the islamic university · the islamic university of gaza ... thanks to the staff and the deans of...

The Islamic University – Gaza

Faculty of Engineering

Higher Education Deanship

Construction project management

زةـــغ –ة ــيــلامــــة الاســـعـــامــجــل ا

ةــــدســنــهــل ة اــيــلــك

اـــيـــلـــعــل ات اـــــدراســادة الــمــع

ةــيـــــسهــنـــدالوعــات رــــشــمالدارة إ

Master Dissertation in Construction Management

The success factors that affecting public construction projects

and their relation to key performance indicators

عوامل النجاح التي تؤثر على مشاريع الإنشاءات العامة وعلاقتها بالأداء

Prepared by:

Sirin K. Elbohisi

Supervised by:

Prof. Adnan Enshassi

Professor of Construction Engineering and Management

A thesis is submitted in partial fulfillment of the requirement for

Degree of Master of Science in Civil Engineering – Construction Management

The Islamic University of Gaza

January, 2016

II

والله مكم الله ويعله بكله شيء عليم واتقوا الله

282سورة البقرة،

III

Dedication

This research is dedicated to all people who inspired, supported and encouraged me.

"To my parents, thank you for your endless love, support, and encouragement."

"To my brothers and sisters: Khadiga, Arwa, Hamzah, Muath, Salam, Abed Elrzaq,

Iman, Sufyan, Asma, Shima, Ahamed and Iqbal, thanks for making my life special and

have never left my side".

To my great teachers, thanks for all the things you have done for me. To my friends who

encourage and support me. Last but not least, deepest thanks go to all people who took

part in making this thesis real. All the people in my life who touch my heart.

IV

Acknowledgement These acknowledgements presented to sincerely thank people who supported, guided, and

encouraged me along the way to complete this research. Without their assistance,

encouragement, suggestions and commitment, this dissertation would not have been a

reality. From the depth of my heart I would like to express sincere gratitude and

appreciation to my supervisor Professor Adnan Enshassi who worked hard with me

throughout the route. Due to his continued support, generous academic advice,

discussions, suggestions, and his incredible understanding and capability to initiate

guidelines, I would like to pass him special thanks. Furthermore, I highly appreciate the

efforts of Dr. Jawad Alagh, Abed Elrhaman Ayyash and my brother Sufyan Elbohisi for

their support and big efforts in helping me in this research.

As well, I would like to thank all experts especially Dr. Yousef Elgaraiz, Dr. Khalid

Alhalaq and Dr. Ibrahim Madi for their contribution and valuable opinion. Also my

thanks to the staff and the deans of the faculty of Engineering at University of Palestine

for their most welcoming support and friendly environment.

A special thanks to consultants and engineers in Gaza Strip and West Bank for their

enormous help in collecting the surveys and their participated in the questionnaire. I am

grateful to Eng. Wasem Elkhaldi for helping in designing Electronic questionnaire and

Mr. Mohammed Elhawajre for helping in distributing and collecting the questionnaire

and Eng. Bassam Shallan for his big support in collecting data from West Bank. Finally,

to my family, very special thanks for all their sacrifices, patience, love and support

throughout my research studies.

Eng. Sirin K. Elbohisi

V

Abstract

Purpose: Construction industry is characterized by complexity nature; being challenged

by high cost pressure, and increasing competition. The aim of this research was to

investigate the success factors that affecting public construction projects and their

relation to key performance indicators in Palestine. This has been achieved throw three

main objectives which were 1) identifying and evaluating the key performance indicators

(KPIs) of public construction projects, 2) investigating the critical success factors CSFs

affecting the public construction projects and 3) evaluating the relationship between KPIs

and CSFs in the public construction projects.

Design/methodology/approach: Intensive literature review was done and a quantitative

survey was designed and used in the research. Two main steps were used to reach the

final amendment of the questionnaire: (1) Experts consultation by presenting the

questionnaire to 6 experts in construction projects from Palestine to evaluate

questionnaire clarity, comprehensivness and readability. (2) Pilot study was conducted by

distributing 20 copies of the questionnaire to respondents from the target group which

include engineering professionals (civil or architectural engineers who works as project

managers, field supervisors and designers) and analyzing them for testing statistical

validity and reliability. Three hundred and eighty four copies of the questionnaire were

distributed and two hundred and seventy four copies were received from the respondents

with a response rate = 71.35%. To draw meaningful results, the collected data have been

analyzed by using the quantitative data analysis techniques (which include Relative

important index RII, Factor analysis, Pearson correlation analysis, and others) through the

Statistical Package for Social Science (SPSS) IBM version 22.

Findings: From literature review and pilot study 13 KPIs were determined in this study.

Factor analysis was used to reduce and group the 13 KPIs. As a result of factoring 11

KPIs were remaining and grouped into three groups namely: 1) project quality and

environment impact, 2) satisfaction and reputation of project parties and 3) overall cost

and time. Descriptive statistics used to rank the 13 KPI and results revealed that the top

three most important KPIs were 1) project conformity to quality and technical

specifications standards, 2) actual project costs compared with planned budget and 3)

actual project duration compared with planned duration. Also results indicated that

Palestinian construction projects suffer from cost and time overrun and the quantity and

costs of variation orders are high.

Also from literature review and pilot study 81 CSFs were obtained. They were classified

according to project life cycle into four phases. By using factor analysis the number were

reduced to 52 CSFs and grouped into 14 component. Results also showed that all 81

CSFs were important since the least RII was above 75.51%. The top five most important

CSFs from the respondents view were 1) project feasibility and priority for the society, 2)

coordinating with related formal parties such as (municipalities, electricity companies,

ministries,… etc.), 3) document the preparation meetings in details, 4) project manager

VI

commitment to meet cost quality and time of project and 5) the client follows project

implementation regularly. Also results showed that there were significant relationship

between CSFs and KPIs which means that project KPIs affected by CSFs.

Theoretical and practical implications of the research: The research unravels about an

important concept and paves the path for future research in this particular area. It is

concerned with construction professionals working in governmental and non-

governmental organizations and consultant firms. The questionnaire survey did not

include all collected factors from literature review, since it was generalized that adopted

to Palestine. Recommendations were made for clients, consultants and contractors

respectively in order to optimize the their construction projects success. It is hoped that

the obtained KPIs and CSFs in this study can be applied and examines practically in

construction projects.

Originality/ value: This research will add to the current body of knowledge about KPIs

and CSFs all over the world. Rarely studies have examined the relationship between KPIs

and CSFs according to projects life cycle. This research is considered as one of these

limited studies which link between KPIs and CSFs according to projects life cycle. It is

the first study that contributes significantly to consider KPIs and CSFs in Palestine. This

study can provide a documentation of reference for the researcher who interested in the

field of the study.

Keywords: key performance indicators KPIs, critical success factors CSFs, life cycle,

public construction projects.

VII

Abstract (Arabic)

ملخص البحث

تحديات ارتفاع التكاليف والمنافسة. بناء على ذلك : تمتاز صناعة الإنشاءات بأنها ذات طبيعة معقدة وتواجه الغرضكان الغرض من هذا البحث دراسة عوامل النجاح وعلاقتها بالأداء في مشاريع الإنشاءات العامة. وقد تم تحقيق هذا

( تحديد وتقييم مؤشرات الأداء المفتاحية لمشاريع 1الغرض عن طريق ثلاثة أهداف من خلال البحث وهي: ( تقييم العلاقة بين 3( دراسة عوامل النجاح الحرجة التي تؤثر على مشاريع الإنشاءات العامة و 2لعامة، الإنشاءات ا

مؤشرات الأداء المفتاحية للمشاريع وعوامل النجاح الحرجة.وفق منهج استبانةومن خلالها تم تصميم الدراسة مجال المتعلقة ب: تم دراسات الأبحاث السابقة منهجية البحث

6( تحكيمه من خلال 1عن طريق الاستبانةاس الكمي في هذا البحث. وقد تم الوصول للنسخة النهائية من القي ةانوضوح وسهولة فهم وشمولية الاستب خبراء في صناعة الإنشاءات بفلسطين حيث استعين بهم لتنقيح وقياس مدى

فئة المستهدفة المتمثلة بمهندسين محترفين نسخة منه لل 20من خلال توزيع عدد للاستبانة( عمل دراسة تجريبية 2المعماري والذين يعملون كمدراء للمشاريع أو مصممين أو مشرفين ميدانيين وبناء عليه تم من تخصصات المدني أو

وتم استعادة مئتان وأربعة استبانةتحليل صدق وثبات الاستبانة. ومن ثم تم توزيع عدد ثلاثمائة واربعة وثمانون %. ومن أجل الخروج بنتائج ذات قيمة تم عمل تحليل للبيانات 71.35ها بنسبة استجابة بلغت قرابة وسبعون من

المحصلة بطرق التحليل الكمي مثل الوزن النسبي والتحليل العاملي ومعامل بيرسون وغيرها وذلك باستخدام برنامج .SPSS22التحليل الإحصائي

مؤشر أداء مفتاحي للمشاريع في هذه الدراسة. وقد تم استخدام التحليل 13تم تجميع وتنقيح عدد نتائج البحث:مؤشر اداء مفتاحي موزعة على ثلاث 11العاملي لتقليل عددها ووضعها ضمن مجموعات. وكنتيجة لذلك بقي عدد

( التكلفة والوقت الإجماليين 3روع و ( رضا وسمعة أطراف المش2( جودة المشروع وتأثيراته البيئية، 1مجموعات وهي مؤشر وكانت النتيجة أن أهم ثلاثة مؤشرات مفتاحية 13للمشروع. كما تم استخدام الإحصاء الوصفي لترتيب ال

( التكلفة الفعلية للمشروع مقارنة بموازنته المخططة و 2( مطابقة المشروع لمعايير ومواصفات الجودة، 1للأداء هي للمشروع مقارنة بالمقدرة. كما وأظهرت النتائج أن صناعة الإنشاءات في فلسطين تعاني من زيادة في ( المدة الفعلية3

التغيرية.الأوامر عدد وتكلفة التكلفة والمدة عن ما هو مخطط وارتفاع فيزيعها وفقا عامل نجاح حرج للمشروع. وقد تم تو 81كما أنه ومن خلال الدراسات السابقة وتحكيم الاستبيان تم تجميع

عامل نجاح حرج 52لدورة حياة المشروع لأربع مراحل. وقد تم استخدام التحليل العاملي الذي قلص عددها إلى هامة ومتوسط الوزن 81مجموعة. كما وأظهرت النتائج أن جميع عوامل النجاح الحرجة وعددها 14مقسمة على ظهر النتائج أن أهم خمس عوامل نجاح حرجة للمشروع هي %. وكنتيجة لترتيبها وفق الأهمية ت75.51النسبي لها

( التنسيق مع الجهات الرسمية من وزارات وبلديات وشركات... 2( دراسة جدوى المشروع وأولويته بالنسبة للمجتمع، 1الك ( متابع ةالم5( التزام مدير المشروع بتكلفة ووقت المشروع و 4( توثيق اللقاءات التحضيرية للعطاءات، 3إلخ،

للمشروع بشكل مستمر. كما وتظهر النتائج وجود علاقة دالة إحصائيا بين مؤشرات قياس الأداء المفتاحية وعوامل النجاح الحرجة للمشروع.

VIII

الدراسة تبحث في عنوان ومفاهيم تفتح الآفاق للبحث المستقبلي في هذا الجزء التطبيقات النظرية والعملية للبحث:محترفي قطاع الإنشاءات الذين يعملون في المؤسسات الحكومية وغير مدت على أراء إن الدراسة اعتالهام.

نما تم تعديل الحكومية. لم يتم وضع جميع ما تم جمعه من الدراسات السابقة في الاستبيان الذي هو أداة الدراسة وا موجهة للمالكين والاستشاريين وتنقيح المؤشرات وعوامل النجاح بما يتناسب مع فلسطين. والتوصيات الخاصة بالبحث

والمقاولين لتساعدهم على تحسين نجاح المشاريع. ويأمل الباحث أن يتم الاستفادة من مؤشرات قياس الأداء المفتاحية وعوامل النجاح الحرجة التي تم الخلوص لها بهذه الدراسة في تطوير مشاريع الإنشاءات بصفة عامة.

بحث إلى الجسم المعرفي حول مؤشرات قياس المشاريع المفتاحية وعوامل النجاح يضيف هذا ال قيمة واهمية البحث:الحرجة. حيث أن يكاد لا يوجد دراسات سابقة تبحث في علاقة مؤشرات قياس الأداء المفتاحية وعوامل النجاح

ال. كما أن هذه الحرجة على أساس دورة حياة المشروع. وتعد هذه الدراسة الأولى من نوعها في فلسطين بهذا المج الدراسة يمكن أن تعتبر مرجعا للباحثين في مجال الدراسة.

IX

Table of contents

The success factors that affecting public construction projects and their relation to key

performance indicators ............................................................................................................... I Dedication ..................................................................................................................................... III

Acknowledgement ......................................................................................................................... IV

Abstract ........................................................................................................................................... V

Abstract (Arabic) .......................................................................................................................... VII

Table of contents ........................................................................................................................... IX

List of abbreviations ..................................................................................................................... XII

List of Tables ............................................................................................................................... XIII

List of Figures .............................................................................................................................. XV

Chapter1: Introduction .................................................................................................................... 1

1.1 Background.......................................................................................................................... 1 1.2 The current status of the construction industry in Palestine ............................................... 1 1.3 Statement of the problem ..................................................................................................... 3 1.4 Research objectives and questions ...................................................................................... 4 1.4.1 Research objectives ............................................................................................................. 4 1.4.2 Research questions .............................................................................................................. 4 1.5 Limitations of the research .................................................................................................. 6 1.6 Research layout ................................................................................................................... 6

Chapter 2: Literature Review .......................................................................................................... 9

2.1 Countries classification ....................................................................................................... 9 2.2 Key performance indicators (KPI) .................................................................................... 10 2.2.1.1 Time and Cost ............................................................................................................. 11 2.2.1.2 Health and Safety ....................................................................................................... 12 2.2.1.3 Value and Profitability ............................................................................................... 12 2.2.1.4 Quality ........................................................................................................................ 12 2.2.1.5 Functionality .............................................................................................................. 13 2.2.1.6 Productivity ................................................................................................................ 13 2.2.1.7 Benchmarks ................................................................................................................ 14 2.2.1.8 Satisfaction ................................................................................................................. 14 2.2.1.9 Environmental sustainability ...................................................................................... 14 2.2.2 KPI on developing countries studies ................................................................................. 15 2.2.3 KPI on developed countries studies................................................................................... 17 2.3 Critical success factors ...................................................................................................... 22 2.3.1 Background........................................................................................................................ 22 2.3.2 CSFs in developing countries studies ................................................................................ 23

X

2.3.3 CSFs in developed countries studies ................................................................................. 32 2.4 Relationship between KPIs and CSFs ............................................................................... 47 2.4.1 KPIs and CSFs relationship on developing countries studies ........................................... 47 2.4.2 KPIs and CSFs relationship on developed countries studies ............................................ 51 2.5 Summary ............................................................................................................................ 52

3. Chapter3: Research Methodology ......................................................................................... 54

3.1 Research framework .......................................................................................................... 54 3.2 Research period ................................................................................................................. 57 3.3 Rationale of use quantative approach ............................................................................... 57 3.4 Research location .............................................................................................................. 58 3.5 Research population and sample ....................................................................................... 59 3.5.1 Research sample elements ................................................................................................. 59 3.5.2 Research population categories ........................................................................................ 59 3.5.3 Sample size ........................................................................................................................ 60 3.5.4 Sampling procedure ........................................................................................................... 62 3.6 Questionnaire Design ........................................................................................................ 63 3.6.1 General information .......................................................................................................... 64 3.6.2 Key performance indicators .............................................................................................. 64 3.6.3 Critical success factors ...................................................................................................... 65 3.7 Pilot study .......................................................................................................................... 67 3.7.1 Experts consultation .......................................................................................................... 67 3.7.2 Distributing questionnaire to limited group ...................................................................... 71 3.7.3 Statistical results of pilot study .......................................................................................... 71 3.7.3.1 Criterion and structural validity of the questionnaire ................................................ 71 3.7.3.2 Half Split Coefficient for reliability of the questionnaire ........................................... 71 3.7.3.3 Cronbach’s Alpha Coefficient for reliability of the questionnaire ............................. 72 3.8 Main questionnaire distribution ........................................................................................ 72 3.9 Quantitative data analysis using SPSS .............................................................................. 74 3.9.1 Reliability statistics ........................................................................................................... 74 3.9.1.1 Alpha-Cronbach coefficient........................................................................................ 75 3.9.1.2 Half Split Method ....................................................................................................... 75 3.9.2 Validity statistics ............................................................................................................... 76 3.9.2.1 Pearson correlation coefficients for criterion related validity ................................... 76 3.9.2.2 Pearson correlation coefficients for structure validity ............................................... 76 3.9.3 Kolmogorov-Smirnov Test of Normality ............................................................................ 76 3.9.4 Relative Importance Index (RII) ........................................................................................ 77 3.9.5 Parametric tests: ............................................................................................................... 78 3.9.5.1 One sample t test. ....................................................................................................... 78 3.9.5.2 One way ANOVA. ....................................................................................................... 78 3.9.6 Factor analysis .................................................................................................................. 78 3.9.6.1 Types of factor analysis .............................................................................................. 79 3.9.6.2 Methods of factoring .................................................................................................. 79 3.9.6.3 The distribution of data .............................................................................................. 79 3.9.6.4 Validity of sample size ................................................................................................ 80 3.9.6.5 Validity of correlation matrix (correlations between variables) ................................ 80 3.9.6.6 Kaiser-Meyer-Olkin (KMO) and Bartlett's Test as a measure of appropriateness of

Factor Analysis .......................................................................................................................... 80 3.9.6.7 Determining the number of factors ............................................................................. 81 3.9.6.8 Mathematical validity of factor analysis .................................................................... 81 3.1 Summary ............................................................................................................................ 82

XI

4. Chapter 4: Results and discussion ......................................................................................... 84

4.1 Scope of chapter ................................................................................................................ 84 4.2 Demographic survey of respondents ................................................................................. 85 4.3 Key performance indicators .............................................................................................. 86 4.3.1 Factor analysis results for KPIs ........................................................................................ 86 4.3.1.1 Appropriateness of factor analysis ............................................................................. 86 4.3.1.2 The extracted components .......................................................................................... 95 4.3.2 Ranking of KPIs of construction projects .......................................................................... 99 4.3.3 Public construction projects KPIs evaluation (actual versus planned performance) ..... 103 4.4 Critical success factors CSFs .......................................................................................... 106 4.4.1 Factor analysis results for CSFs ..................................................................................... 106 4.4.1.1 CSFs related to conceptualizing and preparation phase ......................................... 106 4.4.1.1.1 Appropriateness of factor analysis ....................................................................... 106 4.4.2 The extracted components ............................................................................................... 115 4.4.2.1 CSFs related to planning and designing phase ........................................................ 119 4.4.2.1.1 Appropriateness of factor analysis ....................................................................... 119 4.4.2.1.2 The extracted components .................................................................................... 131 4.4.2.2 CSFs related to tendering and contracting phase .................................................... 135 4.4.2.2.1 Appropriateness of factor analysis ....................................................................... 135 4.4.2.2.2 The extracted components .................................................................................... 146 4.4.2.3 CSFs related to implementation phase ..................................................................... 150 4.4.2.3.1 Appropriateness of factor analysis ....................................................................... 150 4.4.2.3.2 The extracted components .................................................................................... 162 4.4.2.4 Summary of factor analysis for CSFs ....................................................................... 168 4.4.3 Ranking of CSFs which affect public construction projects ............................................ 169 4.5 KPIs and CSFs relationship ............................................................................................ 173 4.6 Differences among respondents toward the analysis of CSFs and KPIs on Palestine .... 175 4.7 Summary of results .......................................................................................................... 180

5. Chapter 5: Conclusions and recommendations ................................................................... 183

References ................................................................................................................................... 190

Appendix I: Literature reviews summary tables .......................................................................... 201

Appendix II: Questionnaire (English) ......................................................................................... 237

Appendix III: Questionnaire (Arabic) ......................................................................................... 245

Appendix IV: Criterion and structural validity of the questionnaire ........................................... 253

Appendix V: Summary of selected and omitted KPIs and CSFs ................................................ 257

Appendix VI: RII, means, SD and rank of CSFs......................................................................... 284

XII

List of abbreviations

Abbreviation The Interpretation Of Abbreviation

GDP Gross Domestic Product

PCBS Palestinian Central Bureau Of Statistics

KPIs Key Performance Indicators

CSFs Critical Success Factors

UN United Nations

NPV Net Present Value

PSI Project Success Index

MHBPs Mass House Building Projects

SEM Structural Equation Model

UK United Kingdom

PPP Public Private Partnership

CPMSF Critical Project Management Success Factors

COMs Comprehension, Competence, Commitment, And Communication

AHP Analytical Hierarchical Method

USA United States Of America

SPSS Statistical Package For Social Science

NGOs Non-Governmental Organizations

MPWH Ministry Of Public Works And Housing

MOHE Ministry Of Education

MOLG Ministry Of Local Government

UNRWA United Nations Relief And Works Agency Of Palestinian Refugees

UNDP United Nations Development Programme

IUG Islamic University Of Gaza

Cα Cronbach’s Coefficient Alpha

RII Relative Important Index ()

ANOVA Analysis Of Variance One Way

r Pearson Correlation Coefficient

EFA Exploratory Factor Analysis

CFA Confirmatory Factor Analysis

PCA Principal Component Analysis

KMO Kaiser-Meyer-Olkin

N Sample Size

DF Degree Of Freedom

XIII

List of Tables

Table 2. 1: Developed and developing countries classification ...................................................... 9

Table 2. 2: Summary of literature review KPIs ............................................................................. 19

Table 2. 3: Summary of CSFs ....................................................................................................... 37

Table 3. 1: Research methods for previous studies ....................................................................... 58

Table 3. 2: Sample size for each of the research population categories ....................................... 63

Table 3. 3: Detailed information for the consulted experts ........................................................... 69

Table 3. 4: Questionnaire review notes gathered from experts .................................................... 69

Table3. 5: Split-Half Coefficient method ....................................................................................... 72

Table 3. 6: Reliability Cronbach's Alpha method ......................................................................... 72

Table 3. 7: Summary of factors and indicators selected and omitted ........................................... 73

Table 3. 8: Kolmogorov-Smirnov test of normality ....................................................................... 77

Table 4. 1: Demographic survey of respondents ........................................................................... 85

Table 4. 2: KMO and Bartlett's Test for KPIs ............................................................................... 88

Table 4. 3:Correlations between items of KPIs ............................................................................. 89

Table 4. 4: Communalities of KPIs ............................................................................................... 90

Table 4. 5: Total variance Explained of KPIs ............................................................................... 91

Table 4. 6: Factor loadings for a three-component model of key performance indicators KPI's . 94

Table 4. 7: Means and test values for “key performance indicators KPI's of projects”- Degree of

importance ................................................................................................................................... 100

Table 4. 8: Means and test values for “key performance indicators KPI's of projects”-

performance evaluation of organization projects ....................................................................... 105

Table 4. 9: KMO and Bartlett's Test for CSFs of conceptualizing and preparation phase .......... 108

Table 4. 10: Correlations between items of CSFs of conceptualizing and preparation phase ... 109

Table 4. 11: Communalities of CSFs of conceptualizing and preparation phase ....................... 110

Table 4. 12: Total variance Explained of CSFs of conceptualizing and preparation phase ....... 111

Table 4. 13: Summary of remaining and removed CSFs in conceptualizing and preparation phase

as a result of factor analysis runs................................................................................................ 113

Table 4. 14: Factor loadings for a three-component model CSFs of conceptualizing and

preparation phase ........................................................................................................................ 115

Table 4. 15: KMO and Bartlett's Test for CSFs of planning and designing phase ..................... 121

Table 4. 16: Correlations between items of CSFs of planning and designing phase .................. 123

XIV

Table 4. 17: Communalities of CSFs of planning and designing phase of first and final runs ... 124

Table 4. 18: Total variance Explained of CSFs of planning and designing phase ..................... 126

Table 4. 19: Summary of remaining and removed CSFs in planning and designing phase as a

result of factor analysis runs ....................................................................................................... 128

Table 4. 20: Factor loadings for a three-component model CSFs of planning and designing phase

..................................................................................................................................................... 130

Table 4. 21: KMO and Bartlett's Test for CSFs of tendering and contracting phase ................. 137

Table 4. 22: Correlations between items of CSFs of tendering and contracting phase .............. 138

Table 4. 23: Communalities of CSFs of tendering and contracting phase of first and final runs 139

Table 4. 24: Total variance Explained of CSFs of tendering and contracting phase ................. 141

Table 4. 25: Summary of remaining and removed CSFs in tendering and contracting phase as a

result of factor analysis runs ....................................................................................................... 143

Table 4. 26: Factor loadings for a three-component model CSFs of planning and designing phase

..................................................................................................................................................... 145

Table 4. 27: KMO and Bartlett's Test for CSFs of implementation phase .................................. 152

Table 4. 28: Correlations between items of CSFs of implementation phase ............................... 153

Table 4.29: Communalities of CSFs of implementation phase of first and final runs ................. 155

Table 4. 30: Total variance Explained of CSFs of implementation phase .................................. 158

Table 4. 31: Factor loadings for a five-component model CSFs of implementation phase ........ 161

Table 4. 32: Factor analysis summary of CSFs .......................................................................... 168

Table 4. 33: Correlation coefficient between CSFs and the degree of importance of KPIs ....... 175

Table 4. 34: Independent Samples T-test of the fields and their p-values for Place of resident . 176

Table 4. 35: ANOVA test of the fields and their p-values for organization type ......................... 177

Table 4. 36: ANOVA test of the fields and their p-values for projects size ................................. 179

Table 4. 37: ANOVA test of the fields and their p-values for years of experience in the

construction industry ................................................................................................................... 180

Table A 1: Summary of KPIs researches ..................................................................................... 202

Table A 2: Summary of CSFs researches .................................................................................... 209

Table A 3: Summary of KPIs and CSFs relationship researches ................................................ 227

Table A 4: Internal validity of the questionnaire ........................................................................ 254

Table A 5: Summary of selected KPIs ......................................................................................... 258

Table A 6: Summary of selected and modified CSFs ................................................................... 263

Table A 7: RII, means, SD and ranks of CSFs ............................................................................ 285

XV

List of Figures

Figure 3. 1: Framework of the research methodology ................................................................... 56 Figure 4. 1: The outline of data analysis and discussion chapter ................................................. 84

Figure 4. 2: Scree Plot for key performance indicators KPI's of projects .................................... 92

Figure 4. 3: Final components extracted from factor analysis for KPIs....................................... 93

Figure 4. 4: RII of KPI's (KPI 1 to KPI 13) ................................................................................ 101

Figure 4. 5: Scree Plot for CSFs of conceptualizing and preparation phase ............................. 112

Figure 4. 6: Final components extracted from factor analysis for CSFs in conceptualizing and

preparation phase ........................................................................................................................ 114

Figure 4. 7: Scree Plot for CSFs of planning and designing phase ............................................ 127

Figure 4. 8: Final components extracted from factor analysis for CSFs in planning and designing

phase ............................................................................................................................................ 129

Figure 4. 9: Scree Plot for CSFs of tendering and contracting phase ........................................ 142

Figure 4. 10: Final components extracted from factor analysis for CSFs in tendering and

contracting phase ........................................................................................................................ 144

Figure 4. 11: Scree Plot for CSFs of implementation phase ....................................................... 159

Figure 4. 12: Final components extracted from factor analysis for CSFs in phase 4................. 160

Figure 4. 17: The RII of the importance KPIs as evaluated by respondents ............................... 181

Figure 4. 18: The RII of the importance CSFs as evaluated by respondents .............................. 181

1

Chapter 1

Introduction

1

Chapter1: Introduction

This chapter presents a general introduction to the research which introduce background about

the construction industry in developing countries in general and especially in Palestine. It also

provide problem statement, research objectives, research questions and hypothesis, research

limitations and an overview of chapters.

1.1 Background

Construction makes a significant contribution to national economy, it creates employment

(especially for the least skilled members of society), it plays a role in the development and

transfer of technology, it creates many opportunities for enterprises, and it contributes directly to

improving quality of life of users of its products (Bourne et al, 2002). Additionally, construction

projects are growing larger and more complicated (Toor and Ogunlana 2008). Construction is

considered to be one of the most human actions that consumes resources and affects the

environment, not only through the construction process but also during lifetime of structures and

buildings (Salameh,2012).

Most construction projects in developing countries are public projects which directed by

government. Public sector projects involve a multitude of stakeholders ranging from the local

municipality to the affected community and even political parties with divergent interests

(Garbharran et al, 2012). In developed countries construction industry faces many challenges.

These challenges including increased competition, more exacting quality standards,

globalization, rapid development of new technologies and increased various risks (Chen and

Chen ,2007).

1.2 The current status of the construction industry in Palestine

Local construction industry is one of the main economic engine sectors, supporting the

Palestinian national economy (Enshassi et al, 2009a). It provides significant improvement in the

overall Gross domestic product GDP of the local economy, and contributes to the improvement

of the quality of life by providing the required infrastructure such as schools, hospitals, roads and

other basic facilities. Therefore, stability, development and growth of the construction industry

2

are critical for the local economy (Enshassi and Ayyash, 2014). Building construction is one of

the pioneer sectors that has achieved high growth rates during late 1994s and early 2015s and has

played a crucial role in absorbing gradual injections into the Palestinian labour force (Enshassi et

al, 2009b). As per the Palestinian Central Bureau of Statistics (PCBS), 15.3% of the employed

persons in the West Bank and Gaza Strip work in the construction industry in 2014. Also, the

construction industry contributed 10.1% of the Palestinians GDP (PCBS, 2015a). There were

8,023 individuals employed in this sector in 2014. The value of output of enterprises in the

construction sector was USD 596.3 million; intermediate consumption totaled USD 285.7

million; and the value added was USD 310.6 million in 2014 (PCBS, 2015b).

There are many challenges affect local construction industry like lack of funding, the dependence

on funding and implementation of aid from donor countries, weak infrastructure, lack of

management, security issues related to political and economic instability in Palestine (Najmi,

2011). The main challenge is that Palestinian construction sector depends on Israel for energy,

communications, raw materials and exports so the closure of border crossings imposed by Israel

has left grave impacts on this sector (Enshassi and Ayyash, 2014).

Palestinian construction sector suffers from cost problems. Cost problems Dealing with

unforeseen costs is usually a problem for construction project parties and is the basic reason of

the failure of many projects. Risks and uncertainty are the main causes of unforeseen costs in

construction projects because these may cause cost overrun and losses for construction parties

(Enshassi and Ayyash, 2014).

Safety and quality are not widely recognized as inherent characteristic of success for Palestinian

construction projects (Enshassi et al, 2009c). The key players in the Palestinian construction

industry do not adopt safe working practices for several reasons including that: employers and

employees are unwilling to spend or invest in safety measures, equipment or practices; hazards

are considered a necessary part and consequence of construction; employees cannot afford to

purchase their own safety equipment (Enshassi et al, 2008). Accidents are happening on

construction projects in Palestine with contributing factors varying between falls, shocks, and

others particularly due to the increase in the number of projects implemented accompanied with

carelessness for safety (Enshassi et al, 2009c).

Variation orders also consider as basic problem in Palestinian construction industry. The

frequent and continuous closure of borders crossing leads to severe shortage of construction

3

materials. Many projects are either on hold or subjected to major variations due to shortage of

construction materials (Enshassi et al, 2007). Also many projects experience extensive delays

and thereby exceed initial time and cost estimates. This problem is more evident in the traditional

or adversarial type of contracts in which the contract is awarded to the lowest bidder which is the

strategy in the majority of public projects in developing countries including Palestine.

1.3 Statement of the problem

Every construction project is unique and comprises of unique complexities and risks across

many issues throughout the construction process (Adnan et al, 2011). A construction project

proceed through stages of concept, scheme design, bidding, contracting, construction, service

and maintenance. The main participants and stakeholders differ among stages, as does the related

professional know-how, technologies and experience (Meng, 2012). Increasing complexity in

design and involvement of multitude of stakeholders in modern construction projects, add further

challenges to deliver the project successfully (Adnan et al, 2011).

In practice poor performance , such as time delays and cost overruns, are common in

construction projects and the reasons behind these problems have attracted the attention of

construction practitioners and researchers (Meng, 2012). In palestine, many local construction

projects reported poor performance due to many evidential project-specific factors such as:

unavailability of materials; excessive amendments of design and drawings; poor

coordination among participants, ineffective monitoring and feedback, lack of project

leadership skills and political situation (Enshassi et al, 2009b).The importance of specifying the

factors which affect the performance needed to improve the performance of the construction

industry has now been recognized in several countries at various levels. Underlying relationships

among the factors that contribute to project success can provide important insights for success

(Cserháti and Szabó, 2014). Also Identification of success factors can help in selection of project

team members, identification of their development needs, forecast of performance level of a

project before it commences and help the firms to decide their strategic standing on the project

(Toor and Ogunlana, 2008). Therefore, this research will be conducted to start paying more

attention to the success factors and their relation to key performance indicators.

4

1.4 Research objectives and questions

The basic research aim is to investigate the success factors that affecting public construction

projects and their relation to key performance indicators in Palestine. The research will thus

explore the present situation of construction projects performance and identify the critical

success factors which affect these projects.

1.4.1 Research objectives

This study was conducted to accomplish the following objectives:

1. To identify and evaluate the key performance indicators (KPIs) of public construction

projects.

2. To investigate the critical success factors CSFs affecting the public construction projects.

3. To evaluate the relationship between CSFs and KPIs in the public construction projects.

1.4.2 Research questions

Question 1: What is the ranking of KPIs according to their degree of importance, and the

evaluation of actual KPIs versus planned?

Question 2: What is the ranking of CSFs according to their degree of importance?

To answer this question, a structured questionnaire is conducted to investigate the suggestions

and expectations of the relevant parties.

Question 3: Is there a significant relationship between CSFs and the degree of importance of

KPIs on Palestine?

Question 4: Are their differences among respondents toward the analysis of CSFs and KPIs due

to place of resident, organization type, projects size and years of experience in the public

construction industry of Palestine?

The questions will be answered using a structured questionnaire and by analyzing the collected

data and by testing the following hypothesis:

5

Hypothesis 1 "H0": Null hypothesis: There is no significant statistical relationship at level (α>=

0.05) in respondents evaluations for CSFs affected public construction projects and the degree of

importance of KPIs in Palestine.

Hypothesis 1 "H1": Alternative hypothesis: There is significant statistical relationship at level

(α>= 0.05) in respondents evaluations for CSFs affected public construction projects and the

degree of importance of KPIs in Palestine.



importance of KPIs in Gaza Strip.

Hypothesis 2 "H1": Alternative hypothesis: There is significant statistical relationship at level


degree of importance of KPIs in Gaza Strip.



importance of KPIs in West Bank.

Hypothesis 3 "H1": alternative hypothesis: There is significant statistical relationship at level


degree of importance of KPIs in West Bank.

The question will be answered using a structured questionnaire and by testing the following

hypothesis:

Hypothesis 4 "H0": Null hypothesis: There is no differences at level (α>= 0.05) in respondents

evaluations for CSFs and KPIs toward the analysis of CSFs and KPIs due to place of resident.

Hypothesis 4 "H1": Alternative hypothesis: There is differences at level (α>= 0.05) in

respondents evaluations for CSFs and KPIs toward the analysis of CSFs and KPIs due to place of

resident.


evaluations for CSFs and KPIs toward the analysis of CSFs and KPIs due to respondents

organizations type.

6


respondents evaluations for CSFs and KPIs toward the analysis of CSFs and KPIs due to

respondents organizations type.


evaluations for CSFs and KPIs toward the analysis of CSFs and KPIs due to respondents

organizations project size.



respondents organizations project size.

1.5 Limitations of the research

1. The research is limited to the public construction projects of Palestine.

2. The research is based on quantitative analysis including questionnaire only.

3. The research sample targeted the construction experts working in governmental

organizations, nongovernmental organizations and consultant offices.

1.6 Research layout

The thesis consists of five chapters as follows:

Chapter 1: Introduction: This chapter contains a general introduction to the subject of

the thesis. It describes research background, statement of the problem, research aim and

objectives, research limitations and research layout.

Chapter 2: Literature review: This chapter discusses general concepts of success criteria

which considered as key performance indicators and critical success factors and also

mentioned the previous studies in this field.

Chapter 3: Methodology: This chapter defines the process of the methodology that will

be applied through the research.

Chapter 4: Results and Discussion: This chapter presents the results of the research and

discusses them in details.

Chapter 5: Conclusions and Recommendations: This chapter states the conclusions and

recommendations for the research.

References.

7

Appendices.

Chapter 2

Literature Review

9

Chapter 2: Literature Review

This chapter composed of four sections. The first section described general concepts of

key performance indicators and also reported the previous studies in this field. The

second section described previous studies about the critical success factors in

construction of both developing and non-developing countries and their categorization.

The third section stated studies which described the relationship between KPIs and the

success factors. The forth section summarized the literature review chapter.

2.1 Countries classification

The classification of developing and developed countries followed in this research

according to United Nations classification which published on their site in 2013 (UN,

2013). Table 2.1 indicated the developed countries and the developing countries.

Table 2. 1: Developed and developing countries classification

Developed countries Developing countries

Austria

Belgium

Denmark

Finland

France

Germany

Greece

Ireland

Italy

Luxembourg

Netherlands

Portugal

Spain

Sweden

United Kingdom

Bulgaria

Cyprus

Czech Republic

Estonia

Hungary

Latvia

Lithuania

Malta

Poland

Algeria

Egypt

Libya

Morocco

Tunisia

Cameroon

Central African Republic

Chad

Congo

Equatorial Guinea

Gabon

Sao Tome and Prinicipe

Burundi

Comoros

Democratic Republic of the Congo

Djibouti

Eritrea

Ethiopia

Kenya

Madagascar

Rwanda

Somalia

Sudan

Uganda

Ghana

Guinea

Guinea-Bissau

Liberia

Mali

Mauritania

Niger

Nigeria

Senegal

Sierra Leone

Togo

Barbados

China

Hong Kong SAR

Indonesia

Malaysia

Myanmar

Papua New Guinea

Philippines

Republic of Korea

Singapore

Taiwan Province of

China

Thailand

Turkey

United Arab

Emirates

Yemen

Cuba

Dominican Republic

Guyana

Haiti

Jamaica

Trinidad and Tobago

Costa Rica

El Salvador

Guatemala

Honduras

Mexico

Nicaragua

Panama

Argentina

Bolivia

(Plurinational State)

Brazil

Chile

Colombia

Ecuador

10

Table 2. 1: Developed and developing countries classification

Developed countries Developing countries

Romania

Slovakia

Slovenia

Iceland

Norway

Switzerland

Australia

Canada

Japan

New Zealand

Canada

Japan

France

Germany

Italy

United Kingdom

United States

United Republic of Tanzania

Angola

Botswana

Lesotho

Malawi

Mauritius

Mozambique

Namibia

South Africa

Zambia

Zimbabwe

Brunei Darussalam

Benin

Burkina Faso

Cape Verde

Côte d’Ivoire

Gambia

Viet Nam

Bangladesh

India

Iran (Islamic Republic

of )

Nepal

Pakistan

Sri Lanka

Bahrain

Iraq

Jordan

Kuwait

Lebanon

Oman

Qatar

Saudi Arabia

Syrian Arab

Paraguay

Peru

Uruguay

Venezuela

(Bolivarian

Republic)

2.2 Key performance indicators (KPI)

This section provides a background through pre studies about KPIs. key performance

indicators are measurable indicators that demonstrate the level of achievement in a

project. KPIs provide information to the decision makers to measure performance and to

compare them with the intended outputs, outcomes, goals, and objectives, and were

chosen to reflect the success criteria of a project (Omran and Mamat, 2011). The purpose

of the KPIs is to enable measurement of project and organizational performance. The

process of developing KPIs involved the following issues (Chan and Chan, 2004)

1. KPIs are general indicators of performance that focus on critical aspects of

outputs or outcomes.

2. Only a limited, manageable number of KPIs is maintainable for regular use.

Having too many (and too complex) KPIs can be time- and resource-consuming.

3. The systematic use of KPIs is essential as the value of KPIs is almost completely

derived from their consistent use over a number of projects.

4. Data collection must be made as simple as possible.

5. A large sample size is required to reduce the impact of project specific variables.

Therefore, KPIs should be designed to be used on every building project.

11

6. For performance measurement to be effective, measures or indicators must be

accepted, understood and owned across the organization.

7. KPIs will need to evolve and it is likely that a set of KPIs will be subject to

change and refinement.

8. Graphic displays of KPIs need to be simple in design, easy to update and

accessible

Different key performance indicators used by different researchers and each indicator

describes project performance on different way. The following indicators were the most

common KPIs had been used in previous literature studies:

2.2.1.1 Time and Cost

Time performance is as important to all construction parties as cost performance

(Meeampol and Ogunlana, 2006). Completing a project in a predictable manner, on time,

within schedule is an important KPI ( LI et al, 2012). Time is defined as the degree to

which the general conditions promote the completion of a project within the allocated

duration (Chan et al, 2002; Lam et al, 2007). It can be measured by time overrun,

construction time, and speed of construction (Chan et al, 2002). Cost is defined as the

degree to which the general conditions promote the completion of a project within the

estimated budget (Chan et al, 2002; Omran and Mamat, 2011; Lam et al, 2007). It can be

measured by cost overrun and unit cost (Chan et al, 2002). Specifically in terms of unit

cost, percentage of net variation over the final cost (Chan and Chan, 2004). Chou et al

(2013) considered the cost refers to the budget.

Cost performance is the most important indicator of project success used by all parties

(LI et al, 2012). It presents firm’s profitability, productivity and is always used to

measure project performance against the estimated target (Meeampol and Ogunlana,

2006; Memon et al, 2013). Time and cost are measured in pre-construction and

construction phases because for design/build projects, price and time certainty are

essential to success, which should be evaluated early at the pre-tendering phase. They

should also be closely monitored during construction to avoid subsequent delays (Chan et

al, 2002). construction time usually interrelates and functions with the actual cost because

12

increasing construction time always results in additional cost to the whole project

(Meeampol and Ogunlana, 2006; Ahsan and Gunawan, 2010).

2.2.1.2 Health and Safety

Health and safety are defined as the degree to which the general conditions promote the

completion of a project without major accidents of injuries (Chan et al, 2002). It is well

known that construction projects have many work-related accidents and injuries and a

successful safety program can be measured in terms of no injury to people, no damage to

equipment, machines and tools, no damage to environment, no loss of market

competition, no damage to company image or brand-name, and increased productivities

(Aksorn and Hadikusumo, 2008). The measurement of safety is mainly focused on the

construction period as most accidents occur during this stage (Alzahrani and Emsley,

2013).With the increasing complexity of construction projects and the rapid increase of

construction activities, construction safety has become a big concern because workers

injuries cause tremendous losses (Ali et al, 2013).

2.2.1.3 Value and Profitability

profitability is also considered as one of the most important key performance indicators

(Ali et al, 2013). Profitability measures financial success of the project. Nowadays,

competition is increasing and firms are aware that the project must be properly managed

to be profitable (Chan et al, 2002). Value is evaluating satisfaction of owner’s needs in a

global sense. It includes the realization for the owner of quantity produced, operational

and maintenance costs, and flexibility. It can be considered as “business benefit” derived

from the completed project (Chan and Chan, 2004). According to Chan and Chan (2004)

The most common measure of financial achievement is net present value (NPV).

2.2.1.4 Quality

Quality is to be assessed in both preconstruction and construction phases as it forms the

‘‘iron triangle’’ with time and cost that is fundamental KPI of the project (Chan et al,

2002). Final product quality and process quality that meet and exceed owner

requirements are an important part of project success ( LI et al, 2012). Sanvido et al

(1992) defined the quality defined as the totality of features, attributes, and characteristics

13

of a facility, product, process, component, service, or workmanship that bear on its ability

to satisfy a given need: fitness for purpose. Chan et al (2002) defined quality as the

degree to which the general conditions promote meeting of the project’s established

requirements of materials and workmanship. Another close definition of quality used by

Lam et al (2007) and Ling and Bui (2010) was that quality is the output quality of the

service rendered or work done from the technical and workmanship aspects. Chou et al

(2013) considered the quality as performance outcome.

2.2.1.5 Functionality

This criterion correlates with expectations of project participant and can best be measured

by the degree of conformance to all technical performance specifications. Both financial

and technical aspects implemented to technical specifications should be considered, to

achieve the ‘‘fitness for purpose’’ objective (Chan et al, 2002). Quality, technical

performance, and functionality are closely related and are considered as important KPIs

to the owner, designer, and contractor (Chan and Chan, 2004). The requirements of

technical performance are normally established in specifications and its performance is

best measured by the degree of variations from those listed in specifications (Lam et al,

2007).

2.2.1.6 Productivity

Productivity is universally accepted as KPI and it is the main key to the cost-effectiveness

of projects. It refers to the amount of resource input to complete a given task and it is

usually assessed on a ranked basis (Chan et al, 2002). Shehata and El-Gohary (2012)

considered that proper management of resources in construction projects can yield

substantial savings in time and cost. In order to improve project performance, they

suggested that variability in labor productivity should be reduced with regard to available

workload and capacity (work hours). These variations that affects labor productivity and

is defined as the time difference between what was planned and what occurred in terms

of task starting times and duration.

14

2.2.1.7 Benchmarks

Benchmarking is currently considered as one of the most effective approaches to help a

company to improve its performance and they considered as the search for “best practice”

(Lam et al, 2007). Benchmarking can be defined as a process of continuously measuring

and comparing an organization’s business process against business leaders anywhere in

the world to gain information which will help the organization to take action to improve

its performance (Shehata and El-Gohary, 2012). Another definition of bench marking

was “A systematic process of measuring one’s performance against results from

recognized leaders for the purpose of determining best practices that lead to superior

performance when adapted and implemented” Ali et al, 2013). Construction companies

can benchmark their performance to enable them to identify strengths and weaknesses

and improve their performance (Lam et al, 2007).

