gaining project management knowledge through working within the built environment. With a weighted average of 4.35, the questionnaire findings in Table 10 show that the respondents view experience in the built environment as a crucial knowledge element for a project manager.

Table 10: Questionnaire responses: Importance of experience in the built environment

Responses1 = Not important 5 = Critically important

1 2 3 4 5 Total


Percentage of total 0 2.5 2.5 52.5 42.5 100

Average rating 4.35

Of the 40 respondents, 38 rated the importance of experience as either 4 or 5, with 52.5% regarding it as very important, and 42.5% as critically important. A total of 95% indicated experience as being either very important or critically important. Table 11 shows the coded interview responses supporting this finding.

Table 11: Interview responses: Knowledge through experience

Important knowledge types

Generic project management qualification without industry-specific knowledge will not sufficeNeeds project management knowledge plus industry-specific knowledgeNeeds to have knowledge and experience in the built environment

4.3 Level of knowledge (qualification)

To determine what the minimum level of qualification for construction project managers should be, respondents rated the NQF level of qualifications they deemed important on a 5-point Likert scale. Table 12 shows the Ms and rank of the NQF level of qualification


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which respondents from the questionnaire survey deemed important for a project manager in the built environment.

Table 12: Questionnaire responses: NQF knowledge level required for a built environment project manager

NQF level (N)

Response and (%)Average

mean score

Rank1 = not important ...... 5 = critically important

1 2 3 4 5

532 24 8 0 0 0

1.25 5% 100 0 0 0 0

632 5 4 10 4 9

3.25 2% 15.6 12.5 31.3 12.5 28.1

736 2 2 4 16 12

3.94 1% 5.6 5.6 11.1 44.4 33.3

835 7 3 16 7 2

2.83 3% 20 8.6 45.7 20 5.7

936 14 12 5 3 2

2.08 4% 38.9 33.3 13.9 8.3 5.6

With a mean score of 1.25, no respondents viewed a qualification on NQF level 5 as important for project managers. NQF level 6, with a mean score of 3.25 was viewed as an important level of qualification which project managers in the built environment should have. With an MS of 3.94, NQF level 7 is rated the most important level of qualification which a project manager in the built environment should have. Only 11.2% stated that it is not important (5.6%), or only fairly important (5.6%), compared to 77.7% who stated that an NQF level 7 is very important (44.4%) and critically important (33.3%). The results show an MS below average for NQF level 8 (2.83) and NQF level 9 (2.08), indicating that respondents overall did not view these levels of qualification as important.

Table 13 shows the coded interview responses of the NQF level required for project managers.

Table 13: Interview responses: NQF knowledge level required qualification for project managers

Required qualification

Generic project management qualification (NQF level 6) without industry-specific knowledge will not sufficeNeeds NQF level 7 qualification in the built environment, such as a degree in engineering, quantity surveying, or architecture


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The majority of the respondents indicated an NQF level 7 qualification as adequate for project management knowledge (theory). Rated as important, and very important, NQF level 6 and NQF level 7, respectively, will be included in the proposed model.

In Table 1, SAQA describes NQF level 6 as ‘detailed knowledge of the main areas of one or more fields, disciplines or practices, including an understanding of, and an ability to apply the key terms, concepts, facts, principles, rules, and theories of that field, discipline or practice’. Rated as important in Table 12, this study suggests that a project manager in the built environment should have technical industry-specific knowledge equivalent to NQF level 6. This implies that s/he needs to have detailed knowledge and understanding of areas such as construction science, design processes, finance and cost, and construction processes, which will be included in the proposed model.

Rated as important in Table 6, with an MS of 3.85, project managers need project management knowledge (theory). This type of knowledge should be on a higher level than technical knowledge, because project managers need to be specialists in their primary field of work, namely project management. The level of project management knowledge needs to be detailed knowledge of that area of specialisation. This implies that construction project managers need to have specialised knowledge and understanding of the 13 project management areas introduced in this study. Rated as very important in Table 12, this study suggests that, for a project manager to gain this specialised level of knowledge, qualifications equivalent to NQF level 7 (First degree such as a BSc), as detailed in Table 1, are suggested and will be included in the proposed model.

5. Proposed model for construction project management knowledge

With the literature and empirical reviews as foundation, a model is proposed that is viewed as an integrated system with effective construction project management knowledge as fundamental core, since the research demonstrated that efficient knowledge through work experience, qualified project management knowledge (theory), and technical (industry) knowledge support effective construction project management.


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5.1 Construction project management knowledge model

Figure 1 illustrates the model for construction project management knowledge. The model is viewed as an expanding circle with technical (industry) knowledge centre to project management knowledge (theory) and work experience. Knowledge influences all activities related to project management. The efficiency of knowledge is again influenced by the level of knowledge (qualification), indicated in Figure 1 as NQF level 6 and NQF level 7. The model consists of effective construction project management knowledge as the foundation with three circles around this core. The first circle constitutes NQF level 6 knowledge (technical knowledge); the second circle, knowledge through industry experience, and the third circle, NQF level 7 of knowledge (project management knowledge theory) that a construction project manager should have.

Figure 1: The construction project management knowledge model


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5.1.1 NQF level 6 knowledge (technical knowledge)

The first circle, NQF level 6, following the core foundation circle, is shown as a circle where construction science, finance and cost, construction processes, and design processes are overlapping to the second circle. This overlapping is sensible, as some of the technical knowledge in this circle is closely linked to the second circle (knowledge through industry experience). The circle shows industry knowledge closely linked to and overlapping to the core circle. An NQF level 6 qualification (Diploma) will assist construction project managers to have detailed technical knowledge, including an understanding of, and an ability to apply the key terms, concepts, facts, principles, rules, and theories of construction science, finance and cost, construction processes, and design processes within the built environment. A construction project manager cannot be without this technical industry knowledge. It is fundamental. However, the second circle, that is knowledge through experience, is also needed, in order to develop an in-depth understanding of the knowledge gained through the first circle.

When the technical knowledge is on at least a NQF level 6 qualification, industry knowledge can be strengthened and enhanced and will assist the construction project manager to have a better overall knowledge set of construction science, finance and cost, construction processes, and design processes.

5.1.2 Knowledge through industry experience

The second circle, Experience, shows the work experience within the industry. The arrows flowing from the second circle over the first circle to the core, illustrate the importance of gaining knowledge through experience to ensure effective construction project management. Experience in industry is essential to contribute to effective project management. However, experience on its own, without the first and third circles, will not sufficiently contribute to effective project management. This set of knowledge supports and strengthens technical knowledge in the second circle and effective construction project management knowledge in the core circle.

5.1.3 NQF level 7 (project management knowledge theory)

The third circle, NQF level 7, shows the level of qualification for project management knowledge areas in a sequence supported by the literature reviewed, but in combinations; this is sensible, as some of the project management knowledge areas are sequential and closely linked. The nine generic project management areas within


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the circle are indicated in blue: Integration management, scope management, time management, cost management, quality management, human resources management, communication management, risk management, and procurement management. The four construction-specific project management areas indicated in green are: Safety management, environmental management, claims management, and financial management.

The third level incorporates the nine project management areas that are necessary for any project to be managed, as well as the four construction-specific areas. All these areas are important and influence each other. If communication management does not take place, all the areas are affected. There may be an increased risk, the project may have scope creep, be of a lower quality, at a higher cost with little integration between all the areas. If time, cost or quality are influenced, this may have an effect on each other. A project that is not completed within time may undergo a cost and quality adjustment.

However, the third circle does not stand alone. The 13 areas in circle three are affected by circles one and two. Lacking industry knowledge and experience may quite likely impact on project management elements in circle one. The aim of a project is to complete it on time, within cost and according to an expected quality. Without the combined knowledge of all three, the achievement of effective project management may be affected.

A qualification on NQF level 7 (First degree such as a BSc) will assist the project manager to have integrated knowledge of the main areas of project management, including an understanding of, and an ability to apply and evaluate the key terms, concepts, facts, principles, rules, and theories of project management. It should also assist project managers to gain specialised knowledge on project management theory so that they can have an understanding of how project management relates to other fields, disciplines or practices such as engineering, and so on.

When project management knowledge theory is on at least a NQF level 7 qualification, project management knowledge can be strengthened and enhanced and will assist the construction project manager to have better knowledge of project management knowledge theory. The arrows flowing from the third circle over the second and first circles to the core illustrate the importance of having a qualification on NQF level 7 for project management knowledge, in order to ensure effective construction project management. This set of knowledge supports and strengthens work experience within


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the industry in the third circle; technical knowledge in the second circle, and effective construction project management knowledge in the core circle.

It is proposed that, if all areas of construction project management knowledge, from project management knowledge theory to technical knowledge and work experience are in position to ensure the gaining of efficient knowledge, the result will be a project manager that possesses efficient knowledge to execute effective construction project management.

6. Conclusion and recommendationAppropriate literature elicited a range of structured questions that were used to obtain quantitative and qualitative data from the survey and interview participants. Analysis of the data with literature and the results from the surveys determined the elements of a proposed model and showed that the knowledge expected from project managers can be grouped into technical knowledge (construction science, finance and cost, construction processes, and design processes within the built environment), and knowledge through industry experience and project management knowledge theory (the nine generic project management areas include integration management, scope management, time management, cost management, quality management, human resources manage-ment, communication management, risk management, and procurement management; the four construction-specific project management areas include safety management, environmental management, claims management, and financial management).

The research results show that knowledge is fundamental to the development of effective construction project management, in order to produce successful projects. The model includes two NQF levels of qualification knowledge sets, which, used in combination with knowledge gain through industry experience, are proposed to assist construction project managers in developing their knowledge sets, and through improved levels of knowledge, ensuring the successful execution of projects.

Implementation and use of the proposed model relies on the willingness of construction project managers relative to understanding the importance of such a model. It is, therefore, recommended that the interrelated knowledge sets included in the model are of utmost importance. These include ‘engaging people’, which will encourage construction project managers to take ownership in an


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attempt to introduce and implement this proposed construction project management knowledge model in their firms.

This research does not consider the model as a complete means to an end. Further research is needed, in order to develop an instrument to measure the level of an individual’s or group’s knowledge levels to improve their construction project management knowledge sets.

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Assessment of housing quality in Ibeju-Lekki peri-urban settlement, Lagos State, Nigeria



AbstractThis article assesses housing quality in Ibeju-Lekki, a peripheral settlement outside Lagos metropolitan region. Using purposive sampling, 370 housing units from clusters of 16 peri-urban settlements constituted the sample size. Primary data was sourced through structured questionnaires, interview (with local planning personnel) and observation schedules adminis-tered through a field survey. Using Statistical Package for Social Sciences, data analysis was done using descriptive analysis to generate frequen cies and percentages on socio-economic profile, neighbourhood quality, locational quality, dwelling quality, and building materials used. Tests of correlation were conducted on the mean of variables of neighbourhood quality, locational quality and building materials, derived through recoding of variables by means of Transform statistical tool, to establish the factors influencing housing quality in the study area. The findings show a significant positive correlation between household income and housing quality. The latter is found to be influenced by respondents’ socio-economic attributes, building materials, neighbourhood quality, and locational quality in the study area. It can be concluded that socio-economic characteristics, predominantly income of households, play a major role in the level of housing quality that can be accessed in the study area. It is, therefore, recommended that the state government and private developers should promote alternative building materials, in order to enhance housing affordability by the low-income group. This will reduce the spread of informal housing development. In addition, the state govern ment should align urban policy to eliminate disparity in

Funmilayo Adedire

Dr Funmilayo M. Adedire (Corresponding author), Department of Architecture, Lead City University, Ibadan, Oyo State, Nigeria. Phone: 234-8080997437, email: <[email protected]>

Michael Adegbile

Dr Michael B.O. Adegbile, Department of Architecture, University of Lagos, Nigeria. Phone: 234-8023892406, email: <[email protected]>







Adedire & Adegbile • Assessment of housing quality

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infrastructural development which has impacted on poor neighbourhood and locational quality in Lagos peri-urban settlements. Keywords: Dwelling quality, housing quality, locational quality, neighbourhood quality, peri-urban settlements

