50
STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN CONSTRUCTION INDUSTRY AFTAB HAMEED MEMON A thesis submitted in fulfilment of the requirements for award of the Doctor of Philosophy Faculty of Civil and Environmental Engineering University Tun Hussein Onn Malaysia MARCH 2013

STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

  • Upload
    phamque

  • View
    231

  • Download
    6

Embed Size (px)

Citation preview

Page 1: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

CONSTRUCTION INDUSTRY

AFTAB HAMEED MEMON

A thesis submitted in

fulfilment of the requirements for award of the

Doctor of Philosophy

Faculty of Civil and Environmental Engineering

University Tun Hussein Onn Malaysia

MARCH 2013

Page 2: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

v

ABSTRACT

Construction industry contributes significantly in improving socio-economic growth

of a country. However, this industry usually faces chronic problems such as time

overrun, cost overrun, poor quality and others. Of all these, cost overrun is a major

problem that occurs globally including Malaysia. Cost overrun is resulted from

various factors which are essential to identify for improving cost performance in

construction project. Hence, this study focused on identifying and modelling the

factors of cost overrun for construction projects in Malaysia. Data collection was

done through structured questionnaire, which was designed based on 78 factors

found from the literature. Qualitative pilot study was done based on the opinions of

15 experts in the construction industry to improve the questionnaire by reducing the

factors to 58. The questionnaire survey was carried out among clients, consultants

and contractors. A total of 231 questionnaires were collected of which 213 responses

were found valid. Partial Least Square Structural Equation (PLS-SEM) model was

developed based on 8 categories/constructs generated through factor analysis test and

found that Global Fit Index (GOF) of the model to be 0.37. The findings from the

model indicate that all the 8 categories have significant effect on the cost overrun.

The most significant category is contractor's site management related issues with

path co-efficient value of 0.448. The developed model was validated statistically

(using power analysis and predictive relevancy) and through interviewing 21

experienced practitioners. Statistical validation tests showed that the developed

model had achieved substantial power in explaining cost overrun problem. All the

experts agreed with the factors and also categories of the model have significant

impact to cost overrun.

Page 3: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

vi

ABSTRAK

Industri pembinaan menyumbang secara ketara dalam meningkatkan pertumbuhan

sosio-ekonomi sesebuah negara. Walau bagaimanapun, industri ini sentiasa

menghadapi pelbagai masalah kronik seperti lebihan masa, lebihan kos, kualiti yang

rendah dan lain-lain. Dari semua ini, lebihan kos adalah masalah utama yang berlaku

di seluruh dunia termasuk Malaysia. Lebihan kos adalah hasil dari pelbagai faktor

yang penting untuk dikenal pasti bagi meningkatkan prestasi kos dalam projek

pembinaan. Oleh itu, kajian ini mengfokuskan kepada mengenal pasti faktor serta

membina model lebihan kos untuk projek pembinaan di Malaysia. Pengumpulan data

dilakukan melalui borang soal selidik berstruktur yang direkabentuk berdasarkan 78

faktor hasil kajian literatur. Kajian rintis berbentuk kualitatif dilaksanakan

berdasarkan pendapat 15 pakar dalam industri pembinaan bagi memperbaiki borang

soal selidik dan hasilnya bilangan faktor menjadi 58 sahaja. Soal selidik sepenuhnya

dijalankan di kalangan klien, perunding dan kontraktor. Sebanyak 231 borang soal

selidik telah dipulangkan dan hanya 213 borang adalah sah. Model Partial Least

Square Structural Equation (PLS-SEM) dibangunkan berdasarkan 8 kategori /

konstruk dijana melalui ujian analisis factor dan didapati Global Fit Indeks (GoF)

model tersebut adalah 0.37. Penemuan menunjukkan bahawa semua 8 kategori

mempunyai kesan ketara terhadap lebihan kos. Kategori yang paling ketara adalah

isu berkaitan pengurusan kontraktor di tapakbina dengan nilai angkali 0.448. Model

yang dibangunkan telah disahkan melalui statistik dan melalui temuramah dengan 21

pakar pembinaan yang berpengalaman. Pengesahan statistik menunjukkan model

yang dibangunkan telah mencapai kuasa yang ketara dalam menjelaskan masalah

lebihan kos. Semua pakar bersetuju bahawa faktor dan kategori yang terdapat dalam

model mempunyai impak yang ketara terhadap lebihan kos.

Page 4: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

vii

TABLE OF CONTENTS

DECLARATION

DEDICATION

ACKNOWLEDGEMENT

ABSTRACT

ABSTRAK

TABLE OF CONTENTS

LIST OF TABLES

LIST OF FIGURES

LIST OF APPENDICES

CHAPTER 1 INTRODUCTION

1.1 Background

1.2 Problem Statement

1.3 Aim and Objectives

1.4 Scope of the Research

1.5 Research Methodology

1.6 Thesis Layout/Organization

CHAPTER 2 LITERATURE REVIEW

2.1 Construction Industry in Malaysia

2.2 Problems in Construction Industry

2.2.1 Time Overrun

2.2.2 Cost Overrun

2.2.3 Construction Waste

2.2.4 Poor Safety

2.2.5 Poor Quality

2.2.6 Excessive Resources Consumption

2.2.7 Threat To Environment

ii

iii

iv

v

vi

vii

xi

xiii

xiv

1

1

2

3

3

3

4

5

5

8

8

9

10

11

12

13

13

Page 5: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

viii

2.3 Construction Cost Overrun

2.3.1 Concept

2.3.2 Cost Performance

2.3.2.1 Developed Countries

2.3.2.2 Developing Countries

2.4 Causative Factors of Cost Overrun

2.5 Summary

CHAPTER 3 RESEARCH METHODOLGY

3.1 Introduction

3.2 Research Plan

3.3 Questionnaire Design

3.3.1 Measurement Scale

3.4 Pilot Study Analysis

3.5 Questionnaire Survey

3.6 Analysis Methods

3.6.1 Descriptive Analysis

3.6.2 Factor Analysis

3.6.3 Structural Equation Modelling (SEM)

3.6.3.1 Why PLS-SEM?

3.7 Summary

CHAPTER 4 DESCRIPTIVE ANALYSIS

4.1 Introduction

4.2 Pilot Study Analysis

4.3 Questionnaire Survey

4.3.1 Sampling Statistics

4.3.2 Respondent’s Organization Demography

4.3.3 Respondent’s Project Handled Demography

4.3.4 Respondent’s Expertise Demography

4.4 Factor Analysis Results

4.5 Reliability Test

4.6 Ranking of Factors Causing Cost Overrun

4.6.1 Design and Documentation (DDF)

4.6.2 Contractor's Site Management (CSM)

14

14

15

16

18

22

29

30

30

30

31

32

33

33

34

34

34

35

36

38

39

39

39

44

44

44

45

46

48

54

55

55

56

Page 6: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

ix

4.6.3 Financial Management (FIN)

4.6.4 Project Management and Contract

Administration (PMCA)

4.6.5 Labour Management (LAB)

4.6.6 Material and Machinery (MMF)

4.6.7 Information and Communication (ICT)

4.6.8 External Factors (EXT)

4.6.9 Ranking of Overall Data

4.7 Comparison with Other Countries

4.8 Summary

CHAPTER 5 PARTIAL LEAST SQUARE SEM (PLS-SEM)

ANALYSIS

5.1 Introduction

5.2 Hypothetical Model of Causes of Cost Overrun

5.3 Mechanism for PLS Model Analysis and

Assessment

5.3.1 Data Input

5.3.2 Run PLS Algorithm

5.3.3 Evaluation of Model Output

5.3.3.1 Assessment of Measurement

Model

5.3.3.2 Modify Theoretical Model

5.3.3.3 Assessment of Structural Model

5.3.4 Test Hypothesis

5.4 Sample Size

5.5 Evaluation of Hypothetical Model

5.5.1 Individual reliability and CV of

measurement Model

5.5.1.1 Optimization of the Model Quality

5.5.2 Discriminant Validity of Measurement

Model

5.5.3 Structural Model Assessment

5.5.4 Test of Hypothesis

58

59

61

62

63

64

64

70

72

73

73

73

74

76

79

80

80

83

84

84

85

86

86

89

91

94

95

Page 7: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

x

5.5.5 Assessment of Overall Model

5.6 Validation of the Results

5.6.1 Statistical Validation

5.6.2 Expert Opinion Validation

5.7 Summary

CHAPTER 6 CONCLUSION AND RECOMMENDATION

6.1 Introduction

6.2 Summary of the Findings

6.2.1 Common Factors of Cost Overrun

6.2.2 Ranking of Causes of Cost Overrun

6.2.3 Developing model to assess significance of

causative factors

6.2.4 Validating SEM Model

6.3 Contribution of this Study

6.4 Recommendations For Future Research

REFERENCES

APPENDIX A: QUESTIONNAIRE FOR PILOT STUDY

APPENDIX B: QUESTIONNAIRE FORM

APPENDIX C: INPUT DATA (*.CSV) WITH FILE FORMAT

USED IN PLS-SEM ANALYSIS

APPENDIX D: PLS ASSESSMENT RESULTS OF ITERATION 1

APPENDIX E: PLS ASSESSMENT RESULTS OF ITERATION 2

APPENDIX F: PLS ASSESSMENT RESULTS OF ITERATION 3

APPENDIX G: PLS ASSESSMENT RESULTS OF ITERATION 4

APPENDIX H: PLS ASSESSMENT RESULTS OF ITERATION 5

APPENDIX I: PLS ASSESSMENT RESULTS OF ITERATION 6

APPENDIX J: PLS ASSESSMENT RESULTS OF ITERATION 7

APPENDIX K: PLS ASSESSMENT RESULTS OF ITERATION 8

APPENDIX L: QUESTIONNAIRE FORM FOR MODEL

VALIDATION

LIST OF PUBLICATIONS

95

97

97

99

107

108

108

108

108

109

110

111

111

112

113

128

133

137

157

160

163

166

169

172

175

177

179

181

Page 8: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

xi

LIST OF TABLES

2.1 Contractors Registered under CIDB

2.2 Cost Performance in Developed Countries

2.3 Cost Performance in Developing Countries

2.4 Mapping Previous Studies (Factors of Cost Overrun)

3.1 Criteria for Selection of SEM Approach

4.1 Respondent’s Demographics in Pilot Study

4.2 Analysis of Pilot Study

4.3 Survey Statistics

4.4 Respondent’s Organization

4.5 Factor Analysis Results

4.6 Categorization of Cost Overrun Factors

4.7 Respondent’s Demographics in Validating Factor

Analysis Results

4.8 Reliability Test Results

4.9 Ranking of Design and Documentation Related

Factors

4.10 Ranking of Contractor's Site Management Related

Factors

4.11 Ranking of Financial Management Related Factors

4.12 Ranking of Project Management and Contract

Administration Related Factors

4.13 Ranking of Labour Management Related Factors

4.14 Ranking of Material and Machinery Related Factors

4.15 Ranking of Information and Communication Related

Factors

4.16 Ranking of External Factors Related Factors

4.17 Ranking of Overall Factors

7

18

21

25

38

40

41

44

45

49

51

53

54

56

57

59

60

62

63

63

64

65

Page 9: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

xii

4.18 Comparison with Factors of Cost Overrun with

other Countries

5.1 Steps in PLS-SEM Process

5.2 Convergent Validity of Model (Iteration 1)

5.3(a) Convergent Validity of Model (Iteration 1 to 4)

5.3(b) Convergent Validity of Model (Iteration 5 to 8)

5.4 Analysis of Cross-Loadings of factors

5.5 Latent Variable Correlations

5.6 Path Results of the Model

5.7 GoF index and its Criteria

5.8 Estimates of Power Analysis

5.9 Estimates Q2 for Predictive Relevancy

5.10 Demographic information of respondents Involved

in Validation Process of the Model Results

5.11 Results of Validation Process of the Model Results

71

79

87

90

91

92

93

95

96

98

99

100

101

Page 10: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

xiii

LIST OF FIGURES

2.1 Construction work on an apartment complex in

Kuala Lumpur

2.2 The construction of the tunnel at Bukit Berapit in

Kuala Lumpur

2.3 Construction waste illegally dumped in mangrove

swamp

2.4 Construction debris along roadside

3.1 The flow chart of methodology for this research

4.1 Experience of Respondents involved in Pilot Study

4.2 Type of Projects Respondents handled

4.3 Size of Projects Handled by Respondents

4.4 Academic Qualification of Respondents

4.5 Respondents Experience

5.1 Hypothetic Model of Causes of Cost Overrun

5.2 Schematic Diagram of PLS-SEM Analysis

5.3 Theoretical Model of Cost Overrun and Causative

Factor

5.4 Data Input Screenshot from SmartPLS Software

5.5 PLS Model Results for Iteration 1

5.6 Result of Structural Model

6.1 Common Factors of Cost Overrun

6.2 Significant Factors of Cost Overrun

6.3 PLS-SEM Showing Causal Relations b/w Cost

Overrun Factors

6.4 Power Analysis Results Obtained from GPower

6

6

11

11

31

40

46

46

47

47

74

75

76

78

87

94

109

110

110

111

Page 11: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

xiv

LIST OF APPENDICES

APPENDIX TITLE PAGE

A Questionnaire for Pilot Study 128

B Questionnaire form for Data Collection 133

C Input Data (*.csv) with file format used in

PLS-SEM Analysis 137

D PLS Assessment results of Iteration 1 157

E PLS Assessment results of Iteration 2 160

F PLS Assessment results of Iteration 3 163

G PLS Assessment results of Iteration 4 166

H PLS Assessment results of Iteration 5 169

I PLS Assessment results of Iteration 6 172

J PLS Assessment results of Iteration 7 175

K PLS Assessment results of Iteration 8 177

L Questionnaire form for Model Validation 179

Page 12: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

CHAPTER 1

INTRODUCTION

1.1 Background

Construction industry is a very important industry that plays a vital role in the socio-

economic growth of a country. Economically, it contributes significantly in the

improvement to the overall GDP of a country. It also improves the quality of life by

providing necessary infrastructure such as roads, hospitals, schools and other basic

and enhanced facilities. Hence, it is fundamentally crucial to make the construction

projects complete successfully within the time, budget and quality expected.

However, being a complex, fragmented and schedule driven industry it is always

facing chronic problems such as low quality, low productivity, cost overrun, time

overrun, construction waste etc. Of these, cost overrun is the major problem as

money is always of high importance.

Cost overrun is a global phenomenon in the construction industry and very

rarely projects are finished within the budgeted cost. The issue of cost overrun in

construction projects is very dominant in both developed and developing countries

but this trend is very severe in developing countries where these overruns sometimes

exceed 100% of the anticipated cost (Azhar, Farooqui, & Ahmed, 2008).

Flyvbjerg, Holm, & Buhl (2003) in their global study of construction project

performance concluded that cost overrun is a major problem in the construction

industry where 9 of 10 projects are faced by these overruns which commonly range

between 50 to 100%. In developed countries like UK also construction industry is

affected by this problem (Olawale & Sun, 2010) and nearly one third of the client’s

complaint that their projects generally overran the allocated budget (Jackson, 2002).

Page 13: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

2

1.2 Problem Statement

Like other developing countries, Malaysia also facing a serious issue of cost overrun

in construction industry (Ali & Kamaruzzaman, 2010, Sambasivan & Soon, 2007,

Abdullah et al., 2009 and Ibrahim et al., 2010). This is confirmed with a research

conducted by Endut, Akintoye, & Kelly (2009) showing that only 46.8% of public

sector and 37.2% of private sector projects were completed within the stipulated

budget. The issue of cost overrun has become a serious concern of the investors,

which needs a serious attention and in-depth research to put forward with solution to

this issue.

According to Toh, Ali, & Aliagha, (2011), Malaysia needs more research

works by academia and practitioners regarding construction cost factors. Since

construction cost is the most dominant component of project’s life cycle, thus it is

important to evaluate it before it is too late so that poor cost performance can be

prevented (Cha & Shin, 2011). The impact of poor cost performance could lead to

cost overrun which is an additional burden over the budgeted cost of project and this

cost overrun can never be recovered. These overruns are resulted from various

factors, thus it is important to identify and to control these responsible factors.

Further, there was no study done on assessing causal relationships among

factors of cost overrun (Toh et al., 2011) and this give an opportunity to the author

adopting Structural Equation Modelling (SEM) approach to assess and also to model

the factors. SEM is a graphical equivalent of a mathematical representation (Byrne,

2010) with features of advance multivariate tool to determine the strength of the

relationships between the factors (Jackson, Dezee, Douglas, & Shimeall, 2005; Hair,

Anderson, Tatham, & Black, 1998). It is becoming very popular in analyzing cause–

effect relations between factors (Hair, Ringle, & Sarstedt, 2011).

Hence, this study focuses on identifying major factors causing cost overrun

run and developing a structural model in representing the factors affecting cost

overrun for Malaysian construction industry.

Page 14: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

3

1.3 Aim and Objectives

The aim of this study is to model the factors contributing to cost overrun in

Malaysian construction industry. To achieve this aim, various objectives were set

which include:

o Identifying the common factors causing cost overrun

o Assessing hieratically the causative factors of cost overrun in Malaysian

construction industry

o Developing Structural Equation Model (SEM) to assess significance of

causative factors to cost overrun

o Validating the results of SEM

1.4 Scope of the Research

This study adopted quantitative approach in identifying and assessing the significant

factors causing overrun. The data samples are collected through questionnaire survey

amongst the clients, consultants and contractors involved in construction industry.

Contractors were selected from “list of approved contractors” in Construction

Industry Development Board (CIDB) Malaysia registered under category from G3 to

G7.

1.5 Research Methodology

This study is based on three research methods which include literature review,

interviews and questionnaires. These three methods acted as supplement to each

other which made the data collection more comprehensive and meaningful. Basically,

literature review focused on gaining a better understanding of cost performance and

causative factors affecting cost overrun in construction projects. These factors were

analyzed in conformance to represent the problems of cost overrun in prevailing

construction industry of Malaysia through interviewing the experience personnel

Page 15: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

4

involved in handling construction projects. Questionnaire survey was conducted to

understand the perception of clients, consultants and contractors towards the factors

causing cost overrun. Gathered data was analyzed with statistical tools in order to

draw the conclusion in determining the current situation of cost overrun problem and

factors contributing to this overrun.

1.6 Thesis Layout/Organization

This study focused on modelling the causative factors of cost overrun to propose the

guidelines for controlling cost overrun problem in construction industry of Malaysia.

The thesis for this study is divided into 6 chapters as follows:

Chapter One: This chapter discusses about the need of this study. It contains

background of the study and problem statement to outline the primary objectives,

scope of the study with introductory remarks.

Chapter Two: This chapter contains the review of published research works

for related study on cost overrun issues and factors of cost overrun.

Chapter Three: This chapter illustrates the methodology adopted for this

study. It provides details of various analyzing approaches used for data analysis

together with the data collection strategy used.

Chapter Four: This chapter explains the descriptive analysis results including

the hierarchal assessment of causative factors of cost overrun and comparison of

findings with similar studies carried out in other countries.

Chapter Five: It discusses the structural equation modelling (SEM) analysis

and achieved results of causal relationships. It also explains the course of validating

the results and prosing the mitigation measure and guidelines to help the practitioners

in controlling causative factors of cost overrun at source.

Chapter Six: The final chapter discusses about the conclusion achieved from

this study with counsel for probable advancement and line of action for future works

to provide more benefits in achieving cost control of construction projects.

Page 16: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

CHAPTER 2

LITERATURE REVIEW

2.1 Construction Industry in Malaysia

Construction industry is necessary in every country to provide physical

developments which help in improving social and economic needs of country (Abedi,

Mohamad, & Fathi, 2011). Hence, construction industry has been growing rapidly

worldwide.

Construction industry in Malaysia developed since its independence. The

industry is generally classified into two areas namely general construction and

special trade works (Ibrahim et al., 2010). General construction focuses on

residential and non-residential constructions and also general civil engineering works.

For special trade works, the activities involved are metal works, electrical works,

plumbing, sewerage and sanitary works, refrigeration and air-conditioning work,

painting work, carpentry, tiling and flooring work, and glass work. Figure 2.1 and 2.2

show the example of construction work of apartment complex and tunnel

construction in Kuala Lumpur.

Construction industry has been an important drive in Malaysian economy

(Ali & Kamaruzzaman, 2010). However, the volatile global economy between 2008

and 2009 constituted an overall decline in revenue stream in Malaysia’s construction

market. It was a challenging period for the construction industry facing that

economic crisis. According to (Rashid & Morledge, 1998) construction industry is

considered in crisis if its growth is less than 5.4% of the Growth Domestic Product

(GDP). Despite of these crises Malaysian construction industry has remained stable

(Leung & Tam, 2004) and registered a strong growth of 5.8% in 2009. The industry

Page 17: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

6

growth subsequently increased to 8.7% in 2010 as against that overall (GDP) growth

of 10.1%. Realizing the huge impact on the economy, the government had allocated

huge amount of the budget for construction development in Malaysia under 10th

Malaysian Plan with a total sum of RM230 billion (Mansor, 2010).

Figure 2.1: Construction work on an apartment complex in Kuala Lumpur

Source: Richter & Scheid (2011)

Figure 2.2: The construction of the tunnel at Bukit Berapit in Kuala Lumpur

Source: Railway-Technology.com (2011)

In Malaysian construction industry, it is mandatory for the contractors to

register with the Construction Industry Development Board (CIDB) before they are

eligible to participate in any construction activities for both public and private

Page 18: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

7

projects. A total of 66,904 contractors are currently registered with CIDB as

classified in 7 categories ranging from grade G1 to grade G7 (CIDB, 2012) as shown

in table 2.1.

Table 2.1: Contractors Registered under CIDB

State Grade

Total G1 G2 G3 G4 G5 G6 G7

Johor 3,320 1,075 1,314 320 309 123 333 6,794

Kedah 2,128 537 375 115 134 63 176 3,528

Kelantan 2,243 314 296 79 134 50 127 3,246

Melaka 1,118 376 392 128 126 43 110 2,293

Negri Sembilan 2,109 468 429 94 126 52 84 3,362

Pahang 2,193 500 557 185 152 59 128 3,774

Perak 2,677 634 641 178 178 71 123 4,502

Perlis 925 92 66 22 27 4 19 1,155

Pulau Pinang 1,405 635 774 141 230 95 287 3,567

Sabah 5,772 1,140 989 140 216 78 401 8,736

Sarawak 1,456 529 418 141 164 89 367 3,164

Selangor 4,536 1,277 2,251 574 816 283 1,005 10,742

Terengganu 2,286 333 356 147 209 76 165 3,572

Wilayah Persekutuan 1,823 870 2,325 529 1,106 368 1,448 8,469

Total 33,991 8,780 11,183 2,793 3,930 1,454 4,773 66,904

Source: (CIDB, 2012)

Table 2.1 shows that large group of contractors are in G1 grade which means

that these contractors are entitled to participate in tendering for project with worth of

maximum contract sum of not exceeding than MR 100,000. G2 contractors are

suitable to participate in tendering for projects of contract sum not exceeding MR

500,000. Similarly, G3 and G4 contractors are qualified for tendering in project with

maximum tender values of not exceeding than RM 1million and RM 3 million

respectively. G5 contractors can participate in tendering process of project of value

not exceeding than RM 5Million. Abdullah et al., (2009) stated that in Malaysia

projects with contract value equal to or less than RM 5 Million are regarded as small

projects. This means the contractors registered under grades G1 to G5 are eligible to

Page 19: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

8

take part for tendering only in small projects. While, contractors registered in G6 and

G7 grades are able to tender for small and large projects. However, grade G6

contractors are limited to tender up to RM 10 million project and G7 contractors

have no limitation.

2.2 Problems in Construction Industry

Construction industry is considered as a locomotive of physical developments which

bring substantial and significant impacts to the country’s economy (Kumaraswamy,

2006). However, it also contributes to negative implications especially to the

environment and social aspect of a country. In addition, the industry is always facing

chronic problems such as time overrun, cost overrun, waste generation (Hussin,

Rahman, & Memon, 2012a), poor safety (Nahmens & Ikuma, 2009), poor quality,

excessive resource consumption and threat to environment (Hussin, Rahman, &

Memon, 2012b).

2.2.1 Time Overrun

Achieving completion of construction projects on time is a basic requirement.

However, seldom projects are completed on time. This has become a worldwide

problem. A study showed that the Vietnamese government has acknowledged this

issue as a serious concern, especially with government-related funded projects (Le-

Hoai, Lee, & Lee, 2008). In Nigeria, out of 3,407 projects only 24 projects were

completed on time, while 1517 were delayed and 1812 were abandoned (Amu &

Adesanya, 2011). Omoregie & Radford (2006) reported that the minimum average

percentage escalation period of projects in Nigeria was found to be 188%. A similar

research was conducted in Bosnia and Herzegovina on 177 projects and found that

the contracted date was not met in 51.40 % of the projects (Zujo, Car-Pusic, &

Brkan-Vejzovic, 2010). Al-Momani (2000) conducted a survey on 130 public

projects in Jordan and found delays occurred in 106 (82%) of the projects. Frimpong,

Page 20: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

9

Oluwoye, & Crawford (2003) found that 33 (70%) out of 47 projects in Ghana were

delayed. Whilst, in Saudi Arabia 70% of projects faced time delay with average time

delay of 10% to 30% of the original duration of the project (Assaf & Al-Hejji, 2006).

Likewise in Malaysia also, the construction industry is facing the same

critical problem of time overrun (Alaghbari, Kadir, Salim, & Ernawati, 2007;

Ibrahim et al., 2010; Sambasivan & Soon, 2007). Abdullah (2010) reported that more

than 90% of large MARA construction projects experienced delay since 1984. Endut

et al. (2009) studied on time performance of 359 projects (301 new constructions

while 58 refurbishment projects) in Malaysia. Of these 301 were public projects and

51 private projects. The study found that only 18.2% of the public sector projects and

29.45% of private sector projects had 0% time deviation (no delays) while the

average percentage of time overrun for other projects was 49.71%. Time Delay can

be due to one or more reasons including problems of financing and payment for

completed works. As an example, Yogeswaran, Kumaraswamy, & Miller (1998)

scrutinized 67 civil engineering projects in Hong Kong and found at least 15–20% of

time overrun was due to inclement weather.

2.2.2 Cost Overrun

Cost is one of the major considerations throughout the lifecycle of a project.

Unfortunately, most of the projects failed to achieve project completion with the

estimated cost. Besides time overrun, cost overrun is also a serious problem in the

construction industry. This is a major problem both in developed and developing

countries. The trend is more severe in developing countries where these overruns

sometimes exceeds 100% of the anticipated cost of the project (Azhar et al. 2008).

The history of the construction industry worldwide is full of projects that

were completed with significant amount of cost overruns. Despite the wide

availability and use of different project management methods and software packages,

many construction projects still suffer cost overruns (Olawale & Sun, 2010).

Developed countries have lessons to learn as well since cost overrun in the

construction industry is a worldwide phenomenon (Ameh, Soyingbe, & Odusami,

2010). Approximately 90% of projects worldwide have cost overrun ranging from 50

Page 21: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

10

to 100% of project cost (Flyvbjerg et al., 2003). Like other countries, Malaysian

construction industry is also facing a lot of challenges in completing the construction

projects within the estimated cost (Ibrahim et al., 2010; Toh et al., 2011) and more

than 50% of projects face cost overrun (Endut et al., 2009).

2.2.3 Construction Waste

Waste is another serious problem in construction projects. Waste has direct impact

on the productivity, material loss and completion time of project resulting in loss of a

significant amount of revenue. Forsberg & Saukkoriipi, (2007) stated that the amount

of waste contributed is around 30-35% of a project’s production cost. The amount of

construction materials wasted on the site is relatively high and equals 9% by weight

of the purchased materials (Bossink & Brouwers, 1996). They investigated material

waste generated in a Dutch construction project and found that the average waste per

house was 6,860 kg which consisted of 4,480 kg of construction debris and 2,380 kg

of other types of solid waste.

In Malaysia also construction waste generation is becoming an important

issue (Begum, Satari, & Pereira, 2010; Nagapan, Rahman, Azis, Memon, & Zin,

2012). The high quantity of construction waste generated in the country is due to the

rapid development of the construction industry. Demand of houses and major

infrastructure projects contributed to the increase of construction waste (Nasaruddin,

Ramli, & Ravana, 2008; Siti & Noor, 2008). Begum, Siwar, Pereira, & Jaafar (2006)

studied the economic feasibility of waste minimization in Malaysian construction

project and concluded that by adopting waste minimization strategy like recycling

and reusing materials, it can save 2.5% of the total budget.

The major impact of increased construction waste generation has caused

illegal dumping and has swelled rapidly in Malaysia (Yahaya & Larsen, 2008). A

study done in Johor district alone indicated that 42% of 46 illegal dumping sites are

of construction waste (Rahmat & Ibrahim, 2007). Furthermore, a study in Seberang

Perai, Pulau Pinang also discovered more illegal dump site along the roadside

(Faridah, Hasmanie, & Hasnain, 2004). Recent news had highlighted that almost 30

tons of construction wastes was dumped illegally in tropical mangrove swamp near

Page 22: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

11

Bandar Hilir, Malacca (Murali, 2011) and construction debris problem near roadside

at Section 17, Petaling Jaya, Selangor (Tan, 2012) as shown in figures 2.3 and 2.4.

Figure.2.3: Construction waste illegally

dumped in mangrove swamp Source: Murali (2011)

Figure.2.4: Construction debris along roadside. Source: Tan (2012)

These illegal dumping has caused a risk to human health and environment

(Faridah et al., 2004; Rahmat & Ibrahim, 2007). The issues of illegal dumping arise

is due to the cost and location of the project (Seow & Mohamad, 2007). The

contractors intended to maximise profit by avoiding transportation cost and payment

charge to the gazetted landfill. Distance between the project location and the landfill

site also hinders the contractor to dispose in legal landfill. A study conducted at 30

construction sites in Malaysia identified six types of waste materials which includes

concrete (12.32%), metals (9.62%), bricks (6.54%), plastics (0.43%), timber (69.10%)

and other wastes (2%) (Faridah et al., 2004). Hence, it is timely for Malaysia to adopt

a systematic and efficient waste management strategy which would minimise the

generation of waste at different level. Advanced techniques such as lean construction

can help in reducing waste at source and can minimised the waste produced during

the operation by re-using and re-cycling.

2.2.4 Poor Safety

The construction industry is notoriously known for its poor safety record as

compared with other industries (Mohamed, 2002). Poor safety resulted to accidents

and fatality which affect significantly on efficiency and cost of the project. Accident

Page 23: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

12

data prepared by the Occupational Safety and Health Branch of the Labour

Department, Hong Kong as summarized by (Rachel, 2006) shows that accident rates

in the construction industry are much worse than all other industries for many years:

for 1000 workers, the accident rates are on an average 3 times more than that of all

industries, whereas the fatality rates are on an average 5 times more than other

industries. Bureau of Labor Statistics USA (in Nahmens & Ikuma, 2009) reported

that in USA total injury and illness incidence rates are 9.5 to 14.3 per 100 workers in

prefabricated wood manufacturing while in the residential construction, incidence

rate is approximately 5 per 100 workers.

Koskela (1992) mentioned that cost incurred because of poor safety practices

in construction industry is approximately 6% of total project cost. In a research,

Everett and Frank (1996) found that the total costs of construction accidents

accounted for 7.9% to 15% of the total costs of projects. UK Health and Safety

Executive reported that the total losses due to accidents in the UK were equal to

about 8.5% of the tender price (Rowlinson, 2003). These accidents may be caused by

different factors. Kartam (1997) stated that accidents are directly attributed to unsafe

design and site practices while Baxendale & Jones (2000) stated that most of the

accidents are caused due to poor management and control.

2.2.5 Poor Quality

Another problem faced by construction industry is poor quality standards. It is very

common and serious problem as the expected quality is not complied in the

construction projects (Kometa & Olomolaiye, 1997). Failure in achieving required

quality has also significant impact of project cost. Koskela (1992) stated that quality

cost (non-conformance) in construction industry of USA contributed to 12% of total

project cost. Burati, Farrington, & Ledbetter (1992); Ledbetter (1994) and Love

(2002) studying quality performance of construction projects through case studies as

summarized in Marosszeky, Thomas, Karim, Davis, & McGeorge (2002) showed

that quality failures had resulted in rework which incurred extra cost approximately 2%

to 12% of project cost while Marosszeky et al (2002) stated that quality rectification

problems contributed to approximately 3.4% to 6.2% of project cost.

Page 24: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

13

2.2.6 Excessive Resources Consumption

Built environment has significant impact on resources where it accounts for one-sixth

of the world’s freshwater withdrawals, one-quarter of its wood harvest and two-fifths

of its material and energy flows. The structures also have impact areas beyond their

immediate location, affecting the watersheds, air quality, and transportation patterns

of communities (Rodman & Lenssen, 1994). Buildings built without due

consideration to energy, environmental impact and natural resources conservation

will result in detrimental wastage affecting our ecological integrity (Shen & Tam,

2002).

Excessive resource and energy use and a growing demand for raw materials

are largely responsible for the depletion of natural resources worldwide and the

acceleration of global warming. About 40% of the world's resource and energy used

is linked to the construction and maintenance of buildings. This contributes to one-

tenth of the global economy (Rodman & Lenssen, 1994). Other studies indicate that

more than half of all resources consumed globally are used in construction, and 45

per cent of energy generated across the world is used to heat, light and ventilate our

buildings, with a further 5 per cent arising from constructing those (Edwards, 2001).

As an example, in the European Union, buildings are responsible for more than 40%

of the total energy consumption and the construction sector is estimated to generate

approximately 40% of all man-made wastes. In addition, the construction sector is

the Union’s largest industrial sector, contributing approximately 11% to the GNP and

having more than 25 million people directly and indirectly engaged (CIB, 1999).

2.2.7 Threat To Environment

Built environment is considered the most environmental unfriendly human activity

because it consumes large amounts of natural resources and produces a huge amount

of pollutants. The environmental impact of the construction industry is extensive and

readily identifiable (Rodman & Lenssen, 1994). Most people are not serious about

environmental protection in construction sites. They assume that a construction site

Page 25: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

14

is only a temporary setup lasting for two to three years. In fact, the industry is a

major source of urban air pollutants (Chan, 2000).

The emission of CO2 by buildings contributed to the global warming and

extreme weather change all over the world. The harvest of timber leads to the loss of

natural forests. Other impacts of constructing a new building include quarrying to

provide aggregates, production of cement, the wasteful use of water and the

widespread use of toxic chemicals in materials (Kin-sun, 2004).

2.3 Construction Cost Overrun

Among the problems faced by construction industry, one of the most critical issues is

cost overrun problem. Cost overrun has become a global phenomenon and rarely

projects are completed within the budgeted cost. While, achieving completion within

the budgetary cost is the fundamental requirement of any construction project

(Olawale & Sun, 2010). Cost overrun normally experiences in construction projects

(Azhar et al., 2008). However, the magnitude of these cost overruns varies

considerably from project to project which are subjected to various causes. Thus

Sohail, Miles, & Cotton (2002) suggested that construction professionals should pay

more attention to cost performance of projects as cited by (Olawale & Sun, 2010)

and unearth the causes affecting it which can be shared amongst construction

community.

2.3.1 Concept

Cost overrun is also called “cost escalation,” “cost increase,” or “budget overrun”

(Zhu & Lin, 2004 in Enshassi, Al-Najjar, & Kumaraswamy, 2009). Cost overrun is

the excess of actual cost over budgeted cost which occurs when the final cost of the

project exceeds the original estimates (Avots, 1983; Azhar et al., 2008). Cost overrun

has become a universal phenomenon (Endut et al., 2009) which adds pressure to

investment decision (Ali & Kamaruzzaman, 2010).

Page 26: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

15

Cost overrun is measured as a percentage of actual costs over the estimated

costs of the project (Cantarelli, 2009; Choudhury & Phatak, 2004) as shown in

expression 2.1:

Cost Overrun = Actual Cost−Estimated CostEstimated Cost

Actual costs are defined as real and accounted construction costs determined

at the time of project completion. Estimated costs are defined as budgeted or

forecasted construction costs determined at the start of projects (Cantarelli, 2009).

2.3.2 Cost Performance

The success of any project can be measured by various norms like time performance,

cost performance, quality standards, achieving safety and health, etc. Atkinson (1999)

stated that cost, time and quality serve as Iron Triangle for success of any project. Of

these, cost performance is the most important indicator of project success (Frimpong

et al., 2003; Olawale & Sun, 2010). It presents not only the firm’s profitability but

also the productivity of organizations at any point during the construction processes.

It can be seen easily in the project account and is always used to measure project

performance against the estimated target.

Unfortunately, construction industry has been experiencing poor cost

performance which described its inability to complete projects within budget. This

chronic issue is experienced worldwide and becoming more critical as been revealed

in World Bank report in 1990. The report pointed out that 63% of the 1778 financed

construction projects faced poor performance with overrun in budget at an average of

40% as cited by (Ameh et al., 2010; Zujo et al., 2010). For worldwide scenario,

Flyvbjerg et al. (2003) had studied 258 projects in 20 nations which approximately

US$90 billion worth of project with size ranging from US$1.5 million to $8.5 billion.

They found that cost escalation happened to almost 9 out of 10 projects with an

average of 28% higher than forecasted costs. The study concluded that cost

performance has not improved over the time and its magnitude has not changed for

the past 70 years. Other study conducted by Odeck (2004) shows that average cost

...........................................(2.1)

Page 27: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

16

overrun was rather small with approximately 7.9% of project cost. The problem of

cost overrun is common issue in both developing and developed countries (Angelo &

Reina, 2002) However, it is more severe in developing countries where actual cost

exceeded 100% of the anticipated cost of the projects (Azhar et al., 2008).

2.3.2.1 Developed Countries

Numerous project control methods and software packages, such as Gantt Bar Chart,

Program Evaluation and Review Technique (PERT), Critical Path Method (CPM),

Microsoft Project, Asta Power Project, Primavera, etc. have been used to control cost

overrun. Despite that, many construction projects in developed countries still suffer

cost overruns (Olawale & Sun, 2010) as discussed below:

UK Scenario: A research conducted by Barrick (1995) showed that nearly

one third of the clients in UK complaints that their projects generally overran

budget. Further, Department of Environment, Transport and the Regions

(DETR, 2000) reported that approximately 55% of projects face the problem

of cost overrun with huge amount as cited by (Jackson, 2002). For example,

British library faced three times over the original budget, Guy’s house at

£152M doubled its original budget (NAO, 1998) parliamentary office

building in London also at cost of £250M doubled its original budget

(Wheeler, 1998) and Holyroad project in Glasgow took £230M against £90M

of the original budget (Fairs, 2001). Olawale & Sun (2010) conducting a

survey on cost overrun problems in construction projects stated that 41% of

respondents experienced overrun on just less than 10% of their projects while

59% of respondents experience cost overrun on 10% or more of their projects.

USA Scenario: A study conducted in 1994 consisting of 8,000 projects

showed that only 16% of the projects satisfied the three famous performance

criteria: completing projects on time, within budgeted cost and quality

standard (Frame, 1997). In study of project performance of cost plus fixed fee

projects, Chang (2002) conducted case studies on four projects. He found that

the entire four projects were facing cost overrun ranging from 12.3% to 51.3%

at an average of 24.8% of the contract amount. The Government

Page 28: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

17

Accountability Office also stated that 77% of highway projects in the USA

experienced cost escalation (Cantarelli, Flyvbjerg, Molin, & Wee, 2010).

Netherlands Scenario: Investigation on 87 projects (29 road projects, 28 rail

projects and 30 fixed link projects) revealed that cost overrun was the

common problem at an average of 10.3% of project cost. The study showed

that the percentage of cost overrun in road projects was the highest with the

rate of 18.5% followed by rail projects with 7.6% and finally fixed link

project with 4.5% (Cantarelli, 2009).

Norway Scenario: Odeck (2004) studied the performance of construction

projects controlled by Norwegian Public Roads Administration. He found

that that cost overrun was a severe problem and the amount of overruns

ranged from -59% to 183%.

Slovenia Scenario: In a study of 92 traffic structures, it was found that

contracted construction price overrun was 51 % as cited by (Zujo et al., 2010).

Sweden Scenario: The Auditor General of Sweden (1995) report showed a

narrow focus on cost overruns involving transport projects. It covered 15

projects (8 road and 7 rail projects). The report showed that average capital

cost overrun for road projects was 86% (ranging between 2 and 182%) and

for rail projects this overrun was 17% (ranging from -14% to 74%) as cited

by (Cantarelli et al., 2010).

Portugal Scenario: Auditing report of public projects published by the

National Court of Audit Portugal (NACL, 2000) on the cost performance of

26 major motorway projects, underground projects launched between 1985

and 2000 and 98 Expo projects revealed that in motorway projects, average

cost overrun was 39% of project cost. In underground projects, cost overrun

averaged 311% while the Expo projects had cost overruns averaged as much

as 41%. Further, an investigating 66 construction projects with average initial

contract amount was €16.530.674. Average final costs of these projects

reached €18.584.954 with an average cost overrun of €2.054.280 i.e. 12% of

the initial average cost (Moura, Teixeira, & Pires, 2007).

Cost performance of construction projects in developed countries is

summarized in table 2.2.

Page 29: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

18

Table 2.2: Cost Performance in Developed Countries

Origin Reference Findings UK DETR (2000)

Jackson (2002) Olawale and Sun

(2010)

55% of projects were overrun 1/3 of project face overrun More than 10% of project face cost overrun

USA Frame (1997) Chang (2002)

Kaliba et al. (2009)

84% project overrun 100% of projects overrun at average 24.8%

77% of highway projects face cost overrun

Netherlands Cantarelli (2009) Cost overrun amounts 10.3% of project cost

Norway Odeck (2004) Cost overrun ranged from -59% to 183% of project cost

Slovenia Zujo (2010) Cost overrun was recorded as 51 % of tender cost

Sweden Auditor General of Sweden (1994)

Average capital cost overrun for road projects equals to 86% of estimated cost

Average cost overrun for rail projects equals to 17%

Portugal N.A.C.L (2000)

Moura et al. (2007)

In motorway projects cost overrun was 39% In underground projects cost overrun was 311% of

original estimate Expo projects faced cost overrun at an average rate

of 41% of project cost

Construction Projects had overrun at average rate of 12% of budgeted cost

2.3.2.2 Developing Countries

Compared to developed countries, the trend of cost overrun is more severe in

developing countries as discussed below:

Bosnia and Herzegovina: In a study of 177 structures, it was found that the

contracted price was not met in 41.23% of structures. Another study of 53

building projects including 29 new construction and 24 reconstruction

projects showed that average cost overrun in reconstruction projects was 9.23%

white it was 6.84% for new construction projects (Zujo et al., 2010; Zujo &

Car, 2008).

Croatia: A multi-annual research of cost overruns conducted as part of the

scientific project on construction project risk and resource management

Page 30: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

19

pointed out that the occurrence of price overrun was in no less than 81 %

projects as cited by (Zujo et al., 2010).

Ghana: Frimpong et al. (2003) studied cost performance of water drilling

projects and found that 38 of total of 47 investigated projects (at a rate of

75%) were facing cost overrun whereas only 25% were completed within the

budget.

India: A study of 290 projects showed a total of Rs 20,024 crore over the

contract cost of projects as Rs 27,568 with an average of 73% of cost overrun

as cited by (Gupta, 2009).

Korea: Lee (2008) investigated 161 projects which included 138 road

projects, 16 rail projects, 2 airport and 5 port projects. Findings of study

showed that 95% of road projects had cost overrun at rate of 50% of the

project cost, all the rail projects faced cost overrun at the rate of 50% of

projects cost while airports projects had overrun of more than 100% of

project cost and port projects had approximately 40% of cost overrun.

Kuwait: In study of 450 private housing projects in 27 metropolitan districts,

Koushki, Al-Rashid, & Kartam (2005) noted that 33% of the projects faced

cost overrun which resulted in increasing the cost of house from US$ 381,612

to US$385,492 (with increase of US$ 3,880).

Malaysia: Malaysians Auditor General 2008 (in Khamidi, Khan, & Idrus

2011) showed that completion of electrified double track project between

Rawang and Ipoh resulted in a cost overrun of RM 1.43 billion. Endut et al.

(2009) analyzed cost overrun problems by investigating 308 public and 51

private projects (a total of 359 projects). They found that only 46.8% and

37.2% of public sector and private sector projects completed within the

budget respectively with average cost deviation of the project was 2.08%.

The maximum deviation was found as 80.76% of project cost. Further, in

MARA large construction project, research conducted by Abdullah et al.

(2009) revealed that more that 90% of large MARA construction project

experienced delay since 1984 with major effects of time and cost overrun.

Later on, in qualitative study of project performance of D & B project

through eight case studies Potty, Idrus, & Ramanathan (2011) found that

seven projects were facing cost overrun, however the risk of these overruns

Page 31: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

20

was borne by contractors as the projects were awarded on fixed price

conditions.

Nigeria: Jackson & Steven (2001) studied the problem of cost overrun by

investigating 15 projects in llorin and found that 73.7% project faced cost

overrun at an average of 34.7% of the initial project cost. They also

conducted a questionnaire survey and mentioned that only 10% respondents

have not experience cost overruns at all while 75% of the respondents

mentioned that cost overruns have sometimes occurred in building projects,

15% said it always occurred. Through 61 cases studies Aibinu & Jagboro

(2002) found that the projects had a mean percentage cost overrun of 17.34%.

Later on an investigation of 137 construction projects showed that 55% of

projects were facing cost overrun problem. These overrun ranged from 5% to

a maximum amount of 808% of project cost (Olatunji, 2008). A research of

cost escalation on infrastructure projects conducted by Omoregie & Radford

(2006) showed that a minimum percentage of cost escalation was found as 14%

of the budgeted cost.

Pakistan: Azhar et al. (2008) stated that cost overrun was a common problem

in construction projects. The minimum range of cost overrun experienced was

found as near around the 10% of the total cost of the project. In large

construction firms these overrun ranged up to about 40% while in medium

size firms this percentage increased up to nearly about 60% of the project cost.

Thailand: Meeampol & Ogunlana (2006) studied cost performance on 99

highway construction projects and found that only 46 projects only were

satisfied with cost performance while the others faced poor cost performance.

Uganda: Northern by-pass project in Kampala was overrun by more than 100%

and a study of a total of 30 projects showed that 53% of the projects had cost

overruns (Apolot, Alinaitwe, & Tindiwensi, 2011).

Vietnam: Government has acknowledged the construction cost overruns

problem as the big headache, especially with government-related funded

projects (Le-Hoai et al., 2008).

Zambia: Kaliba, Muya, & Mumba (2009) studying the project performance

in road construction projects of worth U$542.7 found that more than 50% of

projects could not meet the contract budget and were facing cost overrun.

Page 32: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

21

Cost performance of construction projects in developing countries is

summarized in table 2.3.

Table 2.3: Cost Performance in Developing Countries

Origin Reference Findings Bosnia and Herzegovina

Zujo and Pusic (2008)

Zujo et al. (2010)

Reconstruction building projects had cost overrun at average rate of 9.23%

New building projects had cost overrun at average rate of 6.84%

41.23% of projects faced cost overrun

Croatia Zujo et al. (2010) More than 81% project had cost overrun

Ghana Frimpong et al (203) 75% of the project face cost overrun run

India Gupta (2009) Project faced cost overrun at an average rate of 73% contracted price of projects

Korea Lee (2008) 95% of road projects had cost overrun at rate of 50% of the project cost

all the rail projects faced cost overrun at the rate of 50% of projects cost

Airport projects had overrun of more than 100% of project cost

Port projects had cost overrun at rate of 40% of project cost

Kuwait Koushki et al. (2005) 33% of the projects faced cost overrun resulting in increase US$ 3,880 in cost of house

Malaysia Malaysians Auditor General (2008)

Endut et al (2009) Abdullah MR (2009)

Potty et al (2011)

Cost overrun of RM 1.43 billion in electrified double track project between Rawang and Ipoh

46.8% and 37.2% of public sector and private sector projects completed within the budget

90% of large MARA construction project experience overruns

87.5% of D&B projects face cost overrun

Nigeria Jackson and Steven (2001)

Aibinu and Jagboro

(2002) Olatunji (2005)

Omoregie and

Radford (2006)

90% respondents participating in survey agreed that they experience cost overruns

Average cost overrun was found as 34.7% of the initial project cost

Mean percentage cost overrun of 17.34%

55% of projects faced cost overrun problem ranging from 5% to 808% of project cost

Minimum percentage of cost escalation in Infrastructure projects was 14% of the budgeted cost

Pakistan Azhar et al (2008) Cost overrun ranged from 10% to 60%

Thailand Meeampol and Ogunlana (2006)

53% highway projects had poor cost performance

Uganda Sepuuya (2008)

Northern by-pass project was overrun by more than 100% of project cost

Page 33: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

22

Apolot et al (2011) 53% of the projects had cost overruns

Vietnam Le-Hoai et al (2008) Most of projects face cost overrun which has become headache.

Zambia Kaliba (2009) more than 50% road construction project faced cost overrun

2.4 Causative Factors of Cost Overrun

Cost overrun in construction projects can occur due to many factors. It is very crucial

to determine these factors in improving cost performance. Since, many research

works had been carried out in determining these factors, hence a comprehensive

literature review was carried out to uncover these factors affecting cost overrun for

further investigation in construction industry of Malaysia.

Kaming, Olomolaiye, Holt, & Harris (1997) identified factors influencing

construction cost overruns on high-rise building projects in Indonesia through a

questionnaire survey administered on 31 project managers. The results showed that

major factors affecting project cost were materials cost increased by inflation,

inaccurate quantity take-off, labour cost increased due to environment restriction,

lack of experience of project location, lack of experience of project type,

unpredictable weather conditions and lack of experience of local regulation.

Jackson & Steven (2001) examined the causes of cost overrun in building

projects of Ilorin through questionnaire survey and found that major factors of cost

overruns were fluctuation in the prices of materials/Labour, variation orders, delay in

honouring certificates, lack of proper analysis of tenders, selection of incompetent

contractors, lack of proper appraisal of projects and unrealistic representation of

clients needs.

Jackson (2002) studied reasons of budget overrun in UK through

questionnaire survey and found that major reasons of overrun were design changes,

design development factors, information availability, method of estimation,

performance of design team and project management.

Chang (2002) studied the reasons of cost increase through 4 case projects to

quantify their contributions in engineering design projects in USA. The finding of the

Page 34: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

23

study showed that the major reason for cost increase was owner request of changes in

scope and additional works.

Frimpong et al. (2003) conducted a questionnaire survey consisting of 26

factors to study major contributors of cost overrun in groundwater drilling projects in

Ghana. Out of 26 factors considered, top 10 factors are monthly payment difficulties,

poor contract management, material procurement, inflation, contractor’s financial

difficulties, escalation of material prices, cash flow during construction, planning and

scheduling deficiencies, bad weather and deficiencies in cost estimates prepared.

Koushki et al. (2005) studying problem of cost increase in the private

residential projects of Kuwait mentioned that three main contributors to cost

overruns were contractor-related problems, material-related problems and owners’

financial constraints.

Omoregie & Radford (2006) study found out the major factors causing cost

overrun in infrastructure projects of Nigeria were price fluctuations, financing &

payments of completed works, poor contract management, schedule delay, changes

in site conditions, inaccurate estimates, shortage of material, imported materials &

plant items, additional works, design changes, subcontractors & nominated suppliers,

weather, non-adherence to contract conditions, mistakes & discrepancies in contract

conditions and fraudulent practices.

Azhar et al. (2008) investigated cost overrun causes in construction industry

of Pakistan. A survey using questionnaire containing forty two (42) factors showed

that the top ten cost overrun factors found were fluctuation in prices of raw materials,

unstable cost of manufactured materials, high cost of machineries, lowest bidding

procurement procedures, poor project (site) management/ poor cost control, delays

between design and procurement phases, incorrect/ inappropriate methods of cost

estimation, additional work, improper planning, and unsupportive government

policies.

Le-Hoai et al. (2008) studied the causes of cost overrun in large construction

project of Vietnam using questionnaire survey. The investigation included 21

causative factors and top 5 common and very sever causes of cost overrun were poor

site management and supervision, poor project management assistance, financial

difficulties of owner, financial difficulties of contractor; design changes.

Page 35: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

24

Enshassi et al. (2009) conducted questionnaire survey to identify major

causes of cost overrun in construction projects of Gaza by investigating 42 factors

amongst contractors, consultants and owners. Results indicated that top ten factors

that cause cost overruns as perceived by the three parties include increment of

materials prices due to continuous border closures, delay in construction, supply of

raw materials and equipment by contractors, fluctuations in the cost of building

materials, unsettlement of the local currency in relation to dollar value, project

materials monopoly by some suppliers, resources constraint: funds and associated

auxiliaries not ready, lack of cost planning/monitoring during pre-and post contract

stages, improvements to standard drawings during construction stage, design changes,

and inaccurate quantity take-off.

Kaliba et al. (2009) carried out a study to determine the contributors of cost

escalation in road construction projects of Zambia. The finding of study showed that

the main causes of cost escalation included bad or inclement weather due to heavy

rain and flooding, scope changes, environmental protection and mitigation costs,

schedule delay, strikes, technical challenges, inflation and local government pressure.

Ameh et al. (2010) investigated the causes of cost overrun in 53

telecommunication projects of Nigeria through structured questionnaire survey

containing 42 factors. Survey results showed that top seven factors were lack of

experience of contractors, cost of material, fluctuation in the prices of materials,

frequent design changes, economic stability, high interest rates charged by banks on

loans received by contractors, mode of financing, bonds & payments as well as

fraudulent practices & kickbacks.

These identified factors are part of the whole literature review on the factors

causing cost overrun happening worldwide. Comprehensive review consisting of 46

published articles has resulted in identifying 78 common factors of cost overrun

which were considered for further investigation to find the relevancy and

significance of these factors towards Malaysian construction industry. As a part of

literature review, studies on time overrun factors were also considered as cost

overrun is directly correlated with time overrun (Abdullah, 2010; Aibinu & Jagboro,

2002) and it is difficult to separate the factors causing overrun between cost and time

overrun as the reasons for cost increases are normally also the reasons for time

Page 36: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

REFERENCES

Abdullah, M. R. (2010). Significant causes and effects of construction delay. Master

thesis, University Tun Hussein Onn Malaysia.

Abdullah, M. R., Aziz, A. A. A., & Rahman, I. A. (2009). Causes of delay and its

effects in large MARA construction project. International Journal of

Integrated Engineering (Issue on Mechanical, Materials and Manufacturing

Engineering).

Abedi, M., Mohamad, M. F., & Fathi, M. S. (2011). Major Causes of Construction

Delays Under Client Category and Contractor Category. Paper presented at

the The Proceeding of the First Iranian Student Scientific Conference in

Malaysia.

Aibinu, A. A., & Al-Lawati, A. M. (2010). Using PLS-SEM technique to model

construction organizations' willingness to participate in e-bidding.

Automation in Construction, 19, 714–724.

Aibinu, A. A., & Jagboro, G. O. (2002). The effects of construction delays on project

delivery in Nigerian construction industry International Journal of Project

Management 20, 593–599.

Aibinu, A. A., Ling, F. Y. Y., & Ofori, G. (2011). Structural equation modeling of

organizational justice and cooperative behaviour in the construction project

claims process: contractors' perspectives. Construction Management and

Economics, 29(5), 463-481.

Akter, S., Ambra, J. D., & Ray, P. (2011a). Trustworthiness in mHealth Information

Services: An Assessment of a Hierarchical Model with Mediating and

Moderating Effects Using Partial Least Squares (PLS). Journal Of The

American Society For Information Science And Technology, 62(1), 100–116

Akter, S., Ambra, J. D., & Ray, R. (2011b, 4th -7th August ). An evaluation of PLS

based complex models: the roles of power analysis, predictive relevance and

Page 37: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

114

GoF index. Paper presented at the Proceedings of the Seventeenth Americas

Conference on Information Systems (AMCIS 2011), Detroit Michigan.

Al-Momani, A. (2000). Construction delay: a quantitative analysis. International

Journal of Project Management, 18(1), 51–59.

Al-Najjar, J. M. (2008). Factors Influencing Time and Cost Overruns on

Construction Projects in the Gaza Strip. Master of Science in Civil

Engineering, Faculty of Engineering, The Islamic University – Gaza.

Alaghbari, W., Kadir, M. R. A., Salim, A., & Ernawati. (2007). The significant

factors causing delay of building construction projects in Malaysia.

Engineering, Construction and Architectural Management, 14(2), 192-206.

Ali, A. S., & Kamaruzzaman, S. N. (2010). Cost performance for building

construction projects in Klang valley. Journal of Building Performance, 1(1),

110-118.

Alwi, S., & Hampson, K. (2003). Identifying the importan causes of delays in

building construction projects. Paper presented at the Proceedings The 9th

East Asia-Pacific Conference on Structural Engineering and Construction,

Bali, Indonesia, Retrived from

https://eprints.qut.edu.au/secure/00004156/01/Bali_Conference_2003.doc.

Ameh, O. J., Soyingbe, A. A., & Odusami, K. T. (2010). Significant factors causing

cost overruns in telecommunication projects in Nigeria. Journal of

Construction in Developing Countries, 15.

Amu, O. O., & Adesanya, D. A. (2011). Mathematical Expressions for Explaining

Project Delays in Southwestern Nigeria. Singapore Journal of Scientific

Research, 1(1), 59-67.

Angelo, W. J., & Reina, P. (2002). Megaprojects need more study up front to avoid

cost overruns. Retrieved May 29, 2011, from

http://flyvbjerg.plan.aau.dk/News%20in%20English/ENR%20Costlies%2015

0702.pdf

Apolot, R., Alinaitwe, H., & Tindiwensi, D. (2011). An Investigation into the Causes

of Delay and Cost Overrun in Uganda’s Public Sector Construction Projects.

Paper presented at the Second International Conference on Advances in

Engineering and Technology.

Page 38: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

115

Assaf, S. A., & Al-Hejji, S. (2006). Causes of delay in large construction projects.

International Journal of Project Management, 24(4), 349-357.

Atkinson, R. (1999). Project management: cost, time and quality, two best guesses

and a phenomenon, its time to accept other success criteria. International

Journal of Project Management, 17(6), 337-342.

Avots, I. (1983). Cost-relevance analysis for overrun control. International Journal of

Project Management, 1, 142-148.

Azhar, N., Farooqui, R. U., & Ahmed, S. M. (2008). Cost Overrun Factors In

Construction Industry of Pakistan. Paper presented at the First International

Conference on Construction In Developing Countries (ICCIDC–I)

“Advancing and Integrating Construction Education, Research & Practice”.

Barclay, D., Thompson, R., & Higgins, C. (1995). The Partial Least Squares (PLS)

approach to causal modeling: personal computer adoption and use as an

illustration. Technology Studies, 2(2), 285–309.

Barclay, D. W., Thompson, R., & Higgins, C. (1995). The Partial Least Squares

(PLS) Approach to Causal Modeling: Personal Computer Adoption and Use

an Illustration. Technology Studies, 2(2), 285-309.

Barrick, A. (1995). Poll reveals one in three jobs late. Building, 28 July, 10.

Baxendale, T., & Jones, O. (2000). Construction design and construction

management safety regulations in practice - Progress and implementation.

International Journal of Project Management, 18(1), 33–40.

Begum, R. A., Satari, S. K., & Pereira, J. J. (2010). Waste Generation and Recycling:

Comparison of Conventional and Industrialized Building Systems. American

Journal of Environmental Sciences, 6(4), 383-388.

Begum, R. A., Siwar, C., Pereira, J. J., & Jaafar, A. H. (2006). A benefit–cost

analysis on the economic feasibility of construction waste minimisation: The

case of Malaysia. Resources, Conservation and Recycling, 48, 86–98.

Boomsma, A., & Hoogland, J. J. (2001). The robustness of LISREL model

ingrevisited . In R. Cudeck, S. duToit & D. Sorbom (Eds), Structural equation

modeling : Present and future (pp. 139–168): Chicago, IL: Scientific Software

International.

Page 39: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

116

Bossink, A. G., & Brouwers, H. J. H. (1996). Construction waste: quantification and

source evaluation. Journal of Construction Engineering and Management,

122(1), 55–60.

Burati, J., Farrington, J., & Ledbetter, W. (1992). Causes of quality deviations in

design and construction. Construction Engineering and Management, 118(1).

Byrne, B. M. (1994). Structural equation modeling with EQS and EQS/Windows:

basic concepts, applications and programming: Sage Publications, Thousand

Oaks, Calif.

Byrne, B. M. (2010). Structural Equation Modeling with AMOS Basic Concepts,

Applications, and Programming (2nd ed.): Taylor and Francis Group, LLC.

Cantarelli, C. C. (2009). Cost overruns in Dutch transportation infrastructure projects.

Bijdrage aan het Colloquium Vervoersplanologisch Speurwerk (Contribution

to the Transport Planning Research Colloquium).

Cantarelli, C. C., Flyvbjerg, B., Molin, E. J. E., & Wee, B. v. (2010). Cost Overruns

in Large-scale Transportation Infrastructure Projects: Explanations and Their

Theoretical Embeddedness. European Journal of Transport and Infrastructure

Research (EJTIR), 10(1), 5-18.

Cha, H. S., & Shin, K. Y. (2011). Predicting Project Cost Performance Level by

Assessing Risk Factors of Building Construction in South Korea. Journal of

Asian Architecture and Building Engineering, 437-444.

Chan, D. W. M., & Kumaraswamy, M. M. (1997). A comparative study of causes of

time overruns in Hong Kong construction projects. International Journal of

Project Management, 15(1), 55-63.

Chan, K. L. (2000). Environmental Awareness: Communicating Needs and

Requirements for the Construction Sector. In Building Journal Hong Kong

(Paper presented at The 9th Annual Business & Industry Environment

Conference).

Chan, S., & Park, M. (2005). Project cost estimation using principal component

regression. Construction Management and Economics, 23, 295-304.

Chang, A. S.-T. (2002). Reasons for Cost and Schedule Increase for Engineering

Design Projects. Journal of Management in Engineering, 18(1), 29–36.

Page 40: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

117

Chimwaso, D. K. (2001). An evaluation of cost performance of public projects: Case

of Botswana. Paper presented at the Proceedings of the 2nd International

Conference of the CIB

http://buildnet.csir.co.za/cdcproc/docs/2nd/chimwaso_dk.pdf.

Chin, W. W. (1998). The partial least squares approach to structural equation

modelling. In G. A. Marcoulides (Ed.), Modern Methods for Business

Research (pp. 295–336): Erlbaum, Mahwah, NJ.

Chin, W. W. (2010). How to Write Up and Report PLS Analyses. In V. Esposito

Vinzi et al. (eds.) (Ed.), Handbook of Partial Least Squares, Springer

Handbooks of Computational Statistics: Springer-Verlag Berlin Heidelberg.

Chin, W. W., Marcolin, B. L., & Newsted, P. R. (1996, December 16-18, 1996).

Partial Least Squares Latent Variable Modeling Approach for Measuring

Interaction Effects: Results From A Monte Carlo Simulation Study And

Voice Mail Emotion/Adoption Study. Paper presented at the Proceedings of

the Seventeenth International Conference on Information Systems, Cleveland,

Ohio.

Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with

small samples using partial least squares. In R. Hoyle (ed.), Statistical

strategies for small sample research, , Thousand Oaks, CA: Sage Publications,

307–341.

Choudhury, I., & Phatak, O. (2004, April 8 - 10, 2004). Correlates of Time Overrun

in Commercial Construction. Paper presented at the ASC Proceedings of the

40th Annual Conference, Brigham Young University - Provo, Utah.

Churchill, G. A. (1979). A Paradigm for Developing Better Measures of Marketing

Constructs. Journal of Marketing Research, 16, 64–73.

CIB. (1999). CIB Agenda 21 on sustainable construction, CIB Report Publication

237, International Council for Building Research Studies and Documentation.

Rotterdam, the Netherlands.

CIDB. (2012). Construction Statistics Quarterly Bulletin, Retrived from

( http://www.cidb.gov.my/cidbweb/index.php?option=com_content&view=ar

ticle&id=218&Itemid=314&lang=en) on 20 September 2012.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.).

Page 41: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

118

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied Multiple

Regression/Correlation Analysis for the Behavioral Sciences (Third ed.):

Lawrence Erlbaum Associates, Publishers, Mahwah, New Jersey, London.

Compeau, D. R., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and

individual reactions to computing technology: a longitudinal study. MIS

Quarterly, 23(2), 145–158.

Davison, A. C., & Hinkley, D. V. (1997). Bootstrap methods and their application:

Cambridge University Press.

DETR. (2000). Performance indicators show improvement, Construction Monitor.

Edwards, B. (2001). Rough Guide to Sustainability: RIBA Publications, London.

Efron, B., & Tibshirani, R. J. (1993). An Introduction to the Bootstrap (Monographs

on Statistics and Applied Probability, # 57): Chapman and Hall, New York.

Elinwa, A. U., & Buba, S. A. (1993). Construction Cost Factors in Nigeria. Journal

of Construction Engineering and Management, 119(4), 698-713.

Endut, I. R., Akintoye, A., & Kelly, J. (2009). Cost and time overruns of projects in

Malaysia. retrieved on August 21, 2009, from

http://www.irbnet.de/daten/iconda/CIB10633.pdf, 243-252.

Enshassi, A., Al-Najjar, J., & Kumaraswamy, M. (2009). Delays and cost overruns in

the construction projects in the Gaza Strip. Journal of Financial Management

of Property and Construction, 14(2), 126-151.

Enshassi, A., Lisk, R., Sawalhi, I., & Radwan, I. (2003). Contributors to construction

delays in Palestine. The Journal of American Institute of Constructors, 27(2),

45-53.

Fairs, M. (2001, 28 September). Scottish parliament: The true story. Building and

Environment, 38-43.

Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling: The University of

Akron Press.

Faridah, A. H. A., Hasmanie, A. H., & Hasnain, M. I. (2004). A study on

construction and demolition waste from buildings in Seberang Perai. Paper

presented at the Proceeding of 3rd NationalConference in Civil Engineering,

Copthorne Orchid, Tanjung Bungah, Malaysia.

Page 42: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

119

Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses

using G*Power 3.1: Tests for correlation and regression analyses. Behavior

Research Methods, 41(4), 1149-1160.

Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3: A flexible

statistical power analysis program for the social, behavioral, and biomedical

sciences. Behavior Research Methods, 39(2), 175-191.

Fellows, R., & Liu, A. (1997). Research methods for construction: 2nd ed.:

Blackwell publication.

Flyvbjerg, B., Holm, M. K. S., & Buhl, S. L. (2003). How common and how large

are cost overruns in transport infrastructure projects? Transport Reviews,

23(1), 71-88.

Fong, N. K., Wong, L. Y., & Wong, L. T. (2006). Fire services installation related

contributors of construction delays. Building and Environment, 41, 211–222.

Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: Lisrel and

PLS applied to customer exit-voice theory. Journal of Marketing Research, 19,

440–452.

Fornell, C., & Cha, J. (1994). Partial least squares. In R. P. Bagozzi (Ed.), Advanced

methods of marketing research (pp. 52–78): Cambridge: Blackwell.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with

unobservable variables and measurement error. Journal of Marketing

Research, 18, 39–50.

Forsberg, A., & Saukkoriipi, L. (2007, July 2007). Measurement of waste and

productivity in relation to lean thinking. Paper presented at the Proceedings

IGLC-15, Michigan, USA.

Frame, J. D. (1997). Establishing project risk assessment teams. In K. Kahkonen & K.

A. Artto (Eds.), Managing risks in projects: E & FN Spon, London.

Frary, B. R. (1996). Hints for Designing Effective Questionnaires. Assessment

Research and Evaluation, Virginia Polytechnic Institute Retrieved from

(http://Pareonline.Net/Getvn.Asp?V=S&N=3), 5(3).

Frimpong, Y., Oluwoye, J., & Crawford, L. (2003). Causes of delay and cost

overruns in construction of groundwater projects in a developing countries;

Ghana as a case study. International Journal of Project Management, 21, 321–

326.

Page 43: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

120

Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modelling

and regression: Guidelines for research practice. Communications of the

Association for Information Systems, 4(5), 1–78.

Gotz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of Structural Equation

Models Using the Partial Least Squares (PLS) Approach. In V. Esposito

Vinzi et al. (eds.) (Ed.), Handbook of Partial Least Squares, Springer

Handbooks of Computational Statistics: Springer-Verlag Berlin Heidelberg

Gupta, N. (2009). Avoiding Time and Cost Overruns in the Construction of Rohtang

Tunnel. Institute for Defence Studies and Analyses, December 14.

Haenlein, M., & Kaplan, A. M. (2004). A beginner's guide to partial least squares

(PLS) analysis. Understanding statistics, 3(4), 283–297.

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data

analysis: 5th ed. Prentice-Hall, Upper Saddle River, N.J.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet.

Journal of Marketing Theory and Practice, 19(2), 139–151.

Hair, J. F., William, C. B., Barry, J. B., & Anderson, R. E. (2010). Multivariate Data

Analysis: Englewood Cliffs, NJ: Prentice Hall.

Harisweni. (2007). The Framework for Minimizing Construction time and Cost

Overruns in Padding and Pekanbaru, Indonesia. Unpublished Unpublished,

Universiti Teknologi Malaysia.

Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The Use of partial least

Squares Path modeling in International Marketing. Advances in International

Marketing, 20, 277–319.

Hill, T., & P. Lewicki. (2006). Statistics Methods and Application: StatSoft.

Hulland, J. (1999). Use of partial least squares (PLS) in strategic management

research: a review of four recent studies. Strategic Management Journal, 20,

195–204.

Hussin, J. M., Rahman, I. A., & Memon, A. H. (2012a). The Way Forward in

Sustainable Construction: Issues and Challenges. International Journal of

Advances in Applied Sciences (IJAAS), 1(3).

Hussin, J. M., Rahman, I. A., & Memon, A. H. (2012b). The Way Forward in

Sustainable Construction: Issues and Challenges. Paper presented at the

Page 44: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

121

International Conference on civil and Environmental Engineering for

Sustainability (IConCEES2012).

Ibrahim, A. R., Roy, M. H., Ahmed, Z., & Imtiaz, G. (2010). An investigation of the

status of the Malaysian construction industry. Benchmarking: An

International Journal, 17(2), 294-308.

Islam, M. D. M., & Faniran, O. O. (2005). Structural equation model of project

planning effectiveness. Construction Management and Economics, 23(2), 215

- 223.

Jack, P. C. K., Russell, C. H. C., & Bert, B. (2001). Validation of trace-driven

simulation models: bootstrap tests. Management Science, 47(11), 1533–1538.

Jackson, J. L., Dezee, K., Douglas, K., & Shimeall, W. (2005). Introduction to

structural equation modeling (path analysis) [Electronic Version]. Precourse

PA08. Society of General Internal Medicine (SGIM), Washington, D.C.

Available from

http://www.sgim.org/userfiles/file/AMHandouts/AM05/handouts/PA08.pdf.

Jackson, O., & Steven, O. (2001). Management of cost overrun in selected building

construction project in Ilorin. Review of Business and Finance, 3(1).

Jackson, S. (2002, 2-4 September). Project cost overruns and risk management.

Paper presented at the Greenwood, D. (Ed.) Proceedings of Association of

Researchers in Construction Management 18th Annual ARCOM Conference,

Newcastle.

Kaliba, C., Muya, M., & Mumba, K. (2009). Cost escalation and schedule delays in

road construction projects in Zambia. International Journal of Project

Management, 27, 522–531.

Kaming, P. F., Olomolaiye, P. O., Holt, G. D., & Harris, F. C. (1997). Factors

influencing construction time and cost overruns on high-rise projects in

Indonesia. Construction Management and Economics, 15, 83-94.

Kartam, N. (1997). Integrating safety and health performance into construction CPM.

Journal of Construction Engineering and Management, 123(2), 121–126.

Khamidi, M. F., Khan, W. A., & Idrus, A. (2011). The Cost Monitoring of

Construction Projects Through Earned Value Analysis. Paper presented at the

International Conference on Economics and Finance Research, Singapore.

Kin-sun, T. (2004). Sustainable construction in Hong Kong, Unpublished Thesis.

Page 45: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

122

Kline, R. B. (2005). Principles and practice of structural equation modeling, 2nd

Edition: Guilford Press, New York.

Kometa, T. S., & Olomolaiye, P. O. (1997). Factors influencing construction client's

decisions to build. Journal of Management in Engineering, 13(2), 77-86.

Koskela, L. (1992). The application of the new production philosophy to

construction'. Technical Report No. 72, Stanford University, Stanford, CA.

Koushki, P. A., Al-Rashid, K., & Kartam, N. (2005). Delays and cost increases in the

construction of private residential projects in Kuwait. Construction

Management and Economics, 23(3), 285–294.

Kumar, R. (2005). Research methodology: a step-by-step guide for beginners: SAGE

Publication.

Kumaraswamy, M. M. (2006). Accelerating construction industry development.

Journal of Construction in Developing Countries, 11(1), 73-96.

Le-Hoai, L., Lee, Y. D., & Lee, J. Y. (2008). Delay and Cost Overruns in Vietnam

Large Construction Projects: A Comparison with Other Selected Countries.

KSCE Journal of Civil Engineering, 12(6), 367-377.

Ledbetter, W. B. (1994). Quality performance on successful projects. Journal of

Construction Engineering and Management, 120(1).

Lee, J.-K. (2008). Cost Overrun and Cause in Korean Social Overhead Capital

Projects: Roads, Rails, Airports, and Ports. Journal of Urban Planning and

Development, 134(2), 59–62.

Leung, W. T., & Tam, C. M. (2004). Scheduling For High-Rise Building

Construction Using Simulation Techniques. Paper presented at the

Proceeding of 20th International Conference CIB-W78.

Litwin, M. S. (1995). How to Measure Survey Reliability and Validity: Sage,

Thousand Oaks, CA.

Long, N. D., Ogunlana, S., Quang, T., & Lam, K. C. (2004). Large construction

projects in developing countries: a case study from Vietnam. International

Journal of Project Management, 22, 553–561.

Love, P. (2002). Influences of project type and procurement method on rework costs

in building construction projects. Journal of Construction Engineering and

Management.

Page 46: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

123

Mansor, S. A. (2010). The 7th Malaysia Construction Sector Review and Outlook

Seminar. Retrieved. from.

Marcoulides, G. A., & Saunders, C. (2006). PLS: A silver bullet? A commentary on

sample size issues in PLS modeling. MIS Quarterly, 30(2), 3-10.

Marosszeky, M., Thomas, R., Karim, K., Davis, S., & McGeorge, D. (2002). Quality

management tools for lean production - moving from enforcement to

empowerment. Paper presented at the Proceedings IGLC-10, Gramado, Brazil.

Meeampol, S., & Ogunlana, S. O. (2006). Factors affecting cost and time

performance on highway construction projects: evidence from Thailand.

Journal of Financial Management of Property and Construction, 11(1), 3 - 20.

Mohamed, S. (2002). Safety climate in construction site environments. Journal of

Construction Engineering and Management, 128(5), 375–384.

Molenaar, K., Washington, S., & Diekmann, J. (2000). Structural equation model of

construction contract dispute potential. Journal of Construction Engineering

and Management 126(4), 268–277.

Moura, H. P., Teixeira, J. C., & Pires, B. (2007). Dealing With Cost and Time in the

Portuguese Construction Industry. Paper presented at the CIB World Building

Congress.

Murali, R. S. N. (2011). An Irresponsable Act: Tropical Mangrove Swamp has

Become a Construction Dumpsite. The Star, Newspaper, 22 September 2011,

Page 3.

NACL. (2000). National Accounting Court of Law Auditory Reports no 20/2001-2,

seccao. Volume III, no 43/2000-2.

Nagapan, S., Rahman, I. A., Azis, A. A. A., Memon, A. H., & Zin, R. M. (2012).

Identifying Causes of Construction Waste – Case of Central Region of

Peninsula Malaysia. International Journal of Integrated Engineering, Issue on

Civil and Environmental Engineering, 4(2), 22-28.

Nahmens, I., & Ikuma, L. H. (2009). An Empirical Examination of the Relationship

between Lean Construction and Safety in the Industrialized Housing

Industry, . Lean Construction Journal, 1-12.

NAO. (1998). Cost Over-runs, Funding Problems and Delays on Guy's Hospital

Phase III Development, Reported by the Comptroller and Auditor General,

National Audit Office, London.

Page 47: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

124

Nasaruddin, F. H., Ramli, N. H. M., & S. D. Ravana. (2008). E-Construction Waste

Exchange in Malaysia: A Preliminary Study. Paper presented at the

Proceedings of Information Technology International Symposium, Kuala

Lumpur, Malaysia.

Nega, F. (2008). Causes and effects of cost overrun on public building construction

projects in Ethiopia.

Ng, T. S., Wong, Y. M. W., & Wong, J. M. W. (2010). A structural equation model

of feasibility evaluation and project success for public private partnerships in

Hong Kong. I E E E Transactions on Engineering Management, 57(2), 310-

322.

Norman, G. R., & Streiner, D. L. (2003). PDQ Statistics, 3rd edition: B C Decker Inc.

Nunnally, J. C. (1976). Psychometric theory: McGraw-Hill, New York.

Odeck, J. (2004). Cost overruns in road construction—what are their sizes and

determinants? Transport Policy, 11(1), 43-53.

Odeh, A. M., & Battaineh, H. T. (2002). Causes of construction delay: traditional

contracts. International Journal of Project Management, 20(1), 67-73.

Ogunlana, S. O., & Promkuntong, K. (1996). Construction delays in a fast-growing

economy: Comparing Thailland with other economies. International Journal

of Project Management, 14(1), 37–45.

Okpala, D. C., & Aniekwu, A. N. (1988). Causes of high costs of construction in

Nigeria. Journal of Construction Engineering and Management Accounting

Research, 114(2), 233-244.

Olatunji, O. A. (2008). A comparative analysis of tender sums and final costs of

public construction and supply projects in Nigeria. Journal of Financial

Management of Property and Construction, 13(1).

Olawale, Y. A., & Sun, M. (2010). Cost and time control of construction projects:

inhibiting factors and mitigating measures in practice. Construction

Management and Economics, 28(5), 509–526.

Omoregie, A., & Radford, D. (2006). Infrastructure delays and cost escalation:

Causes and effects in Nigeria. Paper presented at the Proceeding of sixth

international postgraduate research conference.

Potty, N. S., Idrus, A. B., & Ramanathan, C. T. (2011). Case Study and Survey on

Time and Cost Overrun of Multiple D&B Projects. IEEE.

Page 48: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

125

Rachel, L. W.-c. (2006). Effectiveness of safety management system on Hong Kong

construction industry under factories and industrial undertakings (safety

management) regulation, .

Rahmat, N. S., & Ibrahim, A. H. (2007). Illegal Dumping Site: Case Study in the

District of Johor Bahru Tengah, Penang, Malaysia.

Railway-Technology.com. (2011). Ipoh-Padang Besar Electrified Railway Project,

Malaysia, retrieved on 8.03am 15-6-2012 from http://www.railway-

technology.com/projects/ipohpadangbesarelect/ipohpadangbesarelect1.html.

Rashid, K. A., & Morledge, R. (1998). Construction procurement processes in

Malaysia: constraints and strategies. Paper presented at the In: Hughes, W

(Ed.), 14th Annual ARCOM Conference, 9-11 September 1998, University of

Reading. Association of Researchers in Construction Management.

Richter, L., & Scheid, J. (2011). A Microsoft Excel Project Planning Form retrieved

from

http://www.brighthubpm.com/office/projectmanagemnet/articles/31029.aspx.

Rigdon, E. E. (1998). Structural equation modeling. In In : G. A. Marcoulides (Ed.),

Modern methods for business research, Mahwah, N J: Lawrence Erlbaum

Associates. (pp. 251–294).

Ringle, C. M., Wende, S., & Will, S. (2005). SmartPLS 2.0 (M3) Beta, Hamburg

2005, http://www.smartpls.de.

Rodman, D., & Lenssen, N. (1994). Our buildings, ourselves. World Watch, 7(6), 9-

21.

Rowlinson, S. (2003). Hong Kong Construction: Safety Management and the Law.

Sweet & Maxwell Asia.

Russell, J. (1992). Underwriting process for construction contract bonds. Journal of

Management in Engineering, 8(1), 63–80.

Sambasivan, M., & Soon, Y. W. (2007). Causes and effects of delays in Malaysian

construction industry. International Journal of Project Management, 25, 517–

526.

Sekaran, U., & Bougie, R. (2010). Research Methods for Business: A Skill Building

Approach. UK: John Wiley & Sons.

Page 49: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

126

Seow, T. W., & Mohamad, A. H. (2007). Construction Waste Management on Site.

Paper presented at the Proceedings of Universiti Perguruan Sultan Idris,

Tanjong Malim, Perak.

Shen, L. Y., & Tam, W. Y. (2002). Implementation of environmental management in

the Hong Kong construction industry. International Journal of Project

Management, 20, 535-543.

Siti, N. M., & Noor, Z. M. (2008). Approach in construction industry: A study on

prefabrication method as a tool for waste minimization. Paper presented at the

Proceeding of International Conference on Environmental Research and

Technology (ICERT), Penang, Malaysia.

Sohail, M., Miles, D., & Cotton, A. (2002). Developing monitoring indicators for

urban micro contracts in South Asia. International Journal of Project

Management.

Staples, D. S., Hulland, J. S., & Higgins, C. (1999). A selfefficacy theory explanation

for the management of remote workers in virtual organizations. Organization

Science, 10(6), 758–776.

Sweden, A. G. o. (1995). Riksrevisionsverket. Infrastrukurinvestingar: En

Kostnadsjamorelse Mellan Poan of Utyfall i 15 Storre Prosjekt

InnomVagverket of Banverket RVV 23.

Tan, K. W. (2012). MBPJ to clear debris before Chinese New Year. Page 4. The Star

Newspaper, 10 January 2012, Page 4.

Thomas, R., Marosszeky, M., Karim, K. M., Davis, S., & McGeorge, D. (2002). The

importance of project cultures in achieving quality outcomes in construction.

Paper presented at the Proceedings of 10th Conference of the International

Group for Lean Construction, Fedral University of Rio Grande do Sul Brazil,.

Toh, T. C., Ali, K. N., & Aliagha, G. U. (2011). Modeling Construction Cost Factors

in the Klang Valley Area of Malaysia. Paper presented at the IEEE

Symposium on Business, engineering and Industrial Applications (ISBEIA).

Vinzi, V. E., Trinchera, L., & Amato, S. (2010). PLS Path Modeling: From

Foundations to Recent Developments and Open Issues for Model Assessment

and Improvement. In V. Esposito Vinzi et al. (eds.), Handbook of Partial

Least Squares, Springer Handbooks of Computational Statistics (pp. 47-82).

Page 50: STRUCTURAL MODELLING OF COST OVERRUN FACTORS IN

127

Wetzels, M., Schroder, G. O., & Oppen, V. C. (2009). Using PLS path modeling for

assessing hierarchical construct models: Guidelines and empirical illustration.

MIS Quarterly, 33(1), 177–195.

Wheeler, C. (1998). Thanks for the insight. Building, 9 January, 17.

Wold, H. (1989). Introduction to the Second Generation of Multivariate Analysis in

Theoretical Empiricism: Paragon House, New York, pp. vii-xi.

Wong, P. S. P., & Cheung, S. O. (2005). Structural Equation Model of Trust and

Partnering Success. Journal of Management in Engineering, 21(2), 70–80.

Yahaya, N., & Larsen, I. (2008). Federalising Solid Waste Management in

Peninsular Malaysia, . Paper presented at the Proceeding of International

Solid Waste Association (ISWA) World Congress, Singapore.

Yang, J. B., & Ou, S. F. (2008). Using structural equation modeling to analyze

relationships among key causes of delay in construction. Canadian Journal of

Civil Engineering, 35, 321–332.

Yogeswaran, K., Kumaraswamy, M., & Miller, D. (1998). Claims for extension of

time in civil engineering projects. Construction Management and Economics,

16(3), 283–293.

Young-Mok, K., Soo-Yong, K., & Truong-Van, L. (2008). Causes of construction

delays of apartment construction projects: Comparative analysis between

Vietnam and Korea. 214-226.

Zhu, K., & Lin, L. (2004). A stage-by-stage factor control frame work for cost

estimation of construction projects. paper presented at Owners Driving

Innovation International Conference, available at:

http://flybjerg.Plan.aau.dk/JAPAASPUBLISHED.pelf.

Zujo, V., Car-Pusic, D., & Brkan-Vejzovic, A. (2010). Contracted price overrun as

contracted construction time overrun function. Technical Gazette, 17(1), 23-

29.

Zujo, V., & Car, D. (2008). Application of “time-cost” model in construction project

management