2.2.1.8 Satisfaction

Satisfaction describes level of ‘‘happiness’’ of people affected by a project. Such people

include key project participants, namely the client, architect, contractor, various

subcontractors, surveyors and engineers, end-users, and third parties (Chan et al, 2002;

Lam et al, 2007). Chan and Chan (2004) divided satisfaction to (1) user expectation and

satisfaction and (2) Participants’ satisfaction. user satisfaction describes the level of

achievement of the expectations in a project ( LI et al, 2012). Success for a given project

participant is defined as the degree to which project goals and expectations are met, these

goals and expectations may include technical, financial, educational, social, and

professional aspects (Sanvido et al, 1992). Satisfaction as KPI have been found to be

better than purely financial criteria that can be turned into corrective managerial decisions

and actions (Lehtiranta et al, 2012)

2.2.1.9 Environmental sustainability

Impacts of a construction project on the environment are notoriously negative (Chan et

al, 2002). The generation of construction waste is one of the major negative impacts from

a construction project on the environment, which can be measured by the difference

15

between the amount of the total delivery of materials to the site and the amount of work

completed (Lam et al, 2007).

2.2.2 KPI on developing countries studies

Shenhar et al (2001) conducted study to develop a multidimensional framework for

assessing project KPIs. Shenhar et al (2001) grouped KPIs into: (1) project efficiency, (2)

impact on the customer, (3) direct business and organizational success, and (4) preparing

for the future. They suggested these dimensions should be addressed during the project’s

definition, planning, and execution phases. They also concerned with customer needs,

competitive advantage, and future market success, and rather than sticking to the initial

plan, they keep making adjustments that will create better business outcomes.

In Hong Kong done by Chan et al (2002) aimed to establish criteria for project success

for a design/build project in construction. They conducted a comprehensive review of the

literature over 10 years in order to make framework for success criteria. They classified

KPIs into objective measures which were time, cost, profitability, health and safety and

subjective measures which were quality, productivity, satisfaction, functionality,

technical performance and environmental sustainability.

Another studies in Hong Kong held by Chan and Chan (2004) aimed to develop a set of

key performance indicators (KPIs) for measuring construction success. They measured a

set of key performance indicators (KPIs), both objectively and subjectively through a

comprehensive literature review. Their study showed that the cost quality and time are in

general good indicators of the performance of construction projects and other measures,

such as safety, functionality and satisfaction, etc., were important too. They also

furnished to project managers, clients and other project stakeholders useful information to

implement a project successfully.

In Taiwan Ko and Cheng (2007) endeavored to dynamically predict project success. They

proposed an evolutionary project success prediction model. Their model is developed

based on a hybrid approach that fuses genetic algorithms, fuzzy logic, and neural

networks. They used KPIs which were actual design complete, actual owner

expenditures, cost of contractor project commitments, cost of owner project

16

commitments, actual owner effort hours, recordable incident rate by period, actual

overtime work, cost of change orders, quantity of change orders and days lost to weather

gross working days.

In Hong Kong Lam et al (2007) aimed to develop a project success index (PSI) to

benchmark the performance of design-build projects from a number KPIs. They claimed

that a construction project is mostly initiated by the needs of the client. In order to satisfy

the client’s requirements in terms of time, cost and quality, various procurement methods

are used to increase the chance of success for the complex sequence of activities one of

them is design build strategy. They formulated an equation to benchmark project success

and their findings showed that time, cost, quality and functionality should be the

principal success criteria for design and built projects.

In Ghana Ahadzie et al (2008) conducted a research to address what constitutes the

determinants of success in mass house building projects (MHBPs). They used A

questionnaire survey and they classified the KPIs into four main clusters, namely

environmental impact, customer’s satisfaction, quality and cost, and time .

In Republic of Korea Cho et al (2009) conducted study to analyze the overall relationship

between project performance and a project’s characteristics. They employed factor

analysis method and a structural equation model (SEM) on quantitative data from actual

case studies to analyze relations. They concluded that the quantitative KPIs measured

construction were cost (i.e., award rate, unit cost, cost growth, etc.) and construction time

(i.e., construction speed, delivery speed, schedule growth, etc.), while the qualitative

KPIs evaluated the quality (i.e., turnover quality, system quality, etc.), and the owner’s

satisfaction.

In Vietnam Ling and Bui (2010) examined the factors that lead to successful outcomes in

construction projects. They used case studies technique and they used the following KPIs

as a sign of successful outcomes:

1. Project delivery which determined by the budget performance, schedule

performance, and quality which defined on the research as “The output quality of

the service rendered or work done from the technical and workmanship aspects”.

17

2. Organizational level competency which determined by owner satisfaction.

3. Profitability.

Another study in Malaysia by Al-Tmeemy et al (2011) aimed to propose a framework to

categorize project success for building projects in Malaysia from the contractors'

perspective. They divided the KPIs into three dimensions which were project

management success, product success and market success. These dimensions included

thirteen KPIs which were cost, time, quality, safety, achieving scope, customer

satisfaction, technical specifications, functional requirements, market share, competitive

advantage, reputation, revenue and profits , and benefit to stakeholder.

In Saudi Arabia Ali et al (2013) conducted study to explore the most important KPIs for

measuring company performance as perceived by large building contractors working in

Saudi Arabia. They used A survey on a randomly selected sample of large construction

firms. They Figured out the most significant KPIs are profitability, quality of service and

work, growth, financial stability, cash flow, external customer satisfaction, safety,

business efficiency, market share, and effective-ness of planning.

2.2.3 KPI on developed countries studies

In the United Kingdom Atkinson (1999) investigated how to determine KPIs. He was the

first one who concluded that iron triangle (time, cost and quality) was not enough to

investigate project success. On his study he focused on project management KPIs. And

he found there were other criteria in addition to iron triangle criteria can be used to

evaluate project performance like information system, organization benefits and

stakeholder and community benefits.

In Annapolis Hughes et al (2004) investigated how experienced construction project

management personnel perceive KPIs, both objectively and subjectively. On their article

they developed a construction project success survey instrument to identify important

KPIs before the start of a project, and to evaluate the level of success achieved at project

completion. The measuring metrics include the objective such as, cost, schedule,

performance, and safety and subjective considerations. They suggest a method of

measuring subjective project success attributes that can ultimately lead to a successful

18

outcome of a project regardless of the values associated with the traditional objective

success attributes.

In UK also Bryde and Robinson (2005) aimed to report client versus contractor

perspectives on project KPIs. Their results showed that contractors put more emphasis on

minimizing project cost and duration, whilst clients put more emphasis on satisfying the

needs of other stakeholders. Also they found clients project management practice showed

no stronger focus on meeting stakeholder needs than contractor organizations.

Another study in United Kingdom by Ojiako et al (2008) aimed to develop a different

understanding of KPIs rather than time, cost and quality. Their data collection and

analysis was rooted in grounded theory (Glaser and Strauss, 1969; Strauss and Corbin,

1990). They conducted semi structured interviews and the study revealed that that it was

impossible to generate a universal checklist of criteria suitable for all projects. KPIs will

differ from project to project depending on a number of variables including size,

uniqueness, industry, complexity and the stakeholders involved. The authors suggested

that it is not enough to assume that time cost and quality are the correct project

deliverables but they must be discovered and quantified with an overall establishment of

a number of complex and inter-related project measurement criteria which the authors

would called “project performance”.

In Australia Yeung et al (2009) conducted an empirical study using Delphi survey

technique to formulate a model to assess the success of relationship-based construction

projects in terms of KPI. They conducted four rounds of Delphi survey questionnaires

and selected eight KPIs to evaluate the success of relationship-based projects which were

client’s satisfaction; cost performance; quality performance; time performance; effective

communications; safety performance; aesthetics (trust and respect); and innovation and

improvement.

The researcher derived 31 KPIs from the previous studies. Table 2.2 summarized KPIs

according to their references.

19

Table 2. 2: Summary of literature review KPIs

NO

. Key performance

indicators

Resources

Shen

har

et

al

(2001)

Chan

et

al

(2002)

Dvir

et

al

(2003)

Fri

mpong e

t al

(2003)

Dvir

and L

echle

r (2

004)

Chan

and C

han

(2004)

Chan

et

al

(2004a)

Hughes

et

al

(2004)

Bry

de

andR

obin

son (

2005)

Wan

g a

nd H

uan

g (

2006)

Sam

bas

ivan

and S

oon (

2007)

Ko a

nd C

hen

g (

2007)

Chen

and C

hen

(2007)

Lam

et

al

(2007)

Ahad

zie

et a

l (2

008)

Ensh

assi

et

al

(2009a)

Yeu

ng e

t al

(2009)

Cho e

t al

(2009)

Lin

g a

nd B

ui

(2010)

Ahsa

n a

nd G

unaw

an (

2010)

Yan

g e

t al

(2011)

Al-

Tm

eem

y e

t al.

(2011)

Sheh

ata

and E

l-G

ohar

y (

2012)

Men

g (

2012)

Ng e

t al

(2012)

LI

et a

l (2

012)

Chou e

t al

(2013)

Hw

ang e

t al

(2013)

Ali

et

al

(2013)

Alz

ahra

ni

and E

msl

ey (

2013)

Mir

and P

innin

gto

n (

2014)

Cse

rhát

i an

d S

zabó (

2014)

Ali

as e

t al

(2014)

Loca

tell

i et

al

(2014)

1 Schedule indicators

2 Cost indicators

3 Satisfying the

customers' needs

4 Meeting the technical

specification

5 Satisfying the needs of

stakeholders

(other than the

customer)

6 Quality of service and

work

7 Safety (accident rate)

8 Efficiency

9 Effectiveness of

planning

20


NO

. Key performance

indicators

Resources

Shen

har

et

al

(2001)

Chan

et

al

(2002)

Dvir

et

al

(2003)

Fri

mpong e

t al

(2003)

Dvir

and L

echle

r (2

004)

Chan

and C

han

(2004)

Chan

et

al

(2004a)

Hughes

et

al

(2004)

Bry

de

andR

obin

son (

2005)

Wan

g a

nd H

uan

g (

2006)

Sam

bas

ivan

and S

oon (

2007)

Ko a

nd C

hen

g (

2007)

Chen

and C

hen

(2007)

Lam

et

al

(2007)

Ahad

zie

et a

l (2

008)

Ensh

assi

et

al

(2009a)

Yeu

ng e

t al

(2009)

Cho e

t al

(2009)

Lin

g a

nd B

ui

(2010)

Ahsa

n a

nd G

unaw

an (

2010)

Yan

g e

t al

(2011)

Al-

Tm

eem

y e

t al.

(2011)

Sheh

ata

and E

l-G

ohar

y (

2012)

Men

g (

2012)

Ng e

t al

(2012)

LI

et a

l (2

012)

Chou e

t al

(2013)

Hw

ang e

t al

(2013)

Ali

et

al

(2013)

Alz

ahra

ni

and E

msl

ey (

2013)

Mir

and P

innin

gto

n (

2014)

Cse

rhát

i an

d S

zabó (

2014)

Ali

as e

t al

(2014)

Loca

tell

i et

al

(2014)

10 Profitability

11 Growth/ market share

12 Financial stability

13 Environmental impact

14 Disputes, arbitrations

and litigations

15 Impact on Long Term

Benefits

16 Functional

requirements

17 Reputation

“professional image”

18 Design team

satisfaction

19 Construction team’s

satisfaction

21


NO

. Key performance

indicators

Resources

Shen

har

et

al

(2001)

Chan

et

al

(2002)

Dvir

et

al

(2003)

Fri

mpong e

t al

(2003)

Dvir

and L

echle

r (2

004)

Chan

and C

han

(2004)

Chan

et

al

(2004a)

Hughes

et

al

(2004)

Bry

de

andR

obin

son (

2005)

Wan

g a

nd H

uan

g (

2006)

Sam

bas

ivan

and S

oon (

2007)

Ko a

nd C

hen

g (

2007)

Chen

and C

hen

(2007)

Lam

et

al

(2007)

Ahad

zie

et a

l (2

008)

Ensh

assi

et

al

(2009a)

Yeu

ng e

t al

(2009)

Cho e

t al

(2009)

Lin

g a

nd B

ui

(2010)

Ahsa

n a

nd G

unaw

an (

2010)

Yan

g e

t al

(2011)

Al-

Tm

eem

y e

t al.

(2011)

Sheh

ata

and E

l-G

ohar

y (

2012)

Men

g (

2012)

Ng e

t al

(2012)

LI

et a

l (2

012)

Chou e

t al

(2013)

Hw

ang e

t al

(2013)

Ali

et

al

(2013)

Alz

ahra

ni

and E

msl

ey (

2013)

Mir

and P

innin

gto

n (

2014)

Cse

rhát

i an

d S

zabó (

2014)

Ali

as e

t al

(2014)

Loca

tell

i et

al

(2014)

20 Productivity

21 Aesthetics

22 Risk

23 Human resources

24 communication

25 Procurement

26 Benchmarks

27 Cost of change orders

28 Quantity of change

orders

29 Pre-contract costs

30 Learning value

31 Overall performance

22

2.3 Critical success factors

2.3.1 Background

This section aimed to determine the critical success factors affecting construction

projects. Rubin and Seeling (1967) were the first ones who introduced the concept of

project success factors in and Rockart (1979) used the terminology critical success factors

(CSFs) for the first time (Toor, and Ogunlana, 2008; Yang et al., 2009 ). The factors that

predicate success were initially derived from the integrated building process model

developed at Penn State by Sanvido in 1990 (Sanvido et al, 1992). CSFs can be

defined as “areas, in which results, if they are satisfactory, will ensure successful

competitive performance for the organization” (Rockart, 1979 cited in Aksorn and

Hadikusumo 2008, p712). Another definition mentioned by Yang et al (2009) was “CSFs

those critical areas of managerial planning and action that must be practiced in order to

achieve effectiveness” or "CSFs are inputs to project management practice which can

lead directly or indirectly to project success and they encompasses many elements, which

have to be synchronized to ensure the project delivery on time" as described by Alias et

al (2014 p61).

Comprehensive success criteria must reflect different interests and views, which lead to a

multi-dimensional, multi-criteria approach (Dvir et al 2003). Successful to construction

project manager may or may not resonate the same way with the construction project

owner, project engineer, operator, or maintenance staff (Hughes et al 2004). From a

project management perspective, critical success factors (CSFs) are characteristics,

conditions, or variables that can have a significant impact on the success of the project

when properly sustained, maintained, or managed (Milosevic and Patanakul, 2005). An

architect may consider success in terms of aesthetic appearance, an engineer in terms of

technical competence, an accountant in terms of dollars spent under budget, a human

resources manager in terms of employee satisfaction and chief executive officers rate

their success in the stock market (Shenhar et al, 2001).

23

2.3.2 CSFs in developing countries studies

On this part the researcher will give general view for the previous studies which divided

into two kinds: 1) studies described CSFs and evaluated them and 2) studies categorized

CSFs.

Studies described CSFs and evaluated them

In Oman Hartman and Ashrafi (2004) conducted a study to develop the simple

measurable analytic realistic time bounded "SMART" project planning framework based

on research into causes of both project failure and success. They recognized that poor

project planning plays a major role as one of the significant causes of project failure.

They also concluded that good planning enabled creativity and supported both team

formulation and effectiveness. It brought out innovative ideas that led to cost or time

savings. They developed a framework presented a unified approach to project planning,

integrating both hard and soft aspects, enhancing current tools and techniques, and

improving the project planning process by providing internal validation.

In Hong Kong Chan et al (2004a) conducted a study to identify critical success factors

for partnering projects. In their study a set of 41 success factors was derived. The results

indicated that certain requirements must be met for partnering to succeed which were the

establishment and communication of a conflict resolution strategy, a willingness to share

resources among project participants, a clear definition of responsibilities, a commitment

to a win-win attitude, and regular monitoring of partnering process were believed to be

the significant underlying factors for partnering success.

In China Wang and Huang (2006) conducted a study to evaluate project success and to

what extent key project stakeholders performance correlates with project success. Their

results showed that the engineers use relation among the key stakeholders as the most

important criterion of project success, the stakeholder project performance positively

correlates with each other and project owners played the most important role in

determining project success.

24

In China Lu and Yuan et al (2010) conducted a study to identify the CSF’s in waste

management in construction projects of Shenzhen. They identified 18 CSFs and they

concluded that the most important CSF’s in Shenzhen were 7 factors namely (1)

regulations, (2) waste management system (3) awareness (4) building technologies, (5)

design changes, (6) research and development, and (7) vocational training.

In Malaysia Adnan et al (2011) aimed to determine the primary factors which support the

successful application of the design and build method. They found that client attributes

for the success of the Design and Built projects in public universities were the main

factors. These factors listed as developing a clear understanding of project scope, a clear

brief thorough assessment of the contractor’s proposal, a clear understanding of project

costs, fulfilling the end-user requirements, quality finish of the project, completion within

the time frame as well as the budget allocated.

In India Tabish and Jha (2011) studied success factors of public construction projects.

They claimed that achieving success in public construction projects is difficult because it

requires economy, efficiency, quality, fairness and transparency. They concluded that

identification of the success factors is considered the key to achieving success in these

projects. Authors identified 36 success attributes. Four success factors which were

‘awareness of and compliance with rules and regulations’, ‘effective partnering among

project participants’, ‘pre-project planning and clarity in scope’, and ‘external monitoring

and control’ were extracted by the application of factor analysis on 36 attributes

developed through a synthesis of empirical studies and opinions from industry

practitioners on public construction projects. The most important factor for overall

performance is found to be ‘awareness of and compliance with rules and regulations’.

Another study conducted in Malaysia by Abdul-Aziz and Kassim (2011) aimed to

examine the objectives, success and failure factors of housing public private partnership

PPP projects. They found that public agencies desired to fulfil an array of objectives

when adopting PPP, the most important factor was to enhance organizational reputation.

They also claimed that the most CSF that impact project success was action against errant

developers. And the factor which had the most influential on project which may lead to

project failure was absence of robust and clear agreement.

25

In South Korea also Yu and Kwon (2011) conducted a research to identify the critical

success factors (CSFs) for urban regeneration projects. They identified and confirmed 10

CSFs. They formulate a model and they concluded that the most CSF’s was minimization

of conflict between stakeholders.

In Taiwan Also Yang et al (2011) examined on their article the impact of teamwork on

project performance and they investigated the relationships among the project manager's

leadership style, teamwork, and project success. They concluded that increased in levels

of leadership may enhanced relationships among team members. The results also

indicated that teamwork exhibits statistically significant influence on project

performance.

In Taiwan Chen et al (2012) conducted a study to explore the success variables in

construction partnering and the relationships among these variables. Research results

showed that four successful factors (collaborative team culture, long-term quality

perspective, consistent objectives, and resource sharing) had a significant influence on

the success of construction partnering. Of the four factors, collaborative team culture and

consistent objectives had the highest correlation. Additionally, results indicated that good

cultural fit has the most influence on characterizing collaborative team culture,

commitment to continuous improvement had the highest influence in characterizing long-

term quality perspective, clear understanding had the highest influence in characterizing

consistent objectives, and availability of resource had the highest influence in

characterizing resource sharing.

Another research in Malaysia done by Ismail et al (2012) to study the management

factors contributing to successful implementation of industrialized building system IBS

projects from contractor point of view. They disclosed that good working collaboration,

effective communication channel and team member involvement during the design stage

are the top three most influential management -related factors towards the successful

implementation of IBS projects in Malaysia. The result reinforced that good coordination

between all parties play the main role towards successful implementation of IBS project.

26

In Nigeria Jagboro et al (2012) evaluated the contribution of construction professionals in

budgeting for infrastructure projects and its effect on the real cost of them. They

indicated that majority of projects budgeted for execution lack adequate technical

evaluation and cost assessment as a result of inadequate professional involvement and

this could be adduced to be a significant problem of success implementation of public

financed infrastructure projects in Nigeria.

In Taiwan Yang et al (2012) held a study to assess the impacts of information technology

on project success through knowledge management practice. They claimed that under the

pressure of globalization, the construction industry employs project teams to respond

quickly to the environmental changes and reach the enterprise goals so the use of

information technology to manage the information is vital. They concluded that

knowledge management is a key factor influencing project performance in terms of

schedule, cost, quality, and safety performance. Also they found that knowledge

management fully mediates the effects of information technology application on project

performance. Another result of the study showed that project success can be improved

when the project team seeks to enhance knowledge management and teams with worse

member relationship may achieve higher levels of project success when they experienced

high levels of knowledge management than those with better member relationships.

In Malaysia Memon et al (2013) studied the effect of resource related causes on the basic

criteria of project performance. They claimed that construction projects are highly

dependable on resources and construction cost is significantly affected by various

resource related factors. Their study results showed that approximately 47% of cost

overrun was influence with resource related factors. Also they concluded that finance

factors were the most critical factors so that an effective financial management can

significantly improve the project's success and help in reducing the cost overrun.

Another Study in Malaysia done by Yong and Mustaffa (2013) to assess the critical

success factors for Malaysian construction projects. They identified 75 CSFs for

construction projects in Malaysia. They revealed that there were a strong consistency

among the perception of project stakeholders in recognizing the significance of human-

related ‘soft’ factors. Also their study results ranked major factors as: (1) project

27

personnel; (2) commitment and communication; and (3) site management and

supervision.

In south Africa a study done by Windapo and Cattell (2013) to investigate the challenges

influencing the performance, development and growth of the construction industry. They

found the main challenges included the increasing costs of building materials, difficulties

on access to mortgage/credits, high interest rates and the high rate of failure of

contracting enterprises. Also they concluded that economic factors invariably introduce

additional uncertainty into the project.

Another study conducted in Nigeria by Ihuah et al (2014) to investigate and establish the

critical project management success factors (CPMSF) for the sustainable social (public)

housing estates. The study revealed that 22 critical project management success factors

are essential and they were related to: the project managers’ performance; the

organization that owns the development project; the characteristics of the team members;

and the external project environment. At the same time, the study revealed that these

were social, economic, and environmental factors that are associated with the triple

objectives of sustainable development. The critical success factors implementation in the

project management for sustainable social (public) housing estates’ delivery and

provision should be supported by government policies based on the people’s real needs

and not for selfish political and financial motives.

In Indonesia Wibowo and Alfen (2014) aimed on their research to investigate the macro-

environmental critical success factors (CSFs) and key areas for improvement for public-

private partnerships (PPP) in infrastructure development. They concluded that the most

important remedial actions should be concentrated to improve the PPP’s projects were:

commitments to policy continuity, financial transparency, and corruption eradication.

Also in Hong Kong Zou et al (2014) held a study to identifying the critical success

factors for relationship management in PPP projects. They considered that the ability to

actively create and develop collaborative relationships is an essential asset for managing

project networks. They identified three essential successful factors for effective

relationship management in PPP included commitment and participation of senior

28

executives; defining the objectives and project strategy; and integration of the divisions

of the organization.

Studies categorized CSFs

Dvir et al (2003) studied the relationship between project planning and project success.

They grouped CSF’s in three groups 1. Meeting planning goals (success at the project

manager level) 2. End-user benefits (success from the end-user point of view) 3.

Contractor benefits (success at the contractor’s level, and includes their last two criteria:

commercial success of the project and potential for future revenues). Their findings

revealed that project success is insensitive to the level of implementation of management

processes and procedures, which are readily supported by modern computerized tools and

project management training. On the other hand, project success is positively correlated

with the investment in requirements’ definition and development of technical

specifications.

In Vietnam by Nguyen et al (2004) held a study to identify project success factors and to

uncover the relationships between that factors. They used survey questionnaire to collect

the data. They categorized the CSFs into four groups namely comfort, commitment,

communication and competence. Study results showed that the most CSFs were

competent of project manager, adequate funding until project completion, competent

project team, commitment to project and availability of resources. Also they found out

the most CSFs are human related factors.

In Hong Kong Chan et al (2004b) held a research to develop a conceptual framework on

critical success factors CSFs. They grouped the variables affecting project success in five

major groups of independent variables, namely project-related factors, project

procedures, project management actions, human-related factors, and external

environment are identified as crucial to project success.

Also on Thailand Toor and Ogunlana (2008) conducted study to explore the

interrelationships between various critical success factors and group them. They

employed questionnaire and interview surveys with construction professionals and used

factor analysis to examine the underlying relationships which resulted in formulation of

29

four factor groupings which were together called critical COMs of success and were

labeled as comprehension, competence, commitment, and communication.

In Thailand Aksorn and Hadikusumo (2008) held a research to identify and quantitatively

prioritize the factors contribute to the successful implementation of construction safety

programs. They grouped 16 CSF’s influencing safety program performance into four

dimensions which were worker involvement, safety prevention and control system, safety

arrangement, and management commitment. They concluded that the most influential

factor is management support.

In Hong Kong Yang et al (2009) made a research to identify CSFs associated with

stakeholder management in construction projects, and explore their ranking and

underlying relationship. They grouped 15 CSFs into five dimensions related basically to

planning stage namely: precondition factor, stakeholder estimation, information inputs,

decision making, and sustainable support. Their results indicated that the top three ranked

CSFs were 1) managing stakeholders with social responsibilities, 2) assessing the

stakeholders' needs and constraints to the project, and 3) communicating with

stakeholders properly and frequently.

In South Korea Park (2009) conducted a research to identify the critical factors CFs and

to evaluate their relative importance to whole life performance assessment. He focused

on procurement stage and he investigated 188 individual factors. Then he grouped CFs

into eight critical categories namely: project scope, time, cost, quality,

contract/administration, human resource, risk, and health and safety. He revealed that

cost, quality, scope, and time are more important than contract/administration, risk,

human resource, and health and safety to all respondents over a project life cycle.

Another founding was that the most critical individual factors in each category were

clarity of contract; fixed construction period; precise project budget estimate; material

quality; mutual/trusting relationships; leadership/team management; and management of

work safety on site.

In Hong Kong also Ng et al (2009) studied the factors contributing to the success of

equipment intensive subcontractors in construction. They grouped 17 CSFs into six major

30

components namely: (i) market position; (ii) equipment-related factors; (iii) human

resources; (iv) earnings; (v) managerial ability to adapt to changes; and (vi) project

success related factors. The top five CSFs identified in the study were ‘‘timely

completion ” , ‘‘relationship with main contractor/client/consultant” , ‘‘profit” , ‘‘cash

flow” , and ‘‘adoption of new technologies/methodologies”.

In China Chan et al (2010) held a research to explore the critical success factors CSFs

necessary to conduct PPP projects. They grouped 18 CSFs into five groups: stable

macroeconomic environment; shared responsibility between public and private sectors;

transparent and efficient procurement process; stable political and social environment;

and judicious government control. They concluded that the most critical factor was

transparent and efficient procurement process.

Another study in Vietnam conducted by Ling and Bui (2010) to examine factors that lead

to successful outcomes in construction projects. They classified the factors into four

groups to 1) project related factors, 2) procurement related factors, 3) project

management related factors, 4) characteristics of owners, consultants, and contractors.

Their results showed that major enablers that lead to project success were foreign

experts’ involvement in the project, government officials inspecting the project, and very

close supervision when new construction techniques are employed. They found that the

factor which leads to poor performance was the lack of accurate data on soil, weather,

and traffic conditions.

In Saudi Arabia Alhaadir and Panuwatwanich (2011) held a research to identify CSFs for

safety program implementation. They grouped the factors into four categories namely: (1)

worker participation; (2) safety prevention and control system; (3) safety arrangement;

and (4) safety commitment. They used Pareto principle, and analytical hierarchical

method AHP and suggested seven critical factors that can account for 80% of the

successful implementation of safety programs in construction companies which were (1)

management support; (2) clear and reasonable objectives; (3) personal attitude; (4)

teamwork; (5) effective enforcement; (6) safety training; and (7) suitable supervision.

31

Also in Malaysia Zawawi et al (2011) conducted study to drive a conceptual framework

for describing CSF of building maintenance management. They claimed that the

implementing CSF concept would enhance the management process and work planning

which would result in a more economic use of resources, a corresponding reduction in

the total cost and create successful competitive performance organization. In this study,

critical success factors were categorized into five primary categories namely: 1.

leadership, 2. culture, 3. structure, roles, and responsibilities, 4. system infrastructure, and

5. measurement.

Another study in Malaysia held by Tan and Ghazali (2011) to determine the CSFs and

provide some guidance for contractors needed to operate overseas. They grouped CSF’s

under seven main categories: (1) project management factors; (2) procurement related

factors; (3) client-related factors; (4) design team-related factors; (5) contractor-related

factors; (6) project manager -related factors; and (7) business and work environment-

related factors. Study evidences showed that project management related factor is more

important than the other main factors in terms of ranking and contractor’s experience is

the most critical among all the sub-factors.

In Nigeria Famakin et al (2012) reported the factors affecting the performance of partners

in joint ventures construction projects. They grouped CSFs into five groups namely: 1)

establishment of joint venture partner’s loyalty, 2) commitment to joint venture

relationship, 3) maintaining of joint venture organization, 4) establishment of joint

venture interests and 5) conflict management. Their study revealed that at the formation

stage, compatibility of objectives, mutual understanding and agreement of the contract

are very much important to the success of joint venture construction projects. At the

implementation stage, the study also revealed that communication and management

control as very important factors at this stage.

Also in Hong Kong Ng et al (2012) held a research to explore the key successful

ingredients to be assessed at the initial stage of PPP projects. In their research they

described the dimensions of CSFs of public private projects as (i) technical factors; (ii)

financial and economic factors; (iii) social factors; (iv) political and legal; and (v)others

32

(staff issue and possible management actions). Study results indicated that the most

critical factors for evaluating PPP were cost effectiveness and financial attractiveness.

In Durban and South Africa Garbharran et al (2012) conducted study to assess the

perceptions of contractors and project managers on the critical success factors that lead to

project success in the construction industry. They used four groups (comfort,

competence, communication and commitment). They emerged that there were no

significant differences between project managers and contractors regarding the critical

success factors.

In China Zhao et al (2013) studied the factors influencing the success of build operate

transfer power plant projects. The results showed that there were 14 CSF’s at two levels,

i.e. macro level and micro level affect the success of these projects. Study results also

indicated that the main success factor of China’s built operate transfer electric power

projects was the existence of combined efforts from all related stakeholders.

2.3.3 CSFs in developed countries studies

On this part the researcher will give general view for the previous studies which divided

into two kinds: 1) studies described CSFs and evaluated them and 2) studies categorized

CSFs.

Studies described CSFs and evaluated them

In Pennsylvania Sanvido et al (1992) carried out a study considered as one of the first

studies on CSFs field. They aimed to define the critical factors that lead to project success

and provide a forecasting tool to enable parties to rapidly assess the possibility of a

successful project from their viewpoint. The research results revealed that four factors

were found to be critical: (1) a well-organized, cohesive facility team to manage, plan,

design, construct, and operate the facility team chemistry was typically developed by

common goals and activities. (2) A series of contracts that allows and encourages the

various specialists to behave as a team without conflicts of interest and differing goals.

these contracts must allocate risk and reward in the correct proportions. (3) Experience in

the management, planning, design, construction, and operations of similar facilities. and

33

(4) Timely, valuable optimization information from the owner, user, designer, contractor,

and operator in the planning and design phases of the facility. Authors also concluded

that if project participants can predict probability of success better, they can take steps

to: (1) avoid unsuccessful projects; (2) identify good projects worth pursuing; and (3)

identify problems on current projects and take corrective action.

In United Kingdom Bourne et al (2002) studied the major factors that impact the success

and failure of the implementation of a performance measurement system. They

considered four factors appeared to be significant on project success which were how the

introduction and launch was handled, who was involved in the project and project

management and procedure. They found that poor strategy and project vision could be

attributed to poor design process which affected implementation issues.

In United States of America (USA) Doerr et al (2004) investigated how the extent and

type of centrality shapes managers’ perceptions of the success or failure of

technologically innovative projects. They consider 6 CSFs which were (1) general

reflections on the “big picture” of project success; (2) social and cultural criteria, such as

reputation; (3) organizational factors, including support from upper level management;

(4) market concerns; (5) efficiencies, for example, in time and costs; and (6)

technological success. They concluded that managers asymmetrically discuss success

more than failure, and the type of centrality they have influences how they talk about

success and interpretive flexibility in the meaning of success occurs among more central

managers who have access to more information through their network ties.

In Germany Dvir and Lechler (2004) investigated on their study the interactions between

the planning variables and their influences on project success. They claimed that planning

is a process with many different activities that cover a variety of issues, using numerous

planning techniques and planning procedures such as analysis, design reviews, reports

and interpersonal communication. They also concluded that the positive total effect of the

quality of planning was almost completely overridden by the negative effect of goal

changes. Also they found out that combined effect of goal changes and plan-changes on

project success was considerably stronger than that of the quality of planning.

34

In Sweden Turner and Müller (2005) conducted a research to prove that the project

manager’s leadership style is a success factor on projects and to assess whether its impact

is different on different types of projects. They concluded that an appropriate leadership

style can lead to better performance.

In Finland Lehtiranta et al (2012) conducted a study to explore a new dimension of the

determinants for construction project success, i.e. relationship between success and multi-

firm project participants’ satisfaction with each other. The results of the study showed

that correlations can be found between certain project participants’ satisfaction with each

other’s performance and the owner’s perception of project success. More specifically,

satisfaction with performance factors within the relationships between the owner and any

other participant (i.e. the contractor, designer or project consultant), within the

relationship between project consultants and designers and within the relationship

between project consultants and contractors were reflected in the owner’s perception of

project success.

Also on UK Meng (2012) held a research to analyze the role of relationship management

as CSF in project performance. He used ten factors to describe the key aspects of a

supply chain relationship. He concluded that supply chain relationship has some

significant influences on project performance, so developing a good supply chain

relationship may help to improve project performance and deterioration of supply chain

relations hips is a major reason for the occurrence of poor performance.

In Finland, Netherlands and Switzerland Verburg et al (2013) conducted a study to

highlight the conditions that are important for successful task accomplishment. Their

results showed that important conditions for successful project execution in a dispersed

setting include rules of communication and its clarity; project management style and

goal-setting; and managers' competences and trust in a team.

Another study in USA held by Molenaar et al (2013) aimed to understand whether

project peer reviews could be an indicator of project success and to identify the questions

most correlated with the outcomes. The results of their research indicated that project

peer reviews should be conducted during the construction process and it can be used to

35

assess and predict final project performance. Additionally they found that there were

significant correlations between project success and questions regarding working

relationships, communication, timing, project controls, and relational approaches to

project participants. Molenaar et al (2013) suggested that companies and organizations

can strategically improve projects by conducting project peer reviews early in the

construction process.

In Italy Locatelli et al (2014) investigated the effect of project characteristics on the

success of megaprojects. Locatelli et al (2014) found out the megaprojects suffer from

very poor performance like over-budget and/or behind schedule and, once finished, they

deliver less benefits than planned. Study results determined main factors needs to be

considered in order to improve performance of megaprojects which were participation of

internal stakeholders in company and external stakeholders (like a governmental

authority), a proper designed project governance, and efficient project delivery chain and

project nature.

In Finland Skaates et al (2014) examined the relationships and project marketing success.

They concluded that project managers should focus their attention on the management of

project relationships before, during and after projects and relevant environmental factors

of project. Also they concluded that project managers are accountable for the successful

delivery of complete projects. Increasingly, success depends on project managers’

processing and utilizing skills and competencies.

In Slovenia Fink (2014) held a study to investigate the effect of customer focus

competence on construction project performance. He defined customer focus competence

as an “awareness of the construction project team members of the customer’s importance,

recognizing customer needs and increasing customer loyalty”. He founded positive

effects of the team average customer focus on examined project goals and it can

considered important factor projects success.

Studies categorized CSFs

In UK Fortune and White (2006) conducted theoretical study to frame a model of project

critical success factors. They used sets of critical success factors from 63 publications to

36

develop the model in order to distinguish between successful and unsuccessful projects.

They suggested to use it in the planning phase in order to provide a way of tackling the

human and organizational aspects of systems development projects. They grouped 27

CSFs into 11 main cluster which were 1) goals objectives, 2) performance monitoring, 3)

decision-makers, 4) transformations, 5) communication, 6) environment, 7) boundaries,

8) resources continuity, 9) viewpoints, 10) project champion, and 11) change agent.

In Lithuania Gudienė et al (2013) and Gudienė et al (2014) conducted study in order to

rank CSF’s in construction industry. They grouped CSF’s into seven groups which were

1) external factors, 2) institutional factors, 3) project related factors, 4) project

management/team related factors, 5) project manager related factors, 6) client related

factors, 7) contractor related factors. Their study revealed that clear and realistic project

goals, project planning, the project manager’s competence, relevant past experience of

the project management/team, the competence of the project management/team, clear and

precise goals/objectives of the client, the project’s value, the project’s complexity and

uniqueness, the project manager’s experience, and the client’s ability to make timely

decisions are the top ranking CSFs.

Another research in UK conducted by Alzahrani and Emsley (2013) to study the impact

of contractors’ attributes on project success from a post construction evaluation

perspective and to identify what critical success factors (CSFs) that greatly impact the

success of project. They used factor analysis and grouped the CSFs that greatly impact

the success of a project on nine clusters which were (i) safety and quality; (ii) past

performance; (iii) environment; (iv) management and technical aspects; (v) resource; (vi)

organization; (vii) experience; (viii) size/type of pervious projects; and (ix) finance. They

investigated that factors such as turnover history, quality policy, adequacy of labor and

plant resources, waste disposal, size of past projects completed, and company image are

the most significant factors affecting projects success.

Another research in Austria, Czech Republic, Germany, Hungary, Poland, Slovakia,

Slovenia and Switzerland done by Cserháti and Szabó (2014) aimed to investigate the

relationship between success criteria and success factors in organizational event projects.

They classify the success factors into two groups which were relationship orientation

37

factors and task focus factors. They concluded that relationship-oriented success factors,

such as communication, co-operation and project leadership, play a crucial role in

carrying out successful organizational event projects.

From the previous studies in both developed and developing countries the researcher

summarized 125 CSFs that may affect the project success. Table 2.3 presented the

summarized CSFs according to their references.

Table 2. 3: Summary of CSFs

No. Factor Resource

1. Accidents and hazards Park (2009); Gudienė et al (2013); Gudienė et al (2014); Marzouk and El-

Rasas (2014); Zavadskas et al (2014).

2. Client approvals and

Payment method

Frimpong et al (2003); Sambasivan and Soon (2007); Ng et al (2009);

Orangi et al (2011); LI et al (2012); Marzouk and El-Rasas (2014).

3. Change in goals plans

and orders

Davies (2002); Dvir and Lechler (2004); Hughes et al (2004); Fortune and

White (2006); Orangi et al (2011); Lehtiranta et al (2012); Yong and

Mustaffa (2013); Hwang et al (2013); Marzouk and El-Rasas (2014);

Wibowo and Alfen (2014); Yang et al (2015).

4. Commitment to

continuous improvement

Davies (2002); Chen and Chen (2007); Meng (2012); Cserháti and Szabó

(2014); Yang et al (2015)

5. Knowledge management Davies (2002); Yang et al (2012); Zou et al (2014).

6.

The project has effective

well established

information and

communication routines

Bourne et al (2002); Dvir et al (2003); Nguyen et al (2004); Chan et al

(2004); Meeampol and Ogunlana (2006); Wang and Huang (2006);

Fortune and White (2006); Iyer and Jha ( 2006); Chen and Chen (2007);

Sambasivan and Soon (2007); Lu et al (2008); Aksorn and Hadikusumo

(2008); Park (2009); Yang et al (2009); Chan et al (2010); Lu and Yuan et

al (2010); Alhaadir and Panuwatwanich (2011); Yang et al (2011); Tan

and Ghazali (2011); Omran and Mamat (2011); Yu and Kwon (2011);

Abdul-Aziz and Kassim (2011); Orangi et al (2011) ; Chen et al (2012);

Alias et al (2014); Gudienė et al (2014); Cho et al (2009); Famakin et al

(2012); Garbharran et al (2012); Ismail et al (2012); Meng (2012);

Lehtiranta et al. (2012); Molenaar et al (2013); Yong and Mustaffa (2013);

Gudienė et al (2013); Verburg et al (2013); Ihuah et al (2014); Cserháti

and Szabó (2014); Zou et al (2014).

7.

Performance

measurement

(Management for

successful outcome).

Davies (2002); Omran and Mamat (2011); Yu and Kwon (2011); Zawawi

et al (2011); Meng (2012); Mir and Pinnington (2014); Cserháti and

Szabó (2014); Yang et al (2015).

8. Control of subcontractor

works

Sambasivan and Soon (2007); Ling and Bui (2010); Orangi et al (2011);

LI et al (2012); Yong and Mustaffa (2013).

9. Effective and timely

conflict resolution

Chan et al (2004a); Chan et al (2004); Iyer and Jha ( 2006); Lu et al

(2008); Park (2009); Cho et al (2009); Yang et al (2009); Yu and Kwon

(2011); Famakin et al (2012); Gudienė et al (2013); Gudienė et al (2014).

10. The project has a clear

and well-planned agenda

of meetings for all

Dvir et al (2003); Nguyen et al (2004); Andersen et al (2006); Iyer and Jha

( 2006); Chen et al (2012); Garbharran et al (2012).

38


No. Factor Resource

participants

11. Parties relationships and

coordination

Chan et al (2004); Meeampol and Ogunlana (2006); Wang and Huang

(2006); Iyer and Jha ( 2006); Lu et al (2008); Ng et al (2009); Park (2009);

Tan and Ghazali (2011); Omran and Mamat (2011); Yu and Kwon (2011);

Meng (2012); Hwang et al (2013); Molenaar et al (2013); Yong and

Mustaffa (2013); Cserháti and Szabó (2014); Yang et al (2015).

12. Team members number

and performance

Wang and Huang (2006); Zavadskas et al (2014); Ihuah et al (2014); Yang

et al (2015).

13. Project nature Chan et al (2004); Cho et al (2009); Yong and Mustaffa (2013); Shehu et

al (2014).

14.

Leadership, monitoring,

coordinating, organizing

manager skills for both

contractor PM and owner

Bourne et al (2002); Dvir et al (2003); Turner and Müller (2005); Iyer and

Jha ( 2006); Andersen et al (2006); Fortune and White (2006); Lu et al

(2008); Ng et al (2009); Park (2009); Tan and Ghazali (2011); Yang et al

(2011); Omran and Mamat (2011); Zawawi et al (2011); Lehtiranta et al

(2012); Ismail et al (2012); Alzahrani and Emsley (2013); Gudienė et al

(2013); Zhao et al (2013); Gudienė et al (2014); Alias et al (2014); Mir

and Pinnington (2014).

15. Decision-making

effectiveness

Frimpong et al (2003); Dvir et al (2003); Iyer and Jha ( 2006); Park

(2009); Tan and Ghazali (2011); Yu and Kwon (2011); Meng (2012);

Lehtiranta et al (2012); Gudienė et al (2013); Gudienė et al (2014); Ihuah

et al (2014).

16. Commitment of all

project participants

Bourne et al (2002); Chan et al (2004a); Nguyen et al (2004); Hughes et al

(2004); Iyer and Jha ( 2006); Wang and Huang (2006); Chen and Chen

(2007); Aksorn and Hadikusumo (2008); Chan et al (2010); Omran and

Mamat (2011); Tan and Ghazali (2011);Chen et al (2012); Garbharran et

al (2012); Lehtiranta et al. (2012); Ismail et al (2012); Ng et al (2012);

Yong and Mustaffa (2013); Cserháti and Szabó (2014); Alias et al (2014);

Zou et al (2014).

17. Environmental plan and

methods during

construction

Fortune and White (2006); Lu et al (2008); Ng et al (2009); Park (2009);

Lu and Yuan et al (2010); Ismail et al (2012); Alzahrani and Emsley

(2013); Son and Kim (2014); Wibowo and Alfen (2014); Zavadskas et al

(2014).

18. Safety issues

Chan et al (2004); Hughes et al (2004); Lu et al (2008); Aksorn and

Hadikusumo (2008); Ng et al (2009); Park (2009); Alhaadir and

Panuwatwanich (2011); Gudienė et al (2013); Yong and Mustaffa (2013);

Gudienė et al (2014); Son and Kim (2014).

19. Complexity and

uniqueness

Chan et al (2004); Hughes et al (2004); Meeampol and Ogunlana (2006);

Fortune and White (2006); Cho et al (2009); Park (2009); Tan and Ghazali

(2011); Yang et al (2011); LI et al (2012); Gudienė et al (2013); Yong and

Mustaffa (2013); Gudienė et al (2014).

20. Profitability

Ng et al (2009); Park (2009); Ng et al (2012); Famakin et al (2012);

Gudienė et al (2013); Zhao et al (2013); Gudienė et al (2014); Zavadskas

et al (2014).

21.

Contract management

and documentation

include penalties, bonds,

incentives, ..etc

Frimpong et al (2003); Dvir et al (2003); Nguyen et al (2004); Chan et al

(2004a); Hughes et al (2004); Wang and Huang (2006); Lu et al (2008);

Ng et al (2009); Park (2009); Tan and Ghazali (2011); Abdul-Aziz and

Kassim (2011); Chen et al (2012); LI et al (2012); Famakin et al (2012);

39


No. Factor Resource

Ng et al (2012); Garbharran et al (2012); Lehtiranta et al (2012); Verburg

et al (2013); Gudienė et al (2013); Yong and Mustaffa (2013); Alzahrani

and Emsley (2013); Gudienė et al (2014); Marzouk and El-Rasas (2014).

22. Subcontractor and

contractor Involvement

Chan et al (2004); Ng et al (2009); Park (2009); Tan and Ghazali (2011);

LI et al (2012).

23. Project type

Chan et al (2004); Yang et al (2011); Cho et al (2009); Gudienė et al

(2013); Gudienė et al (2014); Locatelli et al (2014); Shehu et al (2014);

Yang et al (2015).