AbstrakHierdie artikel evalueer behuisingsgehalte in Ibeju-Lekki, ’n perifere nedersetting buite die Lagos Metropolitaanse streek. Met behulp van doelgerigte steek-proefneming, is 370 behuisingseenhede uit groepe van 16 stedelike neder settings gekies om die steekproefgrootte te verteenwoordig. Primêre data is verkry deur gestruktureerde vraelyste, onderhoud (met plaaslike beplanning personeel) en waarnemingsskedules opgestel tydens veldwerk. Met behulp van die Statistiese Pakket vir Sosiale Wetenskappe SSPS 22 is data-analise gedoen met behulp van beskrywende analise om frekwensies en persentasies op sosio-ekonomiese profiel, buurtkwaliteit, liggingskwaliteit, woonkwaliteit en boumateriaal te genereer. Korrelasietoetse is gedoen op die gemiddeldes van veranderlikes van buurtkwaliteit, lokasiekwaliteit en boumateriaal, afgelei deur herkodering van hierdie veranderlikes deur die Transform statistiese instrument, om die faktore wat behuisingskwaliteit in die studiegebied beïnvloed, vas te stel. Die resultate toon ’n beduidende positiewe verband tussen huishoudelike inkomste en behuisingskwaliteit. Behuisingskwaliteit word ook beïnvloed deur die respondente se sosio-ekonomiese eienskappe, boumateriaal, buurtkwaliteit en liggingskwaliteit in die studiegebied. Daar kan afgelei word dat sosio-ekonomiese eienskappe, hoofsaaklik inkomste van huishoudings, ’n belangrike rol speel in die vlak van behuisingskwaliteit wat in die studiegebied verkry kan word. Daar word dus aanbeveel dat die staatsregering en private ontwikkelaars alternatiewe boumateriaal bevorder om die behuisings-bekostigbaarheid van die lae inkomstegroep te verbeter. Dit sal die verspreiding van informele behuisingsontwikkeling verminder. Ook moet die staatsregering die stedelike beleid in ooreenstemming bring om ongelykheid in infrastruktuurontwikkeling uit te skakel wat die swak omgewing en liggingskwaliteit in Lagos peri-stedelike nedersettings beïnvloed het.Sleutelwoorde: Behuisingskwaliteit, buurtkwaliteit, liggingskwaliteit, wonings-kwaliteit, peri-stedelike nedersettings

1. IntroductionThe interaction of different internal and external factors plays a role in the measurement of housing quality in peri-urban settlements (Allen, 2010; Chirisa, 2010). The geographical and ethnographic composition of the residents plays an important role in shaping housing quality in peri-urban settlements (Rapoport, 1998). Other factors such as neighbourhood quality, locational quality and regional response to patterns of development show that housing quality as a function is not limited to physical components of construction, but rather entails human satisfaction with urban attributes and facilities, environmental quality and locational advantages (El Din, Shalaby, Farouh & Elariane, 2013; Rapoport, 1998).

In African cities, in general, state or regional governments are respon-sible for the planning and infrastructure of peri-urban settlements


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located outside the city (Allen, 2010). The governance of peri-urban settlements in Lagos is shared between local land owners and the state government, but less attention is paid to the infrastructure development of settlements outside state government’s acquired land (Adedire & Adebamowo, 2018). Environmental quality, which has to do with good sanitation, security, parking space, light and drainage, and locational quality of housing, which is the spatial position relative to the central business district, are all external factors that create a gap in services delivery, giving room to infiltration of informal development and infrastructure inadequacy in peripheral towns (Chirisa, 2010; Allen, 2003).

Dwelling quality is internally controlled by the socio-economic and socio-cultural characteristics of the residents in peri-urban settlements; these determine the level of quality of housing they can access through their choice of building construction materials and methods of construction (Fiadzo, Houston & Godwin, 2001). In the majority of peri-urban settlements, there exists social differentiation and service inequality among the indigenous residents and the immigrants (Simon, 2008; Ibem & Aduwo, 2015).

The saturation of the built-up area in metropolitan Lagos has gradually led to the conversion of agricultural land in the peri-urban settlements in Lagos for residential purposes to accommodate the multicultural and heterogeneous urban population (Nwokoro & Dekolo, 2012). The influx of low-income urban immigrants into Lagos peri-urban settlements is significantly impacting on housing quality. Lower income groups inhabit poor residential areas in peri-urban settlements associated with poor physical conditions, illegal development, limited or no access to water, and poor sanitation (Daramola & Ibem, 2010; Lawanson, Yadua & Salako, 2012). The assessment of housing quality in Lagos peri-urban settlements is significant to determine to what extent neighbourhood quality, location quality and the use of building materials contribute to the level of housing quality in these settlements. The findings might assist the state government to support the use of alternative building materials in the development of better quality housing for residents in these peri-urban areas.

2. Literature reviewThe differentiation of housing quality occurs on the basis of several dimensions: the structural or dwelling quality, neighbourhood quality, and locational quality (Bates, 2006: 25; Kain & Quigley, 1970). Each of these factors is influenced by elements such as, for example, income, family size, education and race of residents in settlements that control them (Goodman, 1978).


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2.1 Structural or dwelling quality

Housing type, design, age of the building, aesthetics, lot size, window sizes, spatial arrangements, the number of rooms per household, tiled toilet, tiled bath, tiled kitchen, lights and water contribute to the measurement of dwelling quality (Aderamo & Ayobolu, 2010; Štreimikiene, 2014: 27; Amao, 2012). The methods of construction, building materials used and aesthetics are also indices for measuring dwelling quality (Bradley & Putnick, 2012).

2.2 Neighbourhood quality

Neighbourhood quality is defined by the effects that neighbourhood characteristics have on a residence as a result of the environment in which it is located (Clark & Huang, 2003). Characteristics such as neighbourhood deterioration, adequacy of services, safety and accessibility, and the overall assessment of the neighbourhood refer to the natural attributes of the neighbourhood (El Din et al., 2013). The dynamic relationship that exists between the physical features of housing, streets, open spaces and general settings in the neighbourhood determines neighbourhood quality (Rapoport, 1998; El Din et al., 2013) that is very poor in most of Lagos’ peri-urban settlements.

The quality of the neighbourhood, particularly in terms of socio-economic attributes, has also been found to be an important determinant for housing quality (South & Crowder, 1997: 1040). Residents’ socio-economic capacity influences the quality of housing they can enjoy (Boamah, 2015). Residential areas for low-income earners in metropolitan peripheral areas are generally known to have limited or no access to services, poor sanitation and are mostly informal developed settlements (Allen, 2010). In these poverty areas, wastes are indiscriminately disposed of into canals and drainage channels; toilet facilities are open defecation, unimproved, or shared improved toilets that include flush toilets, flush latrines, and ventilated improved pit (VIP) (Allen, 2003; Puttal & Ravadi, 2014). Depending on the income status of houses in the majority of peri-urban settlements, access to drinking water could be unimproved, improved and piped (Allen, 2003). Building materials in these poor areas include wood, reeds, grass for construction and roofing (Simon, 2008).

Neighbourhoods occupied by middle-income earners have better dwelling quality and are usually segregated from the indigenous residents and the immigrants (Simon, 2008; Ibem & Aduwo 2015). Predominantly in African peri-urban settlements, community participation is a means for securing improved neighbourhood quality (Lawanson et al., 2012; Binns, Maconachie & Tanko, 2003). This


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is encouraged in externally initiated projects such as government-led infrastructure development, developer-initiated or in projects initiated by an association of community residents (Obeng & Whittal, 2014; Binns et al., 2003).

2.3 Locational quality

The key measurement for locational quality involves residents’ mobility and living convenience, including features such as access to place of work, accessibility to central business district, access to public services, closeness to the market, and availability of schools, hospitals and shopping places (Adebayo & Aliu, 2010). In African peri-urban settlements, commuting and daily travels are often slow, due to traffic congestion and the poor conditions of the access roads to and from the main arterial routes linking peri-urban settlements to amenities (Lawanson et al., 2012; Acheampong & Anokye, 2013).

Housing quality in peri-urban settlements in Lagos suffer from neglect, due to the locational disadvantage of these settlements and the perception that it has no economic contribution to state development (Adedire, 2017). As a result, these settlements, in consonance with prior findings, suffer from poor sanitary conditions, increasing commuting time, traffic congestion, pollution, poor water supply and sanitation problems, solid waste disposal, and lack of open space (Dutta, 2012; Simon, 2008). In addition, housing quality in peri-urban settlements in Lagos is negatively affected by these poor environmental conditions, as they affect not only the sustainability of these places, but also people’s health. The spread of epidemic diseases is common where environmental quality is poor (Boamah, 2015).

2.4 Ibeju-Lekki local government area

Ibeju-Lekki Local Government Area is located outside the metro-politan region of Lagos State in Nigeria. Ibeju-Lekki represents one of the rapidly urbanising peri-urban settlements in Lagos in terms of residential development and population growth (Obiefuna, Nwilo, Atagbaza & Okolie, 2013). Ibeju-Lekki serves the housing needs of migrants from Lagos Island and its environs. It is approximately 75 kilometres long and roughly 20 kilometres wide, with a land area of approximately 646 kilometres square, which equals one quarter of the total land mass of Lagos state (Aluko, 2010). It is situated at approximately latitude 40 15’ north latitude 40 17’ north and longitude 13015’ east and 13020’ east. According to the National Population Commission (2006) census, Ibeju-Lekki had a population of 117,481 out of Lagos State’s total of 9,113,605.


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Figure 1: Map of Lagos State showing Ibeju-Lekki peri-urban settlementsSource: Adapted from the Report on the Review of the Lagos State Regional Plan

(2002), LASG Ministry of Physical Planning & Urban Development


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3. Research methodologyThe purpose of this research was to assess housing quality in Ibeju-Lekki, a peripheral settlement outside Lagos metropolitan region. A quantitative research design was adopted, as this type of design allows for the use of structured questionnaire surveys that enable researchers to generalise their findings from a sample of a population (Creswell, 1994). Descriptive analysis was used to analyse the interview and field survey data on socio-economic profile, neighbourhood quality, locational quality, dwelling quality, and building materials used in the study area. This technique summarises data in an understandable way, by using frequencies and percentages (numerical) to reduce the number of responses to a mean score (Satake, 2016: 663). From these numerical data (mean scores), the variables to measure dwelling quality, neighbourhood quality and locational quality could be determined and set. Regression analysis was used to test these variables for correlation, by examining relationships among these quantitative variables (Rossoni, Engelbert & Bellegard, 2016: 200). Several regression analysis methods are available, but correlation analysis was used, because the coefficient and P-values could be extracted, which explains the strength of the relationship between a pair of variables (Bewick, Cheek & Ball, 2003: 452).


Statistics from the Lagos State Government Digest of Statistics (2016) shows that, in 2016, Ibeju-Lekki had a total of 11,749 housing units and a population of 179,187 (LSG, 2016: 27). For adequate representation of the target population, the sample size was taken from the population of the residents and the housing units. A two-stage cluster sampling technique was adopted, because the population could be subdivided into clusters, and random samples could be collected from each cluster (Alvi, 2016: 22). In the first stage, 16 peri-urban clusters were purposively selected from all LCDAs/wards in the peri-urban settlements of Ibeju-Lekki. In the second stage, purposive sampling was used to select units based on the uniqueness of each peri-urban settlement. The samples chosen represent housing initiatives in the clusters; that is, self-built housing, government housing, and private developer housing. From the cluster sample, random sampling was used to select 370 housing units to represent the population. With a margin error of 5% and a confidence level of 95%, the Krejcie & Morgan’s (1970: 608) sample size table recommends a sample size for a population of 10,000 as 370. This recommendation validates the sample size of 370 as efficient for the population of 11,749.


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3.2 Response rate

From the 370 original questionnaires, 366 completed ones were retrieved, resulting in a high response rate of 99%. According to Moyo & Crafford (2010: 68), contemporary built-environment survey response rates range from 7% to 40%, in general.

3.3 Data collection

A questionnaire survey was done on 370 selected household heads in Ibeju-Lekki housing settlement, using the spot collection method during non-working days and hours from 14 January to 25 March 2017. Topics on different housing development initiatives used in the survey were extracted from reviews of the literature, resulting in the formulation of a questionnaire divided into two sections. Section one, on respondents’ profile, obtained personal information on gender, occupation, literacy level, tribe, monthly income, household size, and tenure of the household head. Section two sets questions grouped by the various variables that define building materials used, dwelling quality, neighbourhood quality, locational quality and informality as determinants to establish which of these factors influence housing quality in the study area.


Version 22 of the Statistical Package for Social Science (SPSS) was used to process and analyse data (Pallant, 2013). For analysis of the socio-economic profile of household heads, as well as the rating of neighbourhood quality, locational quality, dwelling quality, informality and building materials used in the study area, the percentages and frequencies of responses were generated, but only the % frequencies of the variables were reported. To measure the existence of (P-value) and how strong (R-value) the relationships were between the set variables, the Pearson’s R test was used (Asuero, Sayago & González, 2006: 43). To do the correlation, the mean scores of variables tested in the survey were used to recode these variables with Transform statistical tool. The newly labelled variables regarded as the Mean Variable defining neighbourhood quality, locational quality, dwelling quality and building materials were correlated to show if there were any relationships between these variables. The correlation coefficient adopted R values between -1 and 1, where: 1 indicates a strong positive relationship; -1 indicates a strong negative relationship, and 0 indicates no relationship at all. The further away R is from 0, the stronger the relationship. To test if the correlations were significant, the significance value (P value) was set at 5% (p < .05) (Dahiru, 2008: 22).


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3.5 Limitation(s) of the study

It is important to note that the study was conducted only on the peri-urban settlements of Ibeju-Lekki; hence, the findings cannot be generalized for Lagos metropolitan region.

4. Findings and discussion

4.1 Socio-economic characteristics of the respondents

Analysis of the research questionnaires presented in Table 1 shows that male-headed households are higher than female-headed households in Ibeju-Lekki peri-urban settlements. Of the population, 36.6% is involved in informal trading and commercial enterprises, making it the predominant occupation in the study area. In addition to other unknown occupations, farming is the least engaged among all the occupations considered. Civil service, skilled work and professional practices are well represented, with 19.1%, 15.3%, and 16.7%, respectively. Only 9% of the respondents had primary school education and below, thus constituting the illiterates in the study area. The Yoruba ethnic group constitutes the largest portion (71.9%) of the population, while the Hausa tribe is the least represented in the study area. The predominant income group in the study area was the high-income group earning above N150,000 ($420) monthly. This income group constitutes 44.6% of the entire population. This runs contrary to the belief that the majority of peri-urban settlements is mainly dominated by the low- and the middle-income groups. In the low-income group, 36.3% earn N25,000 ($70)-N50,000 ($140) and live mostly in informal buildings and self-built housing. In the middle-income group, 19.1% earn N50,000 ($140)-N150,000 ($420) monthly and is the least represented in the study area. Household sizes of 3-5 persons are the commonest, with 55.2% of the respondents’ population. Household sizes of 10-12 persons are the least represented, with 2.2%. People have lived in the study area for over ten years, signifying the longest tenure as shown by 31.7% of the population.

Table 1: Socio-economic profile of the household head

VariablesIbeju-Lekki

N=366 %

Gender of household head

Male 223 60.9

Female 143 39.1


135


N=366 %

Occupation of household head

Civil service 70 19.1

Informal trading 134 36.6

Professional practice 61 16.7

Skilled work (artisan) 56 15.3

Farming 1 0.3

Others 44 11.9

Literacy level of household head

Postgraduate 56 15.3

First degree/Higher diploma 105 28.7

National diploma 62 16.9

Secondary 110 30.1

Primary/Below 33 9.0

Respondent’s tribe

Yoruba 263 71.9

Hausa 6 1.6

Ibo 70 19.1

Others 27 7.4

Monthly income of household head

Low income N25,000-N50,000 ($70-$140) 133 36.3

Middle income N50,001-N150,000 ($140-$420) 70 19.1

High income N150,001 and above ($420) 163 44.6

Household size

1-2 persons 48 13.1

3-5 persons 202 55.2

6-9 persons 96 26.2

10-12 persons 8 2.2

More than 13 persons 12 3.3

Tenure

Less than 5 years 114 31.1

5-10 years 116 31.7

More than 10 years 134 36.6

Others 2 0.5

Field survey (2017)* Salary grouping is culled from the Federal Republic of Nigeria’s Federal Civil Service Commissions


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4.2 Assessment of building materials

The observation schedule and the analysis of the structured ques-tionnaires presented in Table 2 show diverse building materials used in the study area. The commonest wall materials were mainly block wall (93.4%), but thatch wall was used in areas belonging to the local natives in the fishing occupation; this is interspersed with thatch (1.9%) and mud wall (3.55%). Aluminium roofing is predominantly used by 75.7% of the respondents. The major type of windows used were aluminium (68.7%). The following types of windows are also used, namely wooden windows (12.8%), louvre windows (10.1%), and casement windows (8.5%). Wooden doors and steel iron doors were the commonest in the peri-urban, with roughly 62.6% and 35.5%, respectively. Observation (Appendix 3) shows that most of the secondary roads in the peri-urban area were either graded earth or ungraded earth roads. This corroborates the findings of early researchers on peri-urban study (Chirisa, 2010; Lawanson et al., 2012; Acheampong & Anokye, 2013). The majority of the housing developments were constructed with conventional building materials such as cement sandcrete blocks, aluminium burglar-proof windows, mostly wooden panel internal doors, and steel external doors. There is a limited use of louvre and wooden windows in the study area. Aluminium roofing is the commonest in Ibeju-Lekki peripheral area. Thatch roof was sparingly used in Ibeju-Lekki by the natives in the fishing and coconut farming. Only some of the secondary roads in both locations are tarred. However, few buildings among self-help housing were built with traditional building materials such as mud block, thatch roofing sparingly in the peri-urban area. Both government-led housing and developer-led housing rely a great deal on the use of conventional building materials. The findings show no trace of alternative building materials for the mentioned housing initiatives in the peri-urban settlement.

Table 2: Building materials used in the study area


N=366 %

Wall

Block wall 342 93.4

Mud wall 13 3.55

Thatch/others 7 1.9


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N=366 %

Roof

Aluminium 277 75.7

Thatch 20 5.5

Concrete slab 23 6.3

Other 46 12.6

Window

Aluminium 251 68.6

Louvre 37 10.1

Wooden 47 12.8

Casement 31 8.5

Door

Steel/iron 130 35.5

Flush/panel/wooden 229 62.6

Glass 2 0.5

Others 5 1.4

Field survey (2017)

4.3 Dwelling quality

In the study area, the variables under consideration for dwelling quality include state of disrepair, lot size, state of painting, building design, good openings (window sizes), burglary installation, number of rooms per family, toilet type, windows per room (cross ventilation), tiled bathroom, tiled kitchen, source of water, and electricity supply.

4.3.1 Internal dwelling quality

The analysis presented in Table 3 shows good natural ventilation, as most of the buildings have cross ventilation aided by the appropriate window sizes. Of the buildings, 85.8% have burglary installation, and 13.9% do not; 52.7% of the buildings have 1-2 rooms, and 47% have 3-4 rooms per household; 71.0% of the respondents’ kitchens are tiled, and 29.0% are not tiled in sampled houses; 72.1% of the toilets are tiled, and 27.9% are not tiled. This also affects the level of sanitary quality in Ibeju-Lekki peri-urban settlement. The vast majority (roughly 74.3%) of the peri-urban residents rely on a borehole water system. Of the population, 25.7% are serviced by well and other sources of water. The quality of the water in the study area is poor, due to the water table and the type of vegetation in the area. There was a


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sparse distribution of electricity in Ibeju-lekki. Electricity is generated by different means in different households. In-depth intervies revealed that most of the households, though connected to the power supply grid, do not have a regular supply of electricity. Self-generated electricity constitutes 69.9%, while approximately 30.1% do not have a supply of electricity.

Table 3: Households’ internal dwelling quality


N=366 %

Good opening

Yes 339 92.6

No 27 7.4

Neutral 0 0

Burglary installation

Yes 314 85.8

No 51 13.9

Neutral 1 0.3

Number of rooms/household

1-2 rooms 193 52.7

3-4 rooms 172 47

Windows/room1 146 39.9

2 220 60.1

Toilet type

Flush 297 81.1

Pit toilet 69 18.9

System 0 0

Tiled bathroomYes 264 72.1

No 102 27.9

Tiled kitchenYes 260 71

No 106 29

Source of waterTap/borehole 272 74.3

Well/others 94 25.7

Electricity supplyYes 256 69.9

No 110 30.1

Field survey (2017)


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4.3.2 External dwelling quality

Findings show the high state of disrepair in most of the buildings. Of the observed buildings, 62.6% had one or more wear and tear. Although most of the disrepair is due to dampness in most of the areas, causing the paint to wear off, some of the disrepair is also caused by poor maintenance, especially among the low-income group. The saline water in the area contributes to change in colour of the external finishing. Other states of disrepair include broken windows, doors and a leaking roof. A large percentage (74.3%) of the buildings observed have good painting, and 25.7% have bad external painting. Of the houses, 83.9% are built on standard full plots, and 15.8% occupy partial plots. Of the buildings observed, 70.2% have an innovative design, and 29.8% have the traditional tenement house design.

Table 4: Observation on households’ external dwelling quality


N=366 %

State of disrepairLow 137 37.4

High 229 62.6

State of paintingGood 272 74.3

Bad 94 25.7

Lot size

Full 307 83.9

Not full 58 15.8

Others 1 0.3

Building designModern family house 257 70.2

Tenement house 109 29.8

Observation survey (2017)

4.4 Neighbourhood quality

The variables considered for measuring neighbourhood quality in this study include noise pollution, a good drainage system, appropriate waste disposal system, good roads, and environmental security. Analysis of the field survey (Table 5) shows that 30.6% of the respondents were affected by noise pollution, while 68.3% were not affected. Of the respondents, 66.4% showed a lack of suitable drainage, thus making most of the areas prone to flooding and environmental


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pollution. Appropriate drainage systems can be observed in the government-serviced housing development in the study area, contrary to what is obtainable in self-help housing schemes. The lack of a suitable drainage system contributes greatly to vehicular congestion during the rainy season, causing high commuting time and reduced productivity. Waste disposal management is a huge burden for peri-urban residents in Ibeju-lekki. Of the respondents, 33.1% are affected by lack of an appropriate waste disposal system. The private developer residential developments are well managed in terms of waste disposal. Observation showed that the greater proportion of the residential areas lacked good roads; sandy untarred roads are common in most of the secondary ring roads in Ibeju-Lekki, and some areas have ungraded earth roads, resulting in delays in linking the primary highways daily. Environmental security is an issue, as indicated by 28.1% of the respondents.

Table 5: Respondents’ assessment of neighbourhood quality


N=366 %

Noise pollution

Yes 112 30.6

No 250 68.3

Neutral 4 1.1

Good drainage system

Yes 119 32.5

No 243 66.4

Neutral 4 1.1

Good waste disposal

Yes 245 66.9

No 121 33.1

Environmental security

Yes 260 71

No 103 28.1

Field survey (2017)


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Figure 2: Well-serviced drainage system in government-led housing and flooded road, due to lack of drainage in self-help housing development area

Source: (Field survey, 2017)

4.5 Locational quality

The variables considered for locational quality in this study include closeness to work, closeness to market/CBD, availability of public transport, availability of children’s school, and availability of health facility. A greater percentage of the sampled population (85.8%) had good locational proximity to their places of work, as indicated by the analysis (Table 6); 14.2% were affected by their residential location in relation to proximity to work. Locational proximity to the Central Business District is an advantage to 86.1% of households in the peri-urban area. Only 13.9% were not close to the Business District Area, thus increasing their frequency of visit to the city centre for basic needs. Public health facilities are made available in the peri-urban area; 10.4% of the settlements further away from the city centre lacked medical facilities, due to the cost implication of locating such facilities in areas where housing density is low. Over 88.5% have access to good health facilities. Of the households, 94.3% showed satisfaction with the provision of children’s schools, and only 5.7% indicated their dissatisfaction. Both government and private schools are evenly distributed in the peri-urban settlements. Approximately 22.1% of households showed a lack of public transport as a locational deficiency in Ibeju-Lekki peri-urban area, while 77.6% are not affected by the lack of public transport.


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Table 6: Respondents’ assessment of locational quality


N=366 %

Closeness to workYes 314 85.8

No 52 14.2

Closeness to CBDYes 315 86.1

No 51 13.9

Availability of public transportYes 284 77.6

No 81 22.1

Availability of children’s schoolYes 345 94.3

No 21 5.7

Availability of health facility

Yes 324 88.5

No 38 10.4

Neutral 4 1.1

Field survey (2017)

Figure 3: Public schools in Ibeju-Lekki peri-urban settlement Source: Field survey, 2017

4.6 Assessment of informality

Different variables such as plot size for building, set-back around the building, set-back from the road, availability of building permit, and basic building regularisation documents were considered in the measurement of informality in the selected peri-urban settlements. Analysis of interview (Appendix 2) with the planning personnel in the local building regulatory office, presented in Table 7, shows the extent of informal housing development in the study area. Of the sampled houses, 75.7% were built on the standard plot size, while 24.3% were not. Of the houses observed, 35% have the standard


143

setback around the house, while 65% did not. Of the household heads observed, 53% have standard setback from the gate, while 47% default. A larger percentage (67.5%) of the buildings were built with a building permit, while 32.5% were built without one. The mostly obtained land regularisation document among the household heads was the receipt of land purchase (73.8%), a deed of assignment (8.5%), and a survey plan (6.8%). It can be deduced from the analysis of the building regularisation documents that the major building regularisation documents obtained by people were the receipt of land purchase. A reasonable number of household heads in Ibeju-Lekki peri-urban settlements are regulation inclined by virtue of the availability of additional building regulation documents.

Table 7: Measurement of informality


N=366 %

Standard plot size

Yes 277 75.7

No 89 24.3

Neither 0 0

Standard setback

Yes 128 35

No 238 65

Nil 0 0

Gate setbackYes 194 53

No 172 47

Building permit

Yes 247 67.5

No 119 32.5

Neither 0 0

Regularisation document

Receipt of land purchase 270 73.8

Deed of assignment 31 8.5

Survey plan 25 6.8

Stamp duty receipt 2 0.5

Building plans 6 1.6

Building permit and approval 9 2.5

Certificate of occupancy/governor consent 5 1.4

Unapproved documents 18 5

No document at all 0 0

Field survey, 2017


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Figure 4: Untarred sandy road in Ibeju-Lekki; Block and plank walls; Thatch roofing and aluminium roofing in Ibeju-Lekki peri-urban area

FSource: ield survey, 2017

4.7 Correlation analysis findings

To determine the factors that influence housing quality in the study area, the mean of building materials, dwelling quality, neighbourhood quality and locational quality was found by using the statistical tool Transform to recode the variables. The new variables regarded as the Mean Variable were correlated to show if there was any relationship.

4.7.1 Test of correlation between building materials and dwelling quality

The correlation analysis presented in Table 8 shows that there is a significant relationship between building materials and dwelling quality (0.556** P < 0.01). Therefore, building materials influence dwelling quality.

Table 8: Test of correlation between building materials and dwelling quality

Test variables Pearson correlation P-value Inference

Mean of building materials vs mean of dwelling quality

0.556** 0.000

There is a significant correlation between the two variables

**. Correlation is significant at the 0.01 level (2-tailed). List wise N=366Source: Field survey, 2017


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4.7.2 Statistical test of correlation between mean neighbourhood quality, mean locational quality and dwelling quality

Correlation between mean neighbourhood quality and mean dwelling quality (see Table 9) shows that there is a significant relationship between the two variables (0.239** P < 0.01) in Ibeju-Lekki. There is also a significant relationship between locational quality and dwelling quality (0.192** P < 0.01). Therefore, findings show that both locational and neighbourhood quality influence dwelling quality.

Table 9: Test of correlation between neighbourhood, locational quality and dwelling quality

Test variables Pearson correlation P-value Inference

Total mean of neighbourhood and locational quality vs dwelling quality

0.236** 0.000There is a significant correlation between the two variables

Mean neighbourhood quality vs dwelling quality 0.239** 0.000

There is a significant positive linear relationship between the two variables

Mean locational quality vs dwelling quality 0.192** 0.000

There is a significant correlation between the two variables

**. Correlation is significant at the 0.01 level (2-tailed). List wise N=366.

4.7.3 Test of correlation between housing typologies and respondents’ socio-economic attributes

The test of correlation between housing typologies and respondents’ socio-economic attributes (see Table 10) shows that income is the only attribute that has a significant relationship with housing typologies in Ibeju-Lekki (-0.205** P < 0.000). This connotes that the lower the respondents’ income, the lower the quality of housing they can access. Therefore, the respondents’ socio-economic attributes influence the housing typologies that are related to dwelling quality.


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Table 10: Test of correlation between housing typologies and respondents’ socio-economic attributes

Test variables Sub-variables

Pearson correlation P-value Inference

Housing typologies vs respondents’ socio-economic attributes

IncomeLiteracy Ethnic group

-0.205**0.0430.061

0.0000.4100.242

There is a significant negative linear relationship between the two variablesThere is no significant correlation between the two variablesThere is no significant correlation between the two variables

**. Correlation is significant at the 0.01 level (2-tailed). List wise N=366.

5. Conclusion Dwelling quality is affected by households’ income in Ibeju-Lekki peri-urban settlements. Housing development in Ibeju-Lekki attracts fairly good quality because of the socio-economic class of the migrants, predominantly high income and middle income. Findings in this article have shown the interrelationship among the variables and how the complex interactions have impacted on the quality of housing in the study area. Among the variables considered for neighbourhood quality, poor road and lack of suitable drainage constituted the major environmental challenges. In addition, waste disposal, to some extent in certain areas, especially the isolated settlements, is a challenge, though not with the magnitude of major challenges. Although, in the majority of government housing, more attention was paid to dwelling and neighbourhood quality, in general, the study area has good locational quality, from the residents’ perception, based on the availability of basic services such as health facilities, children’s schools, and public transport. The external dwelling quality is generally fair, except in areas of disrepair which, by observation, are caused primarily by dampness and poor maintenance. In terms of internal dwelling quality, the major area of concern is the supply of water and electricity. There is no good supply of water; a greater percentage of households in Ibeju-Lekki relies on a borehole water system. Observation shows that the quality of water from boreholes is very poor, due to the nature of the soil in Ibeju-Lekki. More houses conform to standard plot sizes in Ibeju-Lekki, but attention needs to be paid to the level of informality. The correlation test shows the factors affecting dwelling quality include building materials,


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neighbourhood quality, and locational quality. In addition, socio-economic attributes of households, notably income, affect the building types. These, in turn, influence the quality of housing. The correlation test shows a negative correlation between housing types and socio-economic attributes: the less the income, the lower the quality of housing a household can access. In addition, the presence of gated exclusive residential developments in certain parts of the study area helps improve the housing quality. This is made possible because of the socio-economic class of the migrants, predominantly high-income group. The areas occupied by the low-income group lack good neighbourhood quality. It can, therefore, be concluded that housing quality in Lagos peri-urban settlements is affected by households’ socio-economic attributes, building materials, dwelling quality, neighbourhood quality, and locational quality.

6. RecommendationWith the understanding of the factors influencing housing quality in the Ibeju-Lekki peri-urban settlements, stakeholders should advocate for participatory efforts toward a sustainable development of the peripheral settlements. The state government should advocate for housing policy that promotes the use of alternative building materials by both government and private developers. This would aid housing affordability in the Lagos peri-urban settlements and ultimately reduce the spread of informal housing development. Government disparity in infrastructure development, which has impacted on poor neighbourhood and locational quality of most of the peri-urban housing developments, should be discouraged and, if possible, eliminated. The state government should regularly update the area of inadequacy and make the basic provisions available where community participation cannot achieve capital-intensive projects. This will improve both the environment and the locational quality that influence housing quality.

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Oorsigsartikels • Review articles

Construction project management through building contracts, a South African perspective



AbstractThis article reviews construction project manage-ment and building contracts in South Africa. It introduces general information and findings on the topic, forming part of a broader in-depth study, which proves difficult to encapsulate in one single article. The novice might perceive contract management, project management, and construction management to be the same concept. To clarify these concepts, the evolution of construction contracts and project management was studied to identify possible similarities between these concepts. This article commences with a brief history prior to a schematic analysis of the general characteristics of construction contracts and project manage-ment. It investigates the application of these concepts within South Africa and compares the general structure of the main contracts used within South Africa. This general investigation clearly shows that the standard conditions of contracts used in South Africa have similar structures to the main construction project management knowledge areas recognised by the Project Management Institute (PMI). The article also reviews the four general conditions of contracts endorsed by the Construction Industry Development Board (CIDB) in South Africa and investigates the general clauses and themes of these contracts. The Construction Contract should consider all the Project Life-Cycle (PLC) stages. The Construction Contract should further be regarded as the Project Implementation Plan (PIP), on which the control procedures during construction are based. With the understanding of the evolution of the two streams (contracts and management), their relevance, goal, dependencies and responsibilities may be understood better. This may enhance the

Hendri du Plessis

Mr Hendri du Plessis, Lecturer, Department of Quantity Surveying and Construction Management, University of the Free State, Bloemfontein 9301, South Africa. Phone: +27 (0) 51 401 3322 or +27 (0) 73 177 8953, email: <[email protected]>

Pierre Oosthuizen

Mr Pierre Oosthuizen, Lecturer, Department of Quantity Surveying and Construction Management, University of the Free State, Bloemfontein 9301, South Africa. Phone: +27 (0) 51 401 3322 or +27 (0) 84 244 1344, email: <[email protected]>


[email protected]





du Plessis & Oosthuizen • Construction project management ...

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professional manner in which the management of the entire Project Life-Cycle (PLC) is implemented and approached.Keywords: Agreement, construction, contract(s), general conditions, project management, project life cycle

AbstrakDie artikel beskou konstruksieprojekbestuur en boukontrakte in Suid-Afrika. Dit stel algemene inligting en resultate voor oor die onderwerp, wat deel uitmaak van ’n wyer indiepte studie, wat moeilik is om in een enkele artikel te vervat. Die beginner kan soms kontrakbestuur, projekbestuur en konstruksiebestuur as dieselfde konsep beskou. Om hierdie konsepte te verduidelik, is die evolusie van konstruksiekontrakte projekbestuur bestudeer om moontlike ooreenkomste te identifiseer. Hierdie artikel begin met ’n kort geskiedenis voor ’n skematiese analise van die algemene kenmerke van konstruksiekontrakte en projekbestuur. Die artikel ondersoek die toepassing van hierdie begrippe binne Suid-Afrika en vergelyk die algemene struktuur van die hoofkontrakte wat in Suid-Afrika gebruik is met mekaar. Uit hierdie algemene ondersoek is dit duidelik dat die standaardvoorwaardes van kontrakte wat in Suid-Afrika gebruik word, baie soortgelyke strukture het in vergelyking met die belangrikste konstruksieprojekbestuursareas soos erken deur die Projekbestuursinstituut (PMI). Die artikel beskou die vier kontrakte wat deur die Konstruksiebedryf-ontwikkelingsraad (CIDB) in Suid-Afrika onderskryf is en ondersoek die algemene klousules en temas van hierdie kontrakte. Die konstruksie kontrak moet al die Projek Lewensiklus (PLC) stadiums in ag neem. Die Konstruksie Kontrak moet verder gesien word as die Projek Implementeringsplan (PIP), waarmee beheer tydens konstruksie toegepas moet word. Met dié begrip van die evolusie van die twee strome (kontrakte en bestuur), kan hul relevansie, doel en afhanklikhede beter verstaan word. Dit kan die professionele manier waarop die totale Projek Lewensiklus (PLC) geïmplementeer en benader word, verbeter.Sleutelwoorde: Algemene voorwaardes, konstruksie, kontrakte, ooreenkoms, projekbestuur, projek lewensiklus

1. IntroductionThe subsequent literature review focuses on the four main construction conditions of contracts currently utilised in South Africa and their relationship with respect to the Project Management Knowledge Areas (PMKA), as recognised by the Project Management Institute (PMI). It is anticipated that this may be the first in a series of articles on the relationship between project and construction management towards construction agreements.

Many different building contracts could be identified within the construction industry, and they are continuously being adjusted and revised to stay relevant in an ever-changing built environment (Putlitz, 2013). The authors of the majority of standard conditions of contracts related to construction projects suggest that their contract conditions allow for the best project management principles and practices for certain projects (NEC, 2015: online; JBCC, 2014: 1).


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This article is limited to a general overview of building conditions of contracts (hereafter referred to as contracts or construction contracts) and project management principles for building projects in South Africa.

Each construction project will dictate the type of agreement that is needed for the specific project (CIDB, 2005: 1-2). It is generally agreed in the construction environment that a successfully completed construction project will comply with the specified quality and will be completed within the allowed time and budget (Cooke & Williams, 2009: 23; Knipe, Van der Waldt, Van Niekerk, Burger & Nell, 2002: 18; Winch, 2010: 71), as agreed upon prior to the commencement of the project.

Loots (1995: 13) highlights that construction law focuses on establishing and administering the contract. The relationships between engineer (agent) and the employer; the contractor and the employer; the contractor and the subcontractors are all intricate and influential towards the success of the project. Managing a building project requires project management knowledge and a diverse range of skills and abilities such as technical, general, leadership and entrepreneurial management skills (Burke & Barron 2007: 25). During the project life cycle (PLC), the implementation phase of a construction project, has a larger time, cost and scope implication, with the result of a higher risk factor than the other phases of the project (Burke, 2010: 88; PMI, 2013: 40). It was observed that, in some cases, the professional team might be blamed for not complying with the conditions of the contract, resulting in unsuccessful completion of projects (Finsen, 2005: 215; Emmitt & Gorse, 2003: 165).

To determine the potential of the construction contract as a means to manage the construction project, it was necessary to find a relationship between the construction contracts most commonly used in South Africa and the project management knowledge areas as defined by the PMI. The general structure of these main contracts was analysed and grouped based on defined main themes and clauses. To place the construction contract’s position within the PLC, a comparison was made between the whole PLC of a construction project and the contract life cycle (construction contract require-ments). Finding similarities will highlight the construction contract’s ability to act as a management tool in an experienced manager’s hands. The construction contract’s ability to assist in the management of the project could be a valuable realisation for all parties involved with the construction contract and could, therefore, make an important contribution to the construction industry.


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1.1 Brief historical overview

In Mesopotamia, unearthed clay tablets show written contracts by the Sumerians, with some set wages for workers and administrative personnel tending to fields, and so on (Phillips, 1999: 3). Between 2284 and 1570 B.C., near the Valley of the Kings in Egypt, painted limestone shards have been found, and show daily work records, administrators, craftsmen, artists and labourers housed in tha area to design, excavate, construct, and decorate the royal tombs (Phillips, 1999: 3). It can be concluded from this, especially the presence of daily work records and administrators, that there were also project management principles at that time. Knipe et al. (2002: 3) established that the origins of project management can be traced back to the construction of the Pyramids as well as the Great Wall of China.

Standard contract conditions have been in use in South Africa since 1904, but it was only in the late 1920s that an assertive effort was made to enforce such conditions for the building industry (Malherbe & Lipshitz, 1979: 1). At that time, prominence was given to a document published in Britain in 1928 named Agreement and schedule of conditions of building contracts (Malherbe & Lipshitz, 1979: 1). This ultimately led to a system of building in South Africa that closely followed the system in Great Britain at the time. Currently, this basic system has hardly changed; where it has changed, it has been done so to accommodate itself to those factors influenced by the South African economy that do not manifest themselves in the British economy (Mills, 1982: 30).

Project management, on the other hand, only started to formalise in the 1930s in the United States of America, with risk analysis and scheduling in the 1950s (Knipe et al., 2002: 3-4). It is interesting to note that the Empire State Building was completed in 1931 (the tallest building in the world at the time) in the early days of formalising what we refer to nowadays as ‘project management’. That amounts to a construction period of 13 months (Berman, 2003). It was, however, only in the 1990s that project management became popular in the South African public sector (Knipe et al., 2002: 3-4). The traditional system in South Africa fragmented the building industry by separating the design phase from the construction phase. This has, over the years, led to an “arm’s length” type of contract that is “ingeniously arranged” between the owner and the contractor with the design team acting as the agent of the owner and the contract is worded in such a way that the contractor is “sure to have to take responsibility for almost any setback” (Mills, 1982: 66). Project management has thus developed to meet the need that has arisen to coordinate this


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fragmentation of the design team. A recent development has been the separate appointment of professional project managers by owners (employers), with the object of selecting the best experienced project team, including contractors, architects, quantity surveyors, consulting engineers, principle agents, legal advisers, subcontractors, and so on (McKenzie, 2014: 1-2). In South Africa, this project team is responsible for choosing the contract arrangement (Van der Merwe, Van Huyssteen, Reinecke, Lubbe & Lotz, 1993: 13).

In the year 2000, a series of acts were introduced to govern the built environment. The Council for the Built Environment Act (No. 43 of 2000), in particular, is the overarching council for all the regulating professional councils found in the built environment (Maritz & Siglé, 2016: 4; South Africa, 2000b: 40). As part of this series of acts, the Construction Industry Development Board (CIDB) Act No. 38 of 2000 and its Regulations established the CIDB, which promulgates the standardisation of the construction contracts used in South Africa (South Africa, 2000a: 8).

2. Construction contracts in South AfricaThe construction contract, in its simplest form, is an agreement between two parties stipulating the responsibilities of both parties for the execution of a specific activity (Finsen, 2005: 2). For example, a building will be erected by the contractor in exchange for a reasonable compensation by the employer (or client). The construction contract usually takes the form of an offer and accep-tance, based on reasonable information available at the time of the tender or bidding (also known as the procurement process) (Finsen 2005: 1; Malherbe & Lipshitz, 1979: 80; McKenzie, 2014: 1).

When considering common law of contracts and Roman-Dutch law (as used in South Africa), the building contract could be categorised as a letting-and-hiring contract (McKenzie, 2014: 1) (in Latin referred to as locatio conductio operis). The building contract could be viewed as an essential tool for organising the relationships between the different parties involved in construction companies (Othman & Harinarain, 2009). The relationship between parties may become complex. In order to gain a similar understanding of concepts, an evaluation of the wording used in the signed building contract may assist in analysing the initial intention of the parties involved (Loots, 1995: 38-39).

Building contracts have also evolved over the years to include the clauses necessary to make them work (McKenzie, 2014: 1). Part of the


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evolution of standard form contracts is the recognition that different categories of construction contracts have different requirements. Therefore, the different categories of contracts offer different degrees of flexibility, levels of incentive and different levels of risk to the parties (Loots, 1995: 89). Thompson introduces the characteristics of the four different categories of construction contracts used in South Africa, as illustrated in Figure 1 (Loots, 1995: 90).

Client Project Manager

Divided management design and

construction

2. Target-cost or cost-

reimbursable contracts

Co-operative management design and

construction

Special emphasis on Management

External project management organisation

Organisation for project

management

In house project management

team

Organization for design and

construction

Alternative contractual arrangements

4. Package deal or turnkey

1. Conventional admeasurement

or lump sum contract

In house team + management

services

3. Management contracting

Divided management design and

construction

Figure 1: Characteristics of different categories of construction contractsSource: Loots, 1995: 90

Conventional admeasurement or lump sum contracts (1) include admeasure contracts, such as contracts with bills of quantities, contracts with provisional bills of quantities, and so on. Thus,


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contracts with some kind of quantifiable costs, on which the contracts are based, and usually with an offer and acceptance (Loots, 1995: 91-149). Target-cost or cost-reimbursable contracts (2): Loots (1995: 142) divides this type of contract into three separate contracts, distinguishing between the incentives and cost limitation. With these type of contracts, the cost is uncertain when the contract is signed. The management of contracting (3) is an arrangement where the employer appoints an external organisation to manage and co-ordinate the design and construction of a project. The management contractor becomes part of the employer’s team as a consultant to the employer on the construction processes. The contractor advises the employer on the construction processes and the employer is, therefore, more involved through his/her project manager (Loots, 1995: 147,148). Package deal or turnkey contracts (4) provide a one-stop service to the client. The appointed contractor/consultant is responsible for the design and construction of the project. The term ‘package’ usually refers to commercial projects, design-and-build to the construction/renovation industries, and the turnkey project usually refers to engineering projects (Maritz & Siglé, 2010: 11).

For the purpose of this study, the search will be limited to conventional admeasurement or lump sum contracts only and the specific conditions of contract used for the study.

In South Africa, the project team remains responsible for choosing the contract arrangement (Van der Merwe et al., 1993: 13). It is important to follow a contract strategy where the project team knows the differences and characteristics of the main contracts to choose from. Loots (1995: 143) lists the main differences between the characteristics in the four main contract categories as follows:

• roles of the parties;• emphasis on management;• method of payment;• allocation of risk, and • nature of the work.

“Whilst the ideal of standardisation on one system of standard forms of contract for all engineering and construction works in South Africa is, probably, just as illogical as it is for each employer to have its own form of contract; a balance has to be found between these two extremes” (CIDB, 2005: 1). To find a balance, the number of forms of contract in use in South Africa should be reduced based on standardisation and documents capable of catering for a wide range of client


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requirements (CIDB, 2005: 2). Therefore, the Best Practice Guideline #C2, set out by the CIDB (2005: 2), recommends and supports four standard conditions of contract for the built environment in South Africa, which are privately owned by independent organisations. These suites of conditions of contract suites are:

• JBCC – Joint Building Contracts Committee;• GCC – General Conditions of Contract for Construction

Works;• NEC – New Engineering Contract, and• FIDIC – The Fédération Internationale des Ingénieurs-Conseils

(CIDB, 2015: 3-4; Vosloo & Maritz, 2005: 48-54).FIDIC, NEC and GCC are forms of contract that are generally used on all types of engineering and construction contracts. The JBCC is, however, mostly confined to building works. The FIDIC, NEC and JBCC series of documents contain short versions of engineering and construction works contracts. The four series of documents collectively cover the commonly encountered contracting strategies that are currently being pursued internationally (CIDB, 2005: 2).

Table 1 illustrates the latest research done by the CIDB on the construc tion industry and shows the percentage usage of the four standard conditions of contract for different project types.

Table 1: Type of contract used for different project types 2014

Project type % Contract document type usage for each project type Total

(%)Contract document type GCC NEC JBCC FIDIC Other

Residential building 20 - 68 8 4 100

Non-residential building 13 1 83 0 3 100

Civil works 76 4 6 10 4 100

Mechanical works 27 13 10 23 27 100

Electrical works 27 20 29 18 6 100

Special works 31 6 44 13 6 100

% Projects with contract document significantly amended 31 36 24 33 18

Source: Marx, 2014: 16

Overall, the JBCC suite of contracts was utilised the most, but it was specifically popular to use for residential and non-residential building projects. The GCC suite of contracts was the most preferred to use for


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civil work contracts. Although the NEC and FIDIC suites of contracts were less preferred, all these document types have been used on building projects previously.

Considering that the NEC, JBCC and FIDIC conditions of contracts comprise different individual contracts, the research narrowed the specific suite of contracts down (CIDB, 2005: 2-11) to Conventional Admeasurement or Lump Sum contracts (category 1) in Figure 1, which, together with the Best Practice Guideline #C2, determined the following specific contracts to be used further in the study (CIDB, 2005: 14):

• General Conditions of Contract for Construction Works (GCC);

• NEC Engineering and Construction Contract (ECC) (hereafter referred to as NEC);

• JBCC Principal Building Agreement (PBA); (hereafter referred to as JBCC), and

• Conditions of Contract for Construction (Red Book) (hereafter referred to as FIDIC).

In order to find a relationship between construction contracts and construction project management, the general structure of these main contracts was analysed and tabulated under the categories of main themes and clauses. Table 2 introduces the main themes and clauses.

Table 2: Content comparison between the four main contracts

FIDIC GCC NEC JBCC PBA

20 Main clauses 10 Main themes 9 Core clauses 7 Main themes

1. General provisions 1. General 1. General 1. Interpretation (clauses 1-7)

2. The employer 2. Basis of contract

2. The contractor’s main responsibilities

2. Insurance and security - Risks (clauses 8-11)

3. The engineer 3. Engineer 3. Time

3. Execution - Roles and responsibilities (clauses 12-17)

4. The contractor4. Contractor’s general obligations

4. Testing and defects

4. Completion (clauses 18-24)

5. Nominated subcontractors

5. Time-related matters 5. Payment 5. Payment

(clauses 25-27)


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FIDIC GCC NEC JBCC PBA

20 Main clauses 10 Main themes 9 Core clauses 7 Main themes

6. Staff and Labour

6. Payment and related matters

6. Compensation events

6. Suspension and termination (clauses 28-29)

7. Plant, materials and workmanship

7. Quality and related matters

7. Title – pertaining to material and plant on site (to whom does it belong?)

7. Dispute resolution (clause 30)

8. Commencement, delays and suspension

8. Risks and related matters

8. Risks and insurance

9. Test on completion

9. Termination of contract 9. Termination

10. Employers taking over

10. Claims and disputes

11. Defects liabilitySupplementary schedule of option

12. Measurement and evaluation

Main option clauses, with six options

13. Variations and adjustments Dispute resolution

14. Contract price and payment

Secondary options clauses

15. Termination by employer

16. Suspension and termination by contractor

17. Risk and responsibility

18. Insurance

19. Force majeure

20. Claims, disputes and arbitration

Source: FIDIC, 1999

Source: SAICE, 2015

Source: NEC, 2013a

Source: JBCC, 2014

McKenzie (2014: 175) highlights specific topics normally found in a construction contract. When these topics are compared to the structures of the identified contracts (Table 2), the following


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most general contract themes are derived and will be used in the final comparison:

• general; • roles and responsibilities;• time-related items;• payment (costs);• quality;• risks or change;• termination, and• claims and disputes.

These topics correspond to the general project management areas, discussed below.

3. Construction project management in South AfricaProject management is regulated by professional bodies. One such body is the Project Management Institute (PMI). The PMI (2013: 3) defines a project as a temporary undertaking to create a unique product, service or result. There is a definite beginning and end, but the impact may last much longer. Every project creates a unique service or result and can create:

• a product that can be either a component of another item or an end in itself – e.g., a building;

• a capability to perform a service – e.g., a business function to support productivity;

• an improvement in the existing product or service line – a Six Sigma project undertaken to reduce defects, or

• a result such as an outcome or document – e.g., a research project.

Lester expands on the definition by defining the purpose and the main differentiating factor to any other business or enterprise. Project management is concerned with the management of change instead of managing a continuum or business as usual. The main objectives of a project are to complete it on time, within budget, and to the required standard or quality (Lester, 2013: 1-2).

The PMI has published a knowledge guide known as the PMBOK guide that stipulates the key terms, concepts, facts, principles, and rules of project management areas. The ten generic Project Management Knowledge areas listed by the PMI (2013: 61) are:


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1. Project Integration Management;2. Project Scope Management;3. Project Time Management;4. Project Cost Management;5. Project Quality Management;6. Project Human Resources Management;7. Project Communications Management;8. Project Risk Management;9. Project Procurement Management, and10. Project Stakeholder Management.

In addition to the ten PMBOK knowledge areas that are generic, the PMI have identified four additional areas known as the Construction Extension to the PMBOK that are industry specific (PMI, 2003: ix). The purpose of the Construction Extension is to improve the efficiency and effectiveness of the management of construction projects. These areas are:

1. Safety Management;2. Environmental Management;3. Financial Management, and4. Claims Management (PMI, 2015).

The Project and Construction Management Professions Act 48 of 2000 defines Construction Project Management as “… the management of projects within the Built Environment from conception to completion, including management of related professional services” (South Africa, 2011: 30). Every new construction project typically consists of a new team. The experience of each individual team player contributes to the success of the project. The project and the management thereof usually take place in an environment larger than the project itself. Kerzner (2003: 69-74) and Burke (2007: 28) state that all construction projects can be divided into phases of development. These phases are collectively known as the project life cycle (PLC) and contribute to better project control for project managers. The PLC can be captured in a methodology with a definite start and end. The items in between can, however, vary considerably (PMI, 2008:15). Burke (2003: 28) divides projects into the following four basic phases: concept, design, implementation, and closing. For the construction industry in South Africa, six phases are identified and set out by the South African Council for the Built Environment (CBE). These phases are inception, concept and


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viability, design development, documentation and procurement, construction and close-out (CBE, n.d.: online).

The greatest effort is experienced during the implementation phase (construction phase) of a project. Effort gradually increases as the design of the project starts, and continues to increase steadily until tapering downwards as the projects nears completion (Burke, 2010: 88).

For the purpose of this article, Project Management and Construc-tion Management will be referred to as Construction Project Management (CPM). With the main themes identified for CPM, the process of comparing the CPM and the construction contracts could be conducted.

4. The project life cycleTo understand how the contract fits into the project life cycle, it is important to show the integration between project phases, so that the relationship between the construction life cycle and the project life cycle is clearly understood. The Standard for Uniformity in Construction Procurement divides the procurement document into two distinct sections, namely the Tender Data and the Contract Data. These two sections culminate into an offer (on the Form of Offer and Acceptance) that is either accepted or rejected (CIDB, 2015: 15). Figure 2 is a simplification of the process and does not necessarily illustrate how much information has to be transferred during this process. The objective of Figure 2 is to illustrate how the procurement and contract formation fits into the PLC.


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Figure 2: Integration between project phases (own diagram)Sources: Adapted from CBE, n.d.: 4; Cooke & Williams, 2009: 81, 132; PMI, 2017: 25;

PMI, 2007: 21; Burke, 2007: 48


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Figure 2 illustrates the construction project life cycle, as described by the CBE on the left with the contract life cycle at the top (stages 1 to 6). The Project Management Processes and the applicable knowledge areas are illustrated adjacent the PLC stages and subsequently linked to the CPM life cycle (PMI, 2017: 25; PMI, 2007: 21). Taking this into account, the South African Council for the Construction Profession defined the six stages of the PLC (South Africa, 2011: 4-10).

Stage 1 (Inception) includes the procedure of agreement of the requirements and preferences of the client, assessing user needs and options, appointment of necessary consultants in establishing project brief, objectives, priorities, constraints, assumptions and strategies in consultation with the client. The PMI lists the Integration and stakeholder management knowledge area used during the ignition process.

Stages 2 and 3 (Concept and viability through to Design development) relate to planning process and to all 14 knowledge areas. Stage 2 is defined as the finalisation of the project concept and feasibility, and stage 3 as the management, co-ordination and integration of the detail design development process within the project scope, time, cost and quality parameters.

Stage 4 (Documentation and procurement) mostly involves the integration, quality, human resources, communication, procurement, stakeholder, safety and environment management planning processes. Even though the decision on the type of contract to use may be decided in the earlier stage, the documentation for the tender process is finalised during stage 4. The SACPCMP defines this stage as the process of establishing and implementing procurement strategies and procedures, including the preparation of necessary documentation, for effective and timeous execution of the project.

Stage 5 (Construction or implementation) may involve the finalisation of the contract and the appointment of the contractor. The main objectives of this stage include the management and administration of the construction contracts and processes, including the preparation and co-ordination of the necessary documentation to facilitate effective execution of the works. It further entails the monitoring and control of the project through the processes of all 14 knowledge areas.

Stage 6 (Close-out) involves the process groups of integration and financial claim management. Practically, this involves managing and administrating the project closeout, including preparation and co-ordination of the necessary documentation, in order to facilitate


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the effective operation of the project. The specific outcomes of this stage may include Works Completion Certificate, Certificate of Final Completion, Record of all Meetings, and a Project Close-out Report depending on the contract used.

In project management, considering Burke (2007: 75), the “Baseline Plan” or “Project Plan” is a portfolio of documents and policies that outlines how to achieve the objectives of the project. Figure 2 illustrates when the contract comes into effect. By this time, a substantial portion of planning and design have been done. The construction contract thus has a very similar position within the PLC to the Project Plan or the Project Implementation Plan (PIP).

5. Similarities between construction contracts and project management

Figure 2 clarified the relationship between the PLC towards the construction contract and the CPM knowledge areas. To consider the similarities between construction contracts and construction project management, in general, this article first considers the entire PLC of a construction project compared to the contract life cycle (construction contract requirements). Secondly, a comparison is made between the project management knowledge areas and the construction contract themes.

Table 3 shows the similarities between the general themes of the construction contracts compared to the knowledge areas of both project management and construction management knowledge areas. It also displays the applicable construction life cycle stages in rectangular blocks next to each theme and knowledge area. This serves as a link between Figure 2, the PLC, contract themes and construction project management themes.


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ent

Cre

atin

g a

scop

e m

anag

emen

t pla

n

An

offe

r by

the

cont

ract

orC

olle

ctin

g th

e re

quire

men

ts

Acc

epta

nce

of th

e of

fer

Defi

ning

and

doc

umen

ting

the

stak

ehol

der

’s n

eed

s

Acc

ess t

o th

e w

orks

- w

ho d

oes t

he si

te

belo

ng to

etc

.

Subd

ivid

ing

proj

ect d

eliv

erab

les

Form

alisi

ng th

e ac

cept

ance

of t

he d

eliv

erab

les

Mon

itorin

g th

e st

atus

of t

he p

roje

ct a

nd th

e sc

ope

and

man

agin

g ch

ange

s.

In

tegr

atio

n m

anag

emen

t

Ensu

re th

at th

e va

rious

ele

men

ts o

f the

pro

ject

are

pr

oper

ly id

entifi

ed, d

efied

, com

bine

d, u

nifie

d a

nd

coor

din

ated

.


169

Con

tract

them

esPr

ojec

t man

agem

ent k

now

led

ge a

reas

Con

stru

ctio

n m

anag

emen

t kno

wle

dge

ar

eas

Con

tract

th

emes

Basic

requ

irem

ents

to

ad

dre

ss in

the

cont

ract

Know

led

ge a

rea

Basic

asp

ects

of a

rea

Know

led

ge a

rea

Basic

asp

ects

of

area

Th

eme

2:

Role

s an

d re

spon

si-bi

litie

s

Who

is re

spon

sible

for

the

des

igns

Reso

urce

man

agem

ent

Defi

ning

how

to e

stim

ate,

acq

uire

, man

age

and

ut

ilise

phys

ical

and

team

reso

urce

sW

ho is

the

empl

oyer

/ cl

ient

’s a

gent

s an

d w

hat i

s the

ir ob

ligat

ions

?

The

proc

ess o

f est

imat

ing

team

reso

urce

s and

the

type

and

qua

ntiti

es o

f mat

eria

ls, e

quip

men

t and

su

pplie

s req

uire

d

Site

repr

esen

tatio

n re

quire

men

ts o

f pa

rties

Acq

uisit

ion

of th

e re

sour

ces

Ass

ignm

ent

Putti

ng th

e pr

ojec

t tea

m in

pla

ceSe

tting

out

of t

he

wor

ksM

anag

e pr

ojec

t tea

m

Ass

ignm

ent

Man

agin

g th

e te

am

Sub-

cont

ract

or

arra

ngem

ents

1 2 3

4 5

St

akeh

olde

r man

agem

ent

Iden

tify

stak

ehol

der

s

Plan

stak

ehol

der

man

agem

ent

Man

age

and

con

trol s

take

hold

er e

ngag

emen

t

Them

e 3:

Tim

e re

late

d ite

ms

Prac

tical

, wor

ks a

nd

final

com

plet

ion

- w

ord

ing

dep

end

ant

on c

ontra

ct

Time

or S

ched

ule

(as

per

2017

PM

I) m

anag

emen

t

Plan

, dev

elop

and

con

trol t

he p

roje

ct sc

hed

ule

Def

ects

liabi

lity

perio

ds

Iden

tify

and

doc

umen

ting

rela

tions

hips

am

ong

activ

ities

Sect

iona

l com

plet

ion

of th

e w

orks

Sequ

ence

Act

iviti

es

Revi

sion

of c

ontra

ct

perio

ds/

dat

es

Estim

ate

Act

ivity

Dur

atio

ns

Ana

lysin

g ac

tivity

sequ

ence

s, d

urat

ions

, res

ourc

e re

quire

men

ts a

nd sc

hed

ule

cons

train

ts

Con

trollin

g th

e sc

hed

ule

Tabl

e 3

cont

inue

d ..

.


170

Con

tract

them

esPr

ojec

t man

agem

ent k

now

led

ge a

reas

Con

stru

ctio

n m

anag

emen

t kno

wle

dge

ar

eas

Con

tract

th

emes

Basic

requ

irem

ents

to

ad

dre

ss in

the

cont

ract

Know

led

ge a

rea

Basic

asp

ects

of a

rea

Know

led

ge a

rea

Basic

asp

ects

of

area

Them

e 4:

Pa

ymen

t

Inte

rim p

aym

ents

(p

aym

ent d

urin

g pr

ojec

t per

iod

)

Cos

t man

agem

ent

Defi

ning

how

the

proj

ect c

osts

will

be e

stim

ated

, bu

dge

ted

, man

aged

mon

itore

d a

nd c

ontro

lled

Fina

ncia

l m

anag

emen

t

It in

clud

es th

e pr

oces

ses t

o ac

quire

an

d m

anag

e fin

anci

al re

sour

ces

on th

e pr

ojec

t

Ad

just

men

ts a

nd

varia

tion

ord

ers

Estim

atin

g th

e co

sts

In c

ontra

cts t

o co

st

man

agem

ent -

it is

m

ore

conc

erne

d

with

reve

nue

sour

ces a

nd

men

torin

g ne

st

cash

flow

s for

the

cons

truct

ion

proj

ect

Reco

very

of

expe

nses

by

eith

er

parti

esEs

tabl

ishin

g th

e co

st b

assli

neM

anag

emen

t of

day

-to-d

ay c

osts

Fina

l Acc

ount

Con

trollin

g th

e co

st a

gain

st th

e ba

selin

e

Them

e 5:

Q

ualit

y

With

in su

pple

men

tary

d

ocum

enta

tion

to

the

cont

ract

Qua

lity

man

agem

ent

Dev

elop

men

t and

impl

emen

tatio

n of

a q

ualit

y m

anag

emen

t sys

tem

with

rega

rd to

pla

nnin

g,

man

agin

g an

d c

ontro

lling

Test

ing

and

co

mm

issio

ning

Spec

ifica

tions

Tabl

e 3

cont

inue

d ..

.


171

Con

tract

them

esPr

ojec

t man

agem

ent k

now

led

ge a

reas

Con

stru

ctio

n m

anag

emen

t kno

wle

dge

ar

eas

Con

tract

th

emes

Basic

requ

irem

ents

to

ad

dre

ss in

the

cont

ract

Know

led

ge a

rea

Basic

asp

ects

of a

rea

Know

led

ge a

rea

Basic

asp

ects

of

area

Them

e 6:

Ri

sks

Wor

k Ri

sk

Risk

man

agem

ent

Plan

ning

, id

entifi

catio

n, a

naly

sis, r

espo

nse

plan

ning

, re

spon

se im

plem

enta

tion

and

mon

itorin

g ris

k on

the

proj

ect a

re a

ll pro

cess

es in

volv

ed in

risk

m

anag

emen

tSa

fety

man

agem

ent

Dev

elop

, exe

cutiv

e an

d a

dm

inist

er

a sa

fety

pla

n to

im

prov

e he

alth

and

in

crea

se th

e sa

fety

on

the

proj

ect

Ind

emni

ties

Insu

ranc

es

Secu

ritie

s, gu

aran

tees

etc

.

Envi

ronm

enta

l m

anag

emen

t

Det

erm

ine

wha

t im

pact

the

proj

ect

will

have

on

the

envi

ronm

ent.

Ass

ure

and

con

trol

that

the

plan

stay

s in

the

envi

ronm

enta

l st

and

ard

s

Them

e 7:

Te

rmin

atio

n

By th

e em

ploy

er

or c

ontra

ctor

and

th

e rig

hts r

elat

ed to

d

efau

lt an

d d

isast

er

Them

e 8:

C

laim

s an

d di

sput

es

Litig

atio

n, a

rbitr

atio

n,

adju

dic

atio

n,

med

iatio

n et

c.

Cla

ims

man

agem

ent

Iden

tify

and

qua

ntify

cl

aim

s

Can

cella

tion

by

the

Empl

oyer

or

cont

ract

or a

nd th

e rig

hts r

elat

ed to

d

efau

lt an

d d

isast

er

Set t

he c

orre

ct in

put

to p

reve

nt c

laim

s

Set t

he c

orre

ct

clai

ms r

esol

utio

n st

eps

Tabl

e 3

cont

inue

d ..

.


172

Con

tract

them

esPr

ojec

t man

agem

ent k

now

led

ge a

reas

Con

stru

ctio

n m

anag

emen

t kno

wle

dge

ar

eas

Con

tract

th

emes

Basic

requ

irem

ents

to

ad

dre

ss in

the

cont

ract

Know

led

ge a

rea

Basic

asp

ects

of a

rea

Know

led

ge a

rea

Basic

asp

ects

of

area

Com

mun

icat

ion

man

agem

ent

Pres

ents

the

form

al c

omm

unic

atio

n pl

an w

ithin

the

proj

ect m

anag

emen

t pla

n

Plan

, man

agem

ent a

nd c

ontro

l com

mun

icat

ions

d

urin

g th

e pr

ojec

t

Proc

urem

ent

man

agem

ent

The

proc

esse

s nec

essa

ry to

acq

uire

pro

duc

ts,

serv

ices

, or r

esul

ts n

eed

ed fr

om o

utsid

e

Sour

ces:

Ver

ster

, 200

6: 7

; FID

IC, 1

999;

SA

ICE,

201

5; N

EC, 2

013;

JBC

C, 2

014

Sour

ces:

PMI 2

017:

69-

536

Sour

ce: P

MI 2

007:

119

-179

Tabl

e 3

cont

inue

d ..

.


173

When comparing the themes of the four main contracts against the main themes of construction project management, they are found to be very similar in nature. It is apparent that the Construction Agreement and the Construction Project Management knowledge areas have very similar themes or goals. However, a proper comparison proves difficult because of the different structures of each of the four standard conditions. An individual comparison of each of the standard contracts will be included in the anticipated forthcoming research.

On the basis of Table 3, the following general similarities could be highlighted.

Theme 1

The general theme of contracts generally relates to the scope and integration management knowledge areas. The document layout of all four of the standard contracts begins with an introduction, followed by general clauses. The general section of these contracts sets out how the contract should be read and interpreted. This is usually followed by a list of definitions. Communication arrangements are included throughout the contracts, although most of the communication arrangements are contained within the general theme. Procurement can also be linked to the general theme, although as shown above, it is contained outside the actual contract (FIDIC, 1999; SAICE, 2015; NEC, 2013; JBCC, 2014).

Theme 2

Roles and responsibilities relate to human resources and stakeholder management knowledge areas. By its nature, a contract can only be concluded by two people, one on each side of the obligation. More than one person may, however, represent either side or parties. Representation is a legal and not a contractual phenomenon. It occurs when one representative concludes a juristic act in such a manner that the legal consequences of the act belong to the principal (person being represented in the case of a construction contract, the employer, or the client). The basic requirement for representation is that the parties must disclose that they are representing the principal. Representation only occurs when the person or party has the authority to do so (Van der Merwe et al., 1993: 168-178).


174

Theme 3

Time-related items in the contract correspond to time management as a knowledge area. According to the terms of most of the building contracts, it is the duty of the contractor to complete the building by a specified date. Where no such time has been specified, a reasonable time shall prevail. If the employer wants to claim damages, s/he will first have to place the contractor in mora (in delay or default) by means of a contract instruction, stipulating his/her default. The necessity for extension of time on the works can be brought about by the contractor’s default, the client’s default, or through factors outside the control of the two contracting parties. The employer’s consultant/representative can also cause delays such as, for example, the late issue of drawings, and so on (McKenzie, 2014: 161-168).

Theme 4

The payment theme relates to the cost management knowledge area of PM and to the financial management of the CM knowledge area. McKenzie (2014: 201) notes that a building contract, in its purest form, is an “entire contract”. This means that only through a contract is the contractor entitled to interim payments. However, the reversed implication of this is that, in the absence of special provisions, payment is due immediately after the work has been completed by the contractor. In like manner, payment for extras is due when completed. To understand the final account specifications in the contract, the construction project manager should clearly define how the project cost is estimated, budgeted, managed, monitored, and controlled.

Theme 5

Quality is also addressed by both the contract management themes and the PM knowledge areas. Building quality is attributed to three main components, namely design, materials, and workmanship (Malherbe & Lipshitz, 1979: 102). Design responsibility is defined in the contract and there may be areas where the subcontractor has to design certain specialist portions of the works. The source and supply are the responsibility of the contractor, except where it is supplied by the employer. Workmanship, however, always remains the responsibility of the contractor (Malherbe & Lipshitz, 1979: 106-120). As a project manager, the contractor should develop and implement a quality-management system with regard to planning, managing, and controlling the specifications as set out in the contract.


175

Theme 6

Risks management is similar to the contractual themes of managing risks and managing health and safety risks. The processes involved in risk management should address time, cost, resources, and environmental management (Loots, 1995: 261-269). Risks must be identified, quantified, and managed through a proper safety plan. The Construction Regulations (South Africa, 2014) emphasise risk identification during the design stage of the project, although these mainly focus on health and safety.

Theme 7

Termination is a theme that is not specifically related to any management knowledge areas (see point 8 below). However, it can be regarded as change, which has to be managed. Cancelation or termination can be caused by the default of one of the parties (employer or contractor) or by “no default” (Finsen, 2005: 195-210). Van der Merwe et al. (1993: 359-395) distinguish between three types of termination of obligations of the parties within a contract, namely:

• discharge by performance;• termination by agreement, and• termination by operation of the law.

Theme 8

Claims and Disputes, however, specifically relates to the CM knowledge area of Claims management. Construction contracts and their interpretation often lead to misinterpretation by one or both parties. This leads to potential disagreements concerning the rights and obligations of the parties and have been the cause of many claims and disputes. Clear contractual arrangements such as the impact of cancellations, litigation, arbitration, and so on should allow for construction managers not only to set the correct input to prevent claims, but also to set the correct claims resolution steps.

6. ConclusionThe evolution of construction contracts as well as project manage-ment in South Africa was studied to identify possible similarities between the general characteristics of construction contracts and project management principles. To determine the potential of the construction contract agreement as a means to manage the construction project, it was necessary to find a relationship between


176

the construction contracts most commonly used in South Africa and the project management knowledge areas as defined by the PMI.

A comparison between the entire PLC of a construction project and the contract life cycle (construction contract requirements) showed that the contract comes into effect only at the end of Stage 4: Documentation and procurement, and the start of Stage 5: Construction.

The four general conditions of contracts endorsed by the CIDB in South Africa were reviewed and the general clauses and themes of these contracts were investigated, resulting in the following general contract themes: general; roles and responsibilities; time-related items; payment (costs); quality; risks or change, and claims and disputes.

Compared to the main construction project management knowledge areas, these themes show that the controlling parameters of a construction project are identified through the main contracts used in South Africa. These controlling parameters include seven areas with particular similarity.

1. The general theme of contracts allows for preparation of the offer, which relates to the scope and integration management knowledge areas. These areas allow for preparing the project scope by ensuring that the various elements of the project are properly identified, defined, combined, unified and coordinated.

2. The roles and responsibilities of the project team are set out in the contract and this relates to human resources and stakeholder management knowledge areas, where the stakeholders and roles of the project team are management.

3. Time-related items in the contract for practical works and final completion depend on the wording of the contract. Such wording corresponds to time management as a knowledge area, where the project manager plans, develops and controls the project schedule.

4. The payment theme in the contract provides for interim payments, recovery of expenses, and the final account. This shows similarity both to Cost management as a knowledge area of PM, which defines how the project costs will be estimated, budgeted, managed, monitored, and controlled, and to Financial management of the CM knowledge area, which includes the processes to acquire and manage


177

financial resources on the project from a contractor’s perspective.

5. Quality specifications in the contract provides for testing and commissioning, which shows similarity to the PM knowledge areas that include the development and implementation of a quality management system with regard to planning, managing, and controlling the project.

6. The contract specifies risks management do address work, indemnities, insurances, guarantees, and so on. It is similar to the PM area of managing risks, which includes all the processes involved in risk management on the project. It shows similarity both to the CM knowledge area of managing health and safety risks and to environmental risks, which includes a plan to improve health, increase the safety on the project, and limit the influence on the environment.

7. The contract provides for Claims and Disputes by setting the legal criteria for the rights related to default and disaster when either the employer or the contractor cancels the project. This shows similarity to the CM knowledge area of Claims management which identifies and quantifies claims, sets the correct steps to prevent claims, and specifies the correct claims resolution steps.

These similarities highlight the building contract’s ability to act as a management tool in an experienced manager’s hands (PIP). The comparison shows that the construction contract’s ability to assist in the management of the project could be a valuable realisation for all parties involved in the construction contract and could, therefore, make an important contribution to the construction industry.

It is obvious that drawing up the building contract is not a simple task. The importance of involving an experienced construction project manager is key towards including the required construction management clauses during the development and selection of the contract agreement. The standard conditions of contract provide a guideline on which the construction project manager can build the contract. The construction contract should, therefore, consider all the Project Life-Cycle (PLC) stages. It should also be viewed as the Project Implementation Plan (PIP), that forms the basis for control procedures during construction. In understanding the evolution of the two streams (contracts and management), their relevance, goal, dependencies and responsibilities may be understood better and may enhance the professional manner in which the management of the entire Project Life-Cycle (PLC) is implemented and approached.


178

It is subsequently recommended that, in the short term, the four specific building contracts be investigated further, in order to investigate more fully the similarities and objectives of each contract.

In the medium to long term, it is recommended to investigate the need for an additional knowledge area to assist in the management of the amount of information to be transferred during the procurement and implementation stages of a construction project. Furthermore, how can the advent of BIM assist in the transfer of this information from design, through the procurement stage into construction and ultimately to the facilities manager?

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Van der Merwe, S., Van Huyssteen, L.F., Reinecke, M.F.B., Lubbe, G.F. & Lotz, J.G. 1993. Contract, general principles. Kenwyn: Juta.

Verster, J.J.P. 2006. Managing cost, contracts, communication and claims: A quantity surveying perspective on future opportunities. In: Semolic, B., Kerin, A. & Stare, A. (Eds.). Proceedings of the 1st ICEC & IPMA Global Congress on Project Management, 5th World Congress on Cost Engineering, Project Management & Quantity Surveying, 23-26 April 2006, Ljubljana, Slovenia: ZMP.

Vosloo, P.T. & Maritz M.J. 2005. Landscaping: An analysis of current contracting processes and documentation. Acta Structilia, 12(2), pp. 42-69.

Winch, G.H. 2010. Managing construction projects. 2nd edition. Chichester: Wiley-Blackwell.

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Boekresensie • Book review

Facilities Management Practice by A.C. Hauptfleisch, 2017. 1st edition. Pretoria: South Africa: Career Excel Academy

Being in Facilities Management for over a decade, I was eager to find out if there is more that I can learn. What a surprise. I found this book to be of utmost value and requested that everyone in our division should read it. It correctly points out that an organisation falls within a particular culture, a way of doing things. This book provides a fresh and practical outlook that can be implemented on ground level. Changing Facilities Management could have a huge impact on the organisation, thus paving the way for new creativity and enthusiasm.

The book covers every aspect of Facilities Management as well as the current buzz-words and trends such as sustainability, technology, intelligent buildings, life-cycle costing, and greening. It clearly defines the role of the facilities manager and provides clear guidelines to processes and practices.

Client satisfaction is part of our daily opera-tions at university. Our success depends on understanding both the client and his/her needs. This book covers this topic well and explains it in such a way that enables the person who works with the clients to understand and act accordingly.

Practical implementation remains the golden thread throughout the book. A sure must for every facilities manager.

Nico Janse van Rensburg

Nico Janse van Rensburg, Senior director University Estate, University of the Free State, Phone: 051 401 9309





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ACTA STRUCTILIA

INLIGTING AAN OUTEURS1. Acta Structilia publiseer artikels in

Afrikaans en Engels. Die verlangde lengte vir ’n artikel is tussen 4 000 en 12 000 woorde.

2. Voornemende outeurs moet ’n elektroniese kopie van ’n artikel in MS Word formaat (oorspronklike word deur die outeur bewaar) voorlê deur dit per epos aan te stuur (sien epos adres by punt 28.).

3. Enige toepaslike artikel, in ’n verstaanbare skryfstyl, duidelik uiteengesit en reeds taalversorg, word verwelkom, vergesel van ’n verklaring dat dit die oorspronklike werk van die outeur(s) is en dat die artikel slegs aan Acta Structilia aangebied is.

4. Tabelleenfigure:Daarmoeniemeeras10figureen tabelle in totaalperartikelwees nie. Alle onderskrifte moet in die teks verskaf word. Afkortings/akronieme wat in figure en tabelle gebruik word,moet in die opskrif/sleutel of voetnoot verduidelik word. Figure moet gestuur word in hoë resolusie TIFF formaat (vermy gekomprimeerde formate soos GIF en JPEG). Maak seker dat die figureduidelik en leesbaar sal wees wanneer dit verminder word. Tabelle moet in ’n geredigeerde formaat in Word of Excel ingedien word en nie as foto’s nie. Excel lêers moet opgelaai word as individuele spreivelle, nie die hele werkboek nie.

5. Die hoofredakteur behou die reg voor om die artikel(s) te verander waar nodig met betrekking tot die styl en aanbieding van die publikasie. As uitgebreide wysigings deur die beoordelaars aanbe veel word, sal die artikel(s) aan die outeur teruggestuur word.

6. Kopiereg word aan die outeur(s) by aanvaarding van die artikel oorgedra.

7. Teksgedeeltes van artikels moet in Microsoft Word, Ariel skrif, font grootte 12, enkel spasiëring gedoen word.

8. Die titel van die artikel moet kort en bondig wees en in beide Afrikaans en Engels aangebied word. Voorsien gepaste opskrifte en subopskrifte waar nodig.

9. ’n Kort opsomming (tussen 200250 woorde), in beide Afrikaans en Engels, moet aan die begin van die teks aangebring word.

10. Toepaslike sleutelwoorde in Afrikaans en Engels moet onder die opsomming aangebring word.

11. Die opsomming moet begin met 23 sinne wat ’n inleiding tot die studieveld gee en die spesifiekeprobleemwatondersoekword, gevolg deur ’n enkelsin oor die hoofbevindings (of gevolgtrekkings, in die geval van ’n oorsigartikel), en ’n verdere 23 sinne wat hierdie bevindinge/gevolgtrekkings in konteks plaas sodat lesers bewus gemaak word van die implikasies van die bevindings. Gewoonlik word bronverwysings nie in opsomming gegee nie.

12. Literatuuroorsigte moet internasionale navorsing oor soortgelyke onderwerpe identifiseer en ’n duidelike gapingin navorsingsartikels met betrekking tot internasionale voorpuntnavorsing aandui. Skrywers moet duidelik demonstreer hoe hul navorsing verband hou met dié van ander geleerdes oor soortgelyke onderwerpe.

13. Die belangrikheid van die hoofbevindinge of gevolgtrekkings behoort nie ’n opsomming van die resultate te wees nie, maar moet die bydrae wat die resultate tot die veld lewer, weerspieël en ook hoe die resultate in hulle onderskeie velde en op ander terreine van toepassing is. Die bevindinge moet begin met algemene bydraes en voortgaan met meer spesifieke bydraes.Die belangrikheid van die bevindings sal gepubliseer word met die doel om groter belangstelling te bevorder, nie net onder lesers in die veld nie, maar ook vir ander lesers. Die belangrike bevindinge moet dus vir ’n niespesialis geskryf word.

14. Opskrifte en onderskrifte word in Arabiese syfers genommer, geskei deur ’n punt en hoogstens tot drie vlakke, waarna ’n letter in hakies gebruik word, bv. 1. en 1.1 gevolg deur 1.1.1 en daarna a) ens.

15. Bronverwysings in die teks geskied volgens die Harvardstyl van verwysing:(Outeur, datum: bladsynommer[s]): bv.(Schleien,2014:20-23).

16. Net egte voet en eindnote met die tersaaklike inligting moet gebruik word. Die Harvardstyl van verwysing is hier van toepassing.

17. Die verwysingslys volgens die Harvardstyl van verwysing moet volledig in alfabetiese volgorde aangebied word. Bv. Sun, M. & Howard, R. 2014. Understanding I.T. in construction. London: SponPress.

184

18. ’n Kopie van alle internet dokumente wat in die teks verwys en gelys is in die bibliografie,moetdieartikelvergesel.

19. Aanhalings word nie kursief gedruk nie, en word in dubbelaanhalingstekens aangedui. Invoegings binne aanhalings word in blokhakies aangedui. Aanhalings wat langer as drie reëls is, word geïndenteer en het nie aanhalingstekens nie.

20. Slegs standaardafkortings word aanbeveel. Afkortings vir instellings kan gebruik word nadat dit vir die eerste keer volledig uitgeskryf is, met die afkorting daarna in hakies, vir terugverwysing.

21. Kursief moet nie oormatig gebruik word nie, indien wel, slegs vir konvensionele Latynse uitdrukkings bv. per se en vir woorde in ander tale.

22. Beklemtonings kry enkelaanhalingstekens.

23. Besonderhede van die oorsprong van ’n artikel moet aangedui word, soos in die geval van ’n kongresreferaat. Artikels word net vir keuring oorweeg indien vergesel van ’n verklaring dat dit in geheel of gedeeltelik nie elders vir publikasie voorgelê is, of reeds gepubliseer is nie.

24. Artikels word anoniem gerefereer. Die outeur(s) kan die name en adresse van tot drie vakkundiges (nie aan outeur[s]se eie instansie van werk verbonde nie) voorstel wat as referente sou kon optree.

25. Die outeur(s) van artikels wat geplaas word, sal elk twee komplimentêre kopieë van die betrokke uitgawe van Acta Structilia ontvang.

26. ’n Artikel moet vergesel word van die volledige titel, kwalifikasie en affiliasie,adres, telefoon en faksimilieenommers en indien moontlik ’n eposadres van die betrokke outeur(s).

27. Neem kennis dat ’n publikasieheffingvan R50 per bladsy op die artikels wat gepubliseer word, betaalbaar is. ’n Faktuur sal aan die hoofouteur ge stuur word.

28. Rigubydrae(s)aan:

DieRedakteur:Acta Structilia Interne Posbus 47 Universiteit van die Vrystaat Posbus 339 Bloemfontein, 9300 SuidAfrika

E-posadres:[email protected]

mailto:struct%40ufs.ac.za?subject=

185

ACTA STRUCTILIA

INFORMATION FOR AUTHORS1. An article may be submitted in Afrikaans

or English. The desired length for an article is between 4 000 en 12 000 words.

2. A copy of the typed article must be submitted (authors keep the original) in electronic format (MS Word) forwarded via email (see point 28.). The format must be kept as plain as possible for extracting and printing purposes.

3. An edited (proofread) article on any relevant topic, well presented and written in easy understandable style, will be considered for publishing on the understanding that they are the original work of the authors named, and that they are being offered only to Acta Structilia.

4. Tables and figures: There should be nomorethan10figuresandtablesintotalper article. All captions must be provided in the text. Abbreviations/acronyms used infiguresandtablesmustbeexplainedinthe heading/legend or footnote. Figures must be provided as highresolution images in TIFF format (avoid compressed formats like GIF and JPEG). Ensure that your figures will be clear and legiblewhen reduced in size. Tables must be submitted in editable format in Word or Excelandnotas imagefiles. Excel filesshould be uploaded as individual sheets, not the entire workbook.

5. The EditorinChief reserves the right to alter the article(s) where necessary with regard to the style and presentation of the publication. If extensive alterations are advised by adjudicators the article(s) will be returned to the author.

6. Copyright is transferred to the author(s) when an article is accepted for publication.

7. Article content must be written in Microsoft Word, Ariel, font size 12, single spacing.

8. Titles must be short and concise, but informative. Supply suitable headings and subheadings where necessary. The title must be in both Afrikaans and English.

9. A short abstract (between 200250 words), in both Afrikaans and English, must be provided at the beginning of the text.

10. Applicable keywords in Afrikaans and English must be given after the summary.

11. The summary should start with 2–3 sentences that provide an introduction to the fieldand theparticularprobleminvestigated, followed by a onesentencestatementofyourmainfindings(or conclusions, in the case of a Review Article), and a further 2–3 sentences placing these findings/conclusions ina general context so that readers are made aware of the implications of the findings. Summary paragraphs typicallydo not include references.

12. Literature reviews should identify international research on similar topics and indicate a clear gap in research articles related to international cutting edge research. Authors should clearly demonstrate how their research relates to that of other scholars on similar topics.

13. Thesignificanceof themainfindingsorconclusions should not be a summary of the results, but should reflect thecontributiontheresultsmaketothefield,and how the results are applicable in their respectivefieldand inotherfields.The points of significance should startwith general contributions and proceed with more specific contributions. Thesignificance of the findings will bepublished with the aim of promoting greater interest not only from readers in thefieldbutalsofromawiderreadership.Thepoints of significance should there-fore be written for a nonspecialist.

14. Use Arabic numbers with full stops in between for headings and subheadings, i.e. 1. followed by 1.1 and 1.1.1 up to a maximum of three levels. After that use a) etc.

15. Source references in the text must be in the Harvard style of referencing (Author, date:pages).i.e.(Schleien,2014:20-40).

16. Foot and endnotes are likewise done in the Harvard style of referencing.

17. The references list (Harvard style of referencing) should contain all the relevant information, and be listed alphabetically according to the names of the authors. i. e. Sun, M. & Howard, R. 2014. Understanding I.T. in construction. London:SponPress.

18. A copy of internet documents cited in the text and listed in the references must accompany the article.

19. Quotations are not in italics and must be written in double inverted commas. Inserts in quotations are placed in block

186

brackets. Quotations longer than three lines are indented and are placed without quotations marks.

20. Avoid uncommon abbreviations and acronyms. Abbreviations should be limited to those in general use. Names of corporations,etcareat firstwrittenoutin full with the abbreviation in brackets after which the abbreviated form may be used.

21. Italics are preferred for stereotyped Latin terms such as per se and for words in other languages.

22. Use single inverted commas to emphasise words or phrases.

23. Details concerning the origin of the article should be indicated, i.e if it was presented at a congress. An article will only be referred to the panel of referees if the author clearly states that it had not received prior publication and is not under consideration for publication elsewhere; also that the research has not been submitted for publication nor has it been published in whole or in part elsewhere.

24. Authors may submit the names and addresses of three scholars (experts) in hisfield(notmembersatownplaceofwork) as possible adjudicators.

25. The author(s) will receive two complimentary copies of the relevant issue of Acta Structilia.

26. The article must contain the title, qualifications and affiliations of theauthor(s), the address, telephone and facsimile numbers and if possible, the email address.

27. Note that a publication fee of R5000 per page is payable for every article published. An invoice will be sent to the main author.

28. Editorialaddress:

TheEditor-in-Chief:Acta Structilia Internal Post Box 47 University of the Free State PO Box 339 9300 Bloemfontein South Africa

E-mailaddress:[email protected]

mailto:struct%40ufs.ac.za?subject=

Referente en konsultante • Referees and consultants

Dr Bankole Awuzie (Department of Built Environment, Central University of Technology, Bloemfontein, South Africa)

Dr Giel Bekker (Graduate School of Technology Management, University of Pretoria, South Africa)

Prof. Chris Cloete (Department of Construction Economics, University of Pretoria, South Africa)

Prof. Linda de Vries (formerly from Departement of Finance, University of the Western Cape) (ORE Group Holdings, South Africa)

Prof. Fidelis Emuze (Department of Built Environment, Central University of Technology, Free State, South Africa)

Dr Franco Geminiani (formerly from Department of Construction Management, NMU, Port Elizabeth, South Africa)

Prof. Daphne Halkias (International School of Management, Paris, France)

Mr Daniel Huggett (Department of Quantity Surveying and Construction Management, University of the Free State, South Africa)

Dr Richard Jimoh (Department of Building, Federal University of Technology, Nigeria)

Emeritus Prof. Tinus Maritz (UP) (Department of Construction Economics, University of Pretoria, South Africa)

Dr Mark Massyn (Department of Construction Economics and Management, University of Cape Town, South Africa)

Prof. Innocent Musonda (Department of the Quantity Surveying and Construction Management, University of Johannesburg, South Africa)

Dr Ruben Ndihokubwayo ( Department of Construction Management and Quantity Surveying, Cape Peninsula University of Technology, South Africa)

Prof. Low Sui Pheng (Department of Building, National University of Singapore, Hong Kong)

Emeritus Prof. Basie Verster (Director: VersterBerryVerster QS, Bloemfontein, South Africa)

Prof. Abimbola Windapo (Department of Construction Economics and Management, University of Cape Town, South Africa)

Acta Structilia 2018:25 (1) ISSN 1023-0564 e-ISSN 2415-0487

Acta Structilia is endorsed by the South African Council for the Quantity Surveying Profession (SACQSP) for promoting research and Continuing Professional Development (CPD).

Inhoud • Contents

Navorsingsartikels • Research articlesAn exploratory factor analysis of risk Bérenger Renault 1 management practices: A study among Justus Agumba small and medium contractors in Gauteng Nazeem Ansary

An assessment of the causes, cost effects Oluwaseun Dosumu 40 and solutions to design-error-induced Clinton Aigbavboa variations on selected building projects in Nigeria

Successful transformational change in revenue Ric Amansure 71 management among beneficiary communities Chris Adendorff of South African renewable energy construction companies

A construction project management Michelle Burger 98 knowledge model: The type and level Benita Zulch of knowledge required

Assessment of housing quality in Ibeju-Lekki Funmilayo Adedire 126 peri-urban settlement, Lagos State, Nigeria Michael Adegbile

Oorsigsartikels • Review articlesConstruction project management Hendri du Plessis 152 through building contracts, a South African Pierre Oosthuizen perspective

Boekresensie • Book reviewFacilities Management Practice by Nico Janse van 182 A.C. Hauptfleisch, 2017. 1st edition. Rensburg Pretoria: South Africa: Career Excel Academy

Inligting aan outeurs • Information for authors 183

ACTA Structilia · Acta Structilia 2018:25(1) Tydskrif vir die fisiese en ontwikkelingswetenskappe...

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