GOOD Gisela E E Gaba 82245 Assignsubmission File Gisela Gaba -MSc Dissertation

The impact of project delivery systems, cost minimisation

and project control on construction project success. Evidence from Ghana

by

GISELA GABA

SEPTEMBER 2013

A dissertation submitted in part fulfilment of the Degree of Master of Science, Built Environment: Facility and Environment Management

University College London

Gisela Gaba September 2013

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ACKNOWLEDGEMENT First of all, I give thanks to the Almighty God for granting me the grace, wisdom, courage and perseverance to pursue my master’s degree. Secondly I thank my parents Florence and Paul, my sister Pauline and brother Paul for giving me support and encouragement throughout my studies. Thirdly I would like to thank Dr. Nathaniel Boso for the giving me guidance and supports during this dissertation process, and for believing in me. Mr. Peter McLennan –program director for always proving sound advice and direction in my academic work. Finally, my greatest appreciation goes to my lecturers for imparting invaluable knowledge to me during my Masters degree and to all those who played a part in making stay in the United Kingdom a memorable one.

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TABLE OF CONTENTS Acknowledgement .................................................................................................................................... 1

Table of contents ...................................................................................................................................... 2

List of tabels ............................................................................................................................................. 4

List of figures ........................................................................................................................................... 4

List of appenices ....................................................................................................................................... 4

Abstract ..................................................................................................................................................... 5

Chapter one ............................................................................................................................................. 6

1. Introduction ...................................................................................................................................... 6 1.1. An overview .................................................................................................................................. 6 1.2. Research gaps ................................................................................................................................ 7 1.3. Research aim ................................................................................................................................. 8 1.4. Research objectives ....................................................................................................................... 8 1.5. Importance of the study ................................................................................................................. 9

Chapter two ........................................................................................................................................... 10

Background ............................................................................................................................................. 10 2.1 Definitions .................................................................................................................................... 10

2.1.1 Project delivery process ........................................................................................................ 10 2.1.2 Project success ...................................................................................................................... 10 2.1.3 Project delivery system ......................................................................................................... 11

2.2 The construction industry - international perspective .................................................................. 14 2.3. Construction industry in ghana ................................................................................................... 15 2.4 Previous research ......................................................................................................................... 16 2.5 Role of the facility manager in project delivery ........................................................................... 19 2.6 Policy position .............................................................................................................................. 19

Chapter three ........................................................................................................................................ 21

Hypotheses development ........................................................................................................................ 21 3.1 Overview ...................................................................................................................................... 21 3.2 Theoretical framework ................................................................................................................. 21 3.3 DBB and DB as independent variables ........................................................................................ 21 3.4 Cost and control as moderating variables .................................................................................... 23 3.5 Project quality .............................................................................................................................. 24

Chapter four .......................................................................................................................................... 25

Research methodology ........................................................................................................................... 25 4.1 Overview ...................................................................................................................................... 25 4.2 Data collection method ................................................................................................................ 25 4.3 Data collection instrument ........................................................................................................... 26 4.4 Sample frame ............................................................................................................................... 26 4.5 Response rate ............................................................................................................................... 26 4.6 Characteristics of respondents ..................................................................................................... 27 4.7 Data analysis ................................................................................................................................ 28

4.7.1 Reliability test ....................................................................................................................... 28 4.7.2 Validity test ........................................................................................................................... 29 4.7.3 Descriptive analysis .............................................................................................................. 30

4.7.3.1 Design build .................................................................................................................. 31 4.7.3.2 Design bid build ............................................................................................................ 32 4.7.3.3 Project control ............................................................................................................... 33 4.7.3.4 Cost minimisation .......................................................................................................... 33


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4.7.3.5 Project effectiveness ...................................................................................................... 34 4.7.3.6 Project quality ................................................................................................................ 35

Chapter five ........................................................................................................................................... 37

Findings .................................................................................................................................................. 37 5.1 Results of regression analysis ...................................................................................................... 37 5.2 Plotting the interactions ............................................................................................................... 39

Chapter six ............................................................................................................................................ 41

Conclusion, implications and limitations ............................................................................................... 41 6.1 Conclusion ................................................................................................................................... 41 6.2 Discussion and implications ......................................................................................................... 41 6.3 Limitations and suggestions for future research .......................................................................... 45

References ............................................................................................................................................. 47

Appenicies ............................................................................................................................................. 54 Appendix i: Cover letter for survey questionnaire ............................................................................. 55 Apendix ii: Survey questionnaire ....................................................................................................... 56 Appendix iii: Coding and factor analysis of variable measures ......................................................... 58

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LIST OF TABELS Table 2.1: Comparison between DBB and DB delivery systems…………………………….12

Table 2.2: Summry of findings on different dimensions and perspective of projects success.18

Table 2.3: Competing strands of public procurement………………………………………...20

Table 4.1: Factor analysis validating research items...……………………………………….29

Table 4.2: Descriptive statistics, correlations and reliability tests……………………………30

Table 5.1: Results of the hypothesis tests…………………………………………………….38

LIST OF FIGURES Figure 1. Stages of a Construction project delivery process…………………………………10

Figure 2. Construction project success model.……………………………………………….11

Figure 3: Design-bid-build project delivery model.………………………………………….14

Figure 4. Design-build project delivery.……………………………………………………...14

Figure 5. Theoretical framework of research model………………………………………….22

Figure 6. Research process…………………………………………………………………...25

Figure 7: Positions held by respondents……………………………………………………...27

Figure 8: Frequency Distribution of Design Build…………………………………………...31

Figure 9: Frequency Distribution of Design-Bid-Build variable……………………………..32

Figure 10: Frequency Distribution of Emphasis on project control Variable………………...33

Figure 11: Frequency Distribution of Cost Minimisation Variable………………..................34

Figure 12: Frequency Distribution of Project Effectiveness Variable………………..............35

Figure 13: Frequency Distribution of Project Quality Variable……………….......................36

Figure 14: Interacion between DBB and DB systems………………………………………..39

Figure 15: Interaction between DB and cost minimisation………………..............................40

Figure 16: Interaction between DB and project control………………....................................40

LIST OF APPENICES Appendix I: Cover letter for survey questionnaire…………………………………………...55

Appendix II: Survey questionnaire…………………………………………………………...56

Appendix III: Coding and factor analysis of variable measures……………….......................58


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ABSTRACT Achieving projects success continues to be a challenge for project owners in public sector

organisations, and ambiguity in what defines project success makes it more challenging to

identify specific factors that affect it. The purpose of this study is to develop a theoretical

framework to examine the effects of design-bid-build (DBB) and design-build (DB) delivery

systems on project success from the owner’s perspective. The research investigates the extent

to which project success is determined by DBB and DB delivery systems when project

owners more or less emphasises cost minimisation versus project control. The link between

project success and project quality is also explored. Findings from a study of public sector

organisations in Ghana reveal a significant relationship between DBB and DB systems and

construction project success. The study finds that projects are more effective when the

delivery system in place is a combination of high levels of DBB and low levels of DB. The

study also finds that project effectiveness in the public sector in Ghana is enhanced when DB

is high and when emphasis on cost minimization is high. The study finds that projects are

more successful when high levels of DB are implemented and when owners emphasize higher

levels of control on projects. Thus, cost minimisation and project control do not seem to

influence the effect of DBB on project success. Finally, project effectiveness is found to be

positively associated with high levels of project quality.

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CHAPTER ONE

1. INTRODUCTION

1.1. An Overview Project delivery systems are critical for achieving project success as they entail an essential

aspects of an organisation’s strategic planning and management processes that seek to

minimise risks and uncertainties. It has been argued that one major factor that often derail

project success is poor management of the delivery system, such that in many occassions

underperforming delivery systems tend to undermine the inevitable uncertainties that need to

be overcome to avoid project failures (Smith, 1999).

The construction industry is one area of project management that has very much been plagued

with project failures. It has been contended that the diverse and multifaceted nature of

construction projects make it more “ difficult to plan for, forecast, manage and control”

(Smith and Jaggar, 2007 p.12), such that decisions taken in the preliminary stages of project

management process are critical to project success (Miller et al, 2000). For example, some

researchers have argued that “decisions made in the initial phases of a project’s life cycle

have a much greater influence on a project’s outcome than decisions made in later phases”

(Miller et al, 2000 p. 60). It has also been established that project success varies from

different perspectives (Davies, 2013) and can be looked at from multiple dimensions such as

achieving project objectives, user satisfaction, operational performance and functionality.

Projects are strategic activities “initiated to create economic value and competitive

advantage” (Shenhar et al, 2002 p. 699), and both large and small organisations in private and

public sectors undertake projects to achieve business goals and objectives. Therefore, the

effective execution and management of a project delivery system (PDS) as mentioned, should

be considered critical, as it has been found to be a major determinant of successful projects

(Doloi, 2012; Chen et al, 2011; Erikson Westerberg, 2010). However, a major concern in

project execution is the extent to which an appropriate PDS selected have long-term effects or

implications on project performance after completion. While there are multiple project

delivery systems [PDSs], design-bid-build (DBB) and design build (DB) are viewed as the

most widely adopted systems by both private and publics sector in the construction industry

(Chen et al, 2010, p. 599; Ameyaw, 2009). Both delivery systems are viewed to have the

potential to deliver owner satisfaction and achieve successful project outcomes. The


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characteristic strengths and weaknesses of both system’s effects on project success may

present an opportunity to project owners to adopt a combination or hybrid of both systems:

that is the impact of one system may reduce the negative effect of the other and inclusion of

other elements like construction management or facility management can improve the success

rate of projects realised though DB and DBB project delivery systems (Miller et al, 2000).

However, high levels of project success can be achieved if the effects of the project delivery

systems on project success are clearly established, and measures are taken by the owner to

eliminate or retain these effects to the benefit of stakeholders (Wang and Huang, 2005).

Studies indicate that the delivery method and the institutional context within which projects

are delivered has important implications for achieving project objectives and project owners

play a significant role in determining project success (Wang and Huang, 2005). These

authors also contend that the institutional context, developed versus developing, with its

related institutional supports and challenges can impinge on the capacity of organisations,

private or public, to attain project success (Ameyaw, Mensah and Osei-Tutu, 2012).

1.2. Research Gaps While some studies have looked at the several project delivery systems and their individual

impacts on project success, what is missing in the literature is the extent to which

combinations of these delivery systems could help aid project effectiveness (or success). Chen

et al. (2010), for example, suggest that there is a crucial need to combine PDSs systems for

superior project delivery success. This call is based on the assumption that both types of

delivery system has strengthens and weaknesses, such that, if well managed and leveraged,

they can compensate each other’s weaknesses for greater project success. Interestingly, the

existing literature is silent on the potential influence of the joint implementation of DBB and

DB delivery sysems on project effectiveness, and as such, this study seeks to address this gap

in the literature by looking at the extent to which DBB and DB, individually and jointly,

influence project effectiveness.

Furthermore, Chen et al. (2011) claim that “If the owner wants to control the project, it is

better to select DBB; if the owner wants to minimize the risk, DB would be a better choice”.

This later argument could be taken to imply that owner expectations and emphasis on cost

minimisation versus control of projects may act to facilitate or inhibit the extent to which any

one delivery system is perceived to affect project success. Interestingly, the mechamism that

explains this process, and empirical evidence supporting suggestions by Chen and colleagues’

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scanty. Therefore, this study aims to examine the extent to which effect of DBB and DB

delivery systems on project success are moderated by owner emphasis on control projects and

owners’ emphasis on minimizing cost.

Several scholars have also raised concerns regarding the validity of transfering knowledge of

project management from Western developed contexts to non-Western developing economy

contexts (e.g. Hoskinsson et al., 2000). The theoretical basis for this concern is that the

institutional context in developed nations and strikingly different from the institutional setting

in developing nations (Arnold and Quelch, 1998). For example, conditions in developed

nations, where the vast majority of empirical studies have been conducted on project delivery

system have been conducted, are advanced with modern sophisticated project delivery and

tracking systems. Yet, in developing nations, especially those in African nations such as

Ghana, institutions supportive of efficient project delivery (e.g. auditing system, modern

technology, and courts) are weak and complicated with poor enforcement of rules of business

transactions. In this respect, this study argues that it would be erroneous to simply transpose

know of project delivery systems in developed nations to developing nations with undertaking

thorough empirical assessment. Accordingly, the third purpose of the current study is to

investigate the project delivery systems and the contingency factors considered in the context

of public sector organisation in Ghana, a developing nation south of the Sahara.

1.3. Research Aim In sum, the study’s aim is to explore the effects of DBB and DB systems on construction

project effectiveness under differing levels of owner’s emphasis on cost minimisation and

project control. The study also looks at how project effectiveness influence project quality

under the assumption that project quality activities such as turnover quality, system quality

and equipment quality levels are of ultimate importance to project owners. The study’s

theoretical framework, is therefore, investigated in public sector organisations in Ghana,

providing opportunity to look at the relationships from developing economy perspectives.

1.4. Research objectives Thus, the specific objectives of the current study are threefold:

a. Examine the extent to which DBB and DB project delivery systems influence project

success, looking at success from an effectiveness and quality perspective;

b. Investigate the extent to which owner emphasis on cost minimisation and control

hinder or increase the effects of both systems on project success; and


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c. Look at how this phenomenon unfolds in a developing country like Ghana

1.5. Importance of the Study The theory of project delivery is a universal phenomenon that plays a major role in a nation’s

development and growth. The amount of financial and non-financial resource lost to failed

projects continues to increase annually in both developed and developing worlds. Since the

1980’s till present, attempts have been made by academics and industry professionals to

define and redefine project success (DeWit, 1988) identify critical success factors (Atkins,

1999) and key performance indicators (KPIs) of success (Chan and Chan, 2004; Toor and

Ogunlana, 2010) to achieve project success, develop quantitative models for selecting the

right PDS (Chen et al, 2010) and suggest management system for project success (Erridge and

McIlroy, 2002). Various dimensions have been explored, but it is an established fact that the

ambiguity of project success (Chan and Chan, 2004) poses a challenge to various stakeholders

including project/facility managers.

However, very little evidence exists on the impact a PDS has on project success with respect

to overall project quality. This study aims at developing a framework, which investigates the

relationship between PDSs like DBB and DB systems have on project success, when owner’s

(i.e. project managers) emphasizes on minimising cost and maximising control of the delivery

process. This present an opportunity for project/facility managers in developing economies

like Ghana and other parts of the world to make informed decision when selecting PDSs

based on its potential outcome of interaction with management function like control and

efficiency.

The remainder of the study is organised as follows. In Chapter two, a the existing literature is

assessed to determine the extent to further explain the gaps in the literature regarding the

project success outcomes of DBB and DB delivery systems. Chapter three focuses on

explaining the specific relationships studied by presenting specific arguments in support of

the study’s hypotheses. Chapter four provides details of the methodological approaches and

data collection activities undertaken. Chapter five presents analyses undertaken whereas

Chapter six discusses the implications and limitations of the findings from the study.

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Operation

CHAPTER TWO BACKGROUND

2.1 Definitions

2.1.1 Project delivery process A project process is defined as the key sequential steps followed in project executions, and

the level of detail is dependent of the “development methodology used” (Griffins Enterprise).

Smith (1999) suggests processes involved in undertaking a project rage between six to twelve

steps depending on the type of project. According to a book of knowledge (BoK) in the

construction industry, delivering a construction project involves eight processes as shown in

Figure 1 below. Thus, both DBB and DB systems constitute these processes, but the

difference in level of involvement of the project owners in the various stages, distribution of

tasks and project management responsibility. This is discussed further in chapter 3.

Figure 1. Stages of a Construction project delivery process

DESIGN (Owner) BID BUILD (Contractor) DESIGN (Contractor) BUILD (Contractor)

Adapted from Smith, N. J (1999)

2.1.2 Project success The basic criteria for determining construction project (CP) success has mainly been centred

on quantitative variables such as- cost, time and quality of specification (Atkinson, 1999;

Schenlar et at, 2002; Hwang and Lim, 2013; Ameyaw, Mensah and Aurthur, 2012; Toor and

Ogunlana, 2011; Meredith and Mantel, 2010; Yu et al, 2005) as mention earlier, commonly

referred to as the “iron triangle” by Roger Atkinson (Atkinson, 1999 p.337). But others

criticise the scope as narrow and inadequate since it fails capture non-quantitative and

subjective criteria based on stakeholder perception (Shenlar et al, 2002) and macro economic

benefits such as – operability, functionality, reliability and long-term gains (Mollaoglu-

Pre-‐feasibility Feasibility Design Contrant/ Pocurement implementation Commissioning Hand Over Operation


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Korkmaz, Swarup and Reily, 2011; Toor and Ogunlana, 2009b; Shcenlar et al, 2002). Various

studies reveal various critical success factors that influence CP success (Abraham, 2002;

Chen et al, 2010; Hwang and Lim, 2013; Meredith and Mantel, 2010; Yu et al, 2005), which

centre on factors shown in Chau’s (1999) model in Figure 2. The model illustrates the

interconnection between critical success factors in CP.

Figure 2. Construction project success model

Source: (Chau, 1999) Project success model cited in Abraham, (2002 p. 82). Identification of critical success factors in construction organisations.

Chua’s (1999) approach to identifying project success as described by Abraham (2002) is

based on levels of impact of the various factors through a process called the “analytical

hierarchy process (AHP)” (Abraham, 2002 p.82). According to his research, the main

determinants of project success are budget performance, schedule performance and quality

performance (Figure 3), consistent with the “iron triangle” theory of cost, time and quality

mentioned earlier. Chen et al (2010) and Hwang and Lim (2013) also adopted the AHP in

their study as listed in Table 2.1, to identify factors that influence selection of project delivery

systems in construction projects in China and to justify the adoption of specific PDS in

construction projects in Singapore respectively. The findings of these studies tell us, project

characteristics, contractual agreements, projects participants and interactive processes

influence the 3 main determinants of projects success as shown in Figure 2.

2.1.3 Project delivery system A project delivery system is a framework “designed to achieve the satisfactory completion of

a construction project from conception to occupancy” (CMAA, 2012 p.6), and the type of

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system adopted is dependent on the objective and type of the project in question. Therefore

based on this definition a PDS can be described as various processes required in materialising

the goals and objective of a client into a project through integrated project team efforts (Chen

et al, 2011).

Table 2.1: Comparison between DBB and DB delivery systems DBB – Design-bid-build DB – Design -build Project team Fragmented roles and Strongly

hierarchical hindering collaboration Integration of design and build team, open and collaborative

Risk Owner bears the greatest risk and contractor bears the least risk

Contractor bears greatest risk cost and construction risk, while owner bears minimal risk.

Process Linear, distinct and segregated, lack of knowledge flow

Concurrent and multi-level, early contribution and sharing of project knowledge.

Selection criteria of contractor

Mostly based on the lowest construction /bid price criteria, and rarely base on best qualification

Commonly based on best value and qualification criteria, price evaluation is base on fees and gross cost rather than construction cost

Control Owner bears maximum control of project delivery and management whiles contractor bears minimum control

Contractor bears a maximum control of design and construction process

Adapted from American Institute of Architects California council (2007 p.1)-Integrated project deliver: A Guide and CMAA (2012) Owners guide to project deliver methods p. 10-11 In table 1, the main characteristics of DBB and DB delivery systems are outlined to give a

clear indication of weaknesses and strengths of the systems.

A PDS acts as a “management function of the owner in project execution” (Chen et al, 2010

p.598), thus the PDS gives the owner added advantage in controlling key success

determinants- cost, time and quality. Based on Table 2.1, it can be said that emphasis on cost

and projecct control can contribut to increase in projects success. Other PDSs emphasize

management functions in project delivery to ensure success, example: contract-management

(CM), construction management at Risk (CMAR), engineering procurement construction

(EPC) and integrated project deliver (IPD) (CMAA, 2012).

2.1.4 Project delivery systems in Ghana In Ghana, the selection of PDS adopted is mostly dependent on the funding available for the

project (MOFEP, 2010), rather than the application of empirically tested models and

techniques for PDS selection. Complex, objective qualitative methods of selecting PDS, “has

invariably left project managers with no alternative than to make project delivery selection

decisions on the basis of subjective evaluations” (Oyetunji and Anderson, 2006).


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Given the historical background of Ghana’s economy1 coupled with challenges of limited

financial resources as in other countries, majority of projects are funded through “internal and

external borrowing, grants from bilateral and multi lateral sources and public-private-

partnerships” (MOFEP, 2010 p.5). The terms and conditions of financial agreements linked to

these funds have led to an increase in the adoption of DB system as the “better alternative”

(Asomoa-Amono, 2010 p.4), which eliminates benefits of competition and market forces.

The DBB is predominantly used in government funded project delivery in accordance with

Ghana’s Public Procurement Law 2003 guidelines (Act 663), to ensure accountability,

transparency, but studies reveal an increase in cost overruns, delayed completion,

unsatisfactory outcomes and unmet project objectives (Ameyaw, 2008). Thus, the adoption of

DB systems is deemed a solution to the limitation of DBB2 in construction project delivery

(Ameyaw, 2009).

“The decision made in the selection of a project delivery system for a project impacts all

phases of execution of the project and greatly impacts the efficiency of project execution”

(Oyetunji and Anderson, 2006).

2.1.5 Traditional (DBB) project delivery System In DBB systems “the owner acts as the general contractor/construction manager on its own

project” (AIA, 2007 P.44), the design and construction service are contracted to separate

entities as shown in Figure 3. This is characteristic of DBB systems are known to result in

implantation issues (Hale at al, 2007). It “involves three sequential phases” (CMAA, 2012) as

shown in Figure 1 earlier: the design, bidding and build phases. It has been proven to offer

some advantage in terms of accountability, transparency and control, and also securing good

market value, which has made it a more frequently adopted option by public sector

organisation (Trauner consulting service, 2007). Doloi (2012) and AIACC (2007) argue that

the DBB system are “complex, highly competitive, costly and time consuming” (Doloi, 2012

p.317; AIACC, 2007 p.44), and various studies attest to this (Frimpong, Oluwoye, Crawford,

2003; Ameyaw, 2008; Mustapha, 2013)

2.1.6 Design-build (DB) delivery System The DB project delivery system has been in existence since the 19th century, but has been

described as a modification and alternative to the DBB system (AIACC, 2007; Chen et al, 1 Anvuur and Kumaraswamy, (2006). Taking forward public procurement reforms in Ghana 2 Ameyaw (2009)

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2010). The adoption of this system by public sector organisation in Ghana has grown over the

past decades in parallel with the increase of private sector involvement in project delivery

(Ameyaw, 2009; Doloi, 2012)). “DB is characterised by a single point of responsibility for

both design and construction activities” (AACC, 2007 p.47) shown in Figure 4, and has been

proven to be more efficient in delivering construction projects compared to DBB systems

(Hale et al, 2009; Asomoa-Amono, 2010). DB allows form minimal control by the owner, but

allows for maximum transfer of “project-based risk” (AIACC, 2007 p.47) to the design-build

team. The outcome of project quality is dependent on the clarity of owner’s design criteria

and the competence of the design-build team. According to Xia (2010), various variations of

the DB system possess different strengths and weaknesses thus having clear project objectives

would help determine the system to adopt (Xia, 2010).

Figure 3. Traditional project delivery model Figure 4. Design-build project delivery model

Source: CMAA Owner’s guide to project delivery methods (2012) p. 12 &21

2.2 The Construction Industry - International perspective

The construction industry is a visible part of a country’s development and cuts across all

sectors of the economy (Smith and Jaggar, 2007) and “ the procurement route chosen

significantly impacts successful project outcomes” (Doloi, 2012 p.317). A number of internal

and external factors have been identified to affect successful project delivery and operations

(NAO, 2005; Ren, Kwao and yang, 2012), public sector projects are more complicated due to

the number of stakeholder’s involved (Hwang and Lim, 2013), and the constraints on

financial resources and unstructured project delivery system processes (Anvuur,

Kumaraswamy, Male, 2006). This elevates the challenge for project project managers.

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CMAA Owner’s Guide to Project Delivery Methods - August 2012

3.0 Project Delivery Methods 3.1 Design-Bid-Build (DBB) Description The Design-Bid-Build system remains the most frequently used delivery method for construction projects. Using this method, the owner engages a designer to prepare the design of the project, including construction drawings, and specifications. The designer may also provide additional services including environmental investigation, permitting, right-of-way purchase documents, hearings for public approval, and submissions for project funding. Once completed, the bid package, including the design and bidder’s information packet, is presented to interested contractors, who prepare and submit their bids for the work. The owner will select a contractor, usually based on the lowest responsive and responsible bid (for most all public work), or some hybrid of price and technical merit. The selected general contractor will then execute contracts with subcontractors to construct various specialty items. The contractor is responsible for constructing the facility in accordance with the contract documents. The designer typically maintains limited oversight of the work and responds to questions about the design on behalf of the owner. If a CM is not involved in the process, the designer may also assist the owner in administering the construction contract, including determination of project progress, for validation of interim payments made to the general contractor.

Risk Analysis

The DBB delivery method has been the standard delivery method for many years. This method gives the owner reliable price information for the project before construction starts. With proper design oversight and budgeting of the total project, costs are somewhat predictable for the owner once the bids are received. In DBB, the owner has more control over the design content, relative to other delivery methods.

However, this method typically involves a longer time period to execute, in that construction may not begin until the design and procurement phases are complete. DBB is prone to creating

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CMAA Owner’s Guide to Project Delivery Methods - August 2012

3.3 Design-Build (DB)

Description

The design-build (DB) project delivery system has grown in popularity, and is seen by some in the industry as a solution for addressing the limitations of other methods. For an owner, the primary benefit is the simplicity of having one party responsible for the design and construction of the project. While the other delivery systems often give rise to disputes among various project participants, with the owner acting as referee (or party ultimately to blame), in DB many of these disputes become internal DB team issues which may not affect the owner.

Under this system, the owner contracts with a DB team, which can be a joint venture of a contractor and a designer, a contractor with a designer as a subconsultant, a designer-led team with a contractor as a subcontracted entity, or a single firm capable of performing both design and construction. Since contractors are most comfortable in the role of risking corporate capital in performing projects, they usually are the lead members of this sort of team. One variation of the typical DB team structure, known as fee-paid developer, involves the owner engaging a developer, which then selects its own designer and contractor partners. However formulated, the DB team performs the complete design of the facility, usually based on a preliminary scope or design presented by the owner.

At some point early in the process, through a prescribed process, the DB team will establish a fixed price to complete the design and construction of the facility. Once underway, the DB team is then responsible for construction of the project, and for all coordination between design and construction.

Risk Analysis

Since the design-build team is working together from the outset, DB offers the opportunity to save time and money. However, the advantages of the system are offset by a significant loss of control and involvement by the owner and other stakeholders. Accordingly, it is difficult for the owner to verify that it is receiving the best value for its money without having a great deal of transparency in the DB team.


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In 2010 the Building and Construction Authority (BCA) in Singapore estimated between $21

billion - $27 billion in construction contracts, and between $18 billion and $25 billion in

2011 and 2012 respectively (Hwang and Lim, 2013 p.204). Similarly in England, the cost of

public sector construction projects completed between 2003 and 2008 is estimated £20

million (NAO, 2009 p.6). Needless to say, this confirms the role of construction projects in

economic growth of a country (Hwang and Lim, 2013), and minimising cost is critical.

Globalization has led to participation of international construction bodies in project delivery

in emerging economies like Ghana, this further complicates project delivery processes like

“negotiations, decision-making and problem solving” (Hwang and Lim, 2013 p.204).

Additionally, externalities such as “politics, economy, society and culture, as well as

“dynamic internal risks” (Kim et al, 2007 p.1961) pose challenges in controlling the execution

of PDSs.

Toor and Ogunlana describe the construction industry in Thailand as vibrant, diversified and

fragmented with various approaches of executing projects (Toor and Ogunlana, 2009), this is

not any different from the situation in Ghana and other parts of the world. “Design

complexity, personnel competence for the job, effective planning and control, commitment to

project goals, effective communication between project participants have been identified by

various studies as key factors leading to realisation of successful construction projects (Doloi,

2012; Toor and Ogunlana, 2007 p. 425; Fringpong, Oluwoye and Crawford; Arts and Finch-

Ell, 2012; Dainty, Cheng and Moor, 2003).

Notwithstanding, the ultimate challenge and responsibility lies with industry professionals

and practitioners implementing projects to ensure optimum completion, functionality and

operations of the project facility whiles delivering maximum satisfaction of all stakeholders

(Wang anf Huang, 2005). There is no empirical evidence that relates the effects of PDSs

adopted to the success or failure of construction projects, but it is pointed out that effects of

unintegrated processes/stages and project team efforts influence “optimal project out-comes”

(Mollaoglu-Korkmaz, Swarup and Riley, 2011p.71). PDSs like the DBB method present a

higher possibility of the latter (AIACC, 2007).

2.3. Construction Industry in Ghana The construction industry in Ghana is expanding rapidly, with majority of projects in

infrastructure development (Mustapha, 2013). In 2008 9.73 per cent of the country’s GDP

16

was invested in the construction industry (Ren, Kwaw and Yang, 2012), from both foreign

and local investors in both private and public sector. Weak public sector institutional support

and ambiguous legislative framework in the construction industry cause project delivery

systems to fail to deliver expected outcomes and stakeholder expectations (Charles, 2006).

The complex nature and uniqueness of construction projects as previously mention amount to

some level of uncertainty and changes during implementation, therefore control of the

delivery process and the owner’s emphasis on critical factors influence the outcome of the

project (Amaeyam, Mensah and Aurthur, 2011).

2.4 Previous Research Studies conducted on determining construction project success reveal that determining project

success varies with every project an perspectives (Davies, 2013), there is no established

framework or specific criterion for judging construction project success which makes it

difficult to measure (Griffin and Page, 1996; Chen et al, 2010; Hughes, Tippet and Thomas,

2003; Schenhar et al, 2003).

Studies confirm that, optimally integrating a PDS and the efforts of project management from

the start, delivers expected project outcomes, particularly the achievement of “sustainability

goals” (Mollaoglu-Korkmaz, Swarup & Riley, 2011p. 71). Way (2005) in his “framework of

soft landings”, introduces a systematic way of ensuring sustainability of projects by

integrating feedback of “continual assessment” of project design into the operation phase

(Way, 2005; BSRIA, 2009 p.8). Therefore in theory, regardless of the PDS adopted, positive

project outcomes should be achieved when projects participants ensure effective project

management practices (De Wit, 1988).

Toor and Ogunlana in their study of problems in large-scale construction projects in Thailand,

reveal that design related problems contribute to project failure (Toor and Ogunlana, 2010).

They go on to suggest that in DBB sytems, where design is executed separately from

construction, “a complete and comprehensive design is critical in the success of implementing

the projec”t (Toor and Ogunlana, 2008 p.426). Abandoned projects, delayed project

completion, high operational and maintenance costs, unsustainable project facilities and

project knowledge gaps are attributed to failed PDSs (Anvuur, Kumaraswamy, Male, 2006;

Ahadzie, Proverbs and Olomolaiye, 2007;Ren, Kwaw and Yang, 2012; Smith and Jaggar,

2007).


17

Doloi (2012) also identifies key risk attributes that influence cost, time and operational

performance of projects, and they include the “financial structure, government policy and

design complexity” (Doloi, 2012 p.316). He opines that, little emphasis is put on performance

of project facilities after completion due to the focus put on “project evaluation context”

(Doloi, 2012 p.316).

However, De Wit (1988) suggests “it is essential that a distinction is made between project

success and the success of the project management effort” (De Wit, 1988 p.164), where

project success is dependent on the degree to which project objectives are met (i.e. the impact

of the final project outcome), whiles project management success is dependent on meeting

time, cost and quality objectives (De Wit, 1988). Studies on project delivery do reveal

majority of project fail as a result of poor management of PDS (Ren, Kwaw and Yang, 2012),

but studies subsequent to his work integrate both project and project management success to

mean the same due to the evolution of the scope and demand of CP in recent times (Dainty,

Cheng and Moore, 2003). Heravi and Ilbeigi (2012), developed on the DeWits theory by

developing a quantitative model which evaluates project success based on the product success

(effect of the final product) and project management success (meeting cost, time and quality

objectives), and argues that the perspective considered in defining project success play a

critical part (Heravi and Ilbeigi, 2012).

The different dimensions and perspectives of project success identified from existing

literature are listed in Table 2.2. Its concluded that stakeholders perceive success based on

factors considered critical to their area of interest (Diallo and Thuiller, 2004; Griffin and

Page, 1996). For instance, an end users perspective of a successful project is based on

satisfaction derived (Lim and Mohamed, 1999).

18

Table 2.2: Summry of findings on different dimensions and perspective of projects success

Authors Dimension of project success Perspective of project success

Model/ technique to determine success

Haravi and Ilbeigi (2012)

Effects of final product Project management success

Contractor’s perspective Index-based model (Quantitative model)

Chinowsky, Taylor and Marco (2011)

Effectiveness of project knowledge and information transfer

Organisation’s perspective

Project Network Interdependency Alignment (PNIA).

Grau, Back and Prince, (2012)

Timely transfer of project knowledge

Alzahrani and Emsley (2012)

Overall project success (successful completion)

Post construction evaluation perspective

Logistic regression techniques and factor analysis

Mark way (1995)

Post construction occupation and operational performance

Operator/ end user perspective

Soft landing framework

Lim and Mohamed (1999)

Conceptual, Construction and operational phase

Micro and macro perspective

Conceptual theory

Toor and Ogunlana (2010)

Key performance indicators (KPIs) Construction stakeholder’s perspective

Empirical investigation

Hwang and Lim (2013)

Customer satisfaction and minimal professional liability

Construction participant’s perspective

Analytical Hierarchy Process (AHP)

Ling (2004) DBB Project performance Contractor’s perspective Performance metrics

Toor and Ogunlana (2007)

Relationship between critical success factors

Construction professional Factor grouping. COMs of success

Schenhar et al (2002)

Multidimensional; (1) Project efficiency, (2) Impact on the customer, (3) Direct business and organizational success, (4) Preparing for the future

Strategic perspective Project managers guidelines

Hughes, Tippett and Thomas (2003)

Objective (cost, schedule, performance and safety) and subjective (quality) success metrics

Project management personnel

(CPSS) Construction project success Survey tool

After a critical review of the varoius dimentions listed in Table 2.2, the research evaluates

success based on both objectve (cost, time and quality of specifications) and subjective

criteria (effectiveness and quality) from the owner’s perspective. David Potts (2002) talks

extensively about project appraisals as a technique used to determine the desirability and

feasibility of projects form different stakeholder perspectives (David Potts, 2002): for

instance, from an owner’s perspective, a successful project is one delivered within estimated

time, cost and according to specifications but from a contractors perspective this might be

dependent on profit margins and turn around (Reiss, 1995).


19

2.5 Role of the facility manager in project delivery

The role of the facility manger in any organization is to provide support services that satisfy

the clients business needs and support the core objective of the organization. Statistics of

projects failing and poor project performance implies the failure of both facility and project

manager to meet their client’s business needs (Brown, Hinks and Sneddon, 2001). The current

role of the facility/project manager:“strategic leader” (Schenhar et al. 2002 p.699) extends

beyond managing operations and processes and providing support services, but involves

executing strategic management strategy in executing project delivery systems to ensure

success (Schenhar et al. 2002). Having maximum control through consistent monitoring and

evaluation of project processes, enables “efficient positioning” (Doloi, 2012p.317) within

project management and allows efficient allocation of resources, sustainable project

performance and optimum project quality, while delivering on direct project objectives

(Meredith and Mantel, 2010; Shenhar et al, 2002). Brown, Hinks and Sneddon (2001) do

argue that, conventional practices and established roles of professionals in the construction

industry hinder best practice in project delivery at the management level (Brown, Hinks and

Sneddon, 2001).

Hence, “the core problem lies with the systems and approaches that are applied to the

management of new building projects rather than any technological or methodological issues

that are unique to construction” (Brown, Hinks and Sneddon, 2001 p.119).

The National audit office’s (NAO) (2011) study on 40 major projects in the United Kingdom

stated that quality of project initiation (planning and design) is “highly predictive of project

success” (NAO, 2011 p.4) over the long term. This supports the theory of this research that,

the PDS adopted can have long-term effects on efficient and effective operations after

completion.

2.6 Policy position In the UK, public procurement of works, products and services cover three main strands as

listed out in Table 2.3 (Erridge and McIlroy, 2002). Commercial, regulatory and social

considerations are taken into consideration when taking decisions on the how, what and who

is involved in the procurement process. Most often the commercial and regulatory aspects of

project delivery drives the delivery process, having more focus put on achieving the cost, time

and specification attributes of the project at the peril of the non-quantifiable aspects like

20

satisfaction and quality. This can be related to the situation in Ghana. In table 2.3, the last

column lists out the commercial, regulatory and social provision made in Ghana to address

the key themes listed. Table 2.3: Competing strands of public procurement. Strand Key themes Achieved through

(UK) Current situation (GHANA)

Commercial • Value for money

• Economy • Efficiency • Effectiveness

• Competition/competitive tendering Legislation

• Closer relationships with suppliers/Contractors

• Longer contracts (PFI/PPP) • Facilities management

• Competitive/ competitive tendering

• Longer commercial contract

Regulatory • Competition • Compliance • Transparency • Equality • Accountability

• EU Public Procurement Directives

• HM Treasury Tendering Procedures

• Organizational tendering rules

• Public procurement Act and guidelines

• Attorney general and PPA project approvals process

• MOFEP -Public borrowing and project selection guidelines

• Value for money Audit process.

Social • Public interest

• Employment concerns

• Environmental policy

• Best Value • Contract compliance • TUPE • Social exclusion • Economic development • Green buying guides

• Economic development

• Mandatory local content

• Inclusion of local suppliers

Adapted from Andrew Erridge and John McIlroy (2002). Public Procurement and Supply Management Strategies. Public Policy and Administration 17 (52) Drawing from the literature review, the operational definition of project success adapted for

this study is focused on two dimensions from the owners’/end-user’s perspective Drawing

from the literature review, the operational definition of project success adapted for this study

is focused on two dimensions from the owners’/end-user’s perspective

1. Effectiveness: An effective project outcome would imply that project objectives are met

(cost, time, specifications and safety), fitness of purpose and maximum end-user

satisfaction. (i.e. functionality and availability (Ling, 2005))

2. Quality: operational performance of final product (i.e. guarantees optimum service

delivery, minimum operational and maintenance costs) (Heravi and Ilbeigi, 2012).


21

CHAPTER THREE HYPOTHESES DEVELOPMENT 3.1 Overview This chapter develops a theoretical framework based on deductions made the literature

review, to address research objective of the study. The key variable are extracted from

research objectives listed below, to determine how they relate to each other.

a. Examining the extent to which DBB and DB project delivery systems influence

project success, looking at success from an effectiveness and quality perspective.

b. Investigating the extent to which owner emphasis on cost and control hinders or

increases the effects of both systems on project success.

c. Studying the extent to which project effectiveness serves as a mechanism through

which DBB and DB influence project quality and how these phenomenon unfolds in

a developing country like Ghana

3.2 Theoretical framework To guide the direction of the study and keep focus on research objectives, a theoretical

framework is developed (Cooper and Schindler, 2010) as illustrated in Figure 5. This was

based on the theory that, the adoption of either DBB or DB delivery systems can positively or

negatively affect the level of project success depending on the emphasis owner’s puts on

either cost minimisation or project control as shown in Figure 5.

To form this theoretical framework, seven variables were identified from the objectives of the

research, and further to this six hypotheses were developed for empirical testing. These

variable are discussed in the following subsections.

3.3 DBB and DB as independent variables The objective of the study is to determine the relationship between DBB and DB and project

success, by investigating whether they predict whether a project is successful or not: making

DBB are DB the independent variables. The DBB and the DB system are the most commonly

adopted systems and according to literature both systems have strengths and weaknesses that

could lead to and increase or decrease in he realisation of a successful project (AIACC, 2007).

22

Literature suggests that to ensure high level of quality in DBB projects, there should be a

balance between price and qualification selection criteria (Ling, 2005), and adopting DBB

system with an additional project/construction management function increases control over

execution and certain critical aspects which leads to project success (CMAA, 2012). The main

criticism of the DBB system is its failure to meet schedules and cost expectations (Ameyaw,

2009), and a lack of coordination between the design and construction phases (Tenah, 2001).

But Reiss (1995) argues, project objective are achieved based on the type and urgency of the

project and how its objectives are prioritised (Reiss, 1995). The first hypothesis is developed

based on this.

Hypothesis 1 (H1): High levels of DBB delivery system will have a positive effect on project

effectiveness.

Figure 5: Theoretical framework of research On the other hand, the DB system has been identified as an alternative to the DBB system.

Empirical evidence reveals it has delivered more projects within estimated time and budget

and offers higher stakeholder satisfaction in comparison to DBB (Xia and Chan,

2010;Ameyaw, 2009), but Chen et al argues DB does not deliver cost saving as claimed by

other studies, but rather limits the risk borne by the owner (Chen et al, 2010). Advantages of

Project success -‐Effectiveness

Design bid build (DBB)

Combination of DBB and DB

H1

H2

H3

H4 H5

Design bid build (DB)

Owner emphasis: -‐ Project cost minimisation -‐Project Control

Project Quality

H6


23

this system include project coordination due to the combined contracting of design and

construction phase, involvement of contractor in the design phase, which results in better

quality of design. (Tenah, 2001; Trauner consulting service, 2007). Criticisms of the system

include minimal involvement of owner in design and construction, little guarantee of client’s

expectations or technical specification due to the lack of checks and monitoring of on-going

works and the owner is allowed very little control of the process (Tenah, 2001). To determine

the effect of DB systems on project success, the second hypothesis is developed:

Hypothesis 2 (H2): High levels of DB delivery system will have a positive effect on project

effectiveness.

Miller et al (2000), in his study suggest the simultaneous adoption of multiple project delivery

methods. They argue that both DBB and DB systems can adopted in coherence, to take

advantage of their strengths for greater project success a third hypothesis is developed.

Hypothesis 3 (H3): The effect of execution of high levels of both DB and DBB delivery

system result in high project effectiveness

3.4 Cost and control as moderating variables The model of the DBB described in the previous chapter contracts separate entities to execute

the design and construction phase of projects, giving the owner maximum control over project

management, cost and final project outcome. Tenah (2001) describes the execution of DBB as

“sequential” (Tenah, 2001 p.33), which increases the potential for time and scheduled delays

that have cost implications (Meredith and Mantel, 2010). Whereas in DB systems, a single

entity is contracted to execute the design and construction of a project based on owner’s

requirements, meaning the final outcome is to a large extent determined to a large extent by

“competence, comprehension, communication and commitment” (Toor and Ogunlana, 2007

p.425) of contractor’s team. The model of the DB system allows for very little participation of

the owner and majority of the risk is transferred to the contractor (Xia and Chan, 2010).

Further to this, “If the owner wants to control the project, it is better to select DBB; if the

owner wants to minimize the risk, DB would be a better choice” (Chen et al claims, 2010).

The later could imply in this case that, owner emphasis on variables like control and cost may

24

act to facilitate or inhibit the extent to which the delivery system is perceived to affect project

success (project effectiveness and quality). Hypotheses 4 and 5 are developed to test this.

Hypothesis 4 (H4): The effect of DBB delivery system on project effectiveness will be higher

when owner emphasis is on cost minimisation and lower when owners’ emphasis is on

control.

Hypothesis 5 (H5): The effect of DB delivery system on project effectiveness will be higher

when owner’s emphasis is on project control and lower when owners’ emphasis is on cost

minimisation.

3.5 Project Quality It is argued there is distinction between achieving project/product success and project

management success (DeWit, 1988 and Heravi and Ilbeigi, 2012), where product success is

related to the attributes of the final outcome and project management success is related to

achieving pre-set objectives on cost, time and quality specification. To determine how DBB

and DB systems influence project success, not only in relation to a subjective criteria -

effectiveness (defined in Chapter 2) but also in relation to post completion success - project

quality. Hypothesis 6 was developed to discover whether project effectiveness was a

mechanism through which DBB and/or DB system can achieve project quality.

Hypothesis 6 (H6): The effect of high levels of project effectiveness (project success) is

related to greater levels of project quality.

In sum, based on literature reviewed six hypotheses were developed to determine the

relationship between independent variable-DBB and DB and dependent variable-project

effectiveness, and the role of moderating variables- cost and control on achieving project

success (effectiveness) in public sector organisation.


25

CHAPTER FOUR

RESEARCH METHODOLOGY

4.1 Overview The research methodology outlines the systematic approach adopted to achieve the objectives

of the research and provide empirical evidence to support it (Cooper and Schindler, 2010). To

undertake this investigation, a quantitative approach was adopted to provide empirical

evidence to explain the relationship between project delivery systems (DBB or DB)

implemented and key variables identified as critical in achieving project success (i.e. cost

minimization, project control), and how they interact to achieve project effectiveness and high

project (quality success).

The research followed a sequence of steps illustrated flow in Figure 6 below.

Figure 6: Research process

Adapted from (Creswell, J. 2003 P.5)

4.2 Data collection method Data gathered for the study was achieved using a questionnaire; which is a survey instrument

(McDaniel and Gates, 2012) commonly used for formal quantitative research. Data collection

was through self-administered questionnaires, which were distributed by hand in the research

environment (Ghana). Taking into consideration the characteristics of research environment

and limited time available to collect data and, hand delivering questionnaires was deemed the

most effective as compare to administering them via Internet or face-to-face interviews which

result in much lower response rates and require more time respectively.

Preliminary research on

topic

Literature review and

Design of survey

questionnaires & Data collection

Data analysis, testing

hypotheses & findings

Validate theoretical framework

26

4.3 Data Collection Instrument Designing the questionnaire for collecting relevant data for the study played a critical part in

the data collection process. To enable respondents to easily understand the questions and

make increase the willingness and ability to answer questions, clear and precise scaled-

response questions were used. This helped capture “measure of intensity of a respondent

answers” (McDaniel and Gates, 2012 p.348) defined by a 7 -point rating scale: 1 indicating

least extremity, importance expectation and 7 representing high extremity, importance

expectation of the statements listed in section 1, 2a and 2b respectively. This gave respondent

a balanced scale of measure. A total of 33 items were contained in the questionnaire

(Appendix II), 29 items measured conceived variables identified and four helped determine

the reliability of respondents. A total of 3 sections were created to capture information needed

to measure conceived variables. Section one contained eight questions focused on DBB and

DB delivery systems and processes involved, section two focused on project objectives

considered key and the level of achievement of these objectives and section three captured

information on individual characteristics of the respondent as a measure to ensure reliability

of respondent’s responses, this is attached in Apendix II.

4.4 Sample Frame In selecting the sample for the research, characteristics of respondents (i.e. the population of

interest) was taken into consideration (McDaniel and Gates, 2012). Based on preliminary

investigation and context of the research, a representative sample of public sector

professionals was drawn from public sector organisations, departments and ministries.

Specifically focusing on professionals working on projects or with prior experience and

understanding of project delivery systems to ensure reliability of responses. Due to limitation

of resources, the sample frame was predominantly focused on government departments and

sector ministries in the Greater Accra region for the convenience of their geographical

location (i.e. centrally located in the business district of the capital city). In sum, respondents

were drawn from five government ministries: Ministry of Health, Ministry of Education.

Ministry of Roads and Highways, Ministry of Energy, Ministry of Finance and Economic

Planning; three state owned companies and four public agencies (NHS estate management

unit, MOH project management unit and special projects units)

4.5 Response Rate


27

A total of 120 questionnaires were distributed, with the target of achieving a response rate of

80 per cent, but on completion of the survey 101 valid responses were received, giving a

response rate of 84.2 per cent higher that the set target. This provided adequate data for

statistical inferences for the research. The response rate of 84 per cent, which is very high,

could be as a result of the following factors:

1. Questionnaire were handed out manually to respondents by the researcher with a cover

letter (Appendix I) explaining the purpose of the study.

2. Familiarity of the researcher in dealing with public sector organisations due to prior

business relationships with various sectorial Ministries.

3. Clarity of questions and type of questions used could have influences the respondents

willingness to complete the questionnaires

4. Familiarity of the researcher with working with various sector ministries prior to the

research facilitated distribution of questionnaire and increased access to respondents.

4.6 Characteristics of Respondents After conducting the survey, total questionnaire retrieved was 101 completed by professionals

working in public sector organisations in Ghana. The breakdown of roles of respondents

included 18.8 per cent directors, 38.6 per cent project managers, 13.9 per cent consultants and

24.8 per cent in the “others” category of project related roles shown in Figur 7. Further

analysis revealed, the average managerial experience of respondent to be 5years, one year

being the minimum work experience and 30 years being the maximum.

Figure 7: Positions held by respondents

20%

40% 14%

26%

Positions held by respondents

Directors

Project managers

Consultants

Others

28

4.7 Data Analysis Having cleaned the data collected, including imputation of missing values and recoding of

variables (Tabachnick and Fidell, 2007), a series of statistical analysis was performed using

the Statistical Package for the Social Science (SPSS) data analysis software to enable

further exploration of the characteristics of the variables understudy to validate the research

theory. In following recommended procedures (e.g, Hair et al., 2006), the following sets of

statistical analyses were carried out:

1. Validity and reliability of questions (items)

2. Summation of the items to create new variables for further inference.

3. Calculation of correlation and descriptive statistic values

4. Moderated regression analysis

5. Mediation analysis of variable

4.7.1 Reliability test First, reliability of all multi-item constructs (that is constructs that were measured with

multiple questions or statements) was undertaken. Hair et al. (2006) and Nunnally and

Berstein’s (1994) recommendation for the use of Cronbach’s Alpha was used to estimate the

reliability of the items. Cronbach’s Alpha analyses the internal consistency of sets of items

that are purported to measure a specific unobservable variable (Nunnally and Berstein, 1994).

High values of Alpha values (α >.60) are recommended. Accordingly, all variables were

tested to ensure that they exhibited high alpha values. Where a specific variable contributed to

poor alpha value, that variable is deleted accordingly. Consequently, Table 4.1 was produced

to show the level of reliability of each multi-item construct. As Table 4.1 shows, all variables

exceed the recommended cut off range for reliability. The lowest alpha value is .605 (project

effectiveness) and the highest is .873 (design build). Furthermore, an inspection of Table 4.1

indicates that where sets of variables are required to correlate highly, this was uncovered (e.g.

design build versus Design Bid Build). Thus, all variables can be viewed as internally

consistent throughout.


29

Table 4.1: Descriptive statistics, correlations and reliability tests

Note: **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Inter-variable correlations are reported at the lower half of the diagonal, and the alpha reliability values are reported in the diagonal.

4.7.2 Validity test Having demonstrated the reliability of the constructs’ measurement items, there was a need to

show that the variables are also valid (Hair et al., 2006). The psychometric literature

recommends that convergent and discriminant validities show be established (Nunnally and

Bernstein, 1994). Thus, to assess the validity of the measures all items were further examined

using exploratory factor analysis (EFA) in SPSS. The purpose of the factor analysis was to

determine the convergent and discriminant validity of the items used to measure each variable

(Hair et al., 2006) and also sum up variable measures(items) into factors (McDaniel and

Gates, 2012 p.616). That is to determine whether the various items used in the questionnaire

are able to measure factors listed in Table 4.1, this allowed for purification of the preliminary

item for further validation. As shown in Table 4.2, it is clear that 21 items out of the 29 used

(Appendis III) in the questionnaire load significantly on its respective factor (or variable) and

each item also discriminates from other variables they are not required to load on, thus,

confirming convergent and discriminant validity.

Variable Mean Standard Deviation 1 2 3 4 5 6 7 8

1 Managerial experience 5.77 3.827 -

2 Company type - - -.266** -

3 Design Build 4.871 1.405 .081 .074 .873

4 Design Bid Build 5.272 1.184 .141 -.025 .559** .781

5 Emphasis on Project Control 5.695 .995 .102

-.118 .375** .488** .812

6 Emphasis on Cost Minimisation 5.356 .821

-.398** .172 .299** .217* .309** .715

7 Project Effectiveness 5.059 1.353 -.322** .152 .184 -.023 .122 .612** .605

8 Project Quality 5.670 1.102 -.260** .102 .119 .024 .249* .602** .509** .725

30

Table 4.2: Factor analysis validating research items Composite

Variables/ Factors

Questions (Items)

Factor Loading

1 Design Bid Build 1. Normally use two or more solicitations and procurement steps to complete one construction project

2. Often enter into a contract with an architect/engineer firm that provides design services based on the requirements we provide

3. Typically ask an architect/engineer firm for deliverables including plans and specifications for the construction of the project

4. Normally use these deliverables as a basis to make a separate contract with a construction company

.697 1.011 .698 . 730

2 Design Build (DB)

1. Award a contract to one company who will both design and build a project for us

2. There normally is only one procurement step to select one construction company to complete a project

3. Often allow one contract between us and one construction company

.717 .760 .799

3 Project Control

1. Meeting or exceeding schedule objectives 2. Emphasizing operational safety in the design philosophy 3. Emphasizing safety in construction 4. Attaining high quality of the constructed facility 5. Minimizing contractor scope changes

.542

.761

.879

.643

.618 4 Cost minimisation 1. Unit cost

2. Cost growth 3. Schedule growth 4. Development cost

.668

.553

.655

.643 5 Effectiveness

1. Construction speed 2. Delivery speed

.667

.637 6 Project Quality 1. System quality

2. Equipment quality 3. Meeting quality specifications

.673

.671

.701

4.7.3 Descriptive Analysis

Having shown that the variables were both reliable and valid, new scores were then created

from the original observed variables. Table 4.1 shows the new variables and their respective

means and standard deviations. Descriptive analysis of each scale was carried out to show that

each scale was normally distributed for hypothesis testing purposes (Hair et al., 2006).

Descriptive analysis was performed to determine whether the means values of variables were

approaches a normal distribution. The values for each variable were subject to descriptive

analysis focusing on skewness or range of the data distribution. The analysis revealed the

values of the variables were fairly normally distributed as shown in figures 7 to 12. Therefore,

the scales can be used to perform hypothesis testing.


31

4.7.3.1 Design Build The frequency distribution of DB variable measure is shown in Figure 8, with mean value of

4.871 and standard deviation of 1.405 with no missing values. The figure shows a fairly

normal distribution of sample data, thus implying the items measured can be used in carrying

out a regression analysis

Figure 8: Frequency Distribution of Design Build

32

4.7.3.2 Design Bid Build The frequency distribution of DBB variable measure is shown in Figure 9, with mean value of

5.272 and standard deviation of 1.184. The figure shows the values are fairly normally

distributed, implying that a regression analysis can be successfully carried out.

Figure 9: Frequency Distribution of Design-Bid-Build variable


33

4.7.3.3 Project control The frequency distribution of the project control variable measure is shown in Figure 10, with

mean value of 5.70 and standard deviation of .995. The figure shows the values are fairly

normally distributed, implying that a regression analysis can be successfully carried out

Figure 10: Frequency Distribution of Emphasis on project control Variable

4.7.3.4 Cost Minimisation The frequency distribution of the cost minimisation variable measure is shown in Figure 11

below, with a mean value of 5.36 and standard deviation of .821. The figure shows the values

are fairly normally distributed, implying that regression analysis can be successfully carried

out.

34

Figure 11: Frequency Distribution of Cost Minimisation Variable

4.7.3.5 Project Effectiveness The frequency distribution of the project effectiveness variable measure is shown in Figure

12, with mean value of 5.06 and standard deviation of 1.353 with no missing values. The

figure shows a fairly normal distribution of sample data, thus implying the items measured

can be used in carrying out a regression analysis.


35

Figure 12: Frequency Distribution of Project Effectiveness Variable

4.7.3.6 Project quality The frequency distribution of frequency variable measure is shown in Figure 13, with mean

value of 5.67 and standard deviation of 1.102 with no missing values. The figure shows a

fairly normal distribution of sample data, thus implying the items measured can be used in

carrying out a regression analysis.

36

Figure 13: Frequency Distribution of Project Quality Variable


37

CHAPTER FIVE FINDINGS 5.1 Results of Regression Analysis After demonstrating that the items used to measure each construct are reliable, valid and

normally distributed, hierarchical moderated regression analysis was undertaken using

ordinary least square approach, in line with the literature (Hair et al., 2006). First of all, to

analyse the effect of DBB and DB on project effectiveness, multiple regression analyses was

used in Model 1. Then secondly, bivariate regression was used to analyse the effect of project

effectiveness on project quality in Model 3, which is considered the final outcome of project

success. Finally, to examine how DBB and DB interact with each other, and to test the extent

to which owners’ emphasis on project cost minimisation (i.e. efficiency) versus project

control, hierarchical moderated regression was used. The use of multiplicative interactions in

regression analysis has the potential to introduce multicollinearity (i.e. increase correlation

between the independent variables), which makes interpretation difficult. Therefore, before

the moderated regression was undertaken, all the independent variables were mean-centred

(i.e. the means values were subtracted from the originally averaged variables) (Aiken and

West, 1991). As can be seen in Table 5.1, the variance inflation factors (VIF) of all variables

included in the moderating effect analysis remain substantially below the minimum cut-off

point of 10 (Hair et al., 2006).

To examine the hypotheses themselves, three regression models were estimated. The first

model looked at the direct effects of DBB, DB, cost minimisation and control on project

effectiveness. Model 1 produced an R2 value of 41%, which is a sufficient explanation of the

variance in the dependent variable and an additional 8% variance was explained when Model

2 was estimated (Tabachnick and Fidell, 2012). Looking at Table 5.1 further, it can be seen

that DBB has negative relationship with project effectiveness (β = -.225; t-value = -2.223; p <

.05), while DB has a significant positive relationship with project effectiveness (β = .126; t-

value = 1.290; p < .10). Therefore, it could be argued that DBB and DB have opposing effects

on project effectiveness, which is interpreted as, when the effectiveness of one system

increases, the effectiveness of the other system decreases. This could therefore be taken to

mean, when both system are implemented simultaneously, they provide competing

implications for project managers.

38

While the above results may be taken to imply H1 is rejected and H2 is supported, one also

needs to be cautious in drawing conclusions from the above results due to the nature of H3, H4

and H5. For example, it can be said that H1 and H2 are part of H3, such that if H3 is supported,

H1 and H2 are rejected. Looking at Table 6 again, the combined effect of DBB and DB on

project effectiveness is negative and significant (β = -.192; t-value = -1.464; p < .10), which

can be taken to mean that H1, H2 and H3 are all rejected. However, looking at the moderating

impacts of cost minimisation and project control on DBB/DB – project effectiveness

relationship, some more interesting findings are uncovered.

Table 5.1: Results of the hypothesis tests

First, focusing on the effect of cost minimisation, it was found that the effect of DBB and cost

minimisation interaction on project effectiveness was non-significant (β = .081; t-value =

.771; p>.10), while the DB and cost minimisation interaction is significantly negative (β = -

.136; t-value = -1.457; p<.10). Further to this, the effect of the interaction between DBB and

project control is positive but non-significant (β = .177; t-value = .862; p>.10), whereas the

effect of the interaction between DB and control on effectiveness is positive and significant (β

= .259; t-value = 1.385; p<.10). These later findings imply that H1 and H4, corresponding to

the effect of DBB on effectiveness are consistently rejected under all conditions considered.

Thus, high levels of DBB lead to decreases in project effectiveness (i.e. project success), even

when owners emphasis either cost minimisation or project control.

Collinearity Statistics

Project effectiveness Projectquality Tolerance VIF

Model 1 Model 2 Model 3

DBB

β t β t β t .598

1.674

-.225

-2.223

-.096

-.826

DB .126 1.290 .090 .825 .649 1.541 Emphasis on cost minimisation .626 7.428 .592 7.055 .865 1.156 Emphasis on Control -.009 -.095 .099 .983 .712 1.404 DB x DBB -.192 -1.464 .330 3.032 DBB x Cost minimisation .081 .771 .521 1.919 DB x Cost minimisation -.136 -1.457 .655 1.527 DBB x Control .177 .862 .135 7.426 DB x Control .259 1.385 .163 6.135 Project effectiveness .509 5.891 Model fit characteristics R2 (% of variance explained) .410 .482 .260 ∆R2 (Change in % of variance) - .082 -


39

1

1.5

2

2.5

3

3.5

4

4.5

5

Low DBB High DBB

Proj

ect e

ffec

tiven

ess

Low DB High DB

On the other hand, high levels of DB are found to be related to increases in project

effectiveness and these positive effects further is amplified when owners’ emphasis on control

is greater and when owners’ emphasis on cost minimisation is lower. Thus, H2 and H5 are

supported. In sum, the study concludes that the impact of DBB and DB on project success is

not simply a matter of a direct relationship, but rather a question of how these project delivery

systems are managed together, and the extent to which owners emphasises cost minimisation

versus control.

Finally, the study looks at the extent to which project success or effectiveness is related to

project quality levels. From Table 5.1, it can be seen that project effectiveness explains 26%

variation in project quality, and its effect on project quality is significant at 1% level (β =

.509; t= 5.891; p<.01). Thus, H6 is strongly supported, suggesting that higher levels of project

effectiveness are related to greater levels of project quality.

5.2 Plotting the interactions The significant interaction effects are now reported in figures 14 to 16 below. Looking at

Figure14, it is obvious that the best fit between DBB and DB is when DBB is high and when

DB is low, suggesting that at least within the context of the public sector organisations in

Ghana, projects are more effective when the delivery system in place is a combination of high

levels of DBB and low levels of DB.

Figure 14: Interaction between DBB and DB delivery systems

40

In the interaction between DB and cost minimisation, the best scenario for project

effectiveness in the public sector in Ghana is when DB is high and when emphasis on cost

minimization is also high as shown in Figure 15 below.

Figure 15: Interaction between DB and cost minimisation

Finally, from the interaction plotted in Figure 16, it can be said that projects are more

successful when high levels of DB are implemented and when owners emphasize higher

levels of control on projects

Figure 16: Interaction between DB and project control

1

1.5

2

2.5

3

3.5

4

4.5

5

Low DB High DB

Proj

ect e

ffec

tiven

ess

Low Cost minimisation High Cost minimisation

1

1.5

2

2.5

3

3.5

4

4.5

5

Low DB High DB

Proj

ect e

ffec

tiven

ess

Low Control

High Control

41

CHAPTER SIX

CONCLUSION, IMPLICATIONS AND LIMITATIONS 6.1 Conclusion The purpose of this research was to investigates the individual and joint impacts of DBB and

DB on project effectiveness (project success) under differing levels of owner’s cost

minimisation and project control emphasises and how project effectiveness eventually relates

to project quality outcome. This theoretical framework is studied within the context of public

sector organisations in Ghana. The argument put forward is that, the appropriateness of a

PDS adopted can positively or negatively affect project success dependent on whether or not

their joint implementation is preferred to implementation of individual PDS, and owner’s

emphasis on achieving cost minimisation or project control in construction projects. Findings

indicate that DBB and DB combination is strongly related to high levels of effectiveness

(project success), with latter also positively related to quality outcomes of construction

projects. Findings also indicate that projects are more effective when the delivery system in

place is a combination of high levels of DBB and low levels of DB. The study also finds that

project effectiveness in the public sector in Ghana is enhanced when DB is high and when

emphasis on cost minimization is high. The study finds that projects are more successful

when high levels of DB are implemented and when owners emphasize higher levels of

control on projects. Thus, cost minimisation and project control emphases do not seem to

influence the effect of DBB on project success. Theoretical, managerial and policy

implications of these findings are discussed below.

6.2Discussion and Implications Key findings reveal that DBB systems have direct negative effect on project success whiles

DB system has a direct positive affect on project success, confirming the theory that the

appropriateness of a PDS adopted directly impacts the outcome of the project (Chen et al,

2010). The finding that DBB negatively influence project success and DB having a positive

impact implies that the two delivery systems interact with each other to influence project

success outcomes. Over and above the direct effects, when the interaction term of the two

delivery systems are examined, a significant interaction effect was uncovered. These findings

suggest the effect of one system influences that the impact of the other system, confirming

Chen et al. (2010) contention that the two traditional delivery systems work in tandem to

42

driver project success. Thus, a theoretical implication here is that when the effectiveness of

one system increases, the effectiveness of the other system decreases and the vice versa.

When both systems are adopted simultaneously the outcome is superior relative to when the

systems are adopted in isolation.

A practical implications for project managers is that, adopting high levels of DBB systems

(i.e. contracting design and construction services independent of each other, selecting

contractor solely based on lowest bid criteria according to the norm without

construction/project management functions in place) will have negative effects on project

success. On the contrary high levels of DB systems with emphasis on control relate to

increase in project success. This implies that contracting of a single entity in executing design

and construction phased has positive effect in project delivery, but the project manager must

ensure participation in both design and construction phases to achieve project success.

Focusing on reducing cost in DB systems, can lead to the contractor providing inferior

designs and low quality construction service, which will negatively affect project

effectiveness and overall quality.

Key finding if the study supports the theory that PDSs are directly related to project success

and the final quality outcome of projects (Chen et al, 2010), and further illustrates there could

positive benefits when these systems are implemented together to complement each other

(Miller et al, 2000). Additionally, when factors like cost minimisation and project control are

emphasised by the owner in the implementation process, the effects could be greater. Chen et

al suggests that PDSs provide owners channel to control and manage the execution process

(Chen et al, 2010), and the significant effect of DB on project success when project control is

high proves this as H5 was supported. Drawing from the finding we realise that DB has a

positively significant effects on project success when there is moderated by project control.

The same cannot be said for DBB; its interaction with project success is negative and when

moderated by cost or control does not yield a significant effect: hence the rejection of H1 and

H4. This can be explained the characteristics of the DBB system that appoints separate

entities to execute design and construction phases, which increases the possibility of gaps or

lapses in project execution resulting in undesired project outcomes poor project coordination

and delayed execution of project phases (AIACC, 2007; Tauner consulting service, 2007;

CMAA, 2012). The implication for manager is some delivery systems like the DB offer better

medium for owners to achieve a high level of project success when the owner’s objective is

43

to control aspects of the delivery system. Meredith and Mantel (2010) emphasizes the need

for a project management to ensure efficient allocation of resources and control project

activities (Meredith and Mantel, 2010).

Looking at the effects of combined interaction of DBB and DB systems with project

effectiveness, the best scenario to adopt is when high levels of DBB and low levels of DB are

implemented in a project. From the analysis it was revealed that simultaneously

implementing DBB and DB present competing implications to project managers, therefore

there should be a balance or. This supports Ibbs et al’s (2003) assertion that “no project

delivery system can be deemed appropriate for a specific project” (Ibbs et al, 2003 p.382),

and the adoption of multiple project systems “allows for greater public benefits” (Miller et al,

2000 p.66). Implication here is, both systems possess positive attributes that when managed

can contribute to effective projects, therefore it will be presumptuous of public sector owners

to select one system over the other without considering the benefits of implementing both in

DBB and DB in varying proportions.

Looking at the moderating roles of emphasis on cost minimisation versus project control on

DBB and DB and how this affects project effectiveness, very interesting observation were

made in relation to DB system. Findings from the study reveal that cost minimisation

negatively moderates achieving high levels of project success when high levels of DB are

implemented with high emphasis on cost minimisation. From literature, it’s gathered that DB

systems restrict the involvement of owners (Table 2.1) in the design and construction phases

and in controlling cost, project schedules and technical specification (Tenah, 2001; AIACC,

2007). This supports Hughes, Tippett and Thomas’s claim that the competence and

experience of the design-build team affects quality of DB projects (Hughes, Tippett and

Thomas, 2003). The implication here for the project owner is that, when adopting DB

systems in project delivery there should be checks and balance measures in place to minimise

cost or the adoption on robust price evaluation techniques should be used when allocating

project budgets.

On the other hand the interaction of DBB and cost minimisation was positive but non-

significant, which implies, emphasis on cost in DBB projects has relation to achieving project

success. Implying that, when project owners adopt DBB system to deliver a project focusing

on reducing cost will not necessarily increase or decrease the possibility of achieving a

44

successful project therefore efforts should be made in emphasising other aspects like process

integration (Way, 2005) or system management (DeWit, 1988).

Cost attributes of a project is identified by most studies as a critical factor/ criteria for

determining or measuring success of a project, and this is usually defined by meeting

budgets, avoiding cost overruns and getting value for money (Atkinson, 1999; Dainty, Cheng

and Moore, 2003; Ahsan and Gunawan, 2009). DeWit argues that, cost measure the progress

of a project not success (DeWit, 1988), but based on the afore mentioned, it can be said that

cost is a priority of most project participants, in terms of cost savings for owner and

minimum risk: profit margins and minimal expense for contractors and best value for project

stakeholders in general.

Cost minimisation as a moderating factor for achieving project success as shown earlier, has

a negatively significant effect on project success when emphasized its emphasized. This

could imply two things in relation to project owners: first emphasis on cost minimisation in

DB system can lead to selecting contractors based on lowest construction price at the expense

of high quality service or materials and secondly, setting early budgets which provides little

room for accommodate proposed changes by the contractor to increase project quality or

contingencies that might have cost implications (Ling, 2005).

For policy makers in public sector organisations, the implication here is, other factors should

be considered when selecting DB or DBB systems. Selecting a PDS based solely on financial

objectives can lead to increased possibility of unsuccessful projects especially in DB.

Empirical evidence shows there has been a 5% increase in the adoption of DB systems (Chen

et al, 2010 p.598) as an alternative to DBB systems due to 30% faster delivery time and 13%

cost reduction (Ameyaw, 2009 p.3), even though the impact is negative in this case it might

hold true in other sectors due to the uniqueness and variation of each project.

Having adequate control of a PDS translates into various positive outcomes like meeting

schedule of works, effective communication, effective allocation of resources and achieving

project and project management objectives. As mentioned earlier in chapter 2, making the

distinction between project success and project management success (Haravi and Ilbeigi,

2012) allows for project manager to develop effect strategies in approaching project

execution (Griffin and Page, 1996). Hence, project control as a moderating factor of the

45

effects of DBB and DB on project effectiveness reveals a positive but non-significant

relationship with DBB and a positive and very significant effect of their interaction.

This reveals that when a DBB system is adopted, project success may or may not be achieved

irrespective of emphasis put on project control. Implying that, to achieve successful project

though DBB systems emphasis can be put on other critical factors identified in literature like

process integration (Way, 2005) or effective construction management (CMAA, 2012) aside

control. The significant interaction effect further confirms that projects are more successful

when high levels of DB are implemented and when owners emphasize higher levels of

control on projects.

Effectiveness in the context of this study was identified as the desired outcome of a

successful PDS project, and further to this it was determined how effectiveness related to

project quality. Based on the analysis, there was a significant relationship between the two:

high levels of project effectiveness were related to greater levels of project quality.

When the end product of a project (i.e. the project facility) is realised through either DBB or

DB system, and it’s able to deliver optimum services and function as its expected, it can be

said that project success (effectiveness) is achieved but the operational performance of the

project after completions attests to the level of quality attained. The implication of this to

project/facility mangers is that, project quality is not dependent on whether DBB or DB

system is adopted, but depends on the level of success of the outcome of the project (i.e. in

this context the level of project effectiveness). Bearing in mind project success varies from

project to project Meaning certain factors need to be present to improve project quality,

examples include superior design and equipment quality, competent project participants,

functionality and availability of facility, empirical evidence from research work by Ling

(2005) confirms that adopting DBB or DB does not directly relate the level of project quality

achieved (Ling, 2005).

6.3 Limitations and suggestions for future research

Limitations of this study were in relation to collection and analysis data. First of all, manually

distributing questionnaires was discovered to be the most effective method for the research

environment, due to difference in culture and technological inclination of public sector works

46

in most developing economies like Ghana. Despite the introductory letter attached to the

questionnaire to explain the purpose of the survey, some respondent were apprehensive about

disclosing information willingly.

Another limitation was the possible effect of the sample size of the data set. Perhaps the

statistical power (correlation coefficient) of variables understudy could have influenced,

resulting in high multicollinearity. Subtle interaction between variables that were interpreted

as non-significant below 5% could have been significant in a larger sample size (Kahane,

2008).

Considering the findings of this study, ther is an opportunity for furthe studies to discover

how applicable this theory is to other project delivery systems, and investigate how emphasis

on cost and control affect project success and if possible how other moderating variables like

time interacts with project success. In addition investigating the theory in the context of

private sector organisations and perspective, can determine the generalization of the findings

in the study.

It would be interesting to study a larger sample to find out if there could be a significant

relationship between DBB and project effectiveness when owner’s emphasis is on cost

minimisation or project control , and also discover the resulting effects on project quality.

47

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APPENICIES

Appendix I: Cover letter for survey questionnaire

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APENDIX II: Survey questionnaire SECTION 1: REGARDING YOUR PROJECT DELIVERY SYSTEM To what extent does your project delivery system follow the following processes? Please circle the number that best describe the condition in your organization.

In our organization we:

Not at all

Neutral

To an extreme extent

1. normally use two or more solicitations and procurement steps to complete one construction project 1 2 3 4 5 6 7

2. often enter into a contract with an architect/engineer firm that provides design services based on the requirements we provide 1 2 3 4 5 6 7

3. typically ask an architect/engineer firm for deliverables including plans and specifications for the construction of the project 1 2 3 4 5 6 7

4. normally use these deliverables as a basis to make a separate contract with a construction company 1 2 3 4 5 6 7

5. we tend to provide requirements for

specific projects 1 2 3 4 5 6 7 6. we award a contract to one company

who will both design and build a project for us 1 2 3 4 5 6 7

7. there normally is only one procurement step to select one construction company to complete a project 1 2 3 4 5 6 7

8. we often allow one contract between us and one construction company 1 2 3 4 5 6 7

SECTION 2: REGARDING YOUR PROJECT OBJECTIVES A. To what extent does your organization consider the following project objectives important to the success of projects?

Extremely unimportant

Somewhat important

Extremely important

1. Meeting or exceeding our cost objectives 1 2 3 4 5 6 7

2. Meeting or exceeding schedule objectives 1 2 3 4 5 6 7

3. Emphasizing operational safety in the design philosophy 1 2 3 4 5 6 7

4. Emphasizing safety in construction 1 2 3 4 5 6 7

5. Attaining high quality of the constructed facility 1 2 3 4 5 6 7

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6. Maximizing plant reliability 1 2 3 4 5 6 7 7. Achieving customer satisfaction 1 2 3 4 5 6 7 8. Optimizing risk/return 1 2 3 4 5 6 7 9. Minimizing contractor scope changes 1 2 3 4 5 6 7 10. Minimizing risk 1 2 3 4 5 6 7 B: To what extent has your organization achieved its project objectives in terms of the following indicators? Below

expectation

Average Above

expectation 1. Unit cost 1 2 3 4 5 6 7 2. Cost growth 1 2 3 4 5 6 7 3. Development cost 1 2 3 4 5 6 7 4. Construction speed 1 2 3 4 5 6 7 5. Delivery speed 1 2 3 4 5 6 7 6. Schedule growth 1 2 3 4 5 6 7 7. Turnover quality 1 2 3 4 5 6 7 8. System quality 1 2 3 4 5 6 7 9. Equipment quality 1 2 3 4 5 6 7 10. Meeting quality specifications 1 2 3 4 5 6 7 11. Meet client satisfaction 1 2 3 4 5 6 7 SECTION 3: ABOUT YOURSELF The next set of questions seeks to learn a little bit about you. 1.

What is your job title?

2. What would you consider to be your employment role? Please circle the most

appropriate number.

[1] Director [2] Project Manager [3] Project Consultant [4] Other, please specify: 3. How long have you been with your

company?

4. Type of

organization

[1] State owned [2] public liability limited [3] Non-‐governmental organization [4] Government department/ministry [5] Other, please specify:

-‐-‐-‐-‐-‐-‐This is the end the questionnaire. Thank you for participating in this study-‐-‐-‐-‐-‐-‐

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Appendix III: Coding and factor analysis of variable measures

DBB = Design-bid-build DB = Design Build CONT = Project control COST = Cost minimisation EFFEC = Effectiveness QUAL = Project Quality ‡ = Items that were droped due to poor factor loadings

Item code Item Item code item DBB1 Normally use two or more

solicitations and procurement steps to complete one construction project

COST1‡ Meeting or exceeding our cost objectives

DBB2 Often enter into a contract with an architecture/engineering firm that provides design services based on the requirements we provide

COST2‡ Optimizing risk/return

DBB3 Typically ask an architecture/engineering firm for deliverables including plans and specifications for the construction of the project

C0ST3‡ Minimizing risk

DBB4 Normally use these deliverables as a basis to make a separate contract with a construction company

COST4 Unit cost

DB1‡ We tend to provide requirements for specific projects

COST 5 Cost growth

DB2 We award a contract to one company who will both design and build a project for us

COST 6 Schedule growth

DB3 There normally is only one procurement step to select one construction company to complete a project

COST7 Development cost

DB4 We often allow one contract between us and one construction company

EFFEC2 Construction speed

CONT 1 Meeting or exceeding schedule objectives

EFFEC3 Delivery speed

CONT2 Emphasizing operational safety in the design philosophy

QUAL1‡ Turnover quality

C0NT3 Emphasizing safety in construction

QUAL2 System quality

CONT4 Attaining high quality of the constructed facility

QUAL3 Equipment quality

CONT5‡ Maximizing plant reliability QUAL4 Meeting quality specification CONT6‡ Achieving customer satisfaction QUAL45‡ Meet client satisfaction CONT7 Minimizing contractor scope

changes