24. Reputation Ng et al (2009); Abdul-Aziz and Kassim (2011); Verburg et al (2013)

25. Transparent and efficient

procurement method

Frimpong et al (2003); Dvir et al (2003); Chan et al (2004); Wang and

Huang (2006); Lu et al (2008); Ng et al (2009); Chan et al (2010); Ling

and Bui (2010); Tan and Ghazali (2011); Garbharran et al (2012); Gudienė

et al (2013); Yong and Mustaffa (2013); Windapo and Cattell (2013);

Gudienė et al (2014); Shehu et al (2014); Son and Kim (2014); Wibowo

and Alfen (2014).

26. Risk identification

management and

allocation

Davies (2002); Dvir et al (2003); Chan et al (2004a); Fortune and White

(2006); Lu et al (2008); Park (2009); Chan et al (2010); Ismail et al

(2012); LI et al (2012); Lehtiranta et al (2012); Ng et al (2012); Meng

(2012); Yong and Mustaffa (2013); Gudienė et al (2013); Gudienė et al

(2014); Ihuah et al (2014); Son and Kim (2014); Zavadskas et al (2014).

27. Size

Chan et al (2004); Fortune and White (2006); Lu et al (2008); Cho et al

(2009); Ng et al (2012); Gudienė et al (2013); Gudienė et al (2014); Shehu

et al (2014); Yang et al (2015).

28. Legal environment

Lu et al (2008); Chan et al (2010); Yu and Kwon (2011); Ng et al (2012);

Gudienė et al (2013); Zhao et al (2013)Gudienė et al (2014); Wibowo and

Alfen (2014).

29. Design management

change and mistakes

Dvir et al (2003); Ahsan and Gunawan (2010); Lu and Yuan et al (2010);

Tan and Ghazali (2011); Orangi et al (2011); Lehtiranta et al (2012); LI et

al (2012); Yong and Mustaffa (2013); Son and Kim (2014); Marzouk and

El-Rasas (2014);

30.

Clear and realistic and

sharable multi-benefit

goals vision and mission

of projects

Bourne et al (2002); Dvir et al (2003); Nguyen et al (2004); ); Hughes et

al (2004); Chan et al (2004a); Iyer and Jha ( 2006); Fortune and White

(2006); Andersen et al (2006); Chen and Chen (2007); Aksorn and

Hadikusumo (2008); Lu et al (2008); Toor et al (2008); Yang et al (2009);

Ahsan and Gunawan (2010); Chan et al (2010); Alhaadir and

Panuwatwanich (2011); Tan and Ghazali (2011); Garbharran et al (2012);

Lehtiranta et al. (2012); Ng et al (2012); Famakin et al (2012); Gudienė et

al (2013); Molenaar et al (2013); Yong and Mustaffa (2013); Verburg et al

(2013); Gudienė et al (2014); Ihuah et al (2014); Son and Kim (2014);

Cserháti and Szabó (2014); Zou et al (2014).

31. Technical capability

(contractor and

managers)

Chan et al (2004); Iyer and Jha ( 2006); Wang and Huang (2006); Chen

and Chen (2007); Lu et al (2008); Ng et al (2009); Tan and Ghazali

(2011); Gudienė et al (2013); Alzahrani and Emsley (2013); Gudienė et al

(2014).

32. Quality standards and

criteria

Tan and Ghazali (2011); Gudienė et al (2013); Yong and Mustaffa (2013);

Gudienė et al (2014); Son and Kim (2014); Yang et al (2015).

33. Consultant recruitment Bourne et al (2002); Fortune and White (2006); Wang and Huang (2006);

40


No. Factor Resource

and involvement in

budgeting and

supervision

Ahsan and Gunawan (2010); Jagboro et al. (2012); Molenaar et al (2013);

Yong and Mustaffa (2013).

34. Design completed before

work on site Park (2009).

35. Value

Dvir et al (2003); Dvir and Lechler (2004); Cho et al (2009); Ng et al

(2012); Gudienė et al (2013); Zhao et al (2013); Gudienė et al (2014); Son

and Kim (2014); Yang et al (2015).

36. Financial security and

stability (contractor,

owner)

Frimpong et al (2003); Nguyen et al (2004); Chan et al (2004); Chen and

Chen (2007); Lu et al (2008); Ng et al (2009); Park (2009); Chen et al

(2012); Famakin et al (2012); Ng et al (2012); Hwang et al (2013); Zhao

et al (2013); Gudienė et al (2013); Gudienė et al (2014); Marzouk and El-

Rasas (2014); Wibowo and Alfen (2014).

37. Project team leader

involvement and

authority

Chan et al (2004); Turner and Müller (2005); Andersen et al (2006); Iyer

and Jha ( 2006); Tan and Ghazali (2011); Yong and Mustaffa (2013);

Ihuah et al (2014).

38. Construction regulations

Chan et al (2004); Park (2009); Lu and Yuan et al (2010); Zhao et al

(2013); Gudienė et al (2013); Windapo and Cattell (2013); Gudienė et al

(2014); Ihuah et al (2014); Son and Kim (2014); Wibowo and Alfen

(2014).

39. Product and service

certification Gudienė et al (2013); Gudienė et al (2014).

40. Cultural issues

Bourne et al (2002); Chen and Chen (2007); Ahsan and Gunawan (2010);

Orangi et al (2011); Zawawi et al (2011); Chen et al (2012); Gudienė et al

(2013); Gudienė et al (2014); Ihuah et al (2014).

41. Adequate and clear

financial budget

Bourne et al (2002); Dvir et al (2003); Frimpong et al (2003); Wang and

Huang (2006); Fortune and White (2006); Andersen et al (2006);

Meeampol and Ogunlana (2006); Park (2009); Ahsan and Gunawan

(2010); Chan et al (2010); Tan and Ghazali (2011); Yang et al (2011);

Garbharran et al (2012); Chen et al (2012); Yong and Mustaffa (2013);

Alzahrani and Emsley (2013); Gudienė et al (2013); Alias et al (2014);

Gudienė et al (2014); Ihuah et al (2014); Locatelli et al (2014); Son and

Kim (2014); Zavadskas et al (2014);.

42. Community,

international and end

user involvement

Fortune and White (2006); Chen and Chen (2007); Orangi et al (2011);

Yang et al (2011); Garbharran et al (2012); Ng et al (2012); Ihuah et al

(2014).

43. Depreciation/devaluation

of local currency Hughes et al (2004); Ahsan and Gunawan (2010); Gudienė et al (2014).

44. Clear prioritization of

project goals by the client

Chan et al (2004); Toor et al (2008); Yang et al (2009); Ling and Bui

(2010); Yang et al (2011); Yong and Mustaffa (2013); Gudienė et al

(2013); Gudienė et al (2014).

45. Political influence

Chan et al (2004); Chan et al (2004a); Iyer and Jha ( 2006); Fortune and

White (2006); Ng et al (2009); Chan et al (2010); Abdul-Aziz and Kassim

(2011); Tan and Ghazali (2011); Garbharran et al (2012); Ng et al (2012);

Yong and Mustaffa (2013); Zhao et al (2013); Gudienė et al (2013);

Gudienė et al (2014).

46. Applicable Construction Bourne et al (2002); Meeampol and Ogunlana (2006); Park (2009); Chan

41


No. Factor Resource

methods et al (2010); Lehtiranta et al (2012); Hwang et al (2013); Alzahrani and

Emsley (2013); Gudienė et al (2013); Gudienė et al (2014).

47. Natural calamities

Frimpong et al (2003); Iyer and Jha ( 2006); Ahsan and Gunawan (2010);

Orangi et al (2011); Gudienė et al (2013); Yong and Mustaffa (2013);


48. Effective control , such

as monitoring, updating

plans and feedback

Davies (2002); Frimpong et al (2003); Chan et al (2004b); Nguyen et al

(2004); Chan et al (2004a); Andersen et al (2006); Wang and Huang

(2006); Iyer and Jha ( 2006); Meeampol and Ogunlana (2006); Fortune

and White (2006); Toor et al (2008); Aksorn and Hadikusumo (2008);

Park (2009); Ahsan and Gunawan (2010); Abdul-Aziz and Kassim (2011);

Tan and Ghazali (2011); Omran and Mamat (2011); Chen et al (2012); Ng

et al (2012); Famakin et al (2012); Gudienė et al (2013); Yong and

Mustaffa (2013); Alias et al (2014); Gudienė et al (2014); Ihuah et al

(2014); Son and Kim (2014); Zavadskas et al (2014).

49. Mutual trust and

understanding

Gudienė et al (2014); Gudienė et al (2013); Chan et al (2004); Chan et al

(2004a); Chen et al (2012); Famakin et al (2012); Park (2009); Tan and

Ghazali (2011); Verburg et al (2013); Chen and Chen (2007); Yong and

Mustaffa (2013)

50. Collaborative team

culture

Chan et al (2004a); Iyer and Jha ( 2006); Aksorn and Hadikusumo (2008);

Lu et al (2008); Ng et al (2009); Park (2009); Yang et al (2009); Alhaadir

and Panuwatwanich (2011); Yang et al (2011); Chen et al (2012); Meng

(2012); Famakin et al (2012); Ismail et al (2012); Verburg et al (2013);

Yang et al (2015).

51. Management support

Bourne et al (2002); Chan et al (2004a); Nguyen et al (2004); Iyer and Jha

( 2006); Andersen et al (2006); Fortune and White (2006); Aksorn and

Hadikusumo (2008); Lu et al (2008); Alhaadir and Panuwatwanich (2011);

Garbharran et al (2012); Gudienė et al (2013); Yong and Mustaffa (2013);

Gudienė et al (2014); Alias et al (2014); Chen et al (2012); Ihuah et al

(2014); Cserháti and Szabó (2014); Zou et al (2014).

52. Training the human

resources in the skill

demanded by the project

Fortune and White (2006); Iyer and Jha (2006); Ng et al (2009); Lu and

Yuan et al (2010); Wibowo and Alfen (2014); Yang et al (2015).

53.

Project manager

commitment to meet cost

quality and time of

project

Dvir et al (2003); Chan et al (2004); Meeampol and Ogunlana (2006);

Chen and Chen (2007); Lu et al (2008); Park (2009); Omran and Mamat

(2011); Chen et al (2012); Gudienė et al (2013); Son and Kim (2014);

Cserháti and Szabó (2014).

54.

The project has a formal

organizational chart

covering the entire

project

Chan et al (2004); Andersen et al (2006); Lu et al (2008); Park (2009); Yu

and Kwon (2011); Zawawi et al (2011); Famakin et al (2012); Gudienė et

al (2013); Tan and Ghazali (2011); Gudienė et al (2014); Son and Kim

(2014); Cserháti and Szabó (2014);

55.

All key participants have

participated in the

detailed project planning

within their area of

expertise

Hughes et al (2004); Fortune and White (2006); Andersen et al (2006);

Famakin et al (2012); Lehtiranta et al (2012); Yong and Mustaffa (2013).

56. Strong /detailed and

updated integrated

Bourne et al (2002); Frimpong et al (2003); Dvir and Lechler (2004);

Nguyen et al (2004); Hughes et al (2004); Chan et al (2004); Chan et al

42


No. Factor Resource

planning effort in

design and construction

(2004a); Andersen et al (2006); Sambasivan and Soon (2007); Fortune and

White (2006); Ng et al (2009); Cho et al (2009); Yu and Kwon (2011);

Garbharran et al (2012); Lehtiranta et al (2012); Ismail et al (2012); LI et

al (2012); Gudienė et al (2013); Hwang et al (2013); Alias et al (2014);

Gudienė et al (2014); Ihuah et al (2014); Locatelli et al (2014); Son and

Kim (2014); Cserháti and Szabó (2014); Marzouk and El-Rasas (2014).

57. Physical environment

(civil works, location,

weather, ..etc)

Frimpong et al (2003); Chan et al (2004); Lu et al (2008); Ahsan and

Gunawan (2010); Tan and Ghazali (2011); Zawawi et al (2011); Windapo

and Cattell (2013); Gudienė et al (2013); Gudienė et al (2014); Ihuah et al

(2014); Shehu et al (2014); Son and Kim (2014); Marzouk and El-Rasas

(2014); Wibowo and Alfen (2014).

58. Ability to Generate

Innovative Ideas

Chan et al (2004a); Lu et al (2008); Lu and Yuan et al (2010); Ng et al

(2012); Gudienė et al (2013); Gudienė et al (2014).

59. Parties relevant past

experience

Hughes et al (2004); Nguyen et al (2004); Dvir and Lechler (2004); Chan

et al (2004a); Fortune and White (2006); Sambasivan and Soon

(2007);Chen et al (2007); Lu et al (2008); Ng et al (2009); Park (2009);

Cho et al (2009); Ling and Bui (2010); Tan and Ghazali (2011); LI et al

(2012); Chen et al (2012); Famakin et al (2012); Garbharran et al (2012);

Ng et al (2012); Hwang et al (2013); Alzahrani and Emsley (2013); Yong

and Mustaffa (2013); Zhao et al (2013); Gudienė et al (2013); Gudienė et

al (2014); Marzouk and El-Rasas (2014).

60. Appropriate supervision

and site management

Bourne et al (2002); Meeampol and Ogunlana (2006); Iyer and Jha (

2006); Sambasivan and Soon (2007); Aksorn and Hadikusumo (2008); Lu

and Yuan et al (2010); Orangi et al (2011); Alhaadir and Panuwatwanich

(2011); Tan and Ghazali (2011); Hwang et al (2013); Yong and Mustaffa

(2013); Gudienė et al (2013); Gudienė et al (2014); Marzouk and El-Rasas

(2014).

61. Tendering/ bidding

strategy and management

Frimpong et al (2003); Nguyen et al (2004); Wang and Huang (2006); Lu

et al (2008); Toor et al (2008); Park (2009); Lu and Yuan et al (2010); Tan

and Ghazali (2011); Abdul-Aziz and Kassim (2011); Molenaar et al

(2013); Yong and Mustaffa (2013); Shehu et al (2014); Marzouk and El-

Rasas (2014).

62. Client contribution in


Chan et al (2004); Chan et al (2004a); Nguyen et al (2004); Hughes et al

(2004); Andersen et al (2006); Iyer and Jha ( 2006); Toor et al (2008); Cho

et al (2009); Orangi et al (2011); LI et al (2012); Gudienė et al (2013);

Ihuah et al (2014).

63. Construction permits Tan and Ghazali (2011); Ng et al (2012); Gudienė et al (2013); Gudienė et

al (2014).

64. Personal motivation

Aksorn and Hadikusumo (2008); Lu et al (2008); Park (2009); Ahsan and

Gunawan (2010); Gudienė et al (2013); Alias et al (2014); Gudienė et al

(2014).

65. Bureaucracy Nguyen et al (2004); Ahsan and Gunawan (2010).

66.

The project is well

described and

coordinated with other

projects and activities

Bourne et al (2002); Dvir and Lechler (2004); Andersen et al (2006); Lu et

al (2008); Zou et al (2014).

67. Project ownership Davies (2002); Ihuah et al (2014).

43


No. Factor Resource

68. One major contractor and

consortium Ng et al (2012); Locatelli et al (2014).

69. Project insurance Lu et al (2008); Ng et al (2009).

70. Responsiveness of

correspondence Molenaar et al (2013).

71. Commitment to

corruption eradication Abdul-Aziz and Kassim (2011); Wibowo and Alfen (2014).

72. An acceptable level of

tariff Ng et al (2012)

73. Access to affordable

mortgage/credit Windapo and Cattell (2013).

74. Critical global

issues/globalization Windapo and Cattell (2013).

75. Contingency funds Ahsan and Gunawan (2010)

76. Extent of subcontracting LI et al (2012); Gudienė et al (2013); Gudienė et al (2014).

77. Close supervision when

new construction

techniques are employed

Hughes et al (2004); Ling and Bui (2010).

78. Willingness to Eliminate

Non-value Added

Activities

Chan et al (2004); Park (2009).

79. Sustainable project

design and construction Park (2009); Ng et al (2012); Windapo and Cattell (2013).

80. Project is not susceptible

to fast-paced change (e.g.

Technological change)

Dvir and Lechler (2004); Ng et al (2012).

81. Customer focus

competence Fink (2014)

82. Fairness of new

conditions to employees Chen and Chen (2007); Ng et al (2012).

83. Knowledge transfer Toor et al (2008); Famakin et al (2012); Cserháti and Szabó (2014)

84.

All the organizations

involved in the project

effort have agreed to

provide the project with

sufficient resources

Chan et al (2004); Chen et al (2012); Famakin et al (2012); Garbharran et

al (2012); Alzahrani and Emsley (2013).

85.

Commitment to Win-

Win Attitude

(compatibility of

objectives)

Chan et al (2004); Abdul-Aziz and Kassim (2011); Yu and Kwon (2011);

Famakin et al (2012); Meng (2012).

86. Partnering was started at

the design stage

Chan et al (2004); Chen and Chen (2007); Park (2009); Chen et al

(2012); Ismail et al (2012).

87.

Open exchange and

consideration of ideas

were promoted during

the partnering process

Chan et al (2004a); Andersen et al (2006); Wang and Huang (2006); Yang

et al (2009); Chen et al (2012).

88. A list of partner selection Chan et al (2004); Famakin et al (2012); Verburg et al (2013).

44


No. Factor Resource

criteria was developed

89. Strong and good private

consortium Chan et al (2010); Cserháti and Szabó (2014).

90. Public -sector capacity Ng et al (2012); Windapo and Cattell (2013).

91. Partnerships with local

and national stakeholders Ng et al (2012); Cserháti and Szabó (2014).

92. Profit-sharing Abdul-Aziz and Kassim (2011); Meng (2012).

93. Identifying stakeholders Yang et al (2009)

94. Social environment

Chan et al (2004); Iyer and Jha ( 2006); Park (2009); Yang et al (2009);

Chan et al (2010); Abdul-Aziz and Kassim (2011); Tan and Ghazali

(2011); Gudienė et al (2013); Yong and Mustaffa (2013); Gudienė et al

(2014).

95. Troubleshooting Gudienė et al (2013); Alias et al (2014); Gudienė et al (2014).

96. Project management was

systematic and

methodical

Davies (2002); Frimpong et al (2003); Nguyen et al (2004); Fortune and

White (2006); Wang and Huang (2006); Ng et al (2009); Park (2009); Yu

and Kwon (2011); Lehtiranta et al (2012); Son and Kim (2014).

97. Transaction cost

economics (preplanning) Park (2009); LI et al (2012); Son and Kim (2014).

98. Close relationship with

suppliers Orangi et al (2011); Ismail et al (2012).

99. Service quality can be

easily defined and

objectively measured

Ng et al (2012); Marzouk and El-Rasas (2014); Yang et al (2015).

100. Technological

environment

Bourne et al (2002); Davies (2002); Dvir and Lechler (2004); Nguyen et al

(2004); Chan et al (2004); Fortune and White (2006); Lu et al (2008);

Park (2009); Lu and Yuan et al (2010); Tan and Ghazali (2011); Omran

and Mamat (2011); Garbharran et al (2012); Gudienė et al (2013); Yong

and Mustaffa (2013); Zhao et al (2013); Verburg et al (2013); Windapo

and Cattell (2013); Alzahrani and Emsley (2013); Gudienė et al (2014);

Son and Kim (2014).

101. Skilled designers Aksorn and Hadikusumo (2008); Park (2009); Tan and Ghazali

(2011);Gudienė et al (2014); Locatelli et al (2014).

102. Staff qualification and

skills

Fortune and White (2006); Ng et al (2009); Park (2009); Tan and Ghazali

(2011); Chen et al (2012); Lehtiranta et al. (2012); LI et al (2012); Yong

and Mustaffa (2013); Alzahrani and Emsley (2013); Verburg et al (2013);

Windapo and Cattell (2013); Cserháti and Szabó (2014); Wibowo and

Alfen (2014).

103. Rework due to errors

during construction

Sambasivan and Soon (2007); Orangi et al (2011); Molenaar et al (2013);

Marzouk and El-Rasas (2014); Zavadskas et al (2014);

104. Litigation, disputes and

arbitrating tendency

Lu et al (2008); Park (2009); Molenaar et al (2013); Alzahrani and Emsley

(2013).

105.

The detailed project

plans are understood and

accepted by all project

team members

Andersen et al (2006); Iyer and Jha ( 2006); Chen and Chen (2007); Toor

et al (2008); Park (2009).

106. Foreign (external)

Experts’ Participation in Chan et al (2004a); Ling and Bui (2010); Chen et al (2012).

45


No. Factor Resource

Projects

107. Having an explicit

competitive strategy Davies (2002); Lu et al (2008); Park (2009).

108. Competition

Hughes et al (2004); Park (2009); Ahsan and Gunawan (2010); Abdul-

Aziz and Kassim (2011); LI et al (2012); Ng et al (2012); Ihuah et al

(2014); Son and Kim (2014).

109. The costs of building

materials Frimpong et al (2003); Windapo and Cattell (2013).

110.

Delegation and allocation

of authority and

responsibility

Chan et al (2004a); Andersen et al (2006); ); Iyer and Jha ( 2006); Aksorn

and Hadikusumo (2008); Lu et al (2008); Park (2009); Chan et al (2010);

Alhaadir and Panuwatwanich (2011); Omran and Mamat (2011); Zawawi

et al (2011); Lehtiranta et al. (2012); Alzahrani and Emsley (2013);

Gudienė et al (2013); Verburg et al (2013); Gudienė et al (2014); Cserháti

and Szabó (2014); Zou et al (2014).

111. Sufficient resource

allocation

Chan et al (2004b); Fortune and White (2006); Aksorn and Hadikusumo

(2008); Park (2009); Alhaadir and Panuwatwanich (2011); Gudienė et al

(2014).

112. Waste management

system Lu and Yuan et al (2010); Son and Kim (2014);

113. Personal competency

Nguyen et al (2004); Fortune and White (2006); Toor et al (2008); Aksorn

and Hadikusumo (2008); Ahsan and Gunawan (2010); Omran and Mamat

(2011); Tan and Ghazali (2011); Garbharran et al (2012); Lehtiranta et al.

(2012); Gudienė et al (2013); Yong and Mustaffa (2013); Gudienė et al

(2014); Ihuah et al (2014); Cserháti and Szabó (2014).

114.

Selection of PM with

proven track record at an

early stage by top

management

Iyer and Jha ( 2006); Omran and Mamat (2011).

115. Personal attitude and

issues

Bourne et al (2002); Dvir and Lechler (2004); Iyer and Jha ( 2006);

Aksorn and Hadikusumo (2008); Alhaadir and Panuwatwanich (2011);

Omran and Mamat (2011); Gudienė et al (2013); Verburg et al

(2013);Gudienė et al (2014).

116. Good governance

(government policy)

Ng et al (2009); Chan et al (2010); Ng et al (2012); Wibowo and Alfen

(2014).

117.

The project is part of a

well-documented or

understood strategy

Davies (2002); Dvir et al (2003); Hughes et al (2004); Andersen et al

(2006); Toor et al (2008); Park (2009); Yu and Kwon (2011); Lehtiranta et

al (2012); Alzahrani and Emsley (2013); Ihuah et al (2014); Son and Kim

(2014); Mir and Pinnington (2014); Zavadskas et al (2014).

118. Research and

development

Davies (2002); Lu et al (2008); Ng et al (2009); Lu and Yuan et al (2010);

Chan et al (2010); Ismail et al (2012).

119.

A team leader or

champion was appointed

to ensure that partnering

principles did not slip out

of focus

Chan et al (2004a)

120. Government Officers’

Participation in Projects

Hughes et al (2004); Ling and Bui (2010); Chan et al (2010); Locatelli et

al (2014); Wibowo and Alfen (2014).

46


No. Factor Resource

121.

Realistic time forecasting

and schedule

management

Bourne et al (2002); Dvir et al (2003); Fortune and White (2006);

Andersen et al (2006); Meeampol and Ogunlana (2006); Lu et al (2008);

Ng et al (2009); Park (2009); Abdul-Aziz and Kassim (2011); Famakin et

al (2012); Hwang et al (2013); Gudienė et al (2013); Molenaar et al

(2013); Gudienė et al (2014); Ihuah et al (2014); Marzouk and El-Rasas

(2014); Zavadskas et al (2014)

122. Economic viability

environment

Chan et al (2004); Iyer and Jha ( 2006); Enshassi et al (2009a); Chan et al

(2010); Ahsan and Gunawan (2010); Tan and Ghazali (2011); Ng et al

(2012); Windapo and Cattell (2013); Gudienė et al (2013); Yong and

Mustaffa (2013); Zhao et al (2013); Gudienė et al (2014); Son and Kim

(2014); Wibowo and Alfen (2014);

123. Adequacy and

management of resources

Frimpong et al (2003); Dvir et al (2003); Nguyen et al (2004); Hughes et

al (2004); Iyer and Jha ( 2006); Meeampol and Ogunlana (2006);

Sambasivan and Soon (2007); Chen and Chen (2007); Lu et al (2008); Ng

et al (2009); Lu and Yuan et al (2010); Omran and Mamat (2011); Orangi

et al (2011); Garbharran et al (2012); Ismail et al (2012); LI et al (2012);

Chen et al (2012); Lehtiranta et al (2012); Gudienė et al (2013); Alzahrani

and Emsley (2013); Yong and Mustaffa (2013); Verburg et al (2013);

Hwang et al (2013); Memon et al (2013); Gudienė et al (2014); Ihuah et al

(2014); Son and Kim (2014); Mir and Pinnington (2014); Marzouk and El-

Rasas (2014); Yang et al (2015).

124. Adaptability to changes,

management of Changes

Dvir et al (2003); Chan et al (2004); Andersen et al (2006); Fortune and

White (2006); Chen and Chen (2007); Cho et al (2009); Ng et al (2009);

Chen et al (2012); Gudienė et al (2013); Yong and Mustaffa (2013);

Gudienė et al (2014); Yang et al (2015).

125.

Client ability on brief,

define roles and make

decisions

Chan et al (2004); Iyer and Jha ( 2006); Cho et al (2009); Tan and Ghazali

(2011); Lehtiranta et al (2012); Gudienė et al (2013); Hwang et al (2013);

Gudienė et al (2014); Son and Kim (2014); Marzouk and El-Rasas (2014);

47

2.4 Relationship between KPIs and CSFs

2.4.1 KPIs and CSFs relationship on developing countries studies

In Ghana Frimpong et al (2003) conducted a research to investigate the CSFs affect the

KPIs time and cost in the construction of groundwater projects. They found the critical

factors which lead to delay and cost overrun in developing countries which were: poor

contractor management, monthly payment difficulties from agencies, material

procurement, poor technical performances, and escalation of material prices according to

their degree of influence.

In Thailand by Meeampol and Ogunlana (2006) aimed to study the factors affecting cost

and time performance on highway construction projects. On their investigation of CSF’s

they concluded that some factors, such as complexity, do not contribute significantly to

project success or failure. They also found that supervision and control, owner

involvement and design effectiveness, are not significant predictors of cost performance

on projects. However, better supervision and control and less owner interference can

reduce construction duration. They also indicated that the most important factors in

discriminating between success and failure on projects are managerial practices factors.

They indicated that change in goals, plans or priorities lead to variations in project stages

and performance.

Another study on India done by Iyer and Jha (2006) to figure out the CSFs affecting cost

KPI of Indian construction projects. They indicated that the factors which adversely

affecting the cost performances of projects were: conflict among project participants;

ignorance and lack of knowledge; presence of poor project specific attributes and non-

existence of cooperation; hostile socio economic and climatic condition; reluctance in

timely decision; aggressive competition at tender stage; and short bid preparation time.

Results showed that coordination among project participants was the most significant of

all the factors and had the maximum positive influence on cost performance.

In Malaysia Sambasivan and Soon (2007) conducted a study to identify the CSFs which

effects time KPI in Malaysian construction industry. They indicated ten critical factors

caused delay in Malaysian projects which were: (1) contractor’s improper planning, (2)

48

contractor’s poor site management, (3) inadequate contractor experience, (4) inadequate

client’s finance and payments for completed work, (5) problems with subcontractors, (6)

shortage in material, (7) labor supply, (8) equipment availability and failure, (9) lack of

communication between parties, and (10) mistakes during the construction stage. Also

they investigated six main effects of delay on project performance were: (1) time overrun,

(2) cost over-run, (3) disputes, (4) arbitration, (5) litigation, and (6) total abandonment.

In Taiwan Chen and Chen (2007) held a study to distinguish between CSFs based on

their degrees of importance in relation to KPI of PPP projects. They identified 19 CSFs

and divided them into four clusters. They concluded that the most important cluster being

collaborative team culture, followed by a long-term quality focus, consistent objectives,

and finally resource sharing.

In United Arabs of Emirates Mir and Pinnington (2014) tested the relationship between

project management PM performance as CSF and project KPIs. In their research, they

demonstrated that PM performance is correlated to project success. And they concluded

that by paying greater attention to this relationship, originations can enhance their

projects performance.

On China Lu et al (2008) conducted study to utilize the CSF approach to identify a few

manageable but vital factors contributing to the overall competiveness of a contractor as

KPI. They indicated that there were 35 success factors contributing to enhancing a

contractor’s competitiveness in the Chinese construction market. They used factor

analysis and generated eight clusters from the 35 CSFs which namely “project

management,” “organization structure,” “resources,” “competitive strategy,”

“relationship.” “bidding,” “marketing,” and “technology”. The most important factors as

the study revealed were “winning enough contracts by adopting successful bidding

strategy,” “having an explicit competitive strategy,” and “developing a good relationship

with the government".

In Korea Cho et al (2009) studied the relationship between project performance and a

project’s characteristics as CSF. They categorized the project characteristics as project

characteristics, owner characteristics, contractor characteristics, and environment

49

characteristics. Results of study showed that the project characteristics positively

influenced the cost growth and negatively influenced the award rate and ‘construction

speed. Also, the contractor characteristics positively influenced the unit cost, cost growth

and the schedule whereas the owner characteristics, negatively influenced the schedule

growth and positively influenced the ‘construction speed. Finally, the environmental

characteristics positively influenced the unit and negatively influenced the schedule

growth and construction speed.

In Gaza strip Enshassi et al (2009a) conducted study to identify the factors affecting the

performance of local construction projects. They found out the most important factors

affecting project performance are: delays because of borders/roads closure leading to

materials shortage; unavailability of resources; low level of project leadership skills;

escalation of material prices; unavailability of highly experienced and qualified

personnel; and poor quality of available equipment and raw materials.

In Malaysia Omran and Mamat (2011) studied cost performance as KPI of construction

projects in Kelantan state located in the east-coast part of Malaysia. The results of their

research indicated that the CSFs affecting the cost performances were identified as

project manager competence in works affecting cost performance. And they concluded

that commitment responsibilities of all participants and various teams to the project was

the top CSF while presence of poor project specific attributes and not existence of

cooperate and ignorance and lack of knowledge in operating, techniques and decision by

project manager were identified as the most important failure factors.

In Taiwan, Indonesia and Vietnam Chou et al (2013) conducted study to determine the

effects of project management body of knowledge techniques/ tools/ skills (TTSs) on

project success. They defined project objectives as success criteria that are quantifiable in

terms of time, cost, and quality. They used Structural equation modeling was used to

determine the effects of PMBOK techniques/tools/skills (TTSs) on project success. they

formulate a model and concluded that TTSs improve project success, enhancing project

performance, and improving the efficient use of management resources.

50

In Korea Son and Kim (2014) endeavored to develop a model to predict the cost and

schedule KPIs of green building projects based on the CSF "the level of definition during

the pre-project planning phase". They reported that the cost and schedule performance of

green projects is highly dependent on the quality of definition in the pre-project planning

phase. they proposed models that could be utilized to credibly assess the cost and

schedule performance based on the 64 factors derived from successful and unsuccessful

projects. They divided the factors into 11 categories, which in turn are grouped into three

sections: basis of project decision, basis of design, and execution approach.

In Malaysia Shehu et al (2014) explored the construction cost as KPI of projects in terms

of project characteristics as CSFs. They categorized project characteristics as project

sector (public or private), nature of project (new build or refurbishment), procurement

methods (traditional, design and build, and project management), nature of project

(residential, infrastructure, commercial, office, educational, and health), tendering

method (open, selected and negotiated), and project size (small, medium, large and very

large ). They established that more than half of Malaysian construction projects (55%)

experienced cost overruns. They also founded that public sector projects performed better

than private sector projects, also design and build projects was associated with reduced

cost overrun, and small and large projects performed better than medium and very large

projects.

Another study in Malaysia done by Alias et al (2014) to identify the extent of the

relationship between CSFs and project performance. They developed conceptual

framework and grouped 61 CSF’s for project success in five variables and they were

project management action, project procedures, human factors, external issues and

project related factors.

In Taiwan also Yang et al (2015) searched on their study the roles of the CSFs

interpersonal conflict, product advantage, and project type in the relationship between

requirement quality and stability in terms of project performance and market

performance. Their results showed that the positive association between requirement

quality and stability and project performance depends on number of groups, the

relationship is stronger for projects with fewer groups than it is for those with more

51

groups. Also they investigated that training and continuous improvement is critical to

requirement definition and management implementation.

2.4.2 KPIs and CSFs relationship on developed countries studies

In UK Andersen et al (2006) studied the relationship between project success factors and

actual KPIs. They found that the most important factors in improving managerial ability

to deliver results in time and at cost were strong project commitment, early stakeholder

influence, stakeholder endorsement of project plans and rich project communications.

In New Zealand Ahsan and Gunawan (2010) applied a study to investigate the major

causes of project delay. They studied 100 project in Asian countries. Their study results

revealed that the root causes of project delay and cost underrun together were long

duration of contract, procurement, civil works and land acquisition, and consultant

recruitment. And the critical causes of project delay were attributed to natural calamities

and host country bureaucracy. Finally they found the main reasons of cost under-run were

categorized as devaluation of local currency, competitive bidding price, lower then

estimated bid, and large contingency budgets.

In Australia and Victoria Orangi et al (2011) aimed to study specific cost overrun and

time overrun issues in the linear construction projects for utility services infrastructure.

They identified the factors which causes time and cost overrun as (i) design changes, (ii)

design errors (including ambiguities and discrepancies of details/ specifications), (iii)

design submission delays, (iv) lack of communication between designers and contractors,

(v) lack of communication between client and project team, (vi) customer/ end-user

related issues, (vii) inadequate geotechnical investigations, (viii) issues regarding client

approvals, (ix) issues regarding permissions/ approvals from other stakeholders, (x)

adverse weather conditions, (xi) delays by materials suppliers, (xii) poor site management

practices, (xiii) planning and scheduling errors, (xiv) construction rework, (xv) cultural

and heritage management issues, (xvi) subcontractor issues.

In Singapore, Hwang et al (2013) identified the critical factors affecting schedule

performance of public housing projects as site management, financing by contractors,

coordination among parties, preparation of schedule plans and updates, experience of

52

contractors, experience of consultants, construction methods, foundation conditions,

speed of decision making of owners, financing by owners during construction, design

changes by owners during construction, experience of owners, project duration set by

owners, availability of laborers on site, availability of staff to manage projects,

availability of equipment, availability of material, Availability of site.

In Lithuania Zavadskas et al (2014) applied a research to analyze common project

management problems and the success factors of construction projects by aggregating

performance indicators. They indicated ten performance indicators namely project

profitability, estimate of project expenditures, income for one executive, number of

accidents during project implementation, repetitive important non conformities in project

quality audits, delay of project close, budget compliance, management of documentation,

environmental project appraisal and personnel risk. They also indicated 13 management

problem. Results of Zavadskas et al (2014) study showed that by using the aggregated

indicators it was easy to compare the projects, the received impartial information was

useful for strategic planning, quality management, for solving the tasks of resource

allocation and motivational project evaluation.

2.5 Summary

The main objectives of this study are to identify and evaluate of the key performance

indicators (KPIs) as a success criteria, to investigate the critical success factors CSFs

affecting the public construction projects and to evaluate the relationship between KPIs

and CSFs in the public construction projects. First section of this chapter conducted

studies to identify briefly KPIs in both developing and developed countries studies. Table

(A 1) in Appendix I summarizes these studies. Second section reviewed studies

concerned about CSFs in developing and developed countries. Table (A 2) in Appendix I

summarizes these studies. In the third section studies about the relationship between

CSFs and KPIs were mentioned. Table (A 3) in Appendix I.

Chapter 3

Research Methodology

54

3. Chapter3: Research Methodology

This research was designed to investigate the success factors that affecting public

construction projects and their relation to key performance indicators; Palestine as case

study. This chapter discusses the methodology which was used in this research. The

research methodology was chosen to achieve the research aims and objectives that to

identify the key performance indicators (KPIs) as a success criteria, to investigate the

critical success factors CSFs affecting the public construction projects and to evaluate the

relationship between KPIs and CSFs.

3.1 Research framework

This study employed a quantitative data. The researcher designed the research by seven

main steps as described below and shown in Figure 3.1.

First step: Theme identification (Problem definition)

It was initiated to define the problem, set the objectives and develop the research plan.

Second step: Literature review

About one hundred published article were reviewed from 38 international journals. And

about 31 KPIs and 125 CSFs were derived.

Third step: Questionnaire development

The pilot study includes two parts. The first part was undertaken by consulting 5 experts

in construction; academic associated doctors, governmental and international

professionals to pre-test the survey and subsequently modified before a final version was

produced. After this, the second part was accomplished by making analysis trial using

some of the population sample for validation before the main survey. The questionnaire

was modified based on the results of the pilot study and the final list of questions was

adopted to be used for the study.

55

Fourth step: The main survey

In this step of the survey, a quantitative approach was utilized as the main statistical

component in the study, to obtain qualitative data using postal questionnaire. An

extensive sampling strategy will be used to ensure meaningful statistical analysis, which

included distributing the questionnaire to the target groups. In order to obtain reliable and

representative quantitative data, the questionnaires will be distributed to four categories

of community members in different positions and disciplines (i.e. NGOs representatives,

construction consultants, esteemed persons, governmental representatives). Moreover, the

targeted group will be from different education levels, ages and work experience years.

Fifth step: Results and discussion

Data collected will be analyzed using both descriptive and inferential tools of statistical

software Statistical Package for Social Science (SPSS 22).

Sixth step: Conclusion and recommendations

This phase of the research included the conclusions and recommendations.

Seventh step: documentation

The final phase of the research included editing the final text, formatting and spelling

and grammatical review.

56

Figure 3. 1: Framework of the research methodology

Stage 5:

Results and

discussions

Distributed 211 electronically

questionnaire in West Bank.

Distributed 173 electronically and paper

questionnaire in Gaza Strip.

Stage 6:

Conclusion and

recommendation

Results Summary with related objectives.

Identifying problem areas from results.

Proposing applicable solution.

Final List of

recommendations

Stage 7:

Documentation

Editing the final text.

Formatting.

Spelling and grammatical review etc.

Final thesis

Activities Stage Deliveries

Stage 1:

Problem definition

Extensive search on recent researches.

Conference topics.

Experts advice.

Setting specific

aim and

objectives

Stage 3:

Questionnaire

development

Interviews with

5 experts to

modify the

questionnaire.

Final modified

questionnaire

Stage 2:

Literature review

Review journals papers.

Review conferences papers

Review thesis.

Initial draft of

questionnaire

Main pilot study by

participating 20

construction experts

to pre-test the

survey.

Stage 4:

Main survey

274 filled

questionnaires

received back

SPSS to perform

quantitative data

Reliability and

validity tests.

Descriptive analysis,

Ranking (RII) and

non-parametric tests.

Factor analysis,

Correlation and

regression analysis.

Obtaining

proposed

objectives

Explaining,

comparing

results and

linking with

previous

studies

57

3.2 Research period

The study started on May 2014 after the proposal was approved. The literature review

was completed at the end of November 2014. The validity testing, piloting and

questionnaire distribution and collection completed at the beginning of August 2015. The

analysis, discussion, conclusion and recommendation were completed at the January

2016.

3.3 Rationale of use quantative approach

The related fieldwork data to this research were collected by using a structured

questionnaire survey which was considered the most widely used data collection

technique for conducting surveys since most of the literature mentioned studies as shown

in Table 3.1. Using postal questionnaire is mostly suited to surveys whose purpose and

objectives are clear enough to be explained in a few paragraphs which are carefully

chosen and guaranteed in this research. Moreover it offers relatively high validity of

results and a quick method of conducting the survey. Therefore the researcher adopted

this strategy.

By surveying the relevant studies mentioned in the literature review, it was obtained that

there were different methodologies and data collection approaches used in order to

achieve the required target, goals and objectives. The collection data methods include

postal quesrionnaire, case study appoach, interviews, focus groups, documents review,

and workshops. Table 3.1 showed the surveyed studies and the adopted corresponding

methodologies. In this study litratures reviews and postal questionaire were used to

collect data.

58

Table 3. 1: Research methods for previous studies

Research methods Research studies

Postal questionnaires

Bourne et al (2002); Dvir et al (2003); Frimpong et al (2003);

Nguyen et al (2004); Dvir and Lechler (2004); Chan et al (2004a);

Bryde and Robinson (2005); Wang and Huang (2006); Meeampol

and Ogunlana (2006); Andersen et al (2006); Iyer and Jha ( 2006);

Sambasivan and Soon (2007); Chen and Chen (2007); Lu et al

(2008); Aksorn and Hadikusumo (2008); Ahadzie et al (2008); Toor

and Ogunlana (2008); Enshassi et al (2009a); Omran and Mamat

(2011); Hwang et al (2013); Ali et al (2013); Ng et al (2009); Yang

et al (2009); Park (2009); Chan et al (2010); Lu and Yuan et al

(2010); Alhaadir and Panuwatwanich (2011); Adnan et al. (2011);

Abdul-Aziz and Kassim (2011); Yu and Kwon (2011); Yang et al

(2011); Al-Tmeemy et al (2011); LI et al (2012); Garbharran et al

(2012); Jagboro et al (2012); Yang et al (2012); Ismail et al (2012);

Lehtiranta et al. (2012); Meng (2012); Ng et al (2012); Chen et al

(2012); Famakin et al (2012); Chou et al (2013); Memon et al (2013);

Yong and Mustaffa (2013); Alzahrani and Emsley (2013); Windapo

and Cattell (2013); Lam et al (2007); Berssaneti and Carvalho (2014);

Gudienė et al (2014); Shehu et al (2014); Mir and Pinnington (2014);

Son and Kim (2014); Cserháti and Szabó (2014); Zou et al (2014);


Case study

Shenhar et al (2001); Bourne et al (2002); Chan and Chan (2004);

Hughes et al (2004); Fortune and White (2006); Aksorn and

Hadikusumo (2008); Cho et al (2009); Abdul-Aziz and Kassim

(2011); Zawawi et al (2011); Orangi et al (2011); Shehata and El-

Gohary (2012); Zavadskas et al (2014); Locatelli et al (2014); Fink

(2014).

Interviews

Bourne et al (2002); Dvir et al (2003); Chan et al (2004b); Hughes et

al (2004); Chan and Chan (2004); Ojiako et al (2008); Toor and

Ogunlana (2008); Lu and Yuan et al (2010); Orangi et al (2011);

Abdul-Aziz and Kassim (2011); Tan and Ghazali (2011); Ng et al

(2012); Windapo and Cattell (2013); Verburg et al (2013); Zhao et al

(2013); Alias et al (2014); Zou et al (2014).

Delphi survey and

brainstorming Yeung et al (2009); Yu and Kwon (2011); Locatelli et al (2014)

Secondary data Shenhar et al (2001); Ahsan and Gunawan (2010); Tan and Ghazali

(2011); Zhao et al (2013); Ihuah et al (2014).

Literatures reviews

Chan et al (2002); Chan and Chan (2004); Chan et al (2004b); Turner

and Müller (2005); Tan and Ghazali (2011); Gudienė et al (2013);

Molenaar et al (2013); Zhao et al (2013); Alias et al (2014).

3.4 Research location

The research was carried out in Palestine territory, in both Gaza Strip and West Bank.

59

3.5 Research population and sample

In this part sample elements, research population, research sample and sample procedure

will be determined.

3.5.1 Research sample elements

The research sample elements consists of construction professionals who can defined in

this study as "civil or architectural engineers who works as project managers, designers

or field supervisors and have more than five years experience in construction projects".

The questionnaire submitted only to those construction professionals.

3.5.2 Research population categories

The research population was mainly limited to three categories: (1) Governmental

organizations, (2) Non-governmental organizations (NGOs) and (3) Engineering

consultants offices. In which, the first category represents local government perspective

and the last two categories represent the local community perspective. In total, the

research population accounted for 1924 engineer.

First category; Governmental organizations: In Gaza Strip and West Bank, there were

several ministries which employed designers, field engineers and project managers that

the researcher targeted three ministries to fill out the questionnaire which were ministry

of public works and housing (MPWH), ministry of education (MOHE); ministry of local

government (MOLG). The selection of those ministries based on their important and

main role in supervising the construction public projects. The population of these

ministries is limited to construction professionals and there total were 226 engineers as

shown in Table 3.2.

Second category; Non-governmental organizations (NGOs): Several NGO's

supervised the public construction projects. But the main there were two associations

targeted only in this study namely united nations relief and works agency (UNRWA) of

Palestinian refugees and united nations development programme (UNDP). The researcher

targeted these agencies only because they are the most and the biggest NGO's which

60

responsible beside the government to supervise most of public construction projects in

Palestine. The population of these agencies is limited to construction professionals and

there total were 230 engineers as shown in Table 3.2.

Third category: Engineering consultants offices: The number of engineering

consultants offices registered in engineering associations on Gaza was 168 offices

(Engineering Association Gaza center, 2015) and in West Bank was 199 office

(Engineering Association Jerusalem center, 2015). The population of these offices is

limited to construction professionals and their number in each office nearly 4 engineers

(Engineering Association Gaza center, 2015), so the population is 1468 engineers for all

offices as shown in Table 3.2.

3.5.3 Sample size

Study sample is a subset of population selected to participate in a research study and its

size refers to the number of the elements to be included in a study, which can be

individuals, groups or organizations (Zikmund et al, 2009). The aim of determining an

adequate sample size is to estimate the population prevalence with a good precision

(Naing et al, 2006). It is extremely rarely possible to conduct full population surveys so

that, a sample can be chosen from the study population that is commonly referred to as

the ‘target population’ (Malhotra and Birks, 2006). The most advantage of using sample

is that it is less time and less costly than collecting data from all of the population.

Otherwise, the disadvantage of using sample is that the selected sample may not

adequately representative of the population and the results obtained from it cannot be

generalized (Marczyk et al, 2005). The principles of statistical sampling which guarantee

a representative sample are employed for economy and speed (Fellows and Liu, 2008).

Several factors can influence the size of the required sample for a study, including the

purpose of the study, population size, sample sizes used in similar studies, the risk of

selecting a “bad” sample, and the allowable sampling error and resource constraints

(Israel, 2013). A statistical calculation approach have been used in this study to calculate

the required sample size. Table 3.2 showed the sample size used on this research. The

61

following formulas was used to determine the sample size of unlimited population (Israel,

2013; Creative research system, 2015).

For infinity population 𝑆𝑆 =𝑍2×𝑃×(1−𝑃)

𝐶2 =1.962×0.5×(1−0.5)

0.052 = 384

Where:

SS: The sample size

Z: Z value (e.g. 1.96 for 95% confidence interval)

P: Percentage picking a choice, expressed as decimal, (0.50 used for sample size needed)

C: Confidence interval expressed as decimal (0.05)

Generally, the confidence interval is the plus or minus figure usually reported in

newspaper or television opinion poll results (Creative research system, 2015). The

general rule relative to acceptable margins of error (a precision ) in categorical data

research is 5% (Israel, 2013). In this study, the population was 1924, and the ratio

between the obtained sample size and the population equals to 0.2 (384/1924) which is

larger than 0.05, then corrected sample size for finite population can be used. For that ,

the sample size for this study was calculated as follows,

𝑆𝑆𝑁𝑒𝑤 =𝑆𝑆

1 +𝑆𝑆 − 1

𝑃𝑜𝑝

=384

1 +384 − 1

1924

= 320.24 = 321

Where: pop is the total population

The method of sampling followed in this research was stratified random sampling. The

population were divided into different sub-populations or categories in order to obtain a

sample that is representative of the population. The stratified sample was obtained by

taking samples from each category which calculated by the following equation (Creative

research system, 2015):

(𝑆𝑆)𝑖 =(𝑃𝑜𝑝)𝑖

𝑅𝑒𝑠𝑒𝑎𝑟𝑐ℎ 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛× 𝑅𝑒𝑠𝑒𝑎𝑐ℎ 𝑆𝑎𝑚𝑝𝑙𝑒 𝑠𝑖𝑧𝑒

Where:

(SS)i: The sample size of category i

(Pop)i: Population of category i

An example for MPWH in Gaza Strip, the sample size was calculated as following:

62

(𝑆𝑆)𝑀𝑃𝑊𝐻/𝐺𝑎𝑧𝑎 =47

1924× 321 = 7.8 ≈ 8

The sample size formulas used above provide the number of responses that need to be

obtained in study. Israel (2013) reported that, many researchers commonly increased the

sample size about 10% to 30% , to compensate for persons that the researcher is unable to

contact and for nonresponse. Thus, the number of distributed questionnaires can be

substantially larger than the number required for a desired level of confidence and

precision. So that, in this study, 384 questionnaires which was the sample before

correction to be distributed to the targeted sample which represented 17.2% of the sample

size after correction.

3.5.4 Sampling procedure

A sample design “sampling procedure” refers to the technique or the procedure the

researcher would adopt in selecting items for the sample (Kothari, 2004). In this study,

the population consisted of three groups which were the first, second and third groups,

then, more complicated sampling method should be adopted to select the questionnaire

respondents. Zikmund et al. (2009) pointed out that, in stratified random sampling, a

subsample is drawn using simple random sampling within each stratum. This method is

one of the random sampling techniques and yields precise estimation and more accurate

than those produced by simple random sampling; particularly, when the sampling frame

is available in the form of a list (Kothari, 2004). According to Love et al (2013) there are

two main benefits can be obtained from using stratified sampling method, which are:

1. Ensuring adequate and representative respondents in each category under study is

acquired.

2. Ensure that the respondents within the same category are homogeneous.

The discussion above forced the researcher in this study to adopt the stratified random

sampling method to select a representative for the study population. Table 3.2 describes

the sampling numbers and percentages used in this study. Also the number of the

returned questionnaires and percent are presented in this table. It was cleared that only

274 questionnaire were collected which was less than the sample size 321 due to several

63

reasons like using electronic questionnaire only in West Bank since the researcher can

not have permission to go there within study period. Also many of targeted elements

hadn't enough time to response. However the total returned percent is considered to be

acceptable since it is nearly 71.35%.

Table 3. 2: Sample size for each of the research population categories

Category

pla

ce o

f w

ork

Po

pu

lati

on

Sam

ple

siz

e

No

. o

f

dis

trib

ute

d

qu

esti

onn

aire

s

Ret

urn

ed

qu

esti

onn

aire

s

% R

etu

rned

qu

esti

onn

aire

s

Governmental

organizations

Gaza

Strip

MPWH 47 8 10 10 100%

MOLG 4 1 2 2 100%

MOHE 5 1 2 2 100%

West

Bank

MPWH 103 17 22 16 72.72%

MOLG 37 6 9 6 66.67%

MOHE 30 5 8 5 62.50%

NGOs Gaza

Strip

UNRWA 105 17 22 18 81.82

UNDP 17 3 4 3 75%

West

Bank

UNRWA 77 13 16 13 81.25%

UNDP 31 5 8 6 75%

Engineering

consultants

offices

Gaza Strip 672 113 112 99 74.44%

West Bank 796 133 133 94 63.51%

Total in Gaza Strip 850 142 173 134 77.46%

Total in West Bank 1074 179 211 140 66.35%

Total 1924 321 384 274* 71.35%

3.6 Questionnaire Design

The questionnaire design was extracted from previous studies in developing countries

and developed countries directly related to the subject of this research. After a long time

of searching, consulting, modifying and reviewing by the supervisor and experts the

questionnaire was established and ready for distribution. The questionnaire was designed

in both English and Arabic languages in order to facilitate the understanding of content

for the concerned population sample. The first page in the questionnaire was a covering

letter that explained the study purpose, aim and the information security.

The questionnaire consisted of close-ended (multiple choice) items. Close-ended

questions are more difficult to design than open-ended items, but they come up with

64

much more efficient data collection, processing and analysis (Bourque and Fielder,

2003). Bourque and Fielder (2003) said that “surveyors should avoid using open-ended

questions in mail and other self-administered questionnaires”. The questionnaire divided

into three main parts, which included (i) general information, (ii) key performance

indicators and (iii) the importance of critical success factors. The first questionnaire draft

was designed and reviewed by pilot study and based on the results, the questionnaire

framework was modified and refined (refer to Appendix II and Apendix III for the final

questionnaire design in English and Arabic respictively).

3.6.1 General information

The first part of the questionnaire consisted of general information. This part had two

segments, the first segment was for personal information of the respondent and the other

segment was about respondent's organization. The first segment included questions about

respondents jop title, working experience, proffesion, and their place of residant. The

second segment seeked some information about respondent organization such as; type,

working field and size of the organization.

3.6.2 Key performance indicators

The second part of the questionnaire consisted of three main fields which were:

1. KPIs degree of importance: The main objective of this field is to determine the

most important KPIs that should be measured to indicate the performance

situation of the project. Respondents asked to give their opinion about the

importance of 13 KPIs which derived from literature review and piloting study.

The items in this field of questionnaire were in statements format. Respondents in

this part were asked to rate each item on five-point likert item that required a

ranking from 1 to 5 according to that "1" not important, "2" low important, "3"

semi important, "4" important, and "5" very important". Where 1 represented

“lowest scale” and 5 represented “highest scale”. Wikipedia (2014) stated that a

Likert item is simply a statement that the respondent is asked to evaluate by

giving it a quantitative value on any kind of subjective or objective dimension,

with level of agreement/disagreement being the dimension most commonly used.

65

Well-designed Likert items exhibit "symmetry" in that they contain equal

numbers of positive and negative positions whose respective distances apart are

bilaterally symmetric about the "neutral"/zero value (whether or not that value is

presented as a candidate. A Likert scale is the sum of responses on several Likert

items.

2. Measuring practices for KPIs in Palestinian construction projects: The

objective of this field is to determine whether the 13 KPIs measured during the

project or not in order to test the effect of this practice on project success.

Respondents asked to give their opinion about the 13 KPIs. They asked wither

they measure them annually by five-point likert item which required a ranking

from 1 to 5 according to that "1" always, "2" Mostly, "3" sometimes, "4" rarely,

and "5" never. Where 1 represented “lowest scale” and 5 represented “highest

scale”.

3. Public construction projects KPIs evaluation: The main objective of this field is

to evaluate the situation of projects according to the KPIs. Respondents asked to

give their opinion about the 13 KPIs. They asked about their evaluation for the

actual KPIs in comparative to planned. The items in this part of questionnaire

were in statements format. Respondents in this part were asked to rate each item

on five-point likert item which required a ranking from 1 to 5 according to that

"1" much less, "2" less, "3" equal, "4" higher, and "5" very high". Where 1

represented “lowest scale” and 5 represented “highest scale”.

3.6.3 Critical success factors

Kerzner (2001) stated that the available life cycle phases of projects were Conceptual,

Planning, Testing, Implementation and Closure. Ng and Walker (2008) conducted a study

of project management leadership styles across life cycle stages of information

technology projects in Hong Kong. They divided projects life cycle into four phases

which were 1) project initiation & design, 2) development, 3) testing and production cut

over and 4) project acceptance. Another study conducted by Saad (2011) investigated the

factors impacting the project’s life cycle and he divided project life cycle into five phases

namely 1) conceptual planning and economics (feasibility study) Phase, 2) engineering

66

and functional design phase, 3) tender and award phase, 4) construction and completion

of the Project (implementation) phase and 5) operation and utilization phase. In this study

the researcher divided the collected CSFs divided into four phases which were:

1. CSFs related to project conceptualizing and preparation phase: this phase

contains 12 CSFs related to issues like project feasibility, type, size, priority and

so on which should be determined at the beginning of the project life cycle. Those

factors was collected from literature reviews such as Abdul-Aziz and Kassim

(2011); Yu and Kwon (2011) ; Yang et al (2011); Chen et al (2012); Ismail et al

(2012); Alzahrani and Emsley (2013); Hwang et al (2013) and Verburg et al

(2013) and from questionnaire piloting. The most important party in this phase is

client and most of the phase factors related to his behavior.

2. CSFs related to project planning and designing phase: this phase contains 19

CSFs related to plans, designs, codes, licenses, cost and time estimations,

consultants involvement and experience and so on. Those factors was collected

from literature reviews such as Lam et al. (2007); Windapo and Cattell (2013);

Chou et al (2013); Ihuah et al (2014); Wibowo and Alfen (2014); Zou et al

(2014); Mir and Pinnington (2014) and Locatelli et al (2014) and from

questionnaire piloting. The most important party in this phase is consultant and

most of the phase factors related to his behavior.

3. CSFs related to project tendering and contracting phase: this phase consists of

16 CSFs related to contracting management, criteria, experience, meetings and so

on. Those factors was collected from literature reviews such as Lam et al. (2007);

Molenaar et al (2013); Locatelli et al (2014); Mir and Pinnington (2014); Son and

Kim (2014); Shehu et al (2014); Alias et al (2014) and Yang et al (2015) and

from questionnaire piloting. The most important party in this phase is client and

most of the phase factors related to his behavior.

4. CSFs related to implementation phase: this phase contains 34 CSFs related to

project implementation monitoring, authorities, team commitment,

communications effectiveness and so on. Those factors was collected from

literature reviews such as Lam et al (2007); Famakin et al (2012); Ng et al

(2012); Garbharran et al (2012); Ali et al (2013); Alzahrani and Emsley (2013);

67

Hwang et al (2013); Verburg et al (2013); Molenaar et al (2013); Gudienė et al

(2014); Cserháti and Szabó (2014); Zavadskas et al (2014) and Mir and

Pinnington (2014) and from questionnaire piloting. The most important party in

this phase is contractor and most of the phase factors related to his behavior.

The items in this part of questionnaire were in statements format. Respondents in this part

were asked to rate each item on five-point likert item which required a ranking from 1 to

5 according to that "1" not important, "2" low important, "3" semi important, "4"

important, and "5" very important". Where 1 represented “lowest scale” and 5

represented “highest scale”.

3.7 Pilot study

In order to test the appropriateness, validity and reliability of the questionnaire before

committing to the complete sample population, a pilot study for the questionnaire was

conducted. It provides a trial run for the questionnaire, which involves testing the

wordings of question, identifying ambiguous questions, testing the techniques that used

to collect data, and measuring the effectiveness of standard invitation to respondents. The

pilot study was divided mainly in three stages which were:

The first stage: in this stage the questionnaire was consulted by experts who have more

than 15 years experience in construction projects and they have academic background in

questionnaires assessment.

The second stage: in this stage the questionnaire was conducted to limited group from

the targeted population by distributing the questionnaire conveniently to 20 respondents

selected randomly.

The third stage: in this stage the questionnaire analyzed using statistical tests in order to

check the questionnaire validity and reliability respectively.

3.7.1 Experts consultation

Before arbitrating the questionnaire from experts the researcher undertaken the following

steps:

Firstly the researcher summarize 125 CSFs from the literature and 31 KPIs and prepared

the first draft of the questionnaire.

68

Secondly: the supervisor review the questionnaire and he canceled the factors related to

PPP part which included 10 factors in order to limit the scope of the research and because

this type of projects not famous on Palestine.

Thirdly: the first draft of the questionnaire was prepared. First draft contained 13 KPIs

and 72 CSFs grouped in five groups namely: project related factors, stakeholders related

factors, external related factors, management practices related factors and relationships

and communications related factors.

Fourthly: Expert A got the first draft of the questionnaire and he suggested the following

general notes to be perform firstly before distribute the questionnaire to other experts:

1. The classification of the CSFs should change to fit project life cycle phases and this

modification was confirmed.

2. He suggest to take Palestine as case study not only Gaza Strip and this idea was

confirmed.

3. He also recommended to distribute the questionnaire electronically and hard copy

and this idea was also confirmed.

Fifthly: the second draft of the questionnaire was prepared and it contained 12 KPIs and

74 CSFs grouped in clusters according to projects life cycle. The questionnaire was

consulting 6 Palestinian experts who have more than 15 years experience in construction

projects to review the questionnaire and make adjustments that best fit the Palestinian

conditions. Table 3.3 showed some detailed information about the experts work and

their experience in construction projects. Each expert got a copy of the questionnaire for

revision, and after that the researcher discussed the notes with each expert. Each expert

developed his own notes for modification (see Table 3.4), and some notes were

confirmed by more than one expert. Each note were carefully considered in preparing

the final questionnaire. The changes undertaken by those experts and are summarized in

Table 3.6.

69

Table 3. 3: Detailed information for the consulted experts

No. Recent Work Related experience

Expert

A

Minister consultant for planning and

international cooperation. MPWH

Previous manager of tendering

department in MPWH.

Previous member in Khan Younis

municipality.

Ph.D. in civil engineering.

Expert

B

Associated Professor in civil

engineering. UCAS

Previous minister of public works and

housing ministry. Palestine.

Manager of engineering office at

UCAS university.

Expert

C

Consultant and expert in UNRWA, Gaza

and UNAMID, Sudan. 15 years' experience in the

international agencies.

Expert

D Assistant Professor in architecture. IUG

Previous minister of public works and

housing ministry. Palestine.

Former Dean of the Faculty of

Engineering at IUG.

Previous manager of engineering

office at IUG university.

Expert

E Assistant Professor in architecture. IUG

Renewable energy expert.

Expert

F

General manager of projects department.

MOLG Over 20 years' experience in the

municipal construction projects.

Table 3. 4: Questionnaire review notes gathered from experts

No. Notes

Expert

A

In general information part:

He suggested to cancel the question about the number of workers in respondent

organization. Confirmed.

In CSFs part:

He suggested to add the definition of CSF's at the beginning of the part.

Confirmed.

He modified several factors wordings.

He suggested to split the factor of "construction permits and detailed it".

He suggested to add 9 factors which were "Studying the level of acceptance of

local community to execute the project in their location", "Taking in consider

the operation and maintenance phase during project planning and designing

phase", "Documentation for all agreements of the preparation meetings in

details", "Visiting project location by all consultants and contractors before

filling out the bid form", " The client (his representative) interprets all project

requirements and location during the preparatory meeting of the bids ", " Giving

enough time for consultants and contractors to fill out the bid form", "

Continuous revision for the project shop drawings and approve them fast", "

Availability and execution of material handling plans" and " Involvement of the

consultant and the contractors in project operating and maintenance plan after

project execution" . All suggested factors confirmed to be added.

Expert

B

In general information part:

He suggested to use five likert scale for both periodically measure of indicator

and performance evaluation of organization projects. Confirmed.

70


No. Notes

He modified the indicator " Project conformity to sustainability and

environmental criteria" to be two indicators which were "Project conformity to

sustainability criteria" and "Project conformity to environment protection

standards during execution". Confirmed.

In CSFs part:


He suggested to add two factors which were "Documentation for all agreements

of the preparation meetings in details" and " Documentation of project activities

clearly and through annual reports". The first added factor also confirmed with

expert A suggestion. The two factors were Confirmed to be added.

He suggested that the CSF's in the questioner should be ranked according to

their rationale weight. The researcher will take this suggestion into account in

data analysis phase.

Expert

C

In KPI part:

He suggested to modify the second indicator which was " Actual project time

comparing with scheduled" to be " Actual project execution time comparing

with scheduled". Confirmed.

He suggested to use five likert scale for both periodically measure of indicator

and performance evaluation of organization projects. Confirmed and it was the

same suggestion of Expert B.

He splited the indicator " Project conformity to sustainability and environmental

criteria" to be two indicators which were "Project conformity to sustainability

criteria" and "Project conformity to environment protection standards during

execution". Confirmed and it was the same suggestion of Expert B.

In CSFs part:



He suggested to add two factors which were " Continuous revision for the

project shop drawings and approve them fast" and " Saving as built drawings of

the project". The first added factor also confirmed with expert A suggestion.

The two factors were Confirmed to be added.

Expert

D

The questionnaire is too long so that, in order to get real and valuable

information, participants should take enough time to fill it.

He suggested to split the questionnaire to three questionnaires for the project

owner, consultant and contractor. The researcher could not apply this

suggestion because it is will take a lot of effort and time and the questionnaire

in this targeted only experts and consultants.

Expert

E

In the front page of the questionnaire add the time required to fill the

questionnaire, do not write headings for the paragraphs, and write the researcher

email. Confirmed.

In General information part rearrange the questions related to the respondent

association together and the questions related to the respondent himself

together. Confirmed

She suggested to split the questionnaire according to engineers fields like

architectural, design, civil, ..etc.. The researcher could not apply this suggestion

because it is will take a lot of effort and time and the questionnaire in this

targeted only experts and consultants and they can answer all questions.



71


No. Notes

Expert

F




3.7.2 Distributing questionnaire to limited group

Many previous studies used less than 20 as the sample of pilot study such as (Enshassi,

2012; Ng et al, 2012; Mir and Pinnington, 2014). In this study the researcher distributed

the questionnaire to limited group consist of 20 person. The sample selected from the

population randomly in order to test the validity and reliability of the questionnaire.

3.7.3 Statistical results of pilot study

After the researcher collected the 20 questionnaire data analyzed using SPSS (22) in

order to test the internal validity and the reliability of the questionnaire. The validity

tested using Pearson correlation coefficient for both criterion and structural validity of the

questionnaire. The reliability tested using two types of tests the first was Half Split

Coefficient and the second was Cronbach’s Alpha Coefficient.

3.7.3.1 Criterion and structural validity of the questionnaire

The correlation coefficient for each domain items were significant at α = 0.01 or α = 0.05,

as shown in Table (A 4) in Appendix IV. It can be concluded that the paragraphs of the

questionnaire were consistent and valid to measure what it was set for.

3.7.3.2 Half Split Coefficient for reliability of the questionnaire

The normal range of corrected correlation coefficient is between 0.0 and + 1.0 As shown

in Table 3.5, all the corrected correlation coefficients values are between 0.835 and 0.879

and the general reliability for all items equal 0.907, and the significant (α ) is less than

0.05 so all the corrected correlation coefficients are significance at α = 0.05. It can be said

that according to the Half Split method, the dispute causes group are reliable.

72

Table3. 5: Split-Half Coefficient method

Field Half split coefficient

Key performance indicators KPI's 0.835

CSFs related to conceptualizing and preparation phase 0.864

CSFs related to planning and designing phase 0.859

CSFs related to tendering and contracting phase 0.851

CSFs related to implementation phase 0.879

Total 0.907

3.7.3.3 Cronbach’s Alpha Coefficient for reliability of the questionnaire

As shown in Table 3.6, The Cronbach’s coefficient alpha was calculated for the

questionnaire domains. The results were in the range from 0.847 and 0.912, and the

general reliability for all items equal 0.935. This range is considered high; the result

ensures the reliability of the questionnaire.

Table 3. 6: Reliability Cronbach's Alpha method

Field Cronbach's Alpha

Key performance indicators KPI's 0.85

Factors related to conceptualizing and preparation phase 0.89

Factors related to planning and designing phase 0.89

Factors related to tendering and contracting phase 0.86

Factors related to implementation phase 0.91

Total 0.94

3.8 Main questionnaire distribution

To sum up, 31 KPIs and 125 CSFs were identified from literature review. The final

questionnaire contain 13 KPIs and 81 CSFs after supervisor, researcher and experts

involved in the study participate in variety of comments include accepted, modifying,

adding, separating, merging and deleting some factors. The KPIs and CSFs are

summarized in Appendix V Tables (A 5) and Table (A 6). Table 3.7 summarized the

selected and omitted KPIs and CSFs and it was cleared all KPIs were modified in order to

fit Palestinian construction projects enviroment.

73

The researcher followed two methods to distribute the questionnaire which were

electronically and papers (by hand). The questionnaire were distributed only

electronically questionnaire in West Bank. The researcher had a list of telephones and

mobiles numbers of the targeted group and she phoned each one of them. The targeted

group sample as mentioned in section 3.5 was 384 questionnaire. In West Bank 211

questionnaire were distributed and 173 questionaire in Gaza Strip. From West Bank 140

person responded which represented 66.35% of total targeted group in West Bank. In

Gaza Strip 40 person responded electronically and 94 person responded on papers which

represented 77.46% of total targeted group in Gaza Strip. The total number of

respondents was 274 which represent 71.35% of the total targeted group.

Table 3. 7: Summary of factors and indicators selected and omitted

Comment types Remaining Factors Omitted Factors

KPIs

Selected 0

Modified 12

Added 1

Merged 9

Cancelled 10

Total used in the questionnaire 13

CSFs

Selected 13

Modified 46

Splitted 5

Added 9

Merged 31

Cancelled 29

Total used in the questionnaire 81

74

3.9 Quantitative data analysis using SPSS

A quantitative method was adopted in the current research, where quantitative methods of

data analysis can be of great value to the researcher who is attempting to draw

meaningful results from a large body of qualitative data. The main beneficial aspect is

that quantitative analytical approach provides the means to separate out the large number

of confounding factors that often obscure the main qualitative findings (Field, 2009).

SPSS 22 (Statistical Package for the Social Sciences) for Windows contains a broad

range of capabilities for the entire analytical process. The decision-making information

can quickly be generated by using powerful statistics, to understand and present the

results with tabular and graphical output, and share the results using a variety of reporting

methods. By using this software, the following tests were adopted in this study:

A. Descriptive Statistics:

1. Frequencies.

2. measures of central tendency (the mean)

3. Measurement of dispersion based on the mean (standard deviation)

4. Relative Important Index (RII)

5. Kolmogorov-Smirnov test of normality.

6. Factor analysis

B. The inferential statistics:

1. Pearson product-moment correlation coefficient/ Pearson's correlation coefficient

(a parametric test)

2. The sample independent t-test to find out whether there is a significant difference

in the mean between two groups (a parametric test).

3. Analysis of Variance One way ANOVA) test (a parametric test).

4. Cronbach's Alpha for Reliability Statistics.

5. Independent Samples T-test.

3.9.1 Reliability statistics

Reliability aimed to examine the quality of measurement. It was the "consistency" or

"repeatability" of the analysis. Polit and Hunger (1985) defined the reliability of an

instrument as "the degree of consistency which measures the attribute it was supposed to

75

be measuring". Reliability was typically assessed by one of two ways: (1) Internal

consistency - Precision and consistency of test scores on one administration of a test and

(2) Stability - Precision and consistency of test scores over time (test-retest).

The less variation an instrument produces in repeated measurements of an attribute, the

higher its reliability. Reliability can be equated with the stability, consistency, or

dependability of a measuring tool (Polit and Hunger, 1985). Period of two weeks to a

month is recommended between two tests. But, in this research, it was too difficult to ask

participants to respond to the questionnaire twice within short period since they were so

busy having full time works. In addition, it was hard for the researcher because it needs a

lot of time. Fortunately, statistician's stated that overcoming the distribution of the

questionnaire twice to measure the reliability could be achieved by using Cronbach Alpha

coefficient and Half Split method through the SPSS software.

3.9.1.1 Alpha-Cronbach coefficient

One of the most commonly used indicators of reliability analysis was Cronbach‟s alpha

coefficient. Its scale should be above 0.6 as stated by Hair et al and Pallant (cited in

Chan, 2008:77). This method was used to measure the reliability of the questionnaire

between each field and the mean of the whole fields of the questionnaire. The normal

range of Cronbach’s coefficient alpha value between 0.0 and + 1.0 (Field, 2009; Weiers,

2011), and the higher values reflects a higher degree of internal consistency. Its scale

should be above 0.7 as stated by Hair et al. and Pallant (cited in Chan, 2008:77). The

results of this test is shown in the pilot study section 3.7.

3.9.1.2 Half Split Method

This method depends on finding Pearson correlation coefficient between the means of

odd rank questions and even rank questions of each field of the questionnaire. Then,

correcting the Pearson correlation coefficients can be done by using Spearman Brown

correlation coefficient of correction. The corrected correlation coefficient (Consistency

coefficient) is computed according to the following equation:

𝐶𝑜𝑛𝑠𝑖𝑠𝑡𝑒𝑛𝑐𝑦 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡 = 2𝑟

𝑟 + 1

Where: r is the Pearson correlation coefficient.

76

3.9.2 Validity statistics

Statistical validity of the questionnaire refers to the degree to which an instrument

measures what it is supposed to be measuring (Pilot and Hungler, 1985). Validity has a

number of different aspects and assessment approaches.

To insure the validity of the questionnaire, two statistical tests should be applied. The

first test is Criterion-related validity test (Pearson test) which measure the correlation

coefficient between each item in the field and the whole field. The second test is structure

validity test (Pearson test) that used to test the validity of the questionnaire structure by

testing the validity of each field and the validity of the whole questionnaire. It measures

the correlation coefficient between one filed and all the fields of the questionnaire that

have the same level of similar scale.

3.9.2.1 Pearson correlation coefficients for criterion related validity

Internal consistency of the questionnaire was measured by a scouting sample, which

consisted of 20 questionnaires, through measuring the correlation coefficients between

each paragraph in one field and the whole filed.

3.9.2.2 Pearson correlation coefficients for structure validity

Structure validity was the second statistical test that used to test the validity of the

questionnaire structure by testing the validity of each field and the validity of the whole

questionnaire. It measures the correlation coefficient between one filed and all the fields

of the questionnaire that have the same level of liker scale.

3.9.3 Kolmogorov-Smirnov Test of Normality

The One-Sample Kolmogorov-Smirnov test procedure compares the observed cumulative

distribution function for a variable with a specified theoretical distribution, which may be

normal, uniform, Poisson, or exponential. The Kolmogorov-Smirnov Z is computed from

the largest difference (in absolute value) between the observed and theoretical cumulative

distribution functions. This goodness-of-fit test tests whether the observations could

reasonably have come from the specified distribution. Many parametric tests require

77

normally distributed variables. The one-sample Kolmogorov-Smirnov test can be used to

test that a variable of interest is normally distributed (Henry and Thode, 2002).

Table 3.8 showed the results for Kolmogorov-Smirnov test of normality. From Table 3.8,

the p-value for each variable is greater than 0.05 level of significance, then the

distributions for these variables are normally distributed. Consequently, parametric tests

can be used to perform the statistical data analysis.

Table 3. 8: Kolmogorov-Smirnov test of normality

Field Kolmogorov-Smirnov

Statistic P-value

Key performance indicators KPI's of projects 0.951 0.327

CSFs related to conceptualizing and preparation phase 0.712 0.690

CSFs related to planning and designing phase 0.731 0.659

CSFs related to tendering and contracting phase 0.599 0.866

CSFs related to implementation phase 0.780 0.577

All paragraphs of the questionnaire 0.754 0.621

3.9.4 Relative Importance Index (RII)

In order to be able to select the appropriate method of analysis, the level of measurement

must be understood. For each type of measurement, there is/are an appropriate method/s

that can be applied and not others. In this research, ordinal scales were used. Ordinal

scale is a ranking or a rating data that normally uses integers in ascending or descending

order. The numbers assigned to the important (1,2,3,4,5) did not indicate that the interval

between scales are equal, nor do they indicated absolute quantities. They are merely

numerical labels. Based on Likert scale shown in questionnaire design section 3.6.

The relative importance index method (RII) was used to determine the ranks of all

factors. The relative importance index was computed as (Sambasivan and Soon, 2007;

AbuHamra, 2015):

𝑅𝐼𝐼 =∑ 𝑊

𝐴 × 𝑁

Where:

W = the weighting given to each factor by the respondents (ranging from 1 to 5)

A = the highest weight (i.e. 5 in this case)

N = the total number of respondents

78

The RII value had a range from 0 to 1 (0 not inclusive), the higher the value of RII, the

more impact of the attribute. However, RII doesn't reflect the relationship between the

various attributes.

3.9.5 Parametric tests:

Parametric test: a test that requires data from one of the large catalogue of distributions

that statisticians have described. Normally this term is used for parametric tests based on

the normal distribution, which require four basic assumptions that must be met for the

test to be accurate: a normally distributed sampling distribution (researcher can

approximate using a normal distribution after invoking the central limit theorem),

homogeneity of variance, interval or ratio data, and independence (Field, 2009).

3.9.5.1 One sample t test.

The t-test is a parametric test which is used to compare the difference between the mean

scores of two samples.

3.9.5.2 One way ANOVA.

If there are more than two independent groups being compared the one-way ANOVA is

used if the parametric assumptions are satisfied—that is, interval-scale variable

approximately normally distributed.

3.9.6 Factor analysis

Factor analysis is a generic term for a family of statistical techniques concerned with the

reduction of a set of observable variables in terms of a small number of latent factors. It

has been developed primarily for analyzing relationships among a number of measurable

entities (such as survey items or test scores). The underlying assumption of factor

analysis is that there exist a number of unobserved latent variables (or “factors”) that

account for the correlations among observed variables. In other words, the latent factors

determine the values of the observed variables (Doloi, 2009; Field, 2009). The main

applications of factor analytic techniques are:

1. Explore data for pattern.

79

2. Data reduction.

3. Confirm the hypothesis of data structure.

3.9.6.1 Types of factor analysis

1. Exploratory factor analysis (EFA), which is used to identify complex

interrelationships among items and group items that are part of unified concepts. The

researcher makes no “a priori” assumptions about relationships among factors.

2. Confirmatory factor analysis (CFA), which is a more complex approach that tests the

hypothesis that the items are associated with specific factors.

3.9.6.2 Methods of factoring

There are several methods for unearthing factors in data (Field, 2009):

1. Principal component analysis (PCA): is a widely used method for factor extraction,

which is the first phase of EFA. Factor weights are computed in order to extract the

maximum possible variance, with successive factoring continuing until there is no

further meaningful variance left. The factor model must then be rotated for analysis;

2. Canonical factor analysis, also called Rao's canonical factoring;

3. Image factoring;

4. Alpha factoring; and

5. Factor regression model

Principal component analysis (PCA) is the preferred method since it is usually result in

similar solution not like remaining methods which their conclusions are restricted to the

sample collected and generalization of the results can be achieved only if analysis using

different samples reveals the same factor structure. thus, Principal component analysis

(PCA) has been selected for factoring in this research to examine the underlying structure

or the structure of interrelationships among the variables.

3.9.6.3 The distribution of data

The assumption of normality is most important requirement to generalize the results of

factor analysis test beyond the sample collected (Field, 2009; Zaiontz, 2014).

80

3.9.6.4 Validity of sample size

The reliability of factor analysis is dependent on sample size. PCA can be conducted on a

sample that has fewer than 100 respondents, but more than 50 respondents. The common

rule is to suggest that sample size contains at least 10–15 respondents per item. In other

words, sample size should be at least 10 times the number of items and some even

recommend 20 times (Field, 2009; Zaiontz, 2014).

3.9.6.5 Validity of correlation matrix (correlations between variables)

It is simply a rectangular array of numbers which gives the correlation coefficients

between a single item and every other item in the investigation. The correlation

coefficient between a variable and itself is always 1; hence the principal diagonal of the

correlation matrix contains 1s. The correlation coefficients above and below the principal

diagonal are the same. PCA requires that there be some correlations greater than 0.30

between the items included in the analysis (Field, 2009; Zaiontz, 2014).

3.9.6.6 Kaiser-Meyer-Olkin (KMO) and Bartlett's Test as a measure of

appropriateness of Factor Analysis

The value of (KMO) can be calculated for individual and multiple items and represents

the ratio of squared correlation between items to the squared partial correlation between

items. It varies from 0 to 1. Interpretive adjectives for the Kaiser Meyer Olkin Measure of

Sampling Adequacy are: in the 0.90 as marvelous, in the 0.80's as meritorious, in the

0.70's as middling, in the 0.60's as mediocre, in the 0.50's as miserable, and below 0.50 as

unacceptable. A value close to 1 indicates that pattern of correlation is relatively compact

and hence factor analysis should give distinct and reliable results (Kaiser, 1974; Field,

2009; Zaiontz, 2014). Bartlett's test of sphericity tests the hypothesis that the correlation

matrix is an identify matrix; i.e. all diagonal elements are 1 and all off diagonal elements

are 0, implying that all of the items are uncorrelated. If the sig. value for this test is less

than alpha level, researcher must reject the null hypothesis that the correlation matrix is

an identity matrix (Field, 2009; Zaiontz, 2014).

81

3.9.6.7 Determining the number of factors

Determining the optimal number of factors to extract is not a straightforward task since

the decision is ultimately subjective. There are several criteria for the number of factors

to be extracted. The “eigenvalues greater than one” rule has been most commonly used

due to its simple nature and availability in various computer packages. The eigenvalue

(variance) criterion stated that each component explained at least one item's 's worth of

the variability, and therefore only components with eigenvalues greater than one should

be retained (Larose, 2006; Field, 2009).

After extraction of factors, Table of “communalities (common variances)” should be

examined to know how much of the variance in each of the original items is explained by

the extracted factors. If the communality for a variable is less than 50%, it is a candidate

for exclusion from the analysis because the factor solution contains less than half of the

variance in the original item, and the explanatory power of that variable might be better

represented by the individual item (Field, 2009; Zaiontz, 2014).

Components are then rotated via varimax rotation approach to assist in the process of

interpretation and to discover the best distribution of the better loading components in

terms of the meaning of the components. This does not change the underlying solution, or

the relationships among the items. Rather, it presents the pattern of loadings in a manner

that is easier to interpret factors/ components (Factor loading: the regression coefficient

of an item/ a variable for the linear model that describes a latent variable or factor in

factor analysis). On other hand, the pattern of factor loadings should be examined to

identify variables that have complex structure (complex structure occurs when one item

has high loadings or correlations (0.50 or greater) on more than one factor/ component).

If an item/ a variable has complex structure, it should be removed from the analysis

(Reinard, 2006; Field, 2009; Zaiontz, 2014).

3.9.6.8 Mathematical validity of factor analysis

Once factors have been extracted, it is necessary to cross check if factor analysis

measured what was intended to be measured by using Cronbach's alpha test (Cα). An

alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or

higher (Field, 2009; Weiers, 2011; Garson, 2013).

82

3.1 Summary

This chapter described the detailed adopted methodology of research. It included the

primary research framework for the study, details of research period, location,

population, and sample size. The questionnaire design was detailed including the initial

draft that was modified and refined through pilot study. Quantitative data analysis

techniques, which include factor analysis, reliability test, normality test and Pearson

correlation analysis, were designed to be applied by the instruments of SPSS. For the

purposes of testing the research validity, reliability, and adequacy of methods used in

analysis, different statistical tests were used and explained in details.

Chapter 4

Results and Discussion

84

4. Chapter 4: Results and discussion

4.1 Scope of chapter

This chapter included analysis and discussion of the results that have been collected from

field surveys. Data was analyzed using SPSS including descriptive and inferential

statistical tools. In this study, total of two hundred and seventy four questionnaires

respondents from the study sample were considered. This chapter included the personal

information and profile of the respondents, quantitative analysis of questionnaire field

survey, and finally the summary framework of the results.

Figure 4. 1: The outline of data analysis and discussion chapter

Data analysis outline

Demographic survey of

respondents

Identifying and

evaluation of the key

performance indicators (KPIs) as a

success criteria

Factor analysis

results for KPIs

Ranking and evaluation of

KPIs as a success criteria

Investigating the critical

success factors CSFs affecting the

public construction

projects.

Factor analysis

results for CSFs

CSFs related to conceptualizing and preparation

CSFs related to planning and

designing stage

CSFs related to tendering and

contracting

Factors related to implementation

Ranking of CSFs affect

construction projects Differences

among respondents toward the analysis of

CSFs and KPIs on Palestine

Summary of results

framework

85

4.2 Demographic survey of respondents

This section of questionnaire mainly designed to provide general information about the

respondents and their companies. Table 4.1 represents the characteristics of respondents.

Table 4. 1: Demographic survey of respondents

Category Place of resident Frequency Percent %

Place of respondents resident Gaza Strip 134 48.91

West Bank 140 51.09

Total respondents 274 100

Category Organization type Frequency Percent %

Respondents organization type

Governmental organization 41 14.96

Non-governmental organization 40 14.59

Consultation offices 193 70.45


Category Value Frequency Percent %

Respondents organization projects

size during the last five years (in

million dollar)

Less than 5 M$ 105 38.32

From 5 -10 M$ 40 14.6

From 11 - 20 M$ 40 14.6

More than 20 M$ 89 32.48


Category Job title Frequency Percent %

Respondents job title

Design consultant 93 33.94

Supervising consultant 116 42.34

project manager 65 23.72


Category Years interval Frequency Percent %

Respondents years of experience in

the construction industry

From 5 -10 years 175 63.87

From 11 -15 years 45 16.42

From 16 -20 years 32 11.68

More than 20 years 22 8.03


86

4.3 Key performance indicators

This part aims to accomplish the first objective of this study by identifying and evaluation

of the key performance indicators (KPIs) of public construction projects. For that, in the

second section of the study questionnaire, 13 common KPIs were identified. These KPIs

have a very important role to measure construction industry success. These KPIs were

subjected to different analysis processes and tests (descriptive, t-tests and factor analysis)

in order to formulate the basic conclusions related to the first objective of this study. The

following sections provide detailed descriptions of the analysis results related to these

KPIs analysis results.

4.3.1 Factor analysis results for KPIs

Factor analysis was employed to establish which variables could be measuring aspects of

the same underlying dimensions. Factor analysis is useful for identifying clusters of

related variables and thus ideal for reducing a large number of variables into a more

easily understood framework (Ahadzie et al, 2008). In other words, it identified subsets

of items that correlate highly with each other, which called factors or components. Factor

analysis was conducted for this study using the Principal Component Analysis (PCA).

4.3.1.1 Appropriateness of factor analysis

The data was first assessed for its suitability to the factor analysis application. According

to the following:

Data distribution


factor analysis test beyond the sample collected (Field, 2009; Zaiontz, 2015). The one-

sample Kolmogorov-Smirnov test was used to test that a variable of interest is normally

distributed. Table 3.8 showed that the distributions of KPIs is normally distributed. So

The results had been satisfied with this requirement.

87

Validity of sample size

The validity of factor analysis is dependent on sample size. PCA can be conducted on a

sample that has fewer than 100 respondents, but more than 50 respondents, and the

sample size for this study was 274. On the other hand, the common rule is to suggest that

sample size contains at least 10:15 respondents per item. In other words, sample size

should be at least 10 times the number of items and some even recommend 20 times

(Field, 2009; Zaiontz, 2015). Fortunately, for KPIs, the condition was verified. This field

contains 13 items and the sample size was 274. With 274 respondents and 13 items KPIs,

the ratio of respondents to items are 21: 1, which exceeds the requirement ratio 10:15.

Measures of reliability for the whole items

Cronbach's alpha test was performed on the items in the field of KPIs. The value of

Cronbach’s alpha (Cα) could be anywhere in the range of 0 to 1, where a higher value

denotes the greater internal consistency and vice versa. An alpha of 0.60 or higher is the

minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009). As

shown in Table 4.2, the value of calculated Cα for all items in the field of (KPIs) is 0.89

in the final run which is considered to be marvelous.

Kaiser-Meyer-Olkin (KMO) and Bartlett's test

The Kaiser-Meyer-Olkin (KMO) sampling adequacy test and Bartlett's test of Sphericity

were carried out. The results of these tests are reported in Table 4.2. The value of the

KMO measure of sampling adequacy was 0.84 for first run and 0.83 for the final run

(close to 1), and was considered acceptable and marvelous because it exceeds the

minimum requirement of 0.50 (‘superb’ according to Kaiser, 1974; Field, 2009; Zaiontz,

2015). Moreover, the Bartlett test of sphericity was another indication of the strength of

the relationship among items. The Bartlett test of sphericity was 1123.36 for the first run

and 999.40 for the final run and the associated significance level was 0.00. The

probability value (Sig.) associated with the Bartlett test is less than 0.01, which satisfies

the PCA requirement. This indicated that the correlation matrix was not an identity

matrix and all of the items are correlated (Field, 2009; Zaiontz, 2015). According to the

results of these two tests, the sample data of (KPIs) were appropriated for factor analysis.

88

Table 4. 2: KMO and Bartlett's Test for KPIs

Factor analysis run description

First run Final run

Number of included variables 13 11

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. 0.84 0.83

Bartlett's Test of Sphericity

Approx.

Chi-Square 1123.36 999.40

Df 78.00 55.00

P-value 0.00 0.00

Cronbach's Alpha 0.85 0.89

Validity of Correlation matrix (Correlations between items)

Table 4.3 illustrates the correlation matrix for the 13 KPIs. It is simply a rectangular array

of numbers which gives the correlation coefficients between a single item and every other

item in the investigation (Field, 2009; Zaiontz, 2015). As shown in Table 4.3, the

correlation coefficient between an item and itself is always 1; hence the principal

diagonal of the correlation matrix contains 1s. The correlation coefficients above and

below the principal diagonal are the same. PCA requires that there be some correlations

greater than 0.30 and less than 0.8 between the items included in the analysis. For this set

of items, that many of the correlations in the matrix are strong and greater than 0.30

(Field, 2009; Zaiontz, 2015). Correlations have been satisfied with this requirement so no

items was removed at this step.

89

Table 4. 3:Correlations between items of KPIs

KPI 1 KPI 2 KPI 3 KPI 4 KPI 5 KPI 6 KPI 7 KPI 8 KPI 9 KPI 10 KPI 11 KPI 12 KPI 13

KPI 1 1.00

KPI 2 0.39 1.00

KPI 3 0.12 0.19 1.00

KPI 4 0.30 0.20 0.26 1.00

KPI 5 0.22 0.18 0.20 0.02 1.00

KPI 6 0.12 0.16 0.15 0.12 0.53 1.00

KPI 7 0.16 0.26 0.19 0.12 0.53 0.69 1.00

KPI 8 0.17 0.35 0.17 0.16 0.44 0.51 0.55 1.00

KPI 9 0.15 0.21 0.21 0.15 0.17 0.21 0.25 0.40 1.00

KPI 10 0.12 0.15 0.25 0.26 0.20 0.23 0.33 0.40 0.52 1.00

KPI 11 0.16 0.22 0.33 0.24 0.34 0.28 0.39 0.41 0.36 0.49 1.00

KPI 12 0.13 0.21 0.34 0.18 0.27 0.35 0.40 0.40 0.37 0.42 0.57 1.00

KPI 13 0.15 0.26 0.38 0.16 0.45 0.37 0.42 0.42 0.21 0.37 0.47 0.57 1.00

90

Communalities (common variance)

Communalities represent the proportion of the variance in the original items that is

accounted for by the factor solution. The factor solution should explain at least half of

each original item's variance, so the communality value for each item should be 0.50 or

higher (Field, 2009; Zaiontz, 2015). Two factor analysis runs were held. On iteration 1 of

factor analysis test, the communality for the variable KPI 3 and KPI 4 were less than

0.50. Since they were less than 0.50, the items had to be removed and the PCA was

computed again (new iteration). Table 4.4 shows that all of the communalities for all

remaining items satisfy the minimum requirement of being larger than 0.50, so items

were not excluded any on the basis of low communalities and all of the remaining 11

items (from the original 13 items) of this field (KPIs) were used in this analysis.

Table 4. 4: Communalities of KPIs

No. KPIs First run

communalities

Final run

(second run)

communalities

KPI 1 Actual project costs compared with planned budget. 0.67 0.67

KPI 2 Actual project duration compared with planned

duration. 0.57 0.68

KPI 3 Financial ability for both owner and contractor to

cover project expenditures 0.39 Removed

KPI 4 Project profitability for contractor comparing with

other related projects 0.46 Removed

KPI 5 Project conformity to quality and technical

specifications standards. 0.61 0.76

KPI 6 Project conformity to sustainability criteria. 0.74 0.62

KPI 7 Project conformity to environment protection

standards during execution. 0.72 0.73

KPI 8 Accidents and injures number in the project. 0.56 0.56

KPI 9 Quantity and costs of variation orders. 0.51 0.52

KPI 10 Number and size of disputes, litigations. 0.57 0.52

KPI 11 Contractor and consultant reputation . 0.61 0.64

KPI 12 Project parties satisfaction. 0.61 0.59

KPI 13 Beneficiaries satisfaction on project functionality. 0.55 0.60

91

Total Variance Explained

Using the output from iteration 2, there were three eigenvalues greater than 1. The

eigenvalue criterion stated that each component explained at least one item's worth of the

variability and therefore only components with eigenvalues greater than one should be

retained (Larose, 2006; Field, 2009). The latent root criterion for number of components

to derive would indicate that there were 3 components to be extracted for these items.

Results were tabulated in Table 4.5. The three components solution explained a sum of

the variance with component 1 contributing 39.93%; component 2 contributing 11.62%;

and component 3 contributing 11.17%. All the remaining components are not significant.

The three components were then rotated via varimax (orthogonal) rotation approach. This

does not change the underlying solution, or the relationships among the items. Rather, it

presents the pattern of loadings in a manner that is easier to interpret factors

(components) (Reinard, 2006; Field, 2009; Zaiontz, 2014). The rotated solution revealed

that the three components solution explained a sum of the variance with component 1

contributing 24.92%; component 2 contributing 24.75%; and component 3 contributing

13.05%. These three components explained 62.72% of total variance for the varimax

rotation since it was more than 50%.

Table 4. 5: Total variance Explained of KPIs

Att

rib

ute

Initial Eigenvalues Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

1 4.39 39.93 39.93 4.39 39.93 39.93 2.74 24.92 24.92

2 1.28 11.62 51.55 1.28 11.62 51.55 2.72 24.75 49.67

3 1.23 11.17 62.72 1.23 11.17 62.72 1.44 13.05 62.72

4 0.90 8.14 70.86

5 0.70 6.38 77.24

6 0.55 4.96 82.20

7 0.50 4.51 86.72

8 0.46 4.22 90.94

9 0.43 3.87 94.81

10 0.31 2.80 97.61

11 0.26 2.39 100.00

92

Scree Plot

The scree plot below in Figure 4.2 is a graph of the eigenvalues against all the

components. This graph can also be used to decide on number of components that can be

derived. Although scree plots are very useful, component selection should not be based

on this criterion alone (Field, 2009). The point of interest is where the curve starts to

flatten. It can be seen that the curve begins to flatten between component 3 and 4. Note

also that component 4 has an eigenvalue of less than 1, so only three components have

been retained to be extracted.

Figure 4. 2: Scree Plot for key performance indicators KPI's of projects

Rotated Component Matrix

Table 4.6 shows the factor loadings after rotation of 11 items (from the original 13 items)

on the three factors extracted and rotated. The pattern of factor loadings should be

examined to identify items that have complex structure (complex structure occurs when

one item has high loadings or correlations (0.50 or greater) on more than one

component). If an item has a complex structure, it should be removed from the analysis

(Reinard, 2006; Field, 2009; Zaiontz, 2014). As shown in Table 4.6, factor loading all

items were above 0.50 and all items had simple structure. The items are listed in the order

of size of their factor loadings.

0

1

2

3

4

5

0 1 2 3 4 5 6 7 8 9 10 11

Eig

en

valu

es

Component

93

Naming the components

Once an interpretable pattern of loadings is done, the components should be named

according to their substantive content or core. The components should have conceptually

distinct names and content. Items with higher loadings on a component should play a

more important role in naming the component. Also the common names for components

in previous studies were used in naming them. One of these studies was Ahadzie et al

(2008) study. They used factor analysis and derived four components and they named

them environmental impact, quality, customer satisfaction and overall cost and time. In

this study the three components were named as the following:

Component 1: “Project quality and environment impact” with items: KPI 5, KPI

6, KPI 7 and KPI 8.

Component 2: “Satisfaction and reputation of project parties” with items: KPI 9,

KPI 10, KPI 11, KPI 12 and KPI 13.

Component 3: “Overall cost and time” with items: KPI 1 and KPI 2.

The proposed naming of the extracted components were discussed with experts and

academics to validate the naming of the principal components. Figure 4.3 below

describes the final results of the components extracted, percent of total variance

explained and the eigenvalue of each component.

Figure 4. 3: Final components extracted from factor analysis for KPIs

Key performance indicators KPIs

Total variance: 62.72%

Component 3

Overall cost and time

Eigenvalue: 1.23

Component 2

Satisfaction and reputation of project parties

Eigenvalue: 1.28

Component 1

Project quality and environmental impact

Eigenvalue: 4.39

94

Measures of reliability for each component

Once components have been extracted and rotated, it was necessary to cross checking if

the items in each component formed collectively explain the same measure within target

dimensions (Doloi, 2009). If items truly form the identified component, it is understood

that they should reasonably correlate with one another, but not the perfect correlation

though. Cronbach's alpha (Cα) test was conducted for each component. The higher value

of Cα denotes the greater internal consistency and vice versa. An alpha of 0.60 or higher

is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009).

According to results which were tabulated in Table 4.6, Cα for component 1 is 0.83; Cα

for component 2 is 0.79; and Cα for component 3 is 0.66. They are considered to be

acceptable.

Table 4. 6: Factor loadings for a three-component model of key performance indicators KPI's

Component and factor loading

Fac

tor

load

ing

Eig

enval

ues

Var

iance

%

expla

ined

Cro

nbac

h's

Alp

ha

(Cα

)

Component 1: Project quality and environmental impact

KPI 5 Project conformity to quality and technical

specifications standards.

0.86

4.39 24.92 0.83

KPI 7 Project conformity to environment

protection standards during execution.

0.81

KPI 6 Project conformity to sustainability criteria. 0.77

KPI 8 Accidents and injures number in the

project.

0.57

Component 2: Satisfaction and reputation of project parties

KPI 11 Contractor and consultant reputation . 0.80

1.28 24.75 0.79

KPI 13 Beneficiaries satisfaction on project

functionality.

0.73

KPI 12 Project parties satisfaction. 0.70

KPI 9 Quantity and costs of variation orders. 0.68

KPI 10 Number and size of disputes, litigations. 0.55

Component 3: Overall cost and time

KPI 1 Actual project costs compared with planned

budget.

0.86

1.23 13.05 0.66 KPI 2 Actual project duration compared with

planned duration.

0.81

Kaiser-Meyer-Olkin measure of sampling adequacy = 0.83

Bartlett's test of sphericity: x2= 999.40,df=55,p-value =0.00

Total variance explained (%) = 62.72 %

Total reliability Cornbach’s α = 0.89

Two insignificant factor loadings (< 0.5) are blanked

95

4.3.1.2 The extracted components

The next section will interpret and discuss each of the extracted components as follows:

Component 1: Project quality and environmental impact

First component named "Project quality and environment impact" explains 24.92 % of

the total variance and contains four items. The majority of items had relatively high

factor loadings (≥ 0.57). The four items are as follows:

1. Project conformity to quality and technical specifications standards KPI 5, with

factor loading=0.86

2. Project conformity to environment protection standards during execution KPI 7, with

factor loading=0.81

3. Project conformity to sustainability criteria KPI 6, with factor loading =0.77

4. Accidents and injures number in the project KPI 8, with factor loading=0.57

Results revealed that the four items that loaded on this component are related to quality

and environment issues. This grouping would appear to be logical and the component can

be termed “Project quality and environmental impact”. According to factor analysis

theory, the first component accounts for the largest part of total variance of the cases.

Hence, it implies that quality and environment impact considered as the most important

KPIs in construction companies in Palestine. Previous study in Gaza strip held by

Enshassi et al (2009c) indicated that quality and safety in construction industry still

suffers from ignorance and lack of supervision and accident rate on construction projects

is very high. In line with this study in Taiwan Yang et al (2011) found that quality was

the highest loaded component accounted variance. Also in Malaysia Al-Tmeemy (2011)

results showed that quality was the second high loaded component. In Ghana Ahadzie et

al (2008) reported that quality is the third high loaded component between four

components derived on their study.

Results also indicated that KPI “Accidents and injures number in the project” was the

lowest loading KPIs of this component with factor loading of 0.57. This result is not

strange since the culture of safety is still weak in Palestine. Recording injuries and

accidents and number in the project is KPIs not common in Palestinian construction

96

project. Same conclusion was indicated by Enshassi et al (2009c) who found that safety

and quality in Gaza Strip is not widely recognized as inherent characteristic of success for

construction projects. However, public construction projects contracts contain provisions

about safety practices but construction parties do not follow them in reality. Enshassi et

al (2008) found that in Palestine, the key players in the construction industry do not adopt

safe working practices for several reasons including that: employers and employees are

unwilling to spend or invest in safety measures, equipment or practices; employees

cannot afford to purchase their own safety equipment and fear they might be penalized if

they request personal protective equipment (PPE) from their employers. Additionally,

contractors are not aware of their legal responsibilities in relation to health and safety

issues. Hughes et al (2004) considered safety measurements was a major competitive

component. In contract to this study result in Ghana Ahadzie et al (2008) stated that

overall health and safety measures component loading was 0.76 and they consider

environmental-safety protection has now become a worldwide challenge facing the

construction industry. Also in contract to this study result Ali et al (2013) ranked safety

measurements as seventh important one among 47 performance indicators.

Component 2: Satisfaction and reputation of project parties

The second component, (Satisfaction of project parties), accounted for 24.75% of the

total variance and contained 5 items. Items had relatively high factor loadings (0.55).

The five items were:

1. Contractor and consultant reputation KPI 11, with factor loading=0.80.

2. Beneficiaries satisfaction on project functionality KPI 13, with factor loading=0.73

3. Project parties satisfaction KPI 12, with factor loading=0.70.

4. Quantity and costs of variation orders KPI 9, with factor loading=0.6.

5. Number and size of disputes, litigations KPI 10, with factor loading=0.55.

The second component was labelled as “Satisfaction and reputation of project parties”,

and comprise 5 items. This component is labelled in accordance with the characteristics

of the set of individual items loaded on it. Throughout this research, it is encouraging to

see that the respondents having a positive attitude towards satisfaction and reputation of

97

project parties KPIs and its related aspects. The importance of this component in

Palestine came from the main reason of implementing public construction projects. The

main reason was to serve people by construct housing buildings, governmental buildings,

roads, hospitals or schools. So parties satisfaction will be important KPIs for the success

of these projects. This result supported Ahadzie et al (2008) study in Ghana which

showed that satisfaction is the second component accounted variance between four

components of KPIs. They stated that Satisfied customers as the evidence suggests are

the backbone of the house building industry in Malaysia. Also in Saudi Arabia Ali et al

(2013) found that satisfaction is the 6th

important KPIs from 47 one. Ali et al (2013)

indicated that there was no doubt that construction organizations depend on their

customers, therefore they should understand and meet their needs and expectations. Also

they stated that satisfaction of customers and other interested parties is necessary for the

success of the project and organization. In other words, increasing the satisfaction of

customers and stakeholders through effective goal deployment, cost reduction,

productivity and process improvement has proved to be essential for organizations to stay

in operation.

Results as shown in Table 4.6 indicated that KPI “Contractor and consultant reputation”

was the highest factor loading item in component 2 with 0.80 factor loading. This item

indicated that the company's reputation can be impressiveness measure of project success

to contractors and consultants. Reputation depends on whether the consultant or

contractor deliver their projects on time, cost, within quality standards and with

satisfaction of project parties. In Palestine construction projects consultant or contractor

reputation is important and awarding of projects depend mostly on low bidding and then

on the good reputation of consultant and contractor. In line with this study in Malaysia

Al-Tmeemy (2011) found that reputation is the third component affect company success

and they found that there is a relationship between market share and reputation by

building up a strong reputation would help a company to gain market share. Also in line

with this study in Israel Dvir et al (2003) showed the that reputation was the second item

which affect contractor benefit.

98

Results also indicated that KPI “Number and size of disputes, litigations” was the lowest

item of factor loading of 0.55. Because of the discrepancy in goals and expectations,

conflicting issues are commonly observed among parties which lead to disputes during

the course of the project. Also conditions such as delay in the payments for completed

work, frequent owner interference, changing requirements, lack of communication

between the various parties, problems with neighbors, and unforeseen site conditions give

rise to disputes between the various parties. The disputes, if not resolved amicably, can

lead to arbitration or litigation. In Palestine disputes and litigations take a long time due

to the fog in laws and regulations since they are outdated, contradicted and uncompleted.

So project parties directed toward solving their disputes by themselves and this make this

KPI to be less important. In USA li et al (2012) found that high level of uncertainty in the

transaction environment file numerous claims, deal with substantial amounts of extra

work, and in general have antagonistic relationships with owners that sometimes end up

in disagreement, conflict and litigation. In contract to this result in Hong Kong Chan et al

(2004a) stated that establishment and communication of conflict resolution strategy was

the highest attribute accounted variance in the second component of his study.

Component 3: Overall cost and time

The third component, (Overall cost and time), accounted for 13.05% of the total variance

and contains two items. The two items had relatively high factor loadings (0.81). The

two items are as follows:

1. Actual project costs compared with planned budget KPI 1, with factor loading=0.86.

2. Actual project duration compared with planned duration KPI 2, with factor

loading=0.81.

The third component was labelled as “Overall cost and time”, and comprises 2 KPIs. This

component was labelled in accordance with the characteristics of the set of individual

items loaded on it. This component measures the efficiency of project execution and

ensures that the project is done right. The issue of shortening construction time, reducing

cost and improving production performance has engaged all project parties on Palestine.

Cost and time are very important KPIs on Palestinian public construction projects since

99

projects have limited budget from funders. However delays and cost overruns are still

major challenges founding in construction projects in Palestine. In Gaza Enshassi et al

(2009b) concluded that the main causes of time delays included strikes and border

closures, material-related factors, lack of materials in markets, and delays in materials

delivery to the site. Additionally, the main causes for cost overruns included price

fluctuations of construction materials, contractor delays in material and equipment

delivery, and inflation. In line with this study results in Annapolis Hughes et al (2004)

considered cost and schedule as very important measurements of project success in the

construction industry. In Ghana also Ahadzie et al (2008) results showed that overall cost

and time was the fourth high loaded component between four components derived on

their study with 0.827 factor loading for overall project costs KPI and 0.765 for overall

project duration. Also in Malaysia Al-Tmeemy (2011) found that overall cost KPI had the

highest factor loading of 0.777 and overall project time KPI had the third factor loading

of 0.701.

4.3.2 Ranking of KPIs of construction projects

In order to evaluate which the degree of importance of KPIs in Palestinian public

construction projects descriptive statistics was used. RII was calculated to weight each

KPI (from KPI 1 to KPI 13) according to the numerical scores obtained from the

questionnaire responses and results have been ranked from the highest degree (The most

important KPI) to the least degree (The most vulnerable KPI). Table 4.7 shows RIIs and

ranks of KPIs, respectively. The numbers in the “rank” column represent the sequential

ranking. It worth mentioning that ranking of KPIs was based on the highest mean, RII,

and the lowest SD. If some items have similar means as in the case of (KPI 1 and KPI 2)

ranking will be depended on RIIs and the lowest SD. More precisely, although KPI 1 and

KPI 2 have the same mean, but KPI 1 was ranked higher than KPI 2 because it has the

higher RII and the lower SD. Items were categorized with ratings from 89.01 % to 71.81

% (Figure 4.4).

100

Table 4. 7: Means and test values for “key performance indicators KPI's of projects”- Degree of

importance

No. KPI of projects Mean S.D RII Test

value

P-value

(Sig.)

Total

rank

KPI 1 Project conformity to quality and

technical specifications standards.

4.47 0.72 89.37 33.40 0.00* 1

KPI 2 Actual project costs compared with

planned budget.

4.45 0.63 89.05 38.25 0.00* 2

KPI 3 Actual project duration compared with

planned duration.

4.45 0.72 89.01 33.22 0.00* 3

KPI 4 Financial ability for both owner and

contractor to cover project expenditures

4.36 0.73 87.25 31.04 0.00* 4

KPI 5 Accidents and injures number in the

project.

4.21 0.84 84.25 23.99 0.00* 5

KPI 6 Beneficiaries satisfaction on project

functionality.

4.17 0.90 83.31 21.26 0.00* 6

KPI 7 Project conformity to sustainability

criteria.

4.12 0.84 82.35 21.89 0.00* 7

KPI 8 Project parties satisfaction. 4.09 0.90 81.78 19.97 0.00* 8

KPI 9 Contractor and consultant reputation. 4.05 0.92 80.97 18.66 0.00* 9

KPI 10 Quantity and costs of variation orders. 3.97 0.89 79.41 17.90 0.000* 10

KPI 11 Project conformity to environment


3.90 0.98 78.09 15.18 0.00* 11

KPI 12 Project profitability for contractor

comparing with other related projects

3.61 0.87 72.18 11.57 0.00* 12

KPI 13 Number and size of disputes, litigations. 3.59 0.93 71.81 10.45 0.00* 13

Overall 4.11 0.50 82.17 36.84 0.00*

101

Figure 4. 4: RII of KPI's (KPI 1 to KPI 13)

The findings indicated that “Project conformity to quality and technical specifications

standards” was the highest important KPI in Palestinian public construction projects. It

has been ranked as the first position with mean = 4.47, RII = 89.37%, Test-value = 33.40

and P-value = 0.00 according to overall respondents. Quality can be defined as the degree

to which the general conditions promote meeting of the project’s established

requirements of materials and workmanship Lam et al (2007). Respondents agreed that

project conformity to quality and technical specifications standards KPI was more

important than cost and time. This result may due to the fact of that donors who fund the

public construction projects give high important to the quality more than any other

consideration. In line with this study in Saudi Arabia Ali et al (2013) found that quality

is the second highest important KPI with RII equal 85.8%. Also not far result in Australia

Yeung et al (2009) ranked quality as third important KPI. In Hong Kong Lam et al

(2007) found that there were four important KPI to determine the success of design and

built projects and quality was the third important KPI.

Results indicated that “Actual project costs compared with planned budget” (mean=4.45,

RII=89.05%, Test-value = 38.25, and P-value=0.000), ranked as the second important

KPI in Palestinian construction industry. Cost is defined as the degree to which the

general conditions promote the completion of a project within the estimated budget (Chan

89.37 89.05

89.01

87.25

84.25

83.31

82.35 81.78

80.97

79.41

78.09

72.18

71.81

0

20

40

60

80

100KPI 1

KPI 2

KPI 3

KPI 4

KPI 5

KPI 6

KPI 7 KPI 8

KPI 9

KPI 10

KPI 11

KPI 12

KPI 13

102

et al, 2002). Cost as KPI is still very important in Palestine due to the limited budget of

projects since most of them are funded by donors. This study result in line with Yeung et

al (2009) study in Australia which ranked cost as the second important KPI. Also it is the

same as in Hong Kong Lam et al (2007) found that there were four important KPI to

determine the success of design and built projects and cost was the most important one.

Results also revealed that “Actual project duration compared with planned duration”

(mean=4.45, RII= 89.01%, Test-value = 33.22, and P-value=0.000) was ranked as the

third important KPI. Time is defined as the degree to which the general conditions

promote the completion of a project within the allocated duration (Chan et al, 2002). In

Palestine most of public projects are funded by donors as mentioned earlier. The donors

give limited time to implement the projects due to the uncertainty of political conditions

in Palestine like annually wars. Although most of Palestinian construction projects

suffered from delays for many reasons such as referral bids to the lowest price, incorrect

bids pricing, lack of sufficient cash for project implementation and irregular owner cash

follow (Albatsh, 2015). Similar to this study results in Australia Yeung et al (2009)

ranked time as the 6th

important KPI. In line with this study in Hong Kong Lam et al

(2007) found that there were four important KPI to determine the success of design and

built projects and time was the second important KPI.

The results showed that the most important KPIs were quality, time and cost which

means that in Palestine construction industry the highest important KPIs were the

traditional basic ones. This result is in line with most previous studies such as in Hong

Kong ( Chan et al, 2002; Chan and Chan, 2004 and Chan and Chan 2004), Ghana

(Ahadzie et al, 2008), Republic of Korea (Cho et al, 2009), Malaysia (Al-Tmeemy et al,

2011) , Saudi Arabia (Ali et al 2013) and Brazil (Berssaneti and Carvalho, 2014) which

consider quality, time and cost as the most important KPIs. This result was different than

other studies which consider satisfaction as the highest important indicator followed by

the iron triangle indicators (cost, quality and time) such studies as in UK (Bryde and

Robinson, 2005), Hong Kong (Lam et al, 2007), and in Australia (Yeung et al, 2009). On

this study respondents gave satisfaction moderate important rank may be due to the bad

103

economic situation and siege which cause inflation and high rates of unemployment and

that give cost and time more attention than satisfaction.

4.3.3 Public construction projects KPIs evaluation (actual versus planned

performance)

The main objective of this field is to evaluate the situation of Palestinian public

construction projects according to the KPIs. Respondents asked to evaluate the actual

KPIs in comparative to planned. The analysis of this part will give general view for

Palestinian public construction projects performance. As a result the problems in

performance will be known. Descriptive analysis was used to obtain the results of this

part. From Table 4.8 the means of KPI "Actual project duration compared with planned

duration", “Actual project costs compared with planned budget” and "Quantity and costs

of variation orders" were 3.85, 3.67 and 3.51 respectively with P-value=0.000 which

were smaller than the level of significance 0.05. And the signs of the test were positive,

so the mean of those indicators was significantly greater than the hypothesized value 3.

Which means Palestinian construction projects suffer from cost overrun and delay and the

quantity and costs of variation orders are high. Since quantity and costs of variation

orders are high this may be the main cause of cost overrun and delay. Other possible

causes of cost overrun and delay were blockade, material shortage in types and quantities

and the limited budget for the Palestinian public construction projects which is basically

depend on grants on. Variation orders are high because of projects multiple owners who

have different interests. In Malaysia Shehu et al (2014) concluded that more than half of

Malaysian construction projects (55%) experienced cost overruns. Also in Malaysia

Young and Mustaffa (2012) indicated that delays, cost overruns and disputes are common

challenges faced by the industry.

Also from Table 4.8 the means of KPI "Beneficiaries satisfaction on project

functionality", "Project conformity to quality and technical specifications standards",

"Project parties satisfaction" and "Financial ability for both owner and contractor to

cover project expenditures" were 3.70, 3.64, 3.61 and 3.55 respectively with P-

value=0.000 which were smaller than the level of significance 0.05. And the signs of the

test were positive, so the mean of this indicators was significantly greater than the

104

hypothesized value 3. This means Palestinian construction projects have good evaluation

for projects quality, satisfaction and ability to cover project expenditures. The

explanation of this result was that public construction projects on Palestine raise based on

people's needs and there is a big shortage in types and numbers of these projects in

comparing with needs. So when the projects implemented parties will be satisfied

regardless the level of quality. Another justification is that mostly the owners of

Palestinian construction public projects are the government which funded these projects

from donors so the parties will be less worried on the ability to finance these projects and

will perceived positively according the evaluation.

Additionally from Table 4.8 the mean of KPI "Accidents and injures number in the

project" is 2.85 with P-value=0.000 which was smaller than the level of significance

0.05. And the signs of the test was negative, so the mean of this indicators was

significantly smaller than the hypothesized value 3. That means Palestinian construction

projects do not suffer from high number of injuries and accidents. In reality it seems to be

high evaluation and may be the basic reason of this evaluation was that there is poor

documentation for injuries and accidents since the safety culture level is still limited in

Palestine.

105

Table 4. 8: Means and test values for “key performance indicators KPI's of projects”-

performance evaluation of organization projects

No. KPI of projects Mean S.D RII Test

value

P-

value

(Sig.)

1 Financial ability for both owner and contractor to

cover project expenditures 3.55 0.87 70.94 10.19 0.000*

2 Project conformity to quality and technical

specifications standards. 3.64 0.92 72.88 11.32 0.000*

3 Project conformity to sustainability criteria. 3.43 0.98 68.57 7.15 0.000*

4 Project conformity to environment protection

standards during execution. 3.30 0.97 65.93 4.93 0.000*

5 Actual project costs compared with planned budget 3.67 0.80 73.36 13.73 0.000*

6 Actual project duration compared with planned

duration 3.85 0.78 77.01 17.77 0.000*

7 Accidents and injures number in the project. 2.85 1.23 57.09 -1.90 0.029*

8 Number and size of disputes, litigations. 3.02 1.13 60.45 0.33 0.745

9 Project profitability for contractor comparing with

other related projects 3.19 0.81 63.73 3.71 0.000*

10 Quantity and costs of variation orders. 3.51 0.91 70.11 9.00 0.000*

11 Contractor and consultant reputation. 3.34 1.05 66.74 5.21 0.000*

12 Project parties satisfaction. 3.61 0.81 72.21 12.17 0.000*

13 Beneficiaries satisfaction on project functionality. 3.70 0.92 73.96 12.40 0.000*

Overall 3.43 0.53 68.70 13.58 0.000*

* The mean is significantly different from 3

106

4.4 Critical success factors CSFs

This part aims to accomplish the second objective of this study by investigating the

critical success factors CSFs affecting the public construction projects. For that, in the

third section of the study questionnaire, 81 common CSFs were identified. These CSFs

were subjected to different analysis processes and tests (descriptive, t-tests and factor

analysis) in order to formulate the basic conclusions related to the second objective of

this study. The following sections provide detailed descriptions of the analysis results

related to these CSFs analysis results.

4.4.1 Factor analysis results for CSFs

This part aims to accomplish the second objective of this study by investigating the CSFs

affecting the public construction projects. The study of these factors gives good insight to

policy makers on how to improve their practices during project life cycle in order to

guarantee project success. For that, in this section of the study questionnaire, 81 common

CSFs were identified. These factors were subjected to different analysis processes and

tests (descriptive, t-tests and factor analysis) in order to formulate the basic conclusions

related to the second objective of this study. The following sections provide detailed

descriptions of the analysis results related to these CSFs analysis results.

4.4.1.1 CSFs related to conceptualizing and preparation phase

In this phase of data analysis process, factor analysis was employed to reduce a large

number of items (CSFs) to a smaller set of underlying components that summarize the

essential information contained in the items. Using SPSS 22, Principle Component

Analysis (PCA) with Varimax rotation were performed to set up which items could

capture the aspects of same dimension of the 12 CSFs and examine the underlying

structure or structure of interrelationships among the CSFs. In order to perform the factor

analysis for used items, all the appropriate checks and procedures were fulfilled.

4.4.1.1.1 Appropriateness of factor analysis


to the following:

107

Data distribution



sample Kolmogorov-Smirnov test was used to test that a item of interest is normally

distributed. Table 3.8 showed that the distributions of CSFs which related to

conceptualizing and preparation phase is normally distributed. So the results had been

satisfied with this requirement.







(Field, 2009; Zaiontz, 2015). Fortunately, for CSFs of conceptualizing and preparation

phase, the condition was verified. This field contains 12 items and the sample size was

274. With 274 respondents and 12 items CSFs, the ratio of respondents to items are 22.8:

1, which exceeds the requirement ratio 10:15.


Cronbach's alpha test was performed on the items in CSFs field of conceptualizing and

preparation phase. The value of Cronbach’s alpha (Cα) could be anywhere in the range of

0 to 1, where a higher value denotes the greater internal consistency and vice versa. An

alpha of 0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or

higher (Field, 2009). As shown in Table 4.9, the value of calculated Cα for all items in

the field CSFs of conceptualizing and preparation phase is 0.86 for the final run which

considered to be marvelous.

108













results of these two tests, the sample data of (CSFs in conceptualizing and preparation

phase) were appropriated for factor analysis.

Table 4. 9: KMO and Bartlett's Test for CSFs of conceptualizing and preparation phase


First run Second run

(Final run)

Number of included items 12 8

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy. 0.79 0.73


Approx. Chi-

Square 822.96 556.82

Df 66 28

P-value < 0.001 .00



Table 4.10 illustrates the correlation matrix for the 12 CSFs. It is simply a rectangular

array of numbers which gives the correlation coefficients between a single item and every

other item in the investigation (Field, 2009; Zaiontz, 2015). As shown in Table 4.10, the





109


(Field, 2009; Zaiontz, 2015). Correlations have been satisfied with this requirement.

Table 4. 10: Correlations between items of CSFs of conceptualizing and preparation phase

CSF

CSF

1

CSF

2

CSF

3

CSF

4

CSF

5

CSF

6

CSF

7

CSF

8

CSF

9

CSF

10

CSF

11

CSF

12

CSF 1 1.00

CSF 2 0.39 1.00

CSF 3 0.24 0.31 1.00

CSF 4 0.12 0.27 0.27 1.00

CSF 5 0.25 0.26 0.21 0.64 1.00

CSF 6 0.24 0.30 0.30 0.34 0.41 1.00

CSF 7 0.10 0.21 0.18 0.13 0.27 0.32 1.00

CSF 8 0.32 0.25 0.21 0.16 0.20 0.29 0.22 1.00

CSF 9 0.23 0.26 0.12 0.17 0.27 0.22 0.13 0.38 1.00

CSF 10 0.16 0.26 0.14 0.22 0.33 0.30 0.35 0.43 0.48 1.00

CSF 11 0.06 0.14 0.16 0.22 0.27 0.17 0.30 0.33 0.41 0.62 1.00

CSF 12 -0.01 0.18 0.06 0.22 0.23 0.23 0.21 0.28 0.29 0.50 0.43 1.00

110




each original item's variance, so the communality value for each item should be 0.50 or

higher (Field, 2009; Zaiontz, 2015). On iteration 1 of factor analysis test, the

communality for the item CSF 3, CSF 6 and CSF 7 were less than 0.50. Since they were

less than 0.50, the items had to be removed and the PCA was computed again (new

iteration). Table 4.11 shows that all of the communalities for all remaining items satisfy

the minimum requirement of being larger than 0.50.

Table 4. 11: Communalities of CSFs of conceptualizing and preparation phase

Item. CSFs First run

communalities

Second run

(Final run)

communalities

CSF 1 Studying the feasibility, cost and priority of the

project for the society. 0.64 0.74

CSF 2 Formalizing deterministic, clear and realistic

objectives for the project and sharing project

relatives in.

0.50 0.59

CSF 3 Determining project size represented by its required

budget. 0.37 Removed

CSF 4 Specifying the project type whether it is new,

maintenance, completion for existing one or rubble

removal project)

0.71 0.84

CSF 5 Determining the construction project nature

(housing, infrastructure, public building, …) 0.69 0.78

CSF 6 Specifying the project designing and execution

complexity comparing with previous related

projects.

0.46 Removed

CSF 7 Endeavoring to decrease the political instability

effect on the project. 0.26 Removed

CSF 8 Studying the level of acceptance of local community

to execute the project in their location. 0.56 Removed

CSF 9 Studying project tendency to accidents and hazards. 0.50 0.55

CSF 10 Existence of experienced and understandable client

(his representative) on project nature and clear

priorities for project execution.

0.74 0.74

CSF 11 Giving suitable and enough time for planning and

designing phase. 0.67 0.69

CSF 12 Recruiting and involving consultant in all project

activities and phases. 0.52 0.56

111












presents the pattern of loadings in a manner that is easier to interpret components (Field,

2009; Zaiontz, 2015). The rotated solution revealed that the three components solution

explained a sum of the variance with component 1 contributing 29.17%; component 2

contributing 20.50%; and component 3 contributing 18.91%. These three components

explained 68.58% of total variance for the varimax rotation which is acceptable since it

was more than 50%.

Table 4. 12: Total variance Explained of CSFs of conceptualizing and preparation phase

Att

rib

ute


Loadings


Loadings

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

1 3.01 37.62 37.62 3.01 37.62 37.62 2.33 29.17 29.17

2 1.37 17.17 54.79 1.37 17.17 54.79 1.64 20.50 49.67

3 1.10 13.79 68.58 1.10 13.79 68.58 1.51 18.91 68.58

4 0.71 8.87 77.45

5 0.58 7.30 84.75

6 0.52 6.51 91.26

7 0.37 4.64 95.90

8 0.33 4.10 100.00

112

Scree Plot


components for final run of analysis. This graph can also be used to decide on number of

components that can be derived. Although scree plots are very useful, component

selection should not be based on this criterion alone (Field, 2009). The point of interest is

where the curve starts to flatten. It can be seen that the curve begins to flatten between

components 3 and 4. Note also that component 4 has an eigenvalue of less than 1, so only

three components have been retained to be extracted.

Figure 4. 5: Scree Plot for CSFs of conceptualizing and preparation phase

Rotated Component (Factor) Matrix

Table 4.14 shows the factor loadings after rotation of 8 items (from the original 12 items)

on the three factors extracted and rotated. The pattern of factor loadings should be

examined to identify items that have complex structure (complex structure occurs when

one item has high loadings or correlations (0.50 or greater) on more than one component.

If an item has a complex structure, it should be removed from the analysis (Reinard,

2006; Field, 2009; Zaiontz, 2015). According to that, it was necessary to remove item

CSF 8 because it demonstrated complex structure. It was loaded under two components

(component 1 and component 3) in the same time with a factor loading of 0.51 under

component 1 and a factor loading of 0.55 under component 3. As shown in Table 4.14,

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

0 1 2 3 4 5 6 7 8

Eig

en

valu

es

Component

113

for each remaining items factor loading were above 0.50 and all items had simple

structure. The items are listed in the order of size of their factor loadings.

As a conclusion of analysis 4 Items were removed and 8 items remaining as summarized

in Table 4.13.

Table 4. 13: Summary of remaining and removed CSFs in conceptualizing and preparation

phase as a result of factor analysis runs

Item. CSFs Result

CSF 1 Project feasibility and priority for the society. Remaining

CSF 2 Deterministic, clear, sharable and realistic project

objectives Remaining

CSF 3 Predetermining of project size and budget. Removed since

communalities less than 0.5

CSF 4 Project type (new, maintenance, completion for

existing one or rubble removal project). Remaining

CSF 5 Determining the construction project nature (housing,

infrastructure, public building, …) Remaining

CSF 6 Project complexity and uniqueness. Removed since


CSF 7 Recognizing political influence on the project. Removed since


CSF 8 Local community acceptance to execute the project in

their location.

Removed since it have

complex structure

CSF 9 Preparing safety and health plans. Remaining

CSF 10 Client understanding of project nature priorities and

needs Remaining

CSF 11 Granting suitable and enough time for project

planning and designing Remaining

CSF 12 Consultant recruitment and involvement in all project

activities. Remaining

Naming the Components

Once an interpretable pattern of loadings is done, the factors or components should be

named according to their substantive content or core. The components should have

conceptually distinct names and content. Items with higher loadings on a component

should play a more important role in naming the component. Also the common names for

114

components in previous studies were used in naming the components. In this study the

three components (factors) were named as the following:

Component 1: “Client actions and capabilities” with items: CSF 10, CSF 11,

CSF 12 and CSF 9.

Component 2: “Project characteristics” with items: CSF 4 and CSF 5.

Component 3: “Project feasibility and goals” with items: CSF 1 and CSF 2.



describes the final results of the components extracted, percent of total explained

variance and eigenvalue of each component..

Figure 4. 6: Final components extracted from factor analysis for CSFs in conceptualizing and

preparation phase

Measures of reliability for each factor (component)





Conceptualizing and preparation phase


Component 3

Project feasibility and goals

Eigenvalue: 1.10

Component 2

Project characteristics

Eigenvalue: 1.37

Component 1

Client actions and capabilities

Eigenvalue: 3.01

115



is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009;

Weiers, 2011; Garson, 2013). According to results which were tabulated in Table 4.14,

Cα for component 1 is 0.77; Cα for component 2 is 0.76; and Cα for component 3 is 0.67.

They are considered to be acceptable.

Table 4. 14: Factor loadings for a three-component model CSFs of conceptualizing and

preparation phase


Fac

tor

load

ing

Eig

enval

ues

Var

ian

ce %

exp

lain

ed

Cro

nb

ach

's

Alp

ha

(Cα

)

Component 1: Client actions and capabilities

CSF 10 Client understanding of project nature

priorities and needs. 0.83

3.01 29.17 0.77 CSF 11 Granting suitable and enough time for

project planning and designing. 0.82

CSF 12 Consultant recruitment and involvement

in all project activities. 0.72

CSF 9 Preparing safety and health plans. 0.62

Component 2: Project characteristics

CSF 4 Project type (new, maintenance, completion

for existing one or rubble removal project). 0.91

1.37 20.50 0.76 CSF 5 Determining the construction project nature

(housing, infrastructure, public building,

…)

0.84

Component 3: Project feasibility and goals

CSF 1 Project feasibility and priority for the

society. 0.86

1.10 18.91 0.67 CSF 2 Deterministic, clear, sharable and realistic

project objectives 0.72





Four insignificant factor loadings (< 0.5) are blanked

4.4.2 The extracted components


116

Component 1: Client actions and capabilities

First component named "Client actions and capabilities" explains 29.17 % of the total

variance and contains four items. The majority of items had relatively high factor

loadings (≥ 0.62). The four items are as follows:

1. Client understanding of project nature priorities and needs CSF 10, with factor

loading=0.83.

2. Granting Suitable and enough time for project planning and designing CSF 11, with

factor loading =0.82.

3. Recruiting and involving consultant in all project activities and phases CSF 12, with

factor loading=0.72.

4. Studying project tendency to accidents and hazards CSF 9, with factor loading=0.62.

Results from Table 4.14 indicated that CSF “Client understanding of project nature

priorities and needs” was the highest factor loading item of component 1 of CSFs in

conceptualizing and preparation phase with factor loading of 0.83. This CSF indicated

that in Palestine client plays an important role in the construction industry. When clients

understand what they need from the proposed project this will consultants and contractors

to understand the project. In addition client experience in similar in project nature is very

important because this will facilitate the management of the project and defining its

priorities easily. In Palestine the client usually governmental organization, UNRWA or

UNDP who's usually the one who write the proposal of the public construction project.

Those organizations mostly know what are they want from the proposed project and its

priorities since they have good experience in similar projects. Different studies results

considering this CSF as one of most important CSFs but not the most important one such

as in Thailand, where Toor et al (2008) stated that this CSF as one of important CSFs.

Also in Malaysia young et al (2014) ranked this CSF as very critical factor. Another

study also in Lithuania Gudienė et al (2013) indicated that the success of construction

projects depends on client’s experience as one of the most important CSFs.

117

The next CSF was “Granting Suitable and enough time for project planning and

designing” which had the second highest factor loading of 0.82. This CSF indicated that

when giving enough time to design and planning phase this will lead to success project in

terms of performance. Enough time giving more concentration for the team in their work

which can reduce variations, mistakes and costs. In Palestine this CSF is important since

it can be traced to the high level of uncertainty in the project environment and thus more

accurate planning is required. Also most public construction projects in Palestine have

multi clients such as government, donor, NGO's and each one have his ideas on designing

and planning so consultant should have enough time in order to satisfy all clients needs as

possible. Most previous studies did not mention this CSF directly. One of studies in

South Korea conducted by Park (2009) ranked this CSF as 10th

most important CSF from

client view point, 8th

from contractor viewpoint and 1st from subcontractor viewpoint.

Component 2: Project characteristics

Second component named "Project characteristics" explains 20.50% of the total variance

and contains two items. The items had relatively high factor loadings (≥ 0.84). The two

items are as follows:

1. Project type (new, maintenance, completion for existing one or rubble removal

project) CSF 4, with factor loading=0.91.

2. Determining the construction project nature (housing, infrastructure, public building,

…) CSF 5, with factor loading =0.84.

Results revealed that the CSF “Project type (new, maintenance, completion for existing

one or rubble removal project)” had high factor loading of 0.91. This CSF indicated that

determining project issues such as choosing project teams, defining the needed project

budget, time, design features, materials and quality levels depend on project type. In

Palestine each project type has his specific consultants, contractors and donors. Not all

donors fund maintenance projects or rubble removal projects also not all donors fund

roads project for examples due to political reasons. This give high important to specify

the type of project in the conceptualizing and preparation phase in order to submit the

project to donors and to hire consultants. In line with this study in Korea Cho et al (2009)

118

found that project type was very important project characteristics that affect the level of

project performance required by owner in the planning phase, and is thus expected to

help facilitate the decision making process in the early planning phase of a project. Also

in Taiwan Yang et al (2011) found that project type has a moderating effect on the

relationship between teamwork dimensions and overall project success. In Malaysia

Shehu et al (2014) observation indicated that project type affect cost variance and they

concluded that refurbishment projects tends to negative cost variance when compared to

new build.

Component 3: Project feasibility and goals

Third component named "Project feasibility and goals" explains 18.91% of the total

variance and contains two items. The items had relatively high factor loadings (≥ 0.72).

The two items are as follows:

1. Project feasibility and priority for the society CSF 1, with factor loading=0.86.

2. Deterministic, clear, sharable and realistic project objectives CSF 2, with factor

loading =0.72.

Results from Table 4.14 revealed that CSF “Project feasibility and priority for the

society” was the highest factor loading of this component with factor loading of 0.86.

This indicated this CSF is very important in public construction project and it should be

cleared in conceptualizing and preparation phase. In Palestine most of public construction

projects are funded by donors. So it is very important to study the feasibility of projects

and whether it can be executed especially in Gaza strip since it suffer from blockade and

shortage in construction materials and equipment's. Also cost is very important in

feasibility study since the budget of the project will be determined in this phase and the

grant amount will be limited to it and it is very hard to have big variation after the fund

approved. Donors and government also should take in consider to execute the top priority

projects that will benefit the society as much as possible. Some studies are in line with

this result like in Taiwan Ng et al (2012) indicated that the support of the community

should be considered as an important success factor. Also in China Zhao et al (2013)

indicated that public perception, awareness, attitude, behavior and acceptability should be

119

taken into consideration seriously at the feasibility phase. Zhao et al (2013) concluded

that since project funds confirmed basically on the feasibility study outputs so the project

developer and the potential investors have to go through the tedious procedure prior to

the final approval and confirmation of the project from donors.

The second CSF in this component is “Deterministic, clear, sharable and realistic project

objectives” and it has factor loading of 0.72. In Palestine commitment to project is

basically depends on commitment to clear and realistic objectives. Thus clear and

realistic objectives helps project team to focus on target and lead to eliminate the non-

value added activities. Respondents in this study give moderate importance this CSF. In

line to this study in Vietnam Nguyen et al (2004) ranked this CSF as the first attribute in

commitment component. Similar results in India Iyer and Jha (2006) indicated that

inadequate project formulation in the beginning was the most critical factor in owner

incompetence component which lead to project failure. And in Saudi Arabia Alhaadir and

Panuwatwanich (2011) found that clear and reasonable project objectives was the second

weighted CSF.

4.4.2.1 CSFs related to planning and designing phase


number of items (CSFs) to a smaller set of underlying components that summarize the








to the following:

120

Data distribution




distributed. Table 3.8 showed that the distributions of CSFs which related to planning and

designing phase is normally distributed. So the results had been satisfied with this

requirement.







(Field, 2009; Zaiontz, 2015). Fortunately, for CSFs of planning and designing phase, the

condition was verified. This field contains 19 items and the sample size was 274. With

274 respondents and 19 items CSFs, the ratio of respondents to items are 14.4:1, which

exceeds the requirement ratio 10:15.


Cronbach's alpha test was performed on the items in CSFs of planning and designing

phase. The value of Cronbach’s alpha (Cα) could be anywhere in the range of 0 to 1,

where a higher value denotes the greater internal consistency and vice versa. An alpha of

0.60 or higher is the minimum acceptable level. Preferably, alpha will be 0.70 or higher

(Field, 2009). As shown in Table 4.15, the value of calculated Cα for all items in the field

CSFs of planning and designing phase for the final run was 0.89 which considered to be

marvelous.

121













results of these two tests, the sample data of (CSFs in planning and designing phase) were

appropriated for factor analysis.

Table 4. 15: KMO and Bartlett's Test for CSFs of planning and designing phase

Factor analysis run

description

First run Fourth run

(Final run)



Sampling Adequacy. 0.93 0.90


Approx. Chi-

Square 2179.29 1461.18

Df 171 78

P-value 0.00 0.00





other item in the investigation (Field, 2009; Zaiontz, 2015). As shown in Table 4, the




122





123

Table 4. 16: Correlations between items of CSFs of planning and designing phase

CSF 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

13 1.00

14 0.41 1.00

15 0.32 0.20 1.00

16 0.24 0.41 0.32 1.00

17 0.27 0.25 0.41 0.34 1.00

18 0.29 0.31 0.34 0.35 0.68 1.00

19 0.30 0.23 0.55 0.35 0.50 0.51 1.00

20 0.25 0.15 0.35 0.21 0.44 0.42 0.53 1.00

21 0.29 0.27 0.24 0.27 0.43 0.43 0.48 0.40 1.00

22 0.28 0.34 0.25 0.34 0.45 0.44 0.42 0.36 0.53 1.00

23 0.22 0.28 0.27 0.32 0.45 0.41 0.47 0.37 0.44 0.36 1.00

24 0.24 0.23 0.15 0.26 0.33 0.37 0.31 0.32 0.29 0.35 0.39 1.00

25 0.33 0.33 0.23 0.36 0.43 0.40 0.40 0.37 0.44 0.42 0.44 0.42 1.00

26 0.25 0.28 0.32 0.34 0.46 0.47 0.50 0.44 0.40 0.39 0.50 0.32 0.42 1.00

27 0.25 0.28 0.29 0.40 0.42 0.47 0.54 0.41 0.51 0.38 0.46 0.27 0.39 0.52 1.00

28 0.23 0.21 0.37 0.31 0.45 0.43 0.47 0.35 0.40 0.45 0.35 0.28 0.29 0.41 0.48 1.00

29 0.19 0.24 0.33 0.42 0.55 0.49 0.45 0.43 0.43 0.36 0.45 0.32 0.42 0.39 0.58 0.58 1.00

30 0.22 0.25 0.28 0.34 0.34 0.41 0.48 0.30 0.43 0.46 0.34 0.26 0.39 0.52 0.52 0.49 0.48 1.00

31 0.22 0.33 0.22 0.36 0.42 0.52 0.36 0.25 0.45 0.44 0.34 0.28 0.42 0.43 0.50 0.41 0.50 0.54 1.00

124




each original item's's variance, so the communality value for each item should be 0.50 or

higher (Field, 2009; Zaiontz, 2015). Four iterations of factor analysis were run. On third

iteration of factor analysis test, the communality for the item CSF 16, CSF 21, CSF 22,

CSF 23, CSF 24 and CSF 25 were less than 0.50. Since they were less than 0.50, the

items had to be removed and the PCA was computed again (new iteration). Table 4.17

shows that all of the communalities for all remaining items satisfy the minimum

requirement of being larger than 0.50.

Table 4. 17: Communalities of CSFs of planning and designing phase of first and final

runs


communalities

Fourth run

(Final run)

communalities

CSF 13 Coordinating with related formal parties

such as (municipalities, electricity

companies, ministries,… etc.).

0.63 0.72

CSF 14 Client contribution on project designing and

planning.

0.71 0.74

CSF 15 Past relevant experience of consultant on

designing similar project.

0.76 0.62

CSF 16 Ability of project parties to generate

innovative ideas.

0.50 Removed

CSF 17 Specific and measurable project quality

standards.

0.57 0.56

CSF 18 Approved, clear and updated codes,

specifications and regulations for

construction industry.

0.54 0.56

CSF 19 Efficient technical capability of consultant

for example existence of skilled team and

designers.

0.69 0.68

CSF 20 Designing project according to updated

codes and standards in order to eliminate

possible errors.

0.62 0.57

CSF 21 Considering operation and maintenance

requirements into project design.

0.50 Removed

125

Table 4. 17: Communalities of CSFs of planning and designing phase of first and final

runs


communalities

Fourth run

(Final run)

communalities

CSF 22 Social, cultural and environmental impacts

on project type, design and planning.

0.48 Removed

CSF 23 Project physical environment of project like

(location, soil works, availability of

surrounding infrastructure, etc.).

0.51 Removed

CSF 24 Ease of having permits, licenses and any

related approvals from governmental

institutions.

0.59 Removed

CSF 25 Availability of organized legal environment

i.e. (laws of industry encouragement,

conflict resolution, litigations, etc).

0.57 Removed

CSF 26 Strong, detailed and updated integrated

planning effort in design and construction.

0.50 0.50

CSF 27 All key participants have participate in the

detailed project planning within their area of

expertise.

0.60 0.61

CSF 28 Effective schedule management and realistic

forecasting of project duration.

0.57 0.52

CSF 29 The project has a formal organizational chart

covering the entire project.

0.61 0.62

CSF 30 Risk identification management and

allocation.

0.62 0.60

CSF 31 Involvement of local community, project

beneficiaries and the affected parties in

project plans and policies.

0.65 0.68










126








was more than 50%.

Table 4. 18: Total variance Explained of CSFs of planning and designing phase

Att

ribute


Loadings


Loadings

Tota

l

% o

f V

aria

nce

Cum

ula

tive

%

Tota

l

% o

f V

aria

nce

Cum

ula

tive

%

Tota

l

% o

f V

aria

nce

Cum

ula

tive

%

1 5.79 44.51 44.51 5.79 44.51 44.51 3.73 28.72 28.72

2 1.15 8.82 53.33 1.15 8.82 53.33 2.74 21.11 49.83

3 1.07 8.20 61.53 1.07 8.20 61.53 1.52 11.70 61.53

4 0.79 6.09 67.61

5 0.72 5.57 73.18

6 0.62 4.80 77.98

7 0.54 4.19 82.17

8 0.51 3.90 86.07

9 0.45 3.48 89.55

10 0.41 3.16 92.71

11 0.38 2.95 95.66

12 0.30 2.34 98.00

13 0.26 2.00 100.00

Scree Plot


components for final run of analysis. This graph can also be used to decide on number of

components that can be derived. Although scree plots are very useful, component



127



Figure 4. 7: Scree Plot for CSFs of planning and designing phase


Table 4.20 shows the component loadings after rotation of 13 items (from the original 19

items) on the three components extracted and rotated. The pattern of factor loadings

should be examined to identify items that have complex structure (complex structure

occurs when one item has high loadings or correlations (0.50 or greater) on more than

one component). If an item has a complex structure, it should be removed from the

analysis (Reinard, 2006; Field, 2009; Zaiontz, 2014). As shown in Table 4.20, all items

factor loading were above 0.50 and all items had simple structure. The items are listed in

the order of size of their factor loadings.


in Table 4.19.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Eig

en

valu

es

Component

128

Table 4. 19: Summary of remaining and removed CSFs in planning and designing phase as a

result of factor analysis runs

Item. CSFs Result

CSF 13 Coordinating with related formal parties such as

(municipalities, electricity companies, ministries,… etc.).

Remaining

CSF 14 Client contribution on project designing and planning. Remaining

CSF 15 Past relevant experience of consultant on designing similar

project.

Remaining

CSF 16 Ability of project parties to generate innovative ideas. Removed since

communalities less

than 0.5

CSF 17 Specific and measurable project quality standards. Remaining

CSF 18 Approved, clear and updated codes, specifications and

regulations for construction industry.

Remaining

CSF 19 Efficient technical capability of consultant for example

existence of skilled team and designers.

Remaining

CSF 20 Designing project according to updated codes and standards

in order to eliminate possible errors.

Remaining

CSF 21 Considering operation and maintenance requirements into

project design.

Removed since

communalities less

than 0.5

CSF 22 Social, cultural and environmental impacts on project type,

design and planning.

Removed since

communalities less

than 0.5

CSF 23 Project physical environment of project like (location, soil

works, availability of surrounding infrastructure, etc.).

Removed since

communalities less

than 0.5

CSF 24 Ease of having permits, licenses and any related approvals

from governmental institutions.

Removed since

communalities less

than 0.5

CSF 25 Availability of organized legal environment i.e. (laws of

industry encouragement, conflict resolution, litigations, etc).

Removed since

communalities less

than 0.5

CSF 26 Strong, detailed and updated integrated planning effort in

design and construction.

Remaining

CSF 27 All key participants have participate in the detailed project

planning within their area of expertise.

Remaining

CSF 28 Effective schedule management and realistic forecasting of

project duration.

Remaining

CSF 29 The project has a formal organizational chart covering the

entire project.

Remaining

CSF 30 Risk identification management and allocation. Remaining

CSF 31 Involvement of local community, project beneficiaries and

the affected parties in project plans and policies.

Remaining

129


Once an interpretable pattern of loadings is done, the factors or components should be

named according to their substantive content or core. The components should have




three components were named as the following:

Component 1: “Planning and designing management” with items: CSF 18, CSF

26, CSF 27, CSF 28, CSF 29, CSF 30 and CSF 31.

Component 2: “Consultant actions and capabilities” with items: CSF 15, CSF

17, CSF 19 and CSF 20.

Component 3: “Client related factors” with items: CSF 13 and CSF 14.



describes the final results of the components extracted, percent total explained variance

and eigenvalues of each component.

Figure 4. 8: Final components extracted from factor analysis for CSFs in planning and

designing phase

Planning and designing phase


Component 3

Client related factors

Eigenvalue: 1.07

Component 2

Consultant actions and capabilities

Eigenvalue: 1.15

Component 1

Planning and designing management

Eigenvalue: 5.79

130











acceptable.

Table 4. 20: Factor loadings for a three-component model CSFs of planning and designing

phase


Fac

tor

load

ing

Eig

enval

ues

Var

iance

%

expla

ined

Cro

nbac

h's

Alp

ha

(Cα

)

Component 1: Planning and designing management

CSF 31 Involvement of local community, project

beneficiaries and the affected parties in

project plans and policies.

0.79

5.79 28.72 0.85

CSF 30 Risk identification management and

allocation.

0.75

CSF 27 All key participants have participate in the

detailed project planning within their area

of expertise.

0.71

CSF 29 The project has a formal organizational

chart covering the entire project.

0.70

CSF 28 Effective schedule management and

realistic forecasting of project duration.

0.61

CSF 26 Strong, detailed and updated integrated

planning effort in design and

construction.

0.58

CSF 18 Approved, clear and updated codes,

specifications and regulations for


0.56

131


phase


Fac

tor

load

ing

Eig

enval

ues

Var

ian

ce %

exp

lain

ed

Cro

nb

ach

's

Alp

ha

(Cα

)

Component 2: Consultant actions and capabilities

CSF 15 Past relevant experience of consultant on

designing similar project.

0.75

1.15 21.11 0.78

CSF 19 Efficient technical capability of consultant

for example existence of skilled team and

designers.

0.72

CSF 20 Designing project according to updated

codes and standards in order to eliminate

possible errors.

0.70

CSF 17 Specific and measurable project quality

standards.

0.57

Component 3: Client related factors

CSF 14 Client contribution on project designing

and planning. 0.81

1.07 11.70 0.67 CSF 13 Coordinating with related formal parties

such as (municipalities, electricity

companies, ministries, etc.).

0.78





Four insignificant factor loadings (< 0.5) are blanked

4.4.2.1.2 The extracted components


Component C 1: Planning and designing management

First component named "Planning and designing management" explains 28.72 % of the

total variance and contains seven items. The majority of items had relatively high factor

loadings (≥ 0.56). The seven items are as follows:

1. Involvement of local community, project beneficiaries and the affected parties in

project plans and policies CSF 31, with factor loading=0.79.

2. Risk identification management and allocation CSF 30, with factor loading =0.75.

132

3. All key participants have participate in the detailed project planning within their area

of expertise CSF 27, with factor loading=0.71.

4. The project has a formal organizational chart covering the entire project CSF 29,

with factor loading=0.70.

5. Effective schedule management and realistic forecasting of project duration CSF 28,


6. Strong, detailed and updated integrated planning effort in design and construction

CSF 26, with factor loading=0.58.

7. Approved, clear and updated codes, specifications and regulations for construction

industry CSF 18, with factor loading=0.56.

Results from Table 4.20 indicated that CSF “Involvement of local community, project

beneficiaries and the affected parties in project plans and policies” was the highest

loaded factor of this component with factor loading =0.79. In Palestinian public

construction projects local community and beneficiaries involvement is are very

important to guarantee project success. Since most Palestinian public projects were

funded from donors and one of the main things that demanded by funders was to satisfy

beneficiaries and local community since the projects holds for serving them. Also the KPI

"Beneficiaries satisfaction on project functionality" which determined in previous section

of this study was ranked as the 6th

important KPI. This support that it was very important

to involve beneficiaries on project planning to enhance their satisfaction. In Durban and

South Africa Garbharran et al (2012) had similar results. Garbharran et al (2012)

classified the community as one of the project stakeholders and they indicated that

community involvement was a key element for project success and enhances the

organization's social responsibility standing. They ranked the involvement of

stakeholders as being the most important item for project success in South Africa. Also

Ihuah et al (2014) concluded that beneficiaries' involvement was ranked as 8th

CSF in

sustainable housing estates’ delivery and provision in Nigeria.

The second high loaded CSF was “Risk identification management and allocation” with

factor loading = 0.75. This CSF indicated that before starting the project all the risks

should predicted to minimize the uncertainty of project environment in order to ensure

133

project success. In Palestine many political events should be considered like wars, ports

closure and windy and raining climate some times. So decision makers and planners

should give high important to identify all those risks. In UK Davies (2002) and Fortune

and White (2006) had the same result on their study and they concluded that risk

identification was an important CSFs that should take in consider in planning phase.

Similar results in Ismail et al (2012) study which held in Malaysia. Ismail et al (2012)

indicated that building industry is not well accepted by the construction parties because

of failure to adequately deal with risks and they concluded that risk management is 10th

ranked important success factor of building projects in Malaysia. Also Lehtiranta et al

(2012) study stated that the main contractor’s ability to manage project risks

systematically can be observed as a predictor of project success in Finland.

Component 2: Consultant actions and capabilities

Second component named "Consultant actions and capabilities" explains 21.11 % of the

total variance and contains four items. The majority of items had relatively high factor

loadings (≥ 0.57). The four items are as follows:

1. Past relevant experience of consultant on designing similar project CSF 15, with


2. Efficient technical capability of consultant for example existence of skilled team and

designers CSF 19, with factor loading =0.72.

3. Designing project according to updated codes and standards in order to eliminate

possible errors CSF 20, with factor loading=0.70.

4. Specific and measurable project quality standards CSF 17, with factor loading=0.57.

Results from Table 4.20 stated that the highest factor loaded CSF of the second

component was “Past relevant experience of consultant on designing similar project”

followed by CSF “Efficient technical capability of consultant for example existence of

skilled team and designers”. These CSFs indicated that consultant experience is a vital

issue to project success since his main responsibilities is to prepare the design of the

project, to identify required quality specification, types of materials, how to use new

technology and forecasting project costs. Without such previous experience in the field of

work the tendency of project to failure will be high. In Palestine most public projects

134

needed professional consultant team since client himself usually hadn't enough skilled

team. So recurring skilled consultant in Palestinian construction industry is main issue.

Tan and Ghazali (2011) study in Malaysia is in line with this study, they mentioned that

design team experience was very important CSF. Also same results in Taiwan in Chen et

al (2007) and Chen et al (2012) studies which ranked the technical experience as the

second important CSF. Chen et al (2007) and Chen et al (2012) concluded that

construction projects rely on organizing the abilities, experience, professional knowledge

and skills at the different levels of the teams involved include project owners, architects,

engineers, consultants, contractors, suppliers, etc.

Component C3: Client related factors

The third component named "Client related factors" explains 11.70 % of the total

variance and contains two items. The majority of items had relatively high factor loadings

(≥ 0.78). The two items are as follows:

1. Client contribution on project designing and planning CSF 14, with factor

loading=0.81.

2. Coordinating with related formal parties such as (municipalities, electricity

companies, ministries, etc.) CSF 13, with factor loading =0.78.

Results revealed that the highest factor loaded item in this component was CSF “Client

contribution on project designing and planning”. This CSF indicated that client should

have important contribution in designing and planning phase. Client contribution is

important because he is the most one who understand project goals, needs and purposes.

The lack in coordination between client, designers and planners will have bad effects like

variations, design changes and less commitment to project goals and objectives. In

Palestine public construction projects supervised generally by engineering departments of

ministries (such ministries like MPWH,MOLG, MOHE)or NGO's like UNRWA and

UNDP. Those organizations are the clients of Palestinian public construction projects. In

UK Andersen et al (2006) support this point of view since they found that the 3rd

most

important factor in improving managerial ability to deliver results in time and at cost was

the stakeholder contribution of project plans. Also in Thailand Toor et al (2008) found

that this CSF was the 3rd loading factor in the comprehension component. Toor et al

135

(2008) also indicated that goals and priorities, demands of client and interests of all

related parties are well recognized and considered in the project plans so for a reasonable

comprehension of the project, the main role is to be played by the client to first clearly

provide his requirements in the planning phase.

4.4.2.2 CSFs related to tendering and contracting phase


number of items (CSFs) to a smaller set of underlying factors that summarize the








to the following:

Data distribution



sample Kolmogorov-Smirnov test was used to test that an item of interest is normally

distributed. Table 3.8 showed that the distributions of CSFs which related to tendering

and contracting phase is normally distributed. So the results had been satisfied with this

requirement.






136


(Field, 2009; Zaiontz, 2015). Fortunately, for CSFs of tendering and contracting phase ,

the condition was verified. This field contains 16 items and the sample size was 274.

With 274 respondents and 19 items CSFs, the ratio of respondents to items are 17.1: 1,

which exceeds the requirement ratio 10:15.


Cronbach's alpha test was performed on the items in CSFs of tendering and contracting

phase . The value of Cronbach’s alpha (Cα) could be anywhere in the range of 0 to 1,



(Field, 2009). As shown in Table 4.21, the value of calculated Cα for all items in the field

CSFs of tendering and contracting phase for the final run was 0.85 which considered to

be marvelous.













results of these two tests, the sample data of (CSFs in tendering and contracting phase )

were appropriated for factor analysis.

137

Table 4. 21: KMO and Bartlett's Test for CSFs of tendering and contracting phase Factor analysis run description

First run Second run

(Final run)



Sampling Adequacy.

0.89 0.86


Approx. Chi-

Square 1617.57 955.14

Df 120.00 55.00

P-value 0.00 0.00













138

Table 4. 22: Correlations between items of CSFs of tendering and contracting phase CSF CSF 32 CSF 33 CSF 34 CSF 35 CSF 36 CSF 37 CSF 38 CSF 39 CSF 40 CSF 41 CSF 42 CSF 43 CSF 44 CSF 45 CSF 46 CSF 47

CSF 32 1.00

CSF 33 0.44 1.00

CSF 34 0.35 0.37 1.00

CSF 35 0.16 0.14 0.35 1.00

CSF 36 0.23 0.26 0.40 0.35 1.00

CSF 37 0.17 0.22 0.27 0.37 0.54 1.00

CSF 38 0.35 0.41 0.40 0.26 0.46 0.41 1.00

CSF 39 0.28 0.53 0.25 0.17 0.27 0.37 0.46 1.00

CSF 40 0.32 0.41 0.36 0.11 0.35 0.20 0.43 0.51 1.00

CSF 41 0.21 0.21 0.27 0.18 0.32 0.33 0.35 0.32 0.43 1.00

CSF 42 0.28 0.31 0.26 0.22 0.39 0.31 0.43 0.38 0.40 0.43 1.00

CSF 43 0.28 0.38 0.34 0.32 0.46 0.37 0.56 0.40 0.42 0.46 0.57 1.00

CSF 44 0.14 0.35 0.26 0.19 0.35 0.25 0.40 0.40 0.42 0.32 0.34 0.52 1.00

CSF 45 0.15 0.17 0.44 0.38 0.38 0.28 0.42 0.22 0.27 0.32 0.30 0.43 0.42 1.00

CSF 46 0.13 0.33 0.35 0.30 0.36 0.32 0.46 0.44 0.41 0.34 0.36 0.45 0.54 0.52 1.00

CSF 47 0.23 0.16 0.31 0.29 0.39 0.44 0.52 0.37 0.34 0.28 0.43 0.44 0.37 0.43 0.52 1.00

139





higher (Field, 2009; Zaiontz, 2015). Two iterations of factor analysis were done. On first

iteration of factor analysis test, the communality for the item CSF 37, CSF 41 and CSF

42 were less than 0.50. Since they were less than 0.50, the items had to be removed and

the PCA was computed again (new iteration). Other CSFs which were (CSF 9 and CSF

14) removed in the other steps of factor analysis. Table 4.23 shows that all of the

communalities for all remaining items satisfy the minimum requirement of being larger

than 0.50.

Table 4. 23: Communalities of CSFs of tendering and contracting phase of first and

final runs


communalities

Second run

(Final run)

communalities

CSF 32 The client has a mechanism to manage the

bids.

0.67 0.69

CSF 33 Transparent and efficient procurement

criteria depends on applicable laws and

regulations.

0.66 0.74

CSF 34 Consider consultant and contractor past

performance and reputation as awarding

criteria.

0.53 0.60

CSF 35 Past relevant experience of client in

awarding bids and managing contracts.

0.58 0.64

CSF 36 Past related experience of consultant in

sharing in similar bids and contracts.

0.54 0.58

CSF 37 Past related experience of contractor in


0.48 Removed

CSF 38 The consultant and the contractor have a

mechanism to manage the tenders and

compete.

0.56 0.59

CSF 39 The client interprets all project requirements

and location during the bids preparatory

meeting.

0.57 0.57

CSF 40 Documentation the preparation meetings in

details.

0.58 Removed

140

Table 4. 23: Communalities of CSFs of tendering and contracting phase of first and

final runs


communalities

Second run

(Final run)

communalities

CSF 41 Visiting project location by all consultants

and contractors before filling out the bid

form.

0.37 Removed

CSF 42 Granting enough time for consultants and

contractors to fill out the bid form.

0.44 Removed

CSF 43 Participating of related project parties in

financial and technical evaluation of tenders.

0.58 0.57

CSF 44 Effective contract management included

precise formulation, documentation and

enough detailed incentives, bonds, penalties,

…etc.

0.58 0.61

CSF 45 Project profitability for consultant and

contractor

0.54 Removed

CSF 46 Economic environment in terms of materials

quantity, quality, and price, local currency

value, …etc.

0.61 0.66

CSF 47 Delegation and authority allocation of

project workers.

0.52 0.52














141




was more than 50%.

Table 4. 24: Total variance Explained of CSFs of tendering and contracting phase

Att

rib

ute


Loadings


Loadings

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

1 4.51 41.04 41.04 4.51 41.04 41.04 2.96 26.95 26.95

2 1.18 10.68 51.72 1.18 10.68 51.72 1.91 17.40 44.35

3 1.07 9.76 61.48 1.07 9.76 61.48 1.88 17.13 61.48

4 0.78 7.10 68.58

5 0.67 6.05 74.63

6 0.60 5.48 80.11

7 0.58 5.31 85.42

8 0.48 4.38 89.80

9 0.42 3.82 93.61

10 0.37 3.35 96.96

11 0.33 3.04 100.00

Scree Plot


components for the final run of analysis. This graph can also be used to decide on number

of components that can be derived. Although scree plots are very useful, component





142

Figure 4. 9: Scree Plot for CSFs of tendering and contracting phase


Table 4.26 shows the factor loadings after rotation of 13 items (from the original 19

items) on the three components extracted and rotated. The pattern of factor loadings



one component). If an item has a complex structure, it should be removed from the

analysis (Reinard, 2006; Field, 2009; Zaiontz, 2014). According to that, it was necessary

to remove item CSF 9 and CSF 14 because they demonstrated complex structure. They

was loaded under two components (component 1 and component 3) in the same time with

a factor loading of more than 0.5. As shown in Table 4.26, all items factor loading were

above 0.50 and all items had simple structure. The items are listed in the order of size of

their factor loadings.


in Table 4.25.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

0 1 2 3 4 5 6 7 8 9 10 11

Eige

nva

lue

s

Component

143

Table 4. 25: Summary of remaining and removed CSFs in tendering and contracting phase as

a result of factor analysis runs

Item. CSFs Result

CSF 32 The client has a mechanism to manage the bids. Remaining

CSF 33 Transparent and efficient procurement criteria depends on

applicable laws and regulations.

Remaining

CSF 34 Consider consultant and contractor past performance and

reputation as awarding criteria.

Remaining

CSF 35 Past relevant experience of client in awarding bids and

managing contracts.

Remaining

CSF 36 Past related experience of consultant in sharing in similar

bids and contracts.

Remaining

CSF 37

Past related experience of contractor in sharing in similar

bids and contracts.

Removed since

communalities less

than 0.5

CSF 38 The consultant and the contractor have a mechanism to

manage the tenders and compete.

Remaining

CSF 39 The client interprets all project requirements and location

during the bids preparatory meeting.

Remaining

CSF 40 Documentation the preparation meetings in details. Removed since it have

complex structure

CSF 41

Visiting project location by all consultants and contractors

before filling out the bid form.

Removed since

communalities less

than 0.5

CSF 42

Granting enough time for consultants and contractors to fill

out the bid form.

Removed since

communalities less

than 0.5

CSF 43 Participating of related project parties in financial and

technical evaluation of tenders.

Remaining

CSF 44

Effective contract management included precise

formulation, documentation and enough detailed incentives,

bonds, penalties, …etc.

Remaining

CSF 45 Project profitability for consultant and contractor Removed since it have

complex structure

CSF 46 Economic environment in terms of materials quantity,

quality, and price, local currency value, …etc.

Remaining

CSF 47 Delegation and authority allocation of project workers. Remaining


Once an interpretable pattern of loadings is done, the components or components should

be named according to their substantive content or core. The components should have



144


three components were named as the following:

Component 1: “Bidding and contracting management” with items: CSF 38, CSF

39, CSF 43, CSF 44, CSF 46 and CSF 47.

Component 2: “Project Parties' capabilities” with items: CSF 34, CSF 35 and

CSF 36.

Component 3: “Client behavior” with items: CSF 32 and CSF 33.




variance and eigenvalue of each component.

Figure 4. 10: Final components extracted from factor analysis for CSFs in tendering and

contracting phase





Tendering and contracting phase


Component 3:

Client behavior

Eigenvalue: 1.07

Component 2:

Project parties capabilities

Eigenvalue: 1.18

Component 1:

Bidding and contracting management

Eigenvalue: 4.51

145







acceptable.


phase


Fac

tor

load

ing

Eig

enval

ues

Var

iance

%

expla

ined

Cro

nbac

h's

Alp

ha

(Cα

)

Component 1: Bidding and contracting management

CSF 46 Economic environment in terms of

materials quantity, quality, and price,

local currency value, …etc.

0.79

4.51 26.95 0.82

CSF 44 Effective contract management included

precise formulation, documentation and

enough detailed incentives, bonds,

penalties, …etc.

0.76

CSF 47 Delegation and authority allocation of

project workers.

0.65

CSF 43 Participating of related project parties in

financial and technical evaluation of

tenders.

0.63

CSF 39 The client interprets all project

requirements and location during the bids

preparatory meeting.

0.58

CSF 38 The consultant and the contractor have a

mechanism to manage the tenders and

compete.

0.57

Component 2: Project parties capabilities

CSF 35 Past relevant experience of client in

awarding bids and managing contracts. 0.79

1.18 17.40 0.67 CSF 36 Past related experience of consultant in


0.66

146


phase


Fac

tor

load

ing

Eig

enval

ues

Var

ian

ce %

exp

lain

ed

Cro

nb

ach

's

Alp

ha

(Cα

)

CSF 34 Consider consultant and contractor past

performance and reputation as awarding

criteria.

0.65

Component 3: Client behavior

CSF 32 The client has a mechanism to manage the

bids.

0.79

1.07 17.13 0.61 CSF 33 Transparent and efficient procurement

criteria depends on applicable laws and

regulations.

0.76





Six insignificant factor loadings (< 0.5) are blanked



Component 1: Bidding and contracting management

First component named "Bidding and contracting management" explains 26.95% of the

total variance and contains six items. The majority of items had relatively high factor

loadings (≥ 0.57). The six items are as follows:

1. Economic environment in terms of materials quantity, quality, and price, local

currency value, …etc CSF 46, with factor loading=0.79.

2. Effective contract management included precise formulation, documentation and

enough detailed incentives, bonds, penalties, …etc CSF 44, with factor loading =0.76.

3. Delegation and authority allocation of project workers CSF 47, with factor

loading=0.65.

4. Participating of related project parties in financial and technical evaluation of

tenders CSF 43, with factor loading=0.63.

147

5. The client interprets all project requirements and location during the bids

preparatory meeting CSF 39, with factor loading=0.58.

6. The consultant and the contractor have a mechanism to manage the tenders and

compete CSF 38, with factor loading=0.57.

Results from Table 4.26 indicated that CSF “Economic environment in terms of materials

quantity, quality, and price, local currency value, …etc” was the highest loading factor in

this component with factor loading =0.79. This CSF indicated that it is important to

understand and study the economic environment in detailed on this phase because many

things will depend on this like pricing bids and tenders, determining quality levels,

identification of materials types and construction technology, agreement formulization.

Palestine situation like any other developing country suffer from bad economic

conditions and high level of uncertainty. So with clear studying and understanding of

project economic environment the hazard of failure this will be decreased. In line with

this study in Gaza Strip Enshassi et al (2009a) found that the most important factor

affecting project performance was delays due of borders/roads closure leading to

materials shortage. Also in Bangladesh, China, India and Thailand Ahsan and Gunawan

(2010) found that the main reason of cost underrun was devaluation of local currency.

The second high factor loaded CSF in this component was “Effective contract

management included precise formulation, documentation and enough detailed

incentives, bonds, penalties, …etc” with factor loading =0.76. This CSF indicated that in

contracting and tendering phase it is a responsibility of all parties to work together in

order to have enough detailed contract that contain all parties responsibilities, authorities

and rights. In Palestine any misfiled on the contract rises the hazard of variations orders,

rework, disputes and litigations. This result in line with Frimpong et al (2003) study in

Ghana who found that the second most important factor attributing to the cause of delay

and cost overruns in groundwater projects was poor contract management. Also in

Malaysia Abdul-Aziz and Kassim (2011) found that the failure factor which had the most

influential was absence of robust and clear agreement.

148

Component 2: Project parties capabilities

Second component named "Project parties' capabilities" explains 17.40% of the total

variance and contains three items. The majority of items had relatively high factor

loadings (≥ 0.65). The three items are as follows:

1. Past relevant experience of client in awarding bids and managing contracts CSF 35,


2. Past related experience of consultant in sharing in similar bids and contracts CSF 36,

with factor loading =0.66.

3. Consider the reputation and the performance in previous projects as one of awarding

criteria CSF 34, with factor loading=0.65.

Results from table 4.26 showed that CSF “Past relevant experience of client in awarding

bids and managing contracts” with factor loading =0.79 was the highest loaded factor of

this component. This CSF indicated that client should know how to evaluate the bids. In

Palestine the most spread wide way to award the bids is lowest bidder with less attention

to other important factors like technical capability. May be due to the limited funds

lowest bid is a solution but it is not always the right one because may be the lowest

bidder have inadequate experience so respondents agreed with that it is very important

for client to have experience in similar bids awarding strategies. Similar results in

Malaysia Sambasivan and Soon (2007) found that the 3rd

cause of delay was awarding

bids to inadequate contractor experience. In contrary in Malaysia Yong and Mustaffa

(2013) ranked Awarding bids to the right designers/ contractors as the 22th

CSF. In

Bangladesh, China, India and Thailand Ahsan and Gunawan (2010) found that contract

evaluation and award was the main cause of delay.

The second high factor loaded CSF in this component was “Past related experience of

consultant in sharing in similar bids and contracts” with factor loading =0.66. This CSF

indicated that consultant should have wide knowledge to compete in order to win. Bid

form considered as a contractor plan for the project. Without availability of past relevant

experience in similar bids contractor may fall in big mistakes and faults in estimation of

cost and time. Also consultant should know his rights and responsibilities and how to

document them on the contract. In Palestine contractors have limited knowledge in this

149

field and this rises many problems like variation orders, delay and cost overrun. Similar

result in Malaysia Sambasivan and Soon (2007) found that the 1st cause of delay was

improper planning during contracting. Also in China Lu et al (2008) ranked a successful

bidding strategy as the most important CSF for indicating a contractor’s or consultant

competitiveness.

Component 3: Client behavior

Third component named "Client behavior" explains 17.13% of the total variance and

contains two items. The majority of items had relatively high factor loadings (≥ 0.76).

The two items are as follows:

1. The client has a mechanism to manage the bids CSF 32, with factor loading =0.79.

2. Transparent and efficient procurement criteria depends on applicable laws and

regulations CSF 33, with factor loading=0.76.

Results from Table 4.26 revealed that CSF “The client has a mechanism to manage the

bids” and CSF " Transparent and efficient procurement criteria depends on applicable

laws and regulations" had high factor loadings. Client is the one who is mainly

responsible to manage the bids preparing, invitation, meetings, awarding and agreements

so he should have the required experience. In Palestine the bidding management is

adversarial in nature as clients and contractors tend to take advantage of one another

during the negotiation process. Clients try to suppress the project cost to an unrealistic

level in order to reap more profit while the contractors in response will bid at an

unrealistic price to get the project. Many projects in Palestine suffer from delay and cost

overrun due to misses in managing the bidders from client and because most of bids

awarded in lowest bid and consultant or contractor reputation rather than technical

capabilities. Recently MPWH give more attention to the technical capabilities in its

construction projects. In Egypt Marzouk and El-Rasas (2014) ranked the factor type of

project bidding and awarding (negotiation, lowest bidder) as the top factor causing delay

according to frequency index.

150

4.4.2.3 CSFs related to implementation phase


number of items to a smaller set of underlying factors that summarize the essential

information contained in the items. Using SPSS 22, Principle Component Analysis

(PCA) with Varimax rotation were performed to set up which items could capture the

aspects of same dimension of the 34 CSFs and examine the underlying structure or

structure of interrelationships among the CSFs. In order to perform the factor analysis for

used items, all the appropriate checks and procedures were fulfilled.



to the following:

Data distribution




distributed. Table 3.8 showed that the distributions of CSFs which related to

implementation phase are normally distributed. So the results had been satisfied with this

requirement.







(Field, 2009; Zaiontz, 2015). Fortunately, for CSFs of implementation phase, the

condition was not verified. With 274 respondents and 12 items CSFs, the ratio of

respondents to items are 8.1: 1, which less than the requirement for the ratio of

respondents to items 10:15. So the accuracy of the factor analysis would depend on the

151

strength of the data itself. The communality of each item should be examined accurately

to measure strength of the data.


Cronbach's alpha test was performed on the items in the field of CSFs of implementation

phase. The value of Cronbach’s alpha (Cα) could be anywhere in the range of 0 to 1,



(Field, 2009). As shown in Table 4.27, the value of calculated Cα for all items in the

CSFs of implementation phase for the final run was 0.90 which considered to be

marvelous.













results of these two tests, the sample data of (CSFs in implementation phase) were

appropriated for factor analysis.

152

Table 4. 27: KMO and Bartlett's Test for CSFs of implementation phase


First run Fifth run (Final

run)



Sampling Adequacy.

0.92 0.91


Approx. Chi-

Square 5152.23 2516.26

Df 561 190

P-value 0.00 0.00













153

Table 4. 28: Correlations between items of CSFs of implementation phase

CSF 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81

48. 1.0

49. 0.4 1.0

50. 0.3 0.5 1.0

51. 0.3 0.5 0.6 1.0

52. 0.3 0.3 0.5 0.6 1.0

53. 0.2 0.5 0.5 0.6 0.6 1.0

54. 0.4 0.3 0.5 0.4 0.4 0.3 1.0

55. 0.2 0.4 0.3 0.4 0.2 0.4 0.3 1.0

56. 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.5 1.0

57. 0.1 0.3 0.3 0.4 0.4 0.4 0.2 0.4 0.4 1.0

58. 0.3 0.5 0.5 0.5 0.3 0.4 0.4 0.4 0.4 0.4 1.0

59. 0.3 0.4 0.4 0.4 0.2 0.3 0.3 0.4 0.3 0.2 0.4 1.0

60. 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.2 0.4 0.5 1.0

61. 0.3 0.3 0.3 0.5 0.4 0.4 0.3 0.3 0.4 0.3 0.4 0.5 0.5 1.0

62. 0.3 0.3 0.4 0.4 0.4 0.4 0.3 0.3 0.4 0.3 0.5 0.4 0.5 0.6 1.0

63. 0.4 0.3 0.3 0.4 0.4 0.3 0.3 0.2 0.4 0.3 0.4 0.4 0.5 0.6 0.7 1.0

64. 0.2 0.2 0.3 0.4 0.4 0.3 0.2 0.2 0.2 0.4 0.3 0.3 0.2 0.5 0.4 0.5 1.0

65. 0.3 0.4 0.4 0.5 0.5 0.4 0.5 0.3 0.5 0.4 0.4 0.4 0.4 0.5 0.4 0.5 0.5 1.0

66. 0.2 0.4 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.5 0.4 0.4 0.4 0.6 1.0

67. 0.3 0.3 0.5 0.5 0.4 0.5 0.4 0.3 0.4 0.5 0.4 0.3 0.3 0.4 0.4 0.4 0.5 0.6 0.6 1.0

68. 0.3 0.4 0.5 0.5 0.4 0.5 0.4 0.3 0.4 0.4 0.5 0.4 0.3 0.5 0.4 0.4 0.4 0.4 0.5 0.6 1.0

69. 0.4 0.5 0.6 0.6 0.5 0.5 0.4 0.3 0.4 0.4 0.5 0.3 0.4 0.5 0.5 0.4 0.4 0.5 0.5 0.5 0.6 1.0

70. 0.3 0.3 0.4 0.5 0.5 0.4 0.3 0.3 0.3 0.4 0.4 0.3 0.3 0.5 0.4 0.5 0.4 0.4 0.4 0.4 0.5 0.6 1.0

71. 0.3 0.3 0.5 0.5 0.5 0.5 0.3 0.2 0.3 0.4 0.4 0.3 0.3 0.4 0.5 0.4 0.3 0.5 0.5 0.4 0.4 0.5 0.5 1.0

72. 0.2 0.3 0.4 0.5 0.5 0.4 0.4 0.2 0.4 0.4 0.5 0.3 0.4 0.5 0.4 0.4 0.4 0.5 0.5 0.6 0.5 0.5 0.5 0.6 1.0

73. 0.2 0.2 0.3 0.4 0.5 0.4 0.2 0.2 0.2 0.3 0.4 0.3 0.2 0.3 0.3 0.4 0.4 0.4 0.4 0.3 0.4 0.5 0.4 0.4 0.5 1.0

154

Table 4. 28: Correlations between items of CSFs of implementation phase

CSF 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81

74. 0.2 0.3 0.5 0.4 0.5 0.4 0.4 0.1 0.3 0.4 0.5 0.3 0.2 0.4 0.3 0.4 0.4 0.4 0.5 0.4 0.6 0.6 0.5 0.4 0.5 0.6 1.0

75. 0.2 0.2 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.4 1.0

76. 0.2 0.3 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.4 0.3 0.4 0.4 0.4 0.5 0.3 0.3 0.4 0.2 0.3 0.4 0.4 0.3 0.3 0.3 0.4 0.3 1.0

77. 0.2 0.3 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.5 0.3 0.4 0.3 0.4 0.5 0.3 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.5 0.4 0.4 0.3 0.5 1.0

78. 0.2 0.3 0.4 0.6 0.5 0.5 0.3 0.3 0.4 0.4 0.5 0.3 0.4 0.5 0.4 0.4 0.4 0.5 0.5 0.4 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.4 0.4 0.6 1.0

79. 0.3 0.4 0.5 0.5 0.4 0.5 0.4 0.3 0.4 0.3 0.6 0.4 0.5 0.5 0.5 0.4 0.3 0.5 0.5 0.5 0.5 0.5 0.4 0.4 0.6 0.3 0.4 0.3 0.4 0.5 0.6 1.0

80. 0.2 0.2 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.3 0.3 0.4 0.4 0.4 0.3 0.4 0.3 0.4 0.4 0.5 0.6 1.0

81. 0.2 0.3 0.4 0.4 0.5 0.4 0.4 0.3 0.3 0.3 0.5 0.4 0.3 0.4 0.4 0.4 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.3 0.4 0.4 0.5 0.5 0.5 1.0

155





higher (Field, 2009; Zaiontz, 2015). Five iteration of factor analysis were done. On

iteration 4 of factor analysis test, the communality for were less than 0.50. Since they

were less than 0.50, the items CSF 54, CSF 75 and CSF 77 in fourth run they had to be

removed. Other CSFs which were (CSF 51, CSF 52, CSF 53, CSF 58, CSF 59, CSF 68,

CSF 70, CSF 71, CSF 72, CSF 76 and CSF 78) removed in the other steps of factor

analysis. Table 4.29 shows that all of the communalities for all remaining items satisfy

the minimum requirement of being larger than 0.50 and not removed on the following

steps of factor analysis.

Table 4.29: Communalities of CSFs of implementation phase of first and final runs


communalities

Fifth run

(Final run)

communalities

CSF 48 The client follows project implementation

regularly.

0.59 0.69

CSF 49 Past relevant experience of contractor in

execution similar projects.

0.62 0.64

CSF 50 Appropriate safety practices during project

execution.

0.59 0.64

CSF 51 Updated plan for supervising and managing

project site.

0.64 Removed

CSF 52 Preparing and implementing environmental

plans included project waste management

works.

0.57 Removed

CSF 53 Commitment of team members on project

plans and objectives.

0.58 Removed

CSF 54 Clear and effective decision making

mechanism.

0.51 Removed

CSF 55 Project manager commitment to meet cost

quality and time of project.

0.74 0.64

CSF 56 Adequacy and effective management of

project financial and material resources.

0.52 0.60

CSF 57 Training the human resources in the skills

demanded by the project.

0.68 0.69

156



communalities

Fifth run

(Final run)

communalities

CSF 58 Leadership, monitoring, coordinating and

organizing manager skills of project

manager.

0.54 Removed

CSF 59 Permanent presence of project manager in

project site.

0.63 Removed

CSF 60 Availability of enough staff in project site

according to works requirements.

0.67 0.66

CSF 61 Top management support for project

workers.

0.65 0.65

CSF 62 Collaborative team work environment.

0.63 0.69

CSF 63 Mutual trust and understanding between

project participants.

0.72 0.78

CSF 64 Social relationships and coordination

between project participants.

0.66 0.69

CSF 65 Annual organized meetings related to

project activities for all participants.

0.63 0.62

CSF 66 Timely and effective conflict resolution.

0.58 0.63

CSF 67 Effective project control , such as

monitoring, updating plans and feedback.

0.65 0.59

CSF 68 Control and monitoring subcontractors

works.

0.60 Removed

CSF 69 Annual measuring of KPIs.

0.65 0.64

CSF 70 Effective well established information and

communication routines.

0.55 Removed

CSF 71 The project is part of a well-documented or

understood strategy

0.57 Removed

CSF 72 Effective knowledge processing and

management systems.

0.65 Removed

CSF 73 Natural climates like winds, rains and high

temperature.

0.67 0.59

CSF 74 Consultant and contractor commitment to

continuous improvement.

0.67 0.72

CSF 75 Client changes in plans and goals during

execution.

0.51 Removed

CSF 76 Client approvals and Payment method.

0.52 Removed

CSF 77 Availability and execution of material

handling plans.

0.51 Removed

157



communalities

Fifth run

(Final run)

communalities

CSF 78 Using applicable construction methods.

0.61 Removed

CSF 79 Continuous revision of project shop

drawings and approve them fast.

0.66 0.67

CSF 80 Saving as built drawings of the project.

0.63 0.69

CSF 81 Consultant and contractors involvement in

project operating and maintenance plan after

project execution.

0.52 0.57


Using the output from iteration 5, there were five eigenvalues greater than 1. The

eigenvalue criterion stated that each component explained at least one item's's worth of

the variability and therefore only components with eigenvalues greater than one should

be retained (Larose, 2006; Field, 2009). The latent root criterion for number of

components to derive would indicate that there were 5 components to be extracted for

these items. Results were tabulated in Table 4.30 The five components solution explained

a sum of the variance with component 1 contributing 40.69%; component 2 contributing

7.27%; component 3 contributing 6.57%, component 4 contributing 5.80% and

component 5 contributing 5.13%. All the remaining components are not significant.

The five components were then rotated via varimax (orthogonal) rotation approach. This


presents the pattern of loadings in a manner that is easier to interpret components

(components) (Field, 2009; Zaiontz, 2015). The rotated solution revealed that the five

components solution explained a sum of the variance with component 1 contributing

14.15%; component 2 contributing 14.06%; component 3 contributing 13.97%;

component 4 contributing 12.74%; and component 5 contributing 10.53%. These five

components explained 65.45% of total variance for the varimax rotation which is

acceptable since it was more than 50%.

158

Table 4. 30: Total variance Explained of CSFs of implementation phase

Att

rib

ute

Initial Eigenvalues

Extraction Sums of Squared

Loadings


Loadings

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

To

tal

% o

f V

aria

nce

Cu

mu

lati

ve

%

1 8.14 40.69 40.69 8.14 40.69 40.69 2.83 14.15 14.15

2 1.45 7.27 47.96 1.45 7.27 47.96 2.81 14.06 28.22

3 1.31 6.57 54.53 1.31 6.57 54.53 2.79 13.97 42.19

4 1.16 5.80 60.32 1.16 5.80 60.32 2.55 12.74 54.93

5 1.03 5.13 65.45 1.03 5.13 65.45 2.11 10.53 65.45

6 0.77 3.85 69.30

7 0.73 3.63 72.94

8 0.65 3.27 76.21

9 0.60 3.02 79.23

10 0.53 2.63 81.85

11 0.52 2.59 84.44

12 0.49 2.45 86.89

13 0.42 2.11 89.00

14 0.41 2.07 91.07

15 0.39 1.94 93.01

16 0.35 1.75 94.76

17 0.30 1.49 96.24

18 0.28 1.38 97.62

19 0.26 1.30 98.92

20 0.22 1.08 100.00

Scree Plot


components for the final run of analysis. This graph can also be used to decide on number

of components that can be derived. Although scree plots are very useful, component





159

Figure 4. 11: Scree Plot for CSFs of implementation phase


Table 4.31 shows the factor loadings after rotation of 21 items (from the original 34

items) on the five components extracted and rotated. The pattern of factor loadings



one component). If an item have a complex structure, it should be removed from the

analysis (Reinard, 2006; Field, 2009; Zaiontz, 2014). According to that, it was necessary

to remove items CSF 51, CSF 52, CSF 53, CSF 58, CSF 59, CSF 68, CSF 70, CSF 71,

CSF 72, CSF 76 and CSF 78 because all of them have factor loading less than 0.5. As

shown in Table 4.31, for each remaining items factor loading were above 0.50 and all

items had simple structure. The items are listed in the order of size of their factor

loadings.


Once an interpretable pattern of loadings is done, the components should be named

according to their substantive content or core. The components should have conceptually

distinct names and content. Items with higher loadings on a component should play a

more important role in naming the component. Also the common names for components

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

0 2 4 6 8 10 12 14 16 18 20

Eige

nva

lue

s

Component

160

in previous studies were used in naming the components. In this study the three

components were named as the following:

Component 1: “Contractor and consultant actions and capabilities” with items:

CSF 49, CSF 69 and CSF 74.

Component 2: “Communication and resource management” with items: CSF 55,

CSF 56, CSF 57, CSF 65, CSF 66 and CSF 67.

Component 3: “Site management” with items: CSF 79, CSF 80 and CSF 81.

Component 4: “Coordination” with items: CSF 61, CSF 62, CSF 63 and CSF 64.

Component 5: “Client commitment” with items: CSF 48, CSF 50 and CSF 73.

The proposed naming of the extracted components was discussed with experts and

academics to validate the naming of the principal components. Figure 4.12 Below


variance and eigenvalue of each component.

Figure 4. 12: Final components extracted from factor analysis for CSFs in phase 4





Implementation phase


Component 1

Contractor and consultant actions and capabilities

Eigenvalue: 8.14

Component 2

Communication and resource management

Eigenvalue: 1.45

Component 3

Site management

Eigenvalue: 1.31

Component 4

Coordination

Eigenvalue: 1.16

Component 5

Client commitment

Eigenvalue: 1.03

161




is the minimum acceptable level. Preferably, alpha will be 0.70 or higher (Field, 2009;

Weiers, 2011; Garson, 2013). According to results which were tabulated in Table 4.31,

Cα for component 1 is 0.79; Cα for component 2 is 0.83; Cα for component 3 is 0.79; Cα


acceptable.

Table 4. 31: Factor loadings for a five-component model CSFs of implementation phase


Fac

tor

load

ing

Eig

enval

ues

Var

iance

%

expla

ined

Cro

nbac

h's

Alp

ha

(Cα

)

Component 1: Contractor and consultant actions and capabilities

CSF 74 Consultant and contractor commitment to

continuous improvement.

0.77

8.14 14.15 0.79 CSF 49 Past relevant experience of contractor in

execution similar projects.

0.72

CSF 69 Annual measuring of KPIs. 0.54

Component 2: Communication and resource management

CSF 57 Training the human resources in the skills

demanded by the project. 0.77

1.45 14.06 0.83

CSF 55 Project manager commitment to meet cost

quality and time of project. 0.64

CSF 67 Effective project control , such as

monitoring, updating plans and feedback. 0.59

CSF 66 Timely and effective conflict resolution. 0.55

CSF 65 Annual organized meetings related to

project activities for all participants. 0.54

CSF 56 Adequacy and effective management of

project financial and material resources. 0.50

Component 3: Site management

CSF 60 Availability of enough staff in project site

according to works requirements.

0.75

1.31 13.97 0.79 CSF 80 Saving as built drawings of the project. 0.68

CSF 79 Continuous revision of project shop

drawings and approve them fast.

0.66

162

Table 4. 31: Factor loadings for a five-component model CSFs of implementation phase


Fac

tor

load

ing

Eig

enval

ues

Var

ian

ce %

exp

lain

ed

Cro

nb

ach

's

Alp

ha

(Cα

)

CSF 81 Consultant and contractors involvement in

project operating and maintenance plan

after project execution.

0.59

Component 4: Coordination

CSF 62 Collaborative team work environment. 0.80

1.16 12.74 0.81

CSF 63 Mutual trust and understanding between


0.71

CSF 61 Top management support for project

workers.

0.62

CSF 64 Social relationships and coordination

between project participants.

0.54

Component 5: Client commitment

CSF 48 The client follows project implementation

regularly.

0.75

1.03 10.53 0.71 CSF 73 Natural climates like winds, rains and high

temperature.

0.68

CSF 50 Appropriate safety practices during project

execution.

0.52





Fourteen insignificant factor loadings (< 0.5) are blanked



Component 1: Contractor and consultant actions and capabilities

First component named "Contractor and consultant actions and capabilities" explains

14.15 % of the total variance and contains three items. The majority of items had

relatively high factor loadings (≥ 0.54). The three items are as follows:

1. Consultant and contractor commitment to continuous improvement CSF 74, with


2. Past relevant experience of contractor in execution similar projects CSF 49, with


163

3. Annual measuring of KPIs CSF 69, with factor loading=0.54.

Results from Table 4.31 showed that CSF “Consultant and contractor commitment to

continuous improvement” was the highest loaded factor of this component with factor

loading =0.77. This CSF indicated that continous improvement has a significant

important due to the fast development in technology and in order to keep up with clients

expectations. Globalization put the world in new phase of evolution and to moderate this

phenomenon it is important to improve the capabilities in order to compete successfully

in construction industry. In Palestine contractor and consultant capabilities still behind

the required since ports are closed and few modern equipment's were entered. Also at

human resource level, contractors and consultants suffer from poor training and

instability in workers experience since the materials prohibited to enter for long times

which enforce construction workers turns to other crafts. This result in line with Davies

(2002) in UK who concluded that continuous improvement of project management

processes and practices represents the 5th

and highest phase of project management

maturity in an organization. And also similar to this results in Taiwan Chen and Chen

(2007) stated that the CSF commitment to continuous improvement had a high loadings

and they ranked it as the 12th

CSF in importance.

The next high factor loading in this component was CSF “Past relevant experience of

contractor in execution similar projects” with factor loading=0.72. In implementation

phase the contractor plays the main role so his experience should coincide with his

importance role. Past relevant experience of the contractor may enhance project

performance since non value added activities will be known to him so he have possible

advantage to minimize project time and cost. In Palestine there were some projects which

executed for first time however due to political situation internal contractors will execute

the projects and preferably to choose the experienced ones. In Malaysia Sambasivan and

Soon (2007) found that the 3rd

cause of delay was inadequate contractor experience. Also

in UK Alzahrani and Emsley (2013) concluded that the CSF contractor past relevant

experience account high factor loading and they concluded that it was better to select a

contractor who has the requisite experience from a similar project type.

164

Component 2: Communication and resource management

Second component named " Communication and resource management" explains 14.06

% of the total variance and contains six items. The majority of items had relatively high

factor loadings (≥ 0.50). The six items are as follows:

1. Training the human resources in the skills demanded by the project CSF 57, with


2. Project manager commitment to meet cost quality and time of project CSF 55, with


3. Effective project control , such as monitoring, updating plans and feedback CSF 67,


4. Timely and effective conflict resolution CSF 66, with factor loading=0.55.

5. Annual organized meetings related to project activities for all participants CSF 65,


6. Adequacy and effective management of project financial and material resources CSF

56, with factor loading=0.50.

Results from Table 4.31 found that CSF “Training the human resources in the skills

demanded by the project” was the highest factor loading item of component 2 with factor

loading of 0.77. This CSF indicated that in Palestine training is a basic requirement of

public projects success. Generally in Palestine and especially in Gaza strip ports close for

long time which effect on construction human resources experience and numbers. To

overcome this problem training is important issue however Palestine suffer from the

shortage of good trainers in some fields of construction industry. Different studies results

considering this factor as one of most important CSFs such as in China Lu and Yuan et al

(2010) found out that most workers in the construction industry in China were from rural

areas who have not been trained sufficiently before starting work on construction

projects. Lu and Yuan et al (2010) findings indicated that the training is the 8th

most CSF.

Also in Taiwan Yang et al (2015) grouped the CSFs into four components in which

training was the most high loaded factor in component one of their study.

The next high factor loading CSF was “Project manager commitment to meet cost quality

and time of project” with factor loading=0.64. This CSF indicated that project manager's

165

commitment plays important role in achieving project success. In Palestine project

manager plays a vital rule in public construction project since he is the one who links the

different stakeholders and the one who monitors project implementation. Similar to this

result in Vietnam Nguyen et al (2004) the most CSF effect on construction projects was

the competent project manager and team. Also in Malaysia Omran and Mamat (2011)

concluded that project manager commitment in works was the most important success

factors affecting the cost performances of projects.

Component 3: Site management

Third component named "Site management" explains 13.97 % of the total variance and

contains four items. The majority of items had relatively high factor loadings (≥ 0.59).

The four items are as follows:

1. Availability of enough staff in project site according to works requirements CSF 60,


2. Saving as built drawings of the project CSF 80, with factor loading =0.68.

3. Continuous revision for the project shop drawings and approve them fast CSF 79,

with factor loading =0.66.

4. Consultant and contractors involvement in project operating and maintenance plan

after project execution CSF 81, with factor loading=0.59.

Results from Table 4.31 stated that the highest factor loading of the third component was

CSF “Availability of enough staff in project site according to works requirements” with

factor loading= 0.75. This item indicated that the human resources in project site should

be available from different crafts and specialists. The shortage or surplus in human

resources numbers in the site will affect project performance by increasing project time

and cost, decreasing the profitability of project or increase the difficulty of managing and

directing them. In Palestine contractor employed few number in order to decrease project

costs and this affects projects quality. Also most contractors did not hire a safety

specialists for example. In line with this result in Nigeria Ihuah et al (2014) indicated that

adequate resources for project are identified as common in four of the frameworks and

ranked as 4th

in the set of the critical success factors for project success. Not far results in

Taiwan Yang et al (2015) found that the relationship is stronger for projects with fewer

166

groups members than it was for those with more groups members which affect quality

and stability and project performance.

The next high factor loading CSF was “Saving as built drawings of the project” with

factor loading=0.68. This CSF indicated was added by experts and it is cleared that it is

important in Palestine. May be due to the extensive amount of variation orders which

happens in Palestinian projects as built drawings should be important CSF. As built

drawings facilitate monitoring, save contractor rights, and important to maintenance

phase.

Component 4: Coordination

Fourth component named " Coordination" explains 12.74% of the total variance and

contains four items. The majority of items had relatively high factor loadings (≥ 0.54).

The four items are as follows:

1. Collaborative team work environment CSF 62, with factor loading=0.80.

2. Mutual trust and understanding between project participants CSF 63, with factor

loading =0.71.

3. Top management support for project workers CSF 61, with factor loading =0.62.

4. Social relationships and coordination between project participants CSF 64, with


Results from Table 4.31 revealed that the highest factor loading of the fourth component

was “Collaborative team work environment” with factor loading= 0.80 followed by CSF

"Mutual trust and understanding between project participants" with factor loading=0.71.

All levels of staff in projects must be engaged in work and its success can be seen as

collective effort which requires cooperation from everyone involved. Generally in

Palestine collaboration and good relations between project team exists. Similar results in

Alhaadir and Panuwatwanich (2011) study in Australia which had used AHP and

indicated that teamwork was ranked as 4th

CSF in importance and effect on successful

safety program on construction projects. Also in line with this result in Finland,

Netherlands and Switzerland Verburg et al (2013) concluded that

communication/collaboration within the team: i.e., clear communication rules, openness,

167

and trust was the most important condition that needs to be fulfilled for successful project

execution.

Component 5: Client commitment

Fifth component named "client commitment" explains 10.53% of the total variance and

contains three items. The majority of items had relatively high factor loadings (≥ 0.52).

The three items are as follows:

1. The client follows project implementation regularly CSF 48, with factor

loading=0.75.

2. Natural climates like winds, rains and high temperature CSF 73, with factor loading

=0.68.

3. Appropriate safety practices during project execution CSF 50, with factor loading

=0.52.

Results from Table 4.31 showed that the highest factor loading of the fifth component

was CSF “The client follows project implementation regularly” CSF 48 with factor

loading= 0.75. According to that it is very important for client to follow implementation

phase in order to guarantee that project is executed within the required goals. In Palestine

public construction projects clients engineers have good experience in construction

industry such as MPWH, MOLG, UNRWA and UNDP and they supervised their projects

periodically.. In China Chan et al (2004b) considered this factor as CSF without ranking

the factors. In Nigeria Ihuah et al (2014) ranked this factor as the 3rd

critical project

management success factors for sustainable social housing.

The next high factor loading CSF was “Natural climates like winds, rains and high

temperature”. This attribute indicated that it is important to take natural climates on

consider during planning and execution phases. Forecasting project time and schedule

preparing affected directly with this factor. Also natural climates have an important effect

on construction works like concrete works and streets paving. In Palestine seasons

weather mostly expected but in recent years temperature degrees rises and rain quantity

increased which affect the projects implementation phase and. But generally, CSF has

moderate affect in Palestine. In Ghana Frimpong et al (2003) ranked unexpected

168

geological conditions as the 12th

CSF which causes delays and cost overrun on

construction industry. also in Malaysia Yong and Mustaffa (2013) considered weather

conditions as critical factors with moderate effect and ranked it as 44th

important CSF.

4.4.2.4 Summary of factor analysis for CSFs

Factor analysis were used in order to reduce the number of factors and group the related

CSFs in components. The number of used CSFs in the questionnaire were 81 divided

into four phases. After using factor analysis 29 CSF removed and 52 CSF remained. Also

each of phases 1, 2 and 3 divided into three components except phase 4 divided into five

components. Table 4.32 summarized the results of factor analysis.

Table 4. 32: Factor analysis summary of CSFs

Phase Components No. of CSFs in

each component

CSFs No.

before factor

analysis

CSFs no.

after factor

analysis

No. of

removed

CSFs

Conceptualizing and

preparation phase

Component1 4

12 8 4 Component 2 2

Component 3 2

Planning and designing

phase

Component1 7


Component 3 2

Tendering and contracting

phase

Component1 6


Component 3 2

Implementation phase

Component1 3

34 20 14

Component 2 6

Component 3 4

Component 4 4

Component 5 3

Sum 14 52 81 52 29

169

4.4.3 Ranking of CSFs which affect public construction projects

A list of the 81 CSFs was adopted from literature and pilot study. These CSFs were

subjected to the views of respondents. In the previous section factor analysis was used

and in this section another analysis will be used like mean value, RII, SD, test value, P-

value, and ranks of each CSF. Analysis of this section considered to be the answer of the

second question of this study which was Question 2: What is the ranking of CSFs

according to their degree of importance?.

RII was calculated to weight each CSFs (from CSF 1 to CSF 81) according to the

numerical scores obtained from the questionnaire responses and results have been ranked

from the highest degree (The most important CSF) to the least degree (The most

vulnerable CSF). Table (A 7) in Appendix VI shows RIIs and ranks of CSFs,

respectively. The numbers in the “rank” column represent the sequential ranking. It worth

mentioning that ranking of CSFs was based on the highest mean, RII, and the lowest SD.

If some items have similar means as in the case of (CSF 9 and CSF 10) ranking will be

depended on the higher RII. More precisely, although CSF 9 and CSF 10 have the same

mean, but CSF 9 was ranked higher than CSF 10 because it has higher RII. Also if some

items have similar means and RII as in the case of (CSF 15 and CSF 19) ranking will be

depended on the lowest SD. More precisely, although CSF 15 and CSF 19 have the same

mean and RII, but CSF 15 was ranked higher than CSF 19 because it has higher SD.

Items were categorized with ratings from 92.55% to 75.51% (Figures 4.12 – Figure 4.16

show the RII for CSFs in the different phase.

170

The mean of the CSF “Project feasibility and priority for the society” equals 4.63

(92.55%), Test-value = 45.65, and P-value=0.000 which is smaller than the level of

significance 0.05. The sign of the test is positive, so the mean of this factor is

significantly greater than the hypothesized value 3. It can be concluded that the

respondents agreed to that this CSF is very important and in the same time the most

important factor that affect Palestinian public construction projects. The main importance

of feasibility study in Palestine is that donors used it to decide the amount of fund. Since

most Palestinian public projects are funded from donors so it is recommended to give

enough time and consult experts when making feasibility study without neglecting to

share the community. This study result is not the same as the majority of previous studies

since they were not considered this CSF as the most important one. In South Korea Son

and Kim (2014) concluded that the cost and schedule performance of green building

projects was highly dependent on the quality of definition in the pre-project planning

phase.

Results also indicated that the mean of the CSF “Coordinating with related formal

parties such as (municipalities, electricity companies, ministries,… etc.)” equals 4.57



significantly greater than the hypothesized value 3. It can be concluded that the

respondents agreed to that this CSF is very important and in the same time the second

most important factor that affect Palestinian public construction projects. This factor was

not detailed like here in previous studies. The researcher in piloting study detailed it

based on expert A, expert C and expert F suggestion. Experts said projects faced many

difficulties on this region specially since permits take long time and many conflicts

appear with municipalities like land property. In this study respondents agree with

experts since this CSF is ranked as the 2nd

important CSF.

The mean of the CSF “Documentation the preparation meetings in details” equals 4.53



171

significantly greater than the hypothesized value 3. Results revealed that the respondents

agreed to that this CSF is very important and in the same time the third most important

factor that affect Palestinian public construction projects. This factor was not found like

here in previous studies. The researcher in piloting study added it based on expert A,

expert B suggestion. Experts said projects faced many difficulties due to poor

documentation on construction projects in Palestine and as found here also respondents

agree with them since it is ranked as the 3rd

important CSF.

The mean of the CSF “Project manager commitment to meet cost quality and time of

project” equals 4.46 (89.26%), Test-value = 36.32, and P-value=0.000 which is smaller

than the level of significance 0.05. The sign of the test is positive, so the mean of this

factor is significantly greater than the hypothesized value 3. According to that results

indicated that respondents agreed to that this CSF is very important and in the same time

the fourth most important factor that affect Palestinian public construction projects. In

contract to this study in China Chan et al (2004b) considered this factor as CSF without

ranking the factors. Similar indication in Australia Orangi et al (2011) study who ranked

the lack of communication between client and project team as the 3rd

cause of projects

delay. Also in line with this result in Nigeria Ihuah et al (2014) ranked this factor as the

3rd

critical project management success factors for sustainable social housing.

The mean of the CSF “The client follows project implementation regularly” equals 4.46



significantly greater than the hypothesized value 3. That means majority of respondents

agreed to that this CSF is very important and in the same time the fifth most important

factor that affect Palestinian public construction projects. In Palestine project managers is

new phenomenon. The need for finding committed project manager rises from the

complex environment and multi stakeholders of the public projects in Palestine. Not far

study in Vietnam Nguyen et al (2004) concluded that competent project manager and

team is the most important CSF. Also in Nigeria Ihuah et al (2014) consider the project

manager performance as the most important CSF affected public construction projects.

Also Hong Kong, Australia, Singapore, China and Greece Zou et al (2014) indicated that

172

the most essential successful factor for effective relationship management in PPP was

commitment and participation of senior executives.

At phases level the mean of the tendering and contracting phase “project tendering and

contracting phase” equals 4.28 (85.53%), Test-value = 45.43, and P-value=0.000 which

is smaller than the level of significance 0.05. The sign of the test is positive, so the mean

of this component is significantly greater than the hypothesized value 3. The respondents

agreed to that tendering and contracting phase is the most important phase that affects

Palestinian public construction projects. Tendering and contracting phase divided

consists of 17 CSFs. In China Lu et al (2008) used factor analysis and he classified 35

CSFs into 8 clusters bidding is one of them and it ranked as 6th factor loading cluster. On

South Africa Park (2009) ranked the clarity of contract as the most important CSF affect

the construction projects. Another study in china by Chan et al (2010) grouped 18 CSF

into 5 groups and ranked transparent and efficient procurement process group as the 3rd

high loading component. In this study this phase was ranked as most important phase

may be the basic reasons are that in this phase most agreements will be formulated,

project parties will be determined and the relations, authorities, rights and responsibilities

between project parties will be determined and begun in this phase. Any fault in pricing

bids, choosing the appropriate contractor, writes all needed provisions will effect on

project implementation and results. So it is recommended on this phase for all parties to

work together to guarantee the project success.

173

4.5 KPIs and CSFs relationship

This part aims to accomplish the third objective of this study by evaluating the

relationship between KPIs and CSFs in the public construction projects. For that,

different analysis processes and tests were held in order to formulate the basic

conclusions related to the third objective of this study. Hypothesis testing will be

conducted to answer Question 3: Are there a significant relationship between KPIs and

the degree of importance of CSFs on Palestine?.

Hypothesis 1 "H0": Null hypothesis: There is no significant statistical relationship at

level (α>= 0.05) in respondents evaluations for CSFs affected public construction

projects and the degree of importance of KPIs in Palestine.

Hypothesis 1 "H1": Alternative hypothesis: There is significant statistical relationship at


projects and the degree of importance of KPIs in Palestine.

Table 4.33 showed that the p-value (Sig.) of correlation coefficient between CSFs and the

degree of importance of KPIs in Palestine less than 0.05, so the correlation coefficient is

statistically significant at 0.05. As a result the null hypothesis is rejected and the

alternative hypothesis is accepted. That means there exists a significant relationship

between CSFs and the degree of importance of KPIs in Palestine. Many researches in

developing countries (Sambasivan and Soon, 2007; Chen and Chen , 2007; Lu et al,

2008; Cho et al, 2009; Enshassi et al, 2009a; Omran and Mamat , 2011; Chou et al ,

2013; Mir and Pinnington, 2014; Son and Kim, 2014; Shehu et al, 2014; Alias et al, 2014

and Yang et al, 2015) and developed countries (Andersen et al, 2006; Ahsan and

Gunawan, 2010; Orangi et al, 2011; Hwang et al, 2013 and Zavadskas et al, 2014) found

a relationship between The CSFs and KPIs. Also in this study the positive relationship

between CSFs and KPIs was found and this enhance the project parties to consider CSFs

in order to guarantee better project performance.

174



projects and the degree of importance of KPIs in Gaza Strip.

Hypothesis 2 "H1": Alternative hypothesis: There is significant statistical relationship at


projects and the degree of importance of KPIs in Gaza Strip.

Table 4.33 showed that the p-value (Sig.) of correlation coefficient between CSFs and the

degree of importance of KPIs in Gaza Strip less than 0.05, so the correlation coefficient is

statistically significant at 0.05. As a result the null hypothesis is rejected and the


between CSFs and the degree of importance of KPIs in Gaza Strip.



projects and the degree of importance of KPIs in West Bank.

Hypothesis 3 "H1": alternative hypothesis: There is significant statistical relationship at


projects and the degree of importance of KPIs in West Bank.

Table 4.33showed that the p-value (Sig.) of correlation coefficient between CSFs and the

degree of importance of KPIs in West Bank less than 0.05, so the correlation coefficient

is statistically significant at 0.05. As a result the null hypothesis is rejected and the


between CSFs and the degree of importance of KPIs in West Bank.

175

Table 4. 33: Correlation coefficient between CSFs and the degree of importance of KPIs

Item

Gaza Strip West Bank Palestine

Pearson

Correlation

Coefficient

P-

Value

(Sig.)

Pearson

Correlation

Coefficient

P-

Value

(Sig.)

Pearson

Correlation

Coefficient

P-

Value

(Sig.)

Relationship between CSFs

related to conceptualizing and

preparation phase and the

degree of importance of KPIs

0.67 0.00* 0.37 0.00* 0.58 0.00*


related to planning and

designing phase and the


0.63 0.00* 0.38 0.00* 0.59 0.00*


related to tendering and

contracting phase and the


0.56 0.00* 0.23 0.008* 0.51 0.00*

Relationship between factors

related to implementation

phase and the degree of

importance of KPIs

0.58 0.00* 0.21 0.016* 0.50 0.00*

* Correlation is statistically significant at 0.05 levels

4.6 Differences among respondents toward the analysis of CSFs and KPIs on

Palestine

In this part the differences among respondents will be developed toward the analysis of

CSFs and KPIs due to place of resident, organization type, projects size and years of

experience in the construction industry of Palestine. This part will answer the Q4 of the

study. Question 4: Are their differences among respondents toward the analysis of CSFs

and KPIs due to place of resident, organization type, projects size and years of experience

in the public construction industry of Palestine?

Place of resident

Hypothesis 4 "H0": Null hypothesis: There is no differences at level (α>= 0.05) in


place of resident.

176



place of resident.

Table 4.34 showed that the p-value (Sig.) was smaller than the level of significance =

0.05 for the fields "The degree of importance of KPIs", "Factors related to

conceptualizing and preparation phase", "Factors related to planning and designing

phase", "Factors related to tendering and contracting phase" and "Factors related to

implementation phase", then as a result the null hypothesis is rejected and the alternative

hypothesis is accepted. That means there is significant difference among the respondents

toward these fields due to place of resident. So place of resident has an effect on

respondents' evaluation. The mean value for West Bank respondents is higher than Gaza

Strip respondents, then it was concluded that respondents on West Bank agreed on the

importance of the mentioned KPIs and CSFs much more than respondents on Gaza Strip.

Table 4. 34: Independent Samples T-test of the fields and their p-values for Place of resident

No. Field

Means Test

Value Sig.

Gaza

Strip

West

Bank

1. The degree of importance of KPIs 4.00 4.27 -4.56 0.000*

2. CSFS related to conceptualizing and preparation

phase 4.15 4.33 -3.27 0.001*

3. CSFs related to planning and designing phase 4.07 4.40 -5.89 0.000*

4. CSFs related to tendering and contracting phase 4.15 4.47 -5.92 0.000*

5. CSFs related to implementation phase 4.11 4.46 -6.30 0.000*

* The mean difference is significant a 0.05 level

Organization type




177




Table 4.35 showed that the p-value (Sig.) was smaller than the level of significance 0.05

for the fields "The degree of importance of KPIs", "Factors related to planning and

designing phase", "Factors related to tendering and contracting phase" and "Factors

related to implementation phase", then as a result the null hypothesis is rejected and the

alternative hypothesis is accepted for those phases. That means there is significant

difference among the respondents toward these fields due to organization type. The mean

for the category "consultation office" respondents have the highest among the other

organizations type, then we concluded that the category "consultation" respondents

agreed on the importance of the mentioned KPIs and CSFs much more than the other

organization type.

For "Factors related to conceptualizing and preparation phase" field the p-value (Sig.)

was greater than the level of significance 0.05. then as a result the null hypothesis is

accepted and the alternative hypothesis is rejected for this phase. That means there was

insignificant difference among the respondents regarding these fields due to organization

type. It was concluded that the respondents' organization type has no effect on this field.

Table 4. 35: ANOVA test of the fields and their p-values for organization type

N

o. Field

Means

Test

Value Sig.

Govermental

organization

Non-

governmental

organization

Consultation

office

1. The degree of importance

of KPIs 4.10 3.88 4.19 9.37

0.000

*

2.

CSFS related to

conceptualizing and

preparation phase

4.20 4.07 4.28 4.49 0.012

*

3. CSFs related to planning

and designing phase 4.21 3.99 4.27 7.92

0.000

*

4. CSFs related to tendering

and contracting phase 4.29 4.12 4.33 4.80

0.009

*

5. CSFs related to

implementation phase 4.22 4.04 4.33 8.42

0.000

* * The mean difference is significant a 0.05 level

178

Projects size







Table 4.36 showed that the p-value (Sig.) is smaller than the level of significance 0.05 for

the fields “Factors related to planning and designing phase", "Factors related to tendering

and contracting phase" and "Factors related to implementation phase”, then as a result the

null hypothesis is rejected and the alternative hypothesis is accepted for those phases.

That means there is significant difference among the respondents toward these fields due

to projects size. So projects size has an effect on this phase. The mean for the category "

Less than 5 M$" respondents have the highest among the other projects size, then we

conclude that the category " Less than 5 M$ " respondents agreed on the importance of

the mentioned KPIs and CSFs much more than the other projects size.

For "The degree of importance of KPIs" and "Factors related to conceptualizing and

preparation phase" fields the p-value (Sig.) was greater than the level of significance

0.05. then as a result the null hypothesis is accepted and the alternative hypothesis is

rejected for this field. That means there is insignificant difference among the respondents

regarding this field due to projects size. It is concluded that the respondents' projects size

has no effect on these fields.

179

Table 4. 36: ANOVA test of the fields and their p-values for projects size

No. Field

Means

Test

Value Sig. Less

than 5

M$

From 5 -

10 M$

From 11

- 20 M$

More

than 20

M$


of KPIs 4.16 4.11 4.01 4.09 0.95 0.419

2.

CSFS related to

conceptualizing and

preparation phase

4.28 4.22 4.06 4.22 2.08 0.104


and designing phase 4.28 4.21 3.97 4.20 3.99 0.008*


and contracting phase 4.35 4.32 4.10 4.25 3.09 0.028*

5. CSFs related to

implementation phase 4.34 4.28 4.07 4.21 3.44 0.017*


Years of experience in the construction industry



respondents years of experience in construction industry.



respondents years of experience in construction industry.

Table 4.37 showed that the p-value (Sig.) was greater than the level of significance 0.05

for the field “Factors related to implementation phase”, then as a result the null

hypothesis is rejected and the alternative hypothesis is accepted for those fields. That

means there is insignificant difference among the respondents toward this field due to

years of experience in the construction industry. We conclude that the years of experience

in the construction industry e has no effect on this field.

For the other fields, the p-value (Sig.) was smaller than the level of significance 0.05,

then as a result the null hypothesis is accepted and the alternative hypothesis is rejected

for those fields. That means there is significant difference among the respondents toward

180

these fields due to years of experience in the construction industry. So years of

experience in the construction industry has an effect on the other fields. The mean for the

category " From 16 -20 years " respondents have the highest among the other years of

experience in the construction industry, then it was concluded that the category " From 16

-20 years " respondents agreed on the importance of the mentioned KPIs and CSFs much

more than the other years of experience in the construction industry.

Table 4. 37: ANOVA test of the fields and their p-values for years of experience in the

construction industry

No. Field

Means

Test

Value Sig. From 5

-10

years

From 11

-15

years

From 16

-20

years

More

than 20

years


of KPIs 4.12 4.03 4.30 3.93 3.02 0.030*

2.

CSFS related to

conceptualizing and

preparation phase

4.24 4.10 4.39 4.08 3.25 0.022*


and designing phase 4.23 4.02 4.37 4.10 3.87 0.010*


and contracting phase 4.30 4.17 4.43 4.10 3.15 0.026*

5. CSFs related to

implementation phase 4.28 4.13 4.38 4.11 2.53 0.058


4.7 Summary of results

Results of analysis showed that all the thirteen mentioned KPIs considered to be

important from respondents' viewpoint. Figure 4.7 showed that all KPIs RII above.

71.81%. Also all the 81 CSFs which derived from factor analysis and respondents

evaluation are considered to be important factors that affect the public construction

projects as shown in Figure 4.8 since their RII above 75.51%.

181

Figure 4. 13: The RII of the importance KPIs as evaluated by respondents

Figure 4. 14: The RII of the importance CSFs as evaluated by respondents

0

20

40

60

80

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13

RII

KPIs

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85

RII

CSFs

182

Chapter 5

Conclusions and

Recommendations

183

5. Chapter 5: Conclusions and recommendations

This chapter summarizes the research aims and results and provides recommendations

and conclusions for the success factors that affecting public construction projects and

their relation to the key performance indicators. Research contribution and suggested

areas of future research were discussed in this chapter. By revising the research

objectives and key findings, an overview will be critically discussed to assess to which

extent the research objectives were met.

In achieving the aim of the research, three main objectives have been outlined and

achieved through the findings of the analyzed collected questionnaires. These objectives

are related with the research questions that were developed to increase one’s knowledge

and familiarity with the subject. The outcomes were found as followings:

Outcomes related to objective one: identification and evaluation of the key

performance indicators (KPIs) of public construction projects.

Key performance indicators used to compare the actual projects results in terms of cost,

time, quality, satisfaction and so on with the planned. Most construction projects in

Palestine and other countries especially developing ones suffer from poor projects

performance such as delay, cost overrun. Intensive literature review was used to specify

project KPIs. Initially 31 KPI were collected and after pilot study KPIs reduced to 13.

In order to minimize KPIs and group them into components factor analysis was used. As

a result the 13 KPIs reduced to 11 KPIs and grouped into three groups namely: 1) project

quality and environmental impact, 2) satisfaction and reputation of project parties and 3)

overall cost and time.

This result indicated that in Palestine quality and environmental impact component was

the highest component accounted variance equal to 24.92%. This component included

quality, environmental impact, safety and sustainability indicators. The second

component which accounted variance equal to 24.75% was satisfaction and reputation of

project parties and it contains KPIs about party's reputation, party's satisfaction, variation

184

orders and disputes and litigations. The third component which consists of KPIs concern

in cost and time was the lowest component accounted variance equal to 13.05%.

In order to rank and evaluate the importance of each KPIs descriptive analysis were used

such as mean, SD and RII. According to that the 13 KPIs was ranked and results revealed

that the top three most important KPIs in Palestine were 1) project conformity to quality

and technical specifications standards, 2) actual project costs comparing with estimations

and 3) actual project execution time comparing with scheduled. And the least important

KPI was number and size of disputes and litigations.

The results showed that the most important KPIs were quality; time and cost which

means that in Palestine construction industry the highest important KPIs are the

traditional basic ones. Generally public construction projects are funded from donors in

Palestine who give high important to quality more than any other consideration. Also the

limited budget of projects from donors gives the KPI cost large importance. In addition

project duration KPIs is very important due to the uncertainty of political conditions in

Palestine like annual wars.

Results also indicated that Palestinian construction projects suffer from cost and time

overrun and the quantity and costs of variation orders are high. On other hand other

indicators like projects quality, satisfaction and ability to cover project expenditures

ranked a good evaluation.

Recommendations related to objective one: It is recommended to measure project

quality, time and cost annually since they are the most important KPIs. Quality materials

should be of a greater interest for project parties in order to improve cost, time, and

quality performance. This can be done by applying quality training and meetings that are

necessary for performing an improvement. Contractors are urged to be more interested in

sequencing of work according to schedule. In addition, contractors should have a cost

engineer in their projects to successfully control costs.

Clients, consultants and contractors should have more realistic plans and estimations of

budget and project duration to improve projects performance. Consultants are urged to

185

facilitate and expedite orders delivered to contractors to obtain better time performance

and to minimize disputes and claims. Also project parties should works together to

improve safety issues and culture.

Outcomes related to objective two: investigating the critical success factors CSFs

affecting the public construction projects

Critical success factors are the factors which have the most effect on project performance.

Intensive literature review was used to specify project CSFs. Initially 125 CSF were

collected and after pilot study CSFs reduced to 81 and they were classified according to

project life cycle into four phases. First phase was conceptualizing and preparation phase

and contained 12 CSFs. Second phase was planning and designing phase and contained

19 CSF. Thired phase was tendering and contracting phase and contained 16 CSF. And

forth phase was implementation phase and contained 34 CSF.

To reduce the number of CSF in each phase and to categorize them into components

factor analysis were used. As a result 52 CSF out of 81 CSF was remaining categorized

into 14 component and 4 phases. CSFs of conceptualizing and preparation phase reduced

to 8 and grouped into three components First component named "Client actions and

capabilities" explains 29.17 % of the total variance and contains four items. Second

component named "Project characteristics" explains 20.50% of the total variance and

contains two items. Third component named "Project feasibility and goals" explains

18.91% of the total variance and contains two items.

CSFs of planning and designing phase reduced to 13 and grouped into three components.

First component named "Planning and designing management" explains 28.72 % of the

total variance and contains seven items. Second component named "Consultant actions

and capabilities" explains 21.11 % of the total variance and contains four items. The third

component named "Client related factors" explains 11.70 % of the total variance and

contains two items.

Also CSFs of tendering and contracting phase reduced by factor analysis to 11 and

grouped into three components. First component named "Bidding and contracting

186

management" explains 26.95% of the total variance and contains six items. Second

component named "Project parties' capabilities" explains 17.40% of the total variance and

contains three items. Third component named "Client behavior" explains 17.13% of the

total variance and contains two items.

Lastly, CSFs of phase 4 reduced by factor analysis to 20 and grouped into five

components. First component named "Contractor and consultant actions and capabilities"

explains 14.15 % of the total variance and contains three items. Second component

named "Communication and resource management" explains 14.06 % of the total

variance and contains six items. Third component named "Site management" explains

13.97 % of the total variance and contains four items. Fourth component named

"Coordination" explains 12.74% of the total variance and contains four items. Fifth

component named "client commitment" explains 10.53% of the total variance and

contains three items.

Results also showed that all 81 CSFs were important since the least RII was above

75.51%. The top five most important CSFs from the respondents view affected

Palestinian project success were 1) project feasibility and priority for the society, 2)

coordinating with related formal parties such as (municipalities, electricity companies,

ministries,… etc.), 3) documentation the preparation meetings in details, 4) project

manager commitment to meet cost quality and time of project and 5) the client follows

project implementation regularly. Also the results indicated that the most important phase

was tendering and contracting phase. Generally the respondents agreed to that tendering

and contracting phase is the most important phase that affects Palestinian public

construction projects.

Recommendations related to objective two: In order to enhance the performance of

public construction projects it is recommended to prepare projects proposals carefully

since donors depend on them basically to fund projects. Also local community and other

project related parties should participate in the feasibility study of the project.

Clients, consultants and contractors should focus in tendering and conceptualizing phase

since it is the most important phase as study results showed. Contract provisions,

documentation and awarding criteria need to be modified in order to guarantee project

187

success. And it is recommended to follow transparent policy for awarding bids rather

than lowest bidder. Visiting project site, document preparation meetings and take enough

time in planning and designing phase is recommended to improve projects success.

Clients play major rule in monitoring projects implementation and they recommended to

follow up projects implementation directly in order to guarantee it is executed according

to their goals and needs.

Also it is recommended to involve consultants in projects several phases. Consultants

should consider all surrounding circumstances while estimating projects cost and time.

Also they should coordinate with projects clients especially in planning and designing

phase to understand his requirements in order to reduce changes and variation orders.

Contractors have a big duty in project success. So they recommended improving their

abilities in tendering management and competing based on criteria other than lowest

bidding. Also they should appointment qualified project managers who have leadership

skills. In addition they recommended improving their abilities continuously and using

applicable methods.

Outcomes related to objective three: evaluate the relationship between KPIs and CSFs

in the public construction projects

In this study the analysis of respondents view points on Gaza Strip and West Bank

showed there was a positive significant relationship between KPIs and CSFs.

Recommendations related to objective three: Since CSFs and KPIs are related to each

other then it is recommended to focus on the CSFs which have mentioned in this study to

guarantee good projects performance.

Research contribution to previous studies

This research aimed to investigate success factors that affecting public construction

projects and their relation to key performance indicators in Palestine. An extensive

review of literature was conducted to achieve this aim. Generally most previous studies

searched on KPIs only or CSFs only but not both. Rare studies searched on KPIs and

CSFs together. In this research both KPIs and CSFs was examined.

188

Most previous studies investigated into CSFs which effect projects success and

categorized them in different clusters without linking with project life cycle. In this

research CSFs was categorized according to project life cycle phases which can help

decision makers to focus their efforts into the mentioned CSFs of each phase rather than

focusing on all CSFs together which will facilitate understanding project needs and

priorities. Also previous studies did not investigate the relation between KPIs and all

CSFs. In this research the relation between KPIs and CSFs was investigated.

Different instruments were conducted by previous studies such as questionnaire, case

studies and brain storming. The outcomes of this research can be used to enhance projects

success by give attention to the mentioned 81 CSFs and 13 KPIs. Most of CSFs were

modified in this study to fit Palestinian situation such as focusing in feasibility and

priority of the projects to the society, and other CSFs were added such as 1) saving as

built drawings of the project, 2) local community acceptance to execute the project in

their location, 3) continuous revision of project shop drawings and approve them fast, 4)

availability and execution of material handling plans, 5) Considering operation and

maintenance requirements into project design, 6) documentation of the preparation

meetings in details and 7) the client should interprets all project requirements and

location during the bids preparatory meeting. Generally the mentioned CSFs and KPIs

can be used in any country with some modifications.

Research value

Palestinian public construction projects faced different challenges such as material

shortage, limited funds and instable political environment. Also many problems faced

public construction projects like delay, cost overrun and big variation orders. This

research can be used practically to help projects decision makers on focusing on the CSFs

which affect project performance and thus to enhance projects ability to face challenges

and problems.

The mentioned KPIs and CSFs were collected from studies conducted in developing and

developed countries and they consider to be the conclusion of different countries

applications and experience in this area. Most CSFs and KPIs were modified and some

CSFs and KPIs were added in this study to fit Palestine situation. However, the used

KPIs and CSFs in this study are not limited to Palestine and can be used into other

189

countries especially developing countries which share Palestine with the similar

challenges and problems in construction projects.

Further Research

Upon completion of the research with the given research objectives, questions and scope,

it is observed that some critical and relevant issues have not been covered by this

research. To facilitate the application of key performance indicators and critical success

factors approach in public construction projects, further researches might be conducted

such as analyzing and introducing methods to measure projects KPIs, using case studies

to evaluate CSFs effect on KPIs. This study can be used to design the case studies by

considering the factors and indicators which mentioned in. Further studies can use other

population such as contractors firms in order to have integrated view of their interests in

this subject.

190

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Appendix I: Literature reviews summary tables

202

Table A 1: Summary of KPIs researches

NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis

approach Results and findings

Background

1.

LI

et a

l (2

012)

Unit

ed S

tate

s of

Am

eric

a

To study the effects of

transaction-related issues

on project performance

const

ruct

ion o

wner

s

Ques

tionnai

re s

urv

ey

structural

equation

modeling

The findings indicated that higher

project performance can be achieved

if transaction costs were kept low;

transaction costs can be kept low if

the uncertainty in the transaction

environment is minimized; minimum

uncertainty in the transaction

environment also enhances contract

or behavior, indirectly contributing to

lower transaction costs; and the party

who can reduce the uncertainty in the

transaction environment is the

construction owner who can take

some or all of the actions.

2.

Sh

ehat

a an

d E

l-G

oh

ary

(20

12)

Eg

yp

t To improve construction

labor productivity and

projects’ performance.

Co

mp

lete

d p

roje

cts

Cas

e st

ud

y

Productivity

equations

There was no standard definition

of productivity and it is important

to define it in projects.

The key for productivity

improvement is not to complete as

many tasks as possible or to

maximize work-load, work output,

or work hours without following

the work plan.

203


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


3.

Ber

ssan

eti

and C

arval

ho

(2014)

Bra

zil To analyze the relation

between project

management maturity

and the project success

Pro

ject

man

agem

ent

pro

fess

ional

s

Ques

tionnai

re s

urv

ey

Comparative

analysis,

binary logistic

regressions

and

conceptual

modeling

Results showed that project

management maturity was

significantly related to all vertices

of the iron triangle (time, cost and

technical performance) dimensions

of success. However, it is not

related to the customer

satisfaction.

It suggests focus on efficiency

aspects rather than effectiveness.

KPI on developing countries studies

4.

Sh

enh

ar e

t al

(2001)

Isra

el

To develop a

multidimensional

framework for the

assessment of project

success.

Pro

ject

man

ager

s

Cas

e st

ud

y a

nd c

oll

ecti

on

of

stat

isti

cal

dat

a

Cross-case

comparative

analysis,

descriptive

Statistics and

Pearson

Correlation

coefficients

and factor

analysis

Project and top managers may

develop towards the need to identify

specific success dimensions for each

individual project according to its

goals, technology, business model,

strategy, and markets. In essence,

projects must be part of the strategic

thinking and the assessment of their

success must be aligned with such

thinking.

204


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


5.

Chan

et

al

(2002)

Hong K

ong

To establish criteria for

project success for a

design/build project in

construction, first by

identifying relevant

measures of project success

for a construction project to

establish a comprehensive

assessment framework for

project success for

design/build projects.

Journ

als

incl

uded

pro

ject

succ

ess

rese

arch

es

com

pre

hen

sive

revie

w o

f th

e

lite

ratu

re o

ver

10 y

ears

Contextual

analysis and

quantitative

equations

Results showed that the criteria for

project success can be divided into

objective and subjective categories,

with time, cost, quality, and satisfaction

the most significant measures.

6.

Ch

an a

nd C

han

(2004)

Hong K

ong

To develop a set of key

performance indicators

(KPIs) for measuring

construction success Journ

als

incl

uded

pro

ject

succ

ess

rese

arch

es

Co

mpre

hen

siv

e re

vie

w o

f

the

lite

ratu

re

and c

ase

study

Contextual

analysis and

comparison

analysis

Results showed that the KPIs in general

good indicators of the performance of

construction projects. They provided a

useful framework for measuring and

comparing project performance for

future studies.

205


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


7.

Ahad

zie

et a

l (2

008)

Ghan

a

To address what

constitutes the

determinants of success

in mass house building

projects (MHBPs)

Ques

tionnai

re s

urv

ey

One-sample t-

test and factor

analysis

Results showed that:

The factor scales identified four

clusters of success criteria,

namely; environmental impact,

quality, customer satisfaction and

cost and time.

With respect to MHBPs in

particular, the findings has

revealed that the expectation of the

customer is one of the critical

issues that property developers

have to contend within a

speculative venture such as in

MHBPs.

The study had also revealed the

emerging importance of

environmental issues.

8.

Ch

o e

t al

(20

09)

Ko

rea

To analyze the overall

relation-ship between

project performance and a

project’s characteristics

Mu

lti-

fam

ily

ho

usi

ng

an

d r

oad

con

stru

ctio

n

pro

ject

s

Cas

e st

udie

s

Factor analysis

and structural-

equation

modeling SEM

Results showed that SEM can identify

the project characteristics that affect the

level of project performance required by

owner in the planning stage, and is thus

expected to help facilitate the decision-

making process in the early planning

stage of a project.

206


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


9.

Al-

Tm

eem

y e

t

al

(2011)

Mal

aysi

a Proposing a framework to

categorize project success

for building projects in

Malaysia from the

contractors' perspective. Contr

acto

rs

Ques

tionnai

re

surv

ey

Factor analysis

The results indicated that a

categorization scheme for success

criteria for building projects should

include the categories of project

management success, product success,

along with market success.

10.

Ali

et

al

(2013)

Sau

di

Ara

bia

To explore the most

important indicators for

measuring company

performance as

perceived by large

building contractors

working in Saudi

Arabia. Cla

ssif

ied c

ontr

acto

rs

Ques

tionnai

re s

urv

ey

Relative

importance

index

Results showed that the traditional

financial measures can no more be

the sole determinant of firm success.

Other performance indicators such as

external customer satisfaction, safety,

business efficiency, and effectiveness

of planning are increasingly

becoming important.

207


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


11.

Lam

et

al

(2007

)

Hon g

Kong

To develop a project

success index (PSI) to

benchmark the

performance of design-

build projects from a

number of key

performance indicators

(KPIs).

Cli

ents

, co

nsu

ltan

ts a

nd m

ain

contr

acto

rs

Ques

tionnai

re s

urv

ey

Principal

components

analysis

The findings indicated time, cost,

quality and functionality should be

the principal success criteria for

design and build projects.

Benchmarking practice and

performance measures indeed

provide a reasonable indication of

the adequacy of a management

system.

KPI on developed countries studies

12.

Atk

inso

n

(19

99)

UK

to investigate how to

determine project

success

Results showed there were other

criteria in addition to iron triangle

criteria can be used to evaluate

project success like information

system, organization benefits and

stakeholder and community benefits

208


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


13.

Hughes

et

al

(2004)

Annap

oli

s To incorporate existing

Construction project

success measurements

into a technique that

accounts for the

subjective, as well as

objective, metrics in

order.

Exper

ience

d

const

ruct

ion p

roje

ct

man

ager

s

Cas

e st

udy a

nd

stru

cture

d i

nte

rvie

ws

Pearson’s

correlation

coefficients

The result was a tool that

accurately reflects the project

manager’s knowledge base and

covers the range of applicable

success metrics related to

construction projects that are not

confined to the classical objective

success metrics (cost, schedule,

performance, And safety).

14.

Bry

de

and

Robin

son (

2005)

UK

To report the findings of an

empirical study that

compares the measures of

success emphasized as

important by client and

contractor organizations. Contr

acto

r an

d

clie

nt

org

aniz

atio

ns

Ques

tionnai

re

surv

ey

(one way)

ANOVA test, chi

square and

Duncan Post Hoc

analysis

Results showed that contractors put

more emphasis on minimizing project

cost and duration, whilst clients put

more emphasis on satisfying the needs

of other stakeholders.

15.

Oji

ako e

t a

l (2

00

8)

Un

ited

Kin

gdo

m

To develop a different

understanding of project

measurement criteria

rather than time, cost

and quality.

Pro

ject

man

agem

ent

pro

fess

ion

als

Sem

i-st

ruct

ure

d

inte

rvie

ws Grounded

theory,

matrices and

coding forms

The results indicated that It is

impossible to generate a universal

checklist of criteria suitable for all

projects. Success (or failure) criteria

will differ from project to project

depending on a number of variables

including size, uniqueness, industry,

complexity and the stakeholders

involved.

209


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


16.

Yeu

ng e

t al

(2009)

Aust

rali

a To assess the success of

relationship based

construction projects in

Australia.

Const

ruct

ion

exper

ts

Del

phi

surv

ey

Four rounds of

Delphi

Questionnaires

Framework with eight KPIs which

were client’s satisfaction; cost

performance; quality performance;

time performance; effective

communications; safety performance;

aesthetics (trust and respect); and

innovation and improvement.

Table A 2: Summary of CSFs researches

NO

.

Au

tho

r/s

Co

un

try

Objectives

Ta

rget

gro

up

Met

ho

d

use

d

Analysis


CSFs on developing countries studies

210


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


17.

Har

tman

and A

shra

fi

(2004)

Om

an

to develop the simple

measurable analytic

realistic time bounded

"SMART" project

planning framework

based on research into

causes of both project

failure and success

Framework

They recognized that poor project

planning plays a major role as one

of the significant causes of project

failure. They also concluded that

good planning enabled creativity

and supported both team

formulation and effectiveness. It

brought out innovative ideas that

led to cost or time savings.

18.

Ch

an e

t a

l (2

004a)

.

Ho

ng

Ko

ng

To review of the

development of the

partnering concept in

general and identifies

critical success factors for

partnering projects from

the Hong Kong

perspective in particular.

Cli

ents

, co

nsu

ltan

ts, an

d c

ontr

acto

rs

Qu

esti

on

nai

re s

urv

ey

Factor analysis

and multiple

regression

Results showed that five of the success

factors are identified as critical in

explaining the personal perception of

partnering success from the multiple

regression results. ‘‘Establishment and

communication of conflict resolution

strategy,’’ ‘‘Willingness to share

resources among project participants,’’

‘‘Clear definition of responsibilities,’’

‘‘Commitment to win-win attitude,’’

and ‘‘Regular monitoring of partnering

process’’ proved to be essential in

bringing successful outcomes to

partnering projects.

211


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


19.

Wan

g a

nd H

uan

g

(2006)

Chin

a

Investigate to what extent

key project stakeholders

performance correlates

with project success. super

vis

ors

Ques

tionnai

re

surv

ey

Factor analysis

with varimax

rotation,

Independent

samples t –test

and Pearson

correlation

Results showed that the engineers use

relation among the key stakeholders as

the most important criterion of project

success, the stakeholder project

performance positively correlates with

each other and project owners play the

most important role in determining

project success.

20.

Lu a

nd Y

uan

et

al

(2010)

Chin

a

to identify the Critical

Success Factors (CSFs)

for Construction and

demolition waste

management in China. Pra

ctit

ioner

s,

rese

arch

ers

and

gover

nm

ent

off

icia

ls

Ques

tionnai

re

surv

ey a

nd se

mi-

stru

cture

d

inte

rvie

ws

Relative

importance

index

The results indicated that the most

important CSFs in Shenzhen (1)

regulations, (2) waste management

system (3) awareness (4) building

technologies, (5) design changes,

(6)research and development, and (7)

vocational training.

21.

Ad

nan

et

al

(20

11)

Mal

aysi

a

To determine the primary

factors which support the

successful application of

the design and build

method

Cli

ents

an

d c

on

trac

tors

Qu

esti

on

nai

re s

urv

ey

Descriptive

statistics

Results showed that client attributes

for the success of the design and build

projects in public universities are:

developing a clear understanding of

project scope, a clear brief thorough

assessment of the contractor’s

proposal, a clear understanding of

project costs, fulfilling the end-user

requirements, quality finish of the

project, completion within the time

frame as well as the budget allocated.

212


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


22.

Tab

ish a

nd

Jha

(2011)

India

To investigate success

factors of public

construction projects

Cli

ents

and

contr

acto

rs

Ques

tionnai

re

surv

ey

Descriptive

statistics

The results showed that the most

important factor for overall

performance is found to be

‘awareness of and compliance with

rules and regulations’.

23.

Abdul-

Azi

z an

d K

assi

m

(2011)

Mal

aysi

a To examine the objectives

of housing PPP, the

success and failure

factors.

Pro

ject

exec

uti

ve

and

engin

eeri

ng c

onsu

ltan

t

Ques

tionnai

re s

urv

ey,

inte

rvie

ws

and c

ase

studie

s

Descriptive

statistics

Results showed that the public

agencies desired to fulfill an array of

objectives when adopting PPP, the

most important being to enhance

organizational reputation. The success

factor which had the most impact is

action against errant developers. The

failure factor which has the most

influential is absence of robust and

clear agreement.

24.

Yu

an

d K

wo

n (

20

11

)

So

uth

Kore

a

To identify the critical

success factors (CSFs) of

such projects and to

prioritize CSFs in each

project phase so that

project promoters and

managers can

appropriately focus their

efforts.

Pro

ject

man

ager

s an

d

city

pla

nn

er,

Bra

inst

orm

ing

an

d

Del

ph

i p

roce

sses

an

d

qu

esti

onn

aire

su

rvey

Delphi rounds,

paired t-test and

Independent

two-sample t -

test

The top priority CSF of an urban

generation projects in South Korea was

minimization of conflict between

stakeholders.

213


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


25.

Yan

g e

t al

(2011)

Tai

wan

To examine the impact of

teamwork on project

performance to investigate

the relationships among

the project manager's

leadership style,

teamwork, and project

success

Pro

ject

dir

ecto

rs,

Pro

ject

pla

nner

s,

and p

roje

ct

super

inte

nden

ts

Ques

tionnai

re

surv

ey

Cluster analysis,

discriminant

analysis,

independent-

samples t tests

and two-way

ANOVAs

Results showed that the increased in

levels of leadership may enhanced

relationships among team members.

Also teamwork exhibits statistically

significant influence on project

performance.

26.

Chen

et

al

(2012)

Tai

wan

To explore the success

variables (SVs ) in

construction partnering

in Taiwan and the

relationships among these

identified SVs. H

ighly

-exper

ience

d

const

ruct

ion

pro

fess

ional

s

Ques

tionnai

re s

urv

ey Correlation

analysis using

Pearson’s

correlation

coefficient,

factor analysis

and structural

equation

modeling

Research results showed that four SVs

have a significant influence on the

success of construction partnering

which were collaborative team culture,

long-term quality perspective,

consistent objectives and resource

sharing.

214


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


27.

Ism

ail

et a

l (2

012)

Mal

aysi

a

To establish the

management factors

contributing to successful

implementation of IBS

projects from contractor

point of view.

Mai

n c

ontr

acto

r

Ques

tionnai

re s

urv

ey

The mean score

Results showed that the management

factors for successful IBS project

implementation were good working

collaboration, effective communication

channel, team members involved

during the design stage, close

relationship with suppliers, extensive

planning and scheduling, improvement

in planning and scheduling of the

project, risk management, management

of supply chain and logistics, top down

commitment, strategy and business

approach, environmentally friendly

methods, and industry marketing

strategies.

28.

Jag

boro

et

al

(20

12

)

Nig

eria

To investigate the

contribution of

construction professionals

to the budgeting process

for the infrastructure

sector.

Arc

hit

ects

, q

uan

tity

surv

eyo

rs, b

uil

der

s,

tow

n P

lan

ner

s, e

stat

e

surv

eyo

rs, en

gin

eers

Qu

esti

on

nai

re s

urv

ey

Descriptive and

inferential

statistics

Majority of projects budgeted for

execution lack adequate technical

evaluation and cost assessment as a

result of inadequate professional

involvement and this could be adduced

to be a significant problem of success

implementation of public financed

infrastructure projects in Nigeria.

215


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


29.

Yan

g e

t a

l (2

012)

Tai

wan

To assess the impacts of

information technology on

project success through

knowledge management

practice

Exec

uti

ve,

A

rchit

ect-

Engin

eeri

ng a

nd

Gen

eral

Contr

acto

r

Ques

tionnai

re s

urv

ey

Structural

equation

modeling

Results showed that knowledge

management was a key factor

influencing project performance

in terms of schedule, cost,

quality, and safety performance.

knowledge management fully

mediates the effects of IT on

project performance.

30.

Mem

on e

t al

(2013)

Mal

aysi

a

To assess the effects of

the resource related

factors on project cost in

the southern part of

peninsular Malaysia.

Ques

tionnai

re s

urv

ey

Structural

equation

modeling

technique with

partial least

square approach

Results showed that

approximately 47% of cost

overrun was influence with

resource related factors.

Effective financial management

can significantly improve the

project's success and help in

reducing the cost overrun.

31.

Yo

ng

an

d

Mu

staf

fa (

20

13)

Mal

aysi

a

To gain a renewed

understanding of the

emerging trend of CSFs

considered by various

stake-holders in the local

industry.

Dev

elo

per

s,

con

sult

ants

an

d

con

trac

tors

Qu

esti

on

nai

re

surv

ey

Kruskal-Wallis

one-way

analysis of

variance

(ANOVA)

Results showed that there were a

strong consistency among the

perception of project stakeholders in

recognizing the significance of human-

related ‘soft’ factors.

216


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


32.

Win

dap

o a

nd

Cat

tell

(2013)

South

Afr

ica

To investigate of the

challenges assumed to

influence the

performance,

development and growth

of the South African

construction industry Arc

hit

ects

, quan

tity

surv

eyors

,

const

ruct

ion

man

ager

s, p

roje

ct

man

ager

s

Des

crip

tive

surv

ey

and s

emi-

stru

cture

d

inte

rvie

ws

Mean item score

(MIS) method

Results showed that the main

challenge for construction industry in

South Africa is the increasing costs of

building materials.

33.

Ihuah

et

al

(2014)

Nig

eria

To investigate and

establish the critical

project management

success factors for the

sustainable social (public)

housing estates’ delivery/

provision in Nigeria. T

heo

reti

cal

revie

w o

f onli

ne

and

vis

ual

docu

men

t

reso

urc

es,

Docu

men

t m

ethod o

f dat

a

coll

ecti

on Content analysis

tools for

qualitatively

generated data

The study revealed that 22 critical

project management success factors

are essential for the achievement of

sustainable social (public) housing

estates’ delivery/provision in Nigeria.

These relate to: the project managers’

performance; the organization that

owns the development project; the

characteristics of the team members;

and the external project environment.

34.

Wib

ow

o a

nd

Alf

en

(20

14)

Ind

on

esia

To identify macro-

environmental critical

success factors (CSFs)

and key areas for

improvement for public-

private partnerships (PPP)

in infrastructure

development. Hig

h-r

ankin

g o

ffic

ials

An

d p

rofe

ssio

nal

s

Qu

esti

on

nai

re s

urv

ey

Gap

Analysis,

importance-

performance

analysis and

inter-rater

agreement

analysis

The results indicated that the factors

requiring immediate improvements are

all associated with commitments: to

policy continuity, financial

transparency, and corruption

eradication.

217


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


35.

Zou e

t al

(2014)

Hong K

ong,

Aust

rali

a,

Sin

gap

ore

, C

hin

a an

d

Gre

ece To identify the CSFs for

relationship management

in PPP projects.

Sen

ior

man

ager

s or

acad

emic

s

Inte

rvie

ws

and

ques

tionnai

re

surv

ey

Relative

importance

The results indicated that the essential

successful factors for effective

relationship management in PPP

included commitment and participation

of senior executives; defining the

objectives and project strategy; and

integration of the divisions of the

organization.

36.

Dv

ir e

t al

(2003)

Isra

el To examine the

relationship between

project planning efforts

and project success. E

nd-u

ser,

pro

ject

man

ager

, an

d

con

trac

ting o

ffic

e

Str

uct

ure

d q

ues

tionnai

res

and

inte

rvie

ws

Correlation

analysis

Results showed that project

success is insensitive to the level

of implementation of

management processes and

procedures, which are readily

supported by modern

computerized tools and project

management training.

Project success is positively

correlated with the investment in

requirements’ definition and

development of technical

specifications.

218


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


37.

Nguyen

et

al

(2004)

Vie

tnam

To research on project

success factors and their

interrelationships.

Des

igner

, ow

ner

,

consu

ltan

ts,

contr

acto

rs a

nd

subco

ntr

acto

rs

Ques

tionnai

re s

urv

ey

Factor analysis,

mean analysis

and Kaiser

Meyer Olkin test

The results showed that:

most critical factors are human

related.

The most CSF’s are competent

project manager and team,

inadequate funding, commitment

to project and availability of

resources.

38.

Chan

et

al

(2004

b)

Hong

Kong

To develop a conceptual

framework on critical

success factors CSFs maj

or

journ

als

in

the

const

ruct

io

n f

ield

Com

pre

he

nsi

ve

revie

w o

f

the

lite

ratu

re

Contextual

Analysis

The results was a conceptual

framework that includes and regroups

the identified variables affecting

project success.

39.

To

or

and

Og

un

lana

(2008)

Thai

land To explore the inter-

relationships between

various critical success

factors con

stru

ctio

n

pro

fess

ional

s

Qu

esti

onnai

re

surv

ey a

nd

sem

i-

stru

cture

d

inte

rvie

ws Factor analysis

and analysis of

variance

(ANOVA)

The results was a formulation of four

factor groupings which were together

called critical COMs of success and

were labeled as comprehension,

competence, commitment, and

communication, respectively.

40.

Ak

sorn

an

d

Had

iku

sum

o

(20

08)

Th

aila

nd

To assess and prioritize

the degree of influence of

those success factors have

on the safety programs as

perceived by the

respondents.

Med

ium

an

d

larg

e sc

ale

con

stru

ctio

n

pro

ject

s

Qu

esti

on

nai

re

surv

ey a

nd

cas

e

stu

dy

Factor analysis

Results showed that the most

influential factor on the safety

programs was management support.

219


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


41.

Yan

g e

t al

(2009)

Hong K

ong

To identify CSFs

associated with

stakeholder management

in construction projects,

and explore their ranking

and underlying

relationship. Pro

ject

man

ager

s

Ques

tionnai

re

surv

ey

Factor analysis

Results showed that the top three

ranked factors for stakeholder

management were “managing

stakeholders with social

responsibilities”, “assessing the

stakeholders' needs and constraints to

the project”, and “communicating with

stakeholders properly and frequently”.

42.

Par

k (

2009)

South

Kore

a

To identify the CFs

influencing whole life

performance of a

construction project and

evaluate their relative

importance

Cli

ents

, co

ntr

acto

rs

and s

ubco

ntr

acto

rs

Ques

tionnai

re s

urv

ey

Relative

importance

index, weighted

average and

Spearman’s rank

correlation

coefficients

Results showed that the most critical

individual factors were “clarity of

contract” scope; “fixed construction

period”; “precise project budget

estimate”; “material quality”;

“mutual/trusting relationships”;

“leadership/team management”; and

“management of work safety on site”.

43.

Ng

et

al

(20

09

)

Ho

ng

Ko

ng

. To identify and classify

subcontractor CSFs from

the perspective of the

principal stakeholders in

the construction industry

of Hong Kong.

Cli

ents

,

con

sult

ants

,

mai

n c

ontr

acto

rs

and

sub

contr

acto

rs

Qu

esti

on

nai

re

surv

ey

Factor analysis,

arithmetic

means and rank

orders, and ne-

way ANOVA

test

Results showed that the top five CSFs

identified in the study were ‘‘timely

completion”, ‘‘relationship with main

contractor/client/consultant”, , ‘‘profit

” , ‘‘cash flow ”, and ‘‘adoption of

new technologies/methodologies ”.

220


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


44.

Chan

et

al

(2010)

Chin

a

To explore the critical

success factors CSFs

necessary to conduct PPP

projects.

Indust

rial

pra

ctit

ioner

s

Fro

m t

he

publi

c,

pri

vat

e, a

nd o

ther

sect

ors

Ques

tionnai

re s

urv

ey

Factor analysis

Results showed that 18 CSFs are

grouped into five groups: stable

macroeconomic environment; shared

responsibility between public and

private sectors; transparent and

efficient procurement process; stable

political and social environment; and

judicious government control.

45.

Alh

aadir

and

Pan

uw

atw

anic

h

(2011)

Sau

di

Ara

bia

To identify the most

critical factors affecting

the implementation of

safety programs among

the construction

companies.

Exper

ts

Ques

tionnai

re

surv

ey

Pareto principle

and AHP

Results showed that critical success

factors which represent the areas

where companies should focus their

attention and effort to achieve better

safety levels through are effective

implementation of programs.

46.

Zaw

awi

et a

l (2

011)

Mal

aysi

a

To derive a generic

process and procedure in

maintenance management

to be used in various

organization in Malaysia.

Lo

cal

auth

ori

ties

org

aniz

atio

n p

erso

nnel

Cas

e st

ud

y

Conceptual

framework

Results showed that implementing

CSF concept would enhance the

management process and work

planning which would result in a more

economic use of resources, a

corresponding reduction in the total

cost and create successful competitive

performance organization.

47.

Tan

an

d G

haz

ali

(20

11)

Mal

aysi

a

To determine the CSFs

and provide some

guidance for contractors

interested in tapping

international markets

Pro

ject

man

ager

s,

dir

ecto

rs, k

ey

exec

uti

ve

and

engin

eeri

ng

firm

s

In-d

epth

inte

rvie

ws

and

seco

ndar

y d

ata

AHP model

Study evidences showed that project

management related factor is more

important than the other main factors

in terms of ranking and contractor’s

experience is the most critical among

all the sub-factors.

221


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


48.

Fam

akin

et

al

(2012)

Nig

eria

To assess the factors

affecting the performance

of partners in joint

ventures construction

projects in Nigeria.

Par

tner

s an

d c

onsu

ltan

ts

Ques

tionnai

re s

urv

ey Mean Item

Score,

Wilcoxon-

Mann-Whitney

(U-test) test,

Kruskal-Wallis

(H-test) test

And factor

analysis

The study results revealed that

communication, compatibility of

objectives and mutual understanding

among partners ranked as the most

important to the performance of

partners in Joint Venture Projects.

49.

Ng e

t al

(2012)

Hong K

ong

To explore the key

successful ingredients to

be assessed at the initial

stage of PPP projects as

perceived public sector,

private consortium and

general community.

Qu

esti

onnai

re s

urv

ey a

nd

sem

i-st

ruct

ure

d

inte

rvie

ws

Descriptive

analysis, Spear-

man’s rank

correlation

coefficient and

independent

sample t-tests

Results indicated that:

The most critical factor for

evaluating the feasibility of PPP

projects is an acceptable level of

tariff.

Cost effectiveness and financial

attractiveness are the most

important evaluation factors as

ranked by the public sector and

private consortium respectively.

222


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


50.

Gar

bhar

ran e

t al

(2012)

Durb

an,

South

Afr

ica To assess the perceptions

of contractors and project

managers regarding

critical success factors

which lead to project

success in the

construction industry in

Durban, South Africa. pro

ject

man

ager

s an

d

contr

acto

rs

ques

tionnai

re s

urv

ey

Descriptive and

inferential

statistics

The study emerged that there are

no significant differences

between project managers and

contractors regarding the critical

success factors.

Four COMs model has been

advocated as being a useful tool

in assessing project success,

especially in developing

countries.

51.

Zh

ao e

t al

(2013)

Chin

a

To identify factors

influencing the success of

Build–operate–transfer

power plant projects in

China.

Go

ver

nm

ent

off

icia

ls,

con

sult

ants

, D

esig

ner

s

and

Contr

acto

rs

Combination

of literature

survey,

Review of

case study

reports and

Semi-

structured

interviews

Conceptual

framework

The results showed that there are 14

factors at both macro level and micro

level, affecting the success of Chinese

BOT projects.

CSFs on developed countries studies

52.

Bo

urn

e et

al

(20

02)

Un

ited

Kin

gdo

m

To investigate the major

factors that impact the

success and failure of the

implementation of a

performance measurement

system.

Dir

ecto

rs a

nd

man

ager

s

Qu

esti

on

nai

re

surv

ey , c

ase

stu

die

s an

d

inte

rvie

ws

Contextual

Analysis

Four factors appeared to be significant.

These are how the introduction and

launch is handled, who is involved in

the project and project management

and procedure.

223


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


53.

Dvir

and L

echle

r

(2004)

Isra

el

To study empirically the

impact of project

planning, project goal

changes, and project plan

changes on project

success.

`-pro

ject

man

ager

,

tech

nic

ians

or

busi

nes

s m

ember

s

Ques

tionnai

re

surv

ey

Exploratory

correlation

analysis, linear

structural

relationships and

structural

equation model

The results of this study support

the view of plans are not nothing,

“changing plans is everything.”

The quality of project planning

affects the project success.

Plan changes is strongly affected

by goal changes

54.

Turn

er a

nd

Müll

er (

2005)

--

To determine Whether the

competence, including

personality and leadership

style, of the project

manager is a success

factor for projects and

whether its impact is

different on different

types of projects A

rtic

les

Lit

erat

ure

rev

iew

--

Results showed that effective leader-

ship as a critical success factor in the

management of organizations, and has

shown that an appropriate leadership

style can lead to better performance.

55.

Leh

tira

nta

et

al.

(20

12)

Fin

lan

d

To evaluate the extent to

which construction project

participants’ perception of

each other’s performance

reflects on the owner’s

perception of project

success

Pro

ject

ow

ner

s,

pro

ject

co

nsu

ltan

ts,

mai

n c

ontr

acto

rs

and

des

igner

s

Qu

esti

on

nai

re

surv

ey

Pearson’s

correlation

coefficients

The results supported the proposition

that satisfaction within both owner-

related and non-owner-related

relationships is reflected on success.

224


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


56.

Men

g (

2012)

Unit

ed K

ingdom

To explore the specific

characteristics of supply

chain relationships in

construction and to assess

their impact on project

performance Mai

n c

ontr

acto

rs,

man

agem

ent

consu

ltan

ts a

nd

spec

iali

st c

ontr

acto

rs

Ques

tionnai

re s

urv

ey

Percent

frequencies and

Chi-square test

Results showed that:

The deterioration of supply chain

relations hips is a major reason

for the occurrence of poor

performance.

Poor performance can be

effectively reduced by improving

some aspects of the relationship.

57.

Ver

burg

et

al

(2013)

Fin

land,

Net

her

lands

and

Sw

itze

rlan

d To determine conditions

that need to be fulfilled

for successful project

execution within

dispersed project settings.

Pro

ject

man

ager

s

In-d

epth

and

stru

cture

d

inte

rvie

ws

Means-End

Chain (MEC)

method

Results showed that important

conditions for successful project

execution in a dispersed setting

included rules of communication and

its clarity; project management style

and goal-setting; and managers'

competences and trust in a team.

58.

Mo

len

aar

et a

l (2

013)

Un

ited

Sta

tes

of

Am

eric

a To understand whether

project peer reviews could

be an indicator of project

success.

--

Pee

r re

vie

w

Point biserial

coefficient

The results showed that project

peer reviews can help to predict

project success.

The relationship between the

designer and contractor appears

to be very import ant to the

outcome of the project, regardless

of project delivery method.

225


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


59.

Loca

tell

i et

al

(2014)

EU

To empirically relate the

identification of a

characteristic of a

megaproject with whether

or not that megaproject

was

Successful.

Res

earc

her

s

Cas

e st

udie

s,

bra

inst

orm

ing

Fisher exact

test, chi-squared

test

Results showed that the different

typologies can point out the relevance

of the type of technology on the

project performance Stakeholders

might have high influence on time-

related Issues in megaprojects

60.

Fin

k (

2014)

Slo

ven

ia,

Bal

kan

countr

ies,

E

aste

rn

Euro

pea

n c

ountr

ies,

Wes

tern

Euro

pe

and

Nort

hea

ster

n

Euro

pe

and R

uss

ia

To examine how CF

competence influences

construction project

performance measured by

reaching internal and

overall budget, quality

and deadline goals.

Tea

m m

ember

s

Cas

e st

udy

Multiple

regression

model

Results showed positive effects of the

team average CF customer focus on

examined project goals.

61.

Fo

rtune

and

W

hit

e

(20

06)

Un

ited

Kin

gdom

To frame project critical

success factors by systems

model. Pu

bli

cati

on

s,

pro

ject

s

dat

a

Cas

e

stu

dy Comparison

analysis and

Formal System

Model

Results showed that the formal system

model allows the underlying benefits

of critical success factors in planning

phase.

62.

Gu

die

nė

et a

l

(20

13)

Lit

huan

ia

To develop a conceptual

critical success factors

model for construction

projects in Lithuania.

Co

mp

reh

ensi

ve

rev

iew

of

the

lite

ratu

re Decision-

making matrix

and a multiple

criteria analysis

of alternatives

Conceptual model adapted to

Lithuania is developed and grouped

decision-making matrix for the

multiple criteria analysis of critical

success factors of construction projects

is presented.

226


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


63.

Alz

ahra

ni

and E

msl

ey (

2013)

Unit

ed K

ingdom

To study the impact

of contractors’

attributes on project

success from a post

construction

evaluation

perspective.

To identify what

critical success

factors (CSFs) that

greatly impact the

success of project.

Contr

acto

rs

Ques

tionnai

re s

urv

ey

Factor analysis

and logistic

regression

techniques

Results showed that the success of a

project is significantly associated with

seven of the advocated variables. They

are: turnover history, quality policy,

adequacy of labor resources, adequacy

of plant resources, waste disposal, size

of past project completed, and

company image.

64.

Gu

die

nė

et a

l (2

014)

Lit

huan

ia To investigate the critical

success factors affecting

the implementation of

projects in construction

enterprises in Lithuania.

con

stru

ctio

n

pro

fess

ional

s

and

ex

per

ts

Qu

esti

on

nai

re s

urv

ey

AHP approach

The study showed that clear and

realistic project goals and project

planning play the key role in

successful implementation of

construction projects in Lithuania.

They should be supported by the top

project management, clear and

precise goals/objectives of the client,

and, finally, by the client’s ability to

make timely decisions.

227


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


65.

Cse

rhát

i an

d S

zabó

(2014)

Aust

ria,

Cze

ch

Rep

ubli

c,

Ger

man

y,

Hungar

y,

Pola

nd, S

lovak

ia,

Slo

ven

ia a

nd

Sw

itze

rlan

d

To develop and

investigate of the

attributes of the success

criteria and factors of

organizational event

projects analysis of the

relationship between the

criteria and factor areas.

Even

t m

anag

ers

Ques

tionnai

re s

urv

ey

Exploratory

facto r analysis

Results showed that the correlations

suggests that relationship-oriented

success factors, such as

communication, co-operation and

project leadership, play a crucial role

in carrying out successful

organizational event projects.

Table A 3: Summary of KPIs and CSFs relationship researches

NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


KPIs and CSFs relationship on developing countries studies

66.

Fri

mp

on

g et

al

(20

03)

Gh

ana

To identify and evaluate

the relative importance of

the significant factors

contributing to delay and

cost overruns in Ghana

groundwater construction

projects.

Ow

ner

s, c

on

sult

ants

an

d

con

trac

tors

Qu

esti

on

nai

re s

urv

ey

Relative

Importance

Weight

The results of the study revealed the

main causes of delay and cost overruns

in construction of groundwater projects

included: monthly payment difficulties

from agencies; poor contractor

management; material procurement;

poor technical performances; and

escalation of material prices.

228


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


67.

Mee

ampol

and O

gunla

na

(2006)

Thai

land To give suggestions

regarding how to improve

cost and time performance

on public Sector projects.

Sit

e pro

ject

man

ager

s

Ques

tionnai

re s

urv

ey

Independent

Sample t-test and

Discriminant

analysis

Results suggested that:

The management of construction

resources, budget management,

construction method, and

communication and report should

reduce the chance of cost overrun.

Improvements in construction

method, construction resource

management, human resource

management, supervision and

control, schedule management, and

communication and report, can

reduce project delays.

68.

Iyer

an

d J

ha

( 2

00

6)

Ind

ia

To identify the relative

importance of success and

failure attributes in Indian

construction industry and

to understand the latent

properties of these success

and failure attributes by

studying the critical

success and failure factors.

Co

nst

ruct

ion

in

dust

ry

pro

fess

ion

als

Qu

esti

on

nai

re s

urv

ey

Mean analysis,

multinomial

logistic

regression and

log of odds ratio

The results showed that commitment of

the project participants; owner’s

competence; and conflict among

project participants have been found to

possess the capability to

enhance performance level.

229


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


69.

Sam

bas

ivan

and S

oon (

2007)

Mal

aysi

a To identify the delay

factors and their impact

(effect) on project

completion.

Cli

ents

, co

nsu

l-ta

nts

, an

d c

ontr

acto

rs

Ques

tionnai

re s

urv

ey

Relative

importance

indices and

Correlation

analysis

The results showed that the ten most

important causes for delay in Malaysian

projects are: (1)contractor’s improper

planning, (2)con-tractor’s poor site

management, (3)inadequate contractor

experience, (4)inadequate client’s

finance and payments for completed

work, (5)problems with subcontractors,

(6)shortage in material, (7)labor supply,

(8)equipment availability and failure,

(9)lack of communication between

parties, and (10)mistakes during the

construction stage.

70.

Ch

en a

nd

Chen

(2007)

Tai

wan

To distinguish between

success factors based on

their degrees of importance

in relation to success.

Go

ver

nm

ent

emplo

yee

s,

ow

ner

s, d

esig

ner

s, a

nd

con

trac

tors

Qu

esti

on

nai

re s

urv

ey

Mean analysis,

one-way

ANOVA and

factor analysis.

The results showed that certain

requirements must be met for partnering

to be successful, including a

collaborative team culture, a long-term

quality focus, consistent objectives, and

resource-sharing.

230


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


71.

Mir

and

pin

nin

gto

n (

2014)

Unit

ed A

rab E

mir

ates

To test the relationship

between project

management performance

and project success

Ques

tionnai

re s

urv

ey

Pearson

correlation,

linear regression

and cross-

tabulating

Study demonstrated that project

management performance is

correlated to project success within

United Arab Emirates

organizations.

The project management

performance construct and its

variables had markedly greater

impact on project success

attributes than did project

efficiency which is more limited in

its influence.

72.

Lu

et

al

(20

08)

Ch

ina

To utilize the CSF

approach to

Identify a few manageable

but vital factors

contributing to the

Overall competitiveness of

a contractor Gra

de

1 c

ontr

acto

rs

Qu

esti

on

nai

re s

urv

ey

Ranking analysis

and factor

analysis

Results showed that factor analysis

generates eight clusters from the 35

CSFs identified by the ranking analysis.

These clusters represent supercritical

success factors affecting a contractor’s

competitiveness, namely “project

management", “organization structure",

“resources", “competitive strategy",

“relationship", “bidding", “marketing,”

and “technology".

231


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


73.

Ensh

assi

et

al

(2009

a)

Pal

esti

ne To identify the factors

affecting the performance

of local construction

projects.

Pro

ject

man

ager

s, s

ite

engin

eers

/off

ice

engin

eers

, an

d

org

aniz

atio

ns’

man

ager

s

Ques

tionnai

re s

urv

ey Relative

importance

index method,

project

managers, site

engineers/office

engineers, and

organizations’

managers

The results indicated that the average

delay because of closures leading to

materials shortage was the most

important performance factor, as it

has the first rank among all factors

from the perspectives of owners,

consultants, and contractors.

74.

Om

ran a

nd

Mam

at (

2011)

Mal

aysi

a

To investigate the factors

affecting cost performance

of construction projects in

Kelantan State located in

the east-coast part of

Malaysia. Mai

n c

ontr

acto

r,

sub

contr

acto

r, s

uppli

er,

dev

eloper

Qu

esti

onnai

re s

urv

ey

Relative

importance

index method

The results indicated that the success

factors affecting the cost performances

of projects identified as project manager

competence in works.

Poor project specific attributes and not

existence of cooperate and ignorance

and lack of knowledge in operating,

techniques and decision by project

manager are identified as the most

important failure factors.

232


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


75.

Chou e

t al

(2013)

Tai

wan

, In

dones

ia ,

and

Vie

tnam

To determine the effects

of project management

body of knowledge

techniques/ tools/skills

(PM TTSs) on project

success

Pro

fess

ional

Engin

eers

in t

he

const

ruct

ion

indust

ry

Ques

tionnai

re s

urv

ey

Structural

equation

modeling and

importance

performance

analysis

The findings of the study provided

guidance for practitioners and

educators by clarifying the current

use of PM TTSs in the

construction engineering field.

To optimize PS, project managers

can use the model to perform

numerical studies of critical

indicators/constructs and to

prioritize and allocate the

components of their managerial

strategies.

76.

So

n a

nd

Kim

(2

014)

So

uth

Kore

a

To develop a model to

predict the cost and

schedule performance of

green building projects

based on the level of

definition during the pre-

project planning phase.

Arc

hit

ect,

dev

elo

per

, or

Pro

ject

man

ager

Qu

esti

on

nai

re s

urv

ey

Support vector

machine, back-

propagation

neural network,

decision tree

algorithm and a

logistic

regression

The cost and schedule performance of

green projects was highly dependent on

the quality of definition in the pre-

project planning phase.

233


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


77.

Sheh

u e

t al

(2014)

Mal

aysi

a

To investigate certain

project characteristics

influencing Malaysian


overruns. Consu

ltan

ts

Ques

tionnai

re s

urv

ey

Descriptive

analysis and

regression

analysis

More than half of Malaysian

construction projects (55%)

experienced cost overruns.

Public sector projects performed

better than private sector projects,

also design and build projects was

associated with reduced cost

overrun, and small and large

projects performed better than

medium and very large projects.

78.

Ali

as e

t al

(2014)

Mal

aysi

a

To identify the extent of

the relationship between

CSFs and project

performance and to assist

the organization in

evaluating the performance

of project management Pro

ject

man

ager

s

Lit

erat

ure

rev

iew

conceptual

framework

The results was a conceptual framework

for determining critical success factors

in project management practices

234


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


79.

Yan

g e

t al

(2015)

Tai

wan

To identify the roles of

interpersonal conflict,

product advantage, and

project type in the

relationship between

requirement quality and

stability in terms of project

performance and market

performance.

pro

duct

man

ager

s

Ques

tionnai

re s

urv

ey

Factor analysis

with varimax

rotation,

confirmatory

factor analysis

and chi-square

tests

The results suggested that resource

definition and management

implementation process and training and

improvement was associated with

requirement quality and stability. The

findings also indicated that the number

of groups moderates the relationship

between requirement quality and

stability and project performance.

KPIs and CSFs relationship on developed countries studies

80.

An

der

sen

et

al

(2006)

Un

ited

Kin

gdom

,

Fra

nce

,

No

rway

an

d C

hin

a

To study the relationship

between project success

factors and actual project

success.

Pro

ject

man

ager

, p

roje

ct

cham

pio

n a

nd c

lien

ts

Qu

esti

on

nai

re s

urv

ey

Exploratory

factor analyses,

using principal

component

analysis (PCA)

with Varimax

Rotation

And regression

The results showed that the most

important factors in improving

managerial ability to deliver results in

time and at cost were strong project

commitment, early stakeholder

influence, stakeholder endorsement of

project plans and rich project

communications.

235


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


81.

Ahsa

n a

nd G

unaw

an (

2010)

Asi

an c

ountr

ies

To identify the root causes

of project delay and cost

under-run.

Inte

rnat

ional

dev

elopm

ent

pro

ject

s

Sec

ondar

y d

ata

Descriptive

statistics

The results indicated that critical

causes of project delay can be

attributed to natural calamities and

host country bureaucracy. The main

reasons of cost under-run are

categorized as devaluation of local

currency, competitive bidding price,

lower then estimated bid, and large

contingency budgets.

82.

Ora

ng

i et

al

(2011)

Vic

tori

a, A

ust

rali

a

To study specific cost

overrun and time overrun

issues in the linear

construction projects in

Victoria, Australia.

Pro

ject

man

ager

s

Tar

get

ed i

nte

rvie

ws

and c

ase

stu

dy

Frequency of

occurrence

The results showed that the set of root

causes in Victoria-based pipeline

projects cost overrun and time overrun,

include design changes, design errors,

poor communication, customer/ end-

user related issues, subsurface

investigation inadequacies, issues

regarding permissions/ approvals,

weather conditions, procurement delays,

site management problems,

subcontractor issues, rework, cultural

and heritage management issues.

236


NO

.

Au

thor/

s

Cou

ntr

y

Objectives

Targ

et

gro

up

Met

hod

use

d

Analysis


83.

Hw

ang e

t al

(2013)

Sin

gap

ore

To identify the critical

factors affecting schedule

performance of public

housing projects in

Singapore.

Reg

iste

red c

ontr

acto

rs

Ques

tionnai

re s

urv

ey

Impact index,

frequency index

and criticality

index

Results indicated that “site management

”, “coordination

Among various parties”, “design

changes by owner during construction”,

“availability of laborers on site ”,

“availability of material ”,and

“availability of staff to manage projects

” are the six most critical factors that

affect schedule performance of public

housing projects in Singapore.

84.

Zav

adsk

as e

t al

(2014)

Lit

huan

ia

To analyze common

project management

problems and projects

success factors and to

illustrate how to assess a

projects' execution

efficiency by mean of the

aggregated indicator in

particular company.

Ex

per

t

Cas

e st

udy Multi-criteria

analysis and

logarithmic

normalization

method

Results showed that by using the

aggregated indicators it is easy to

compare the projects, the received

impartial information is useful for

strategic planning, quality management,

for solving the tasks of resource

allocation, motivational project

evaluation.

Appendix II: Questionnaire (English)

238

The Islamic university of Gaza

Higher studies deanery

Faculty of engineers – master program

Engineering project management

Questionnaire for

The success factors that affecting public construction projects and their relation to

key performance indicators

Dear participants greetings:

Firstly, I want to thank and appreciate your kindness to grant me a part of your valuable

time to fill out my questionnaire, which considered as a basic requirement for the

completion of my research in order to award the master of science degree in engineering

project management at Islamic university of Gaza. This research titled as " The success

factors that affecting public construction projects and their relation to key performance

indicators; Palestine as case study".

The aim of my research is to determine the key performance indicators which affect the

performance of public construction projects and to specify the critical factors which

affecting the success of these projects. Also it aims to evaluate the relationship between

those success factors and the construction projects performance. The targeted

construction projects in the research include housing projects and infrastructure projects

such as roads, schools hospitals public buildings and so on.

This questionnaire target group is construction consultants and experts especially those

who worked in the public sector, NGO's and the engineering consulting offices. And in

order to achieve my research objectives I cordially invite you to fill out this

questionnaire. Knowing that it needs 15 minute to fill out and any collected information

from this study will be used to purely academic purposes.

All appreciations and thanks for your contribution to support scientific research

Researcher

Sirin K. Elbohisi

Supervisor

Dr. Adnan Enshassi

Associated professor in civil

engineering

239

The questionnaire contents:

This questionnaire consists of three sections:

First section: general information.

Second section: key performance indicators KPI's of projects.

Third section: critical success factors affecting public construction projects.

First section: general information

Please tick √ versus the convenient option for you, taking into account to put it in

front of only one option.

Place of your resident

Gaza Strip West Bank

The type of your organization

Govermental

organization

Consultation

office

Non-governmental

organization

other, specify……..

Size of your organization suppervised projects during the last five years (in million

dollar):

Less than 5 M$ From 5 -10 M$ From 11 - 20 M$ More than 20 M$

Your organization working field

Housing

bulidings

projects

Govermental

buildings

projects

Public service

projects (schools,

hospitals,..)

Rubble

removal

projects

Roads

projects

Other, specify

Job Title for the participant who filling out the questionnaire

Design consultant Supervising consultant project manager Else, specify:……..

Years of experience in the construction industry for the participant who filling out the

questionnaire

From 5 -10 years From 11 -15 years From 16 -20 years More than 20 years

Please determine in years your practical experince in the following fields

Govermental

engineering

experience

Consulting

offecies

experience

Contracting

companies

experience

Financing

organizations

experience

Other experiences,

specify

240

Second section: key performance indicators KPI's of projects. Selections in the following Table related to specify the most important KPIs which can be

used to measure the projects performance in order to know whether the project is

succeeded or not (so please give attention to tick √ sign versus your suitable choice for

degree of importance, periodically measure of indicator and performance evaluation of

organization projects ).

#

. KPI

Degree of importance

Was KPI measured

during or after the

project ends?

Your evaluation for the

public construction

projects followed by

your organization, in

comparative to planned

according to each KPI

Ver

y

imp

ort

an

t

Imp

ort

an

t

Sem

i

imp

ort

an

t

Lo

w

imp

ort

an

t

No

t

imp

ort

an

t

Alw

ay

s

Mo

stly

So

met

imes

Ra

rely

Nev

er

Ver

y h

igh

Hig

her

Eq

ua

l

Les

s

Mu

ch l

ess

1. Actual project costs compared with

planned budget.

2. Actual project duration compared with

planned duration.

3.

Financial ability for both owner and

contractor to cover project

expenditures.

4. Project profitability for contractor

comparing with other related projects.

5. Project conformity to quality and


6. Project conformity to sustainability

criteria.

7. Project conformity to environment


8. Accidents and injures number in the

project.

9. Quantity and costs of variation orders.

10. Number and size of disputes,

litigations.

11. Contractor and consultant reputation.

12. Project parties satisfaction.

13. Beneficiaries satisfaction on project

functionality.

241

Third section: critical success factors affecting public construction projects. Project consider to be successful when KPIs which second section of this questionnaire

very close to planning. There is many factors contribute in project success which named

success factors. In this following Table some factors were mentioned that seemed to be

success factors. These factors classified according to project life cycle.

Selections in the following Table related to specify the importance of the effect of each

mentioned factor on projects success (so please give attention to tick √ sign versus your

suitable choice).

#.

Important degree of the critical factor effect

Critical factor

Very

important Important Neutral

Low

important

Not

important

First: Factors related to conceptualizing and preparation phase

1. Studying the feasibility, cost and priority of the project for the

society.

2. Formalizing deterministic, clear and realistic objectives for

the project and sharing project relatives in.

3. Determining project size represented by its required budget.

4. Specifying the project type whether it is new, maintenance,

completion for existing one or rubble removal project)

5. Determining the construction project nature (housing,

infrastructure, public building, …)

6. Specifying the project designing and execution complexity

comparing with previous related projects.

7. Endeavoring to decrease the political instability effect on the

project.

8. Studying the level of acceptance of local community to

execute the project in their location.

9. Studying project tendency to accidents and hazards.

10. Existence of experienced and understandable client (his

representative) on project nature and clear priorities for

project execution.

11. Giving suitable and enough time for planning and designing

phase.

12. Recruiting and involving consultant in all project activities

and phases.

Second: Factors related to planning and designing phase

1. Coordinating with related formal parties such as

(municipalities, electricity companies, ministries,… etc.).

2. Client contribution on project designing and planning.

3. Past relevant experience of consultant on designing similar

project.

4. Ability of project parties to generate innovative ideas.

5. Specific and measurable project quality standards.

6. Approved, clear and updated codes, specifications and

regulations for construction industry.

242

#.


Critical factor

Very


Low

important

Not

important

7. Efficient technical capability of consultant for example

existence of skilled team and designers.

8. Designing project according to updated codes and standards

in order to eliminate possible errors.

9. Considering operation and maintenance requirements into

project design.

10. Social, cultural and environmental impacts on project type,

design and planning.

11. Project physical environment of project like (location, soil

works, availability of surrounding infrastructure, etc.).

12. Ease of having permits, licenses and any related approvals

from governmental institutions.

13. Availability of organized legal environment i.e. (laws of

industry encouragement, conflict resolution, litigations, etc).

14. Strong, detailed and updated integrated planning effort in

design and construction.

15. All key participants have participate in the detailed project

planning within their area of expertise.

16. Effective schedule management and realistic forecasting of

project duration.

17. The project has a formal organizational chart covering the

entire project.

18. Risk identification management and allocation.

19. Involvement of local community, project beneficiaries and

the affected parties in project plans and policies.

Third: Factors related to tendering and contracting phase

1. The client has a mechanism to manage the bids.

2. Transparent and efficient procurement criteria depends on

applicable laws and regulations.

3. Consider consultant and contractor past performance and

reputation as awarding criteria.

4. Past relevant experience of client in awarding bids and

managing contracts.

5. Past related experience of consultant in sharing in similar bids

and contracts.

6. Past related experience of contractor in sharing in similar bids

and contracts.

7. The consultant and the contractor have a mechanism to

manage the tenders and compete.

8. The client interprets all project requirements and location

during the bids preparatory meeting.

243

#.


Critical factor

Very


Low

important

Not

important

9. Documentation the preparation meetings in details.

10. Visiting project location by all consultants and contractors

before filling out the bid form.

11. Granting enough time for consultants and contractors to fill

out the bid form.

12. Participating of related project parties in financial and

technical evaluation of tenders.

13.

Effective contract management included precise formulation,

documentation and enough detailed incentives, bonds,

penalties, …etc.

14. Project profitability for consultant and contractor

15. Economic environment in terms of materials quantity,

quality, and price, local currency value, …etc.

16. Delegation and authority allocation of project workers.

Fourth: Factors related to implementation phase

1. The client follows project implementation regularly.

2. Past relevant experience of contractor in execution similar

projects.

3. Appropriate safety practices during project execution.

4. Updated plan for supervising and managing project site.

5. Preparing and implementing environmental plans included

project waste management works.

6. Commitment of team members on project plans and

objectives.

7. Clear and effective decision making mechanism.

8. Project manager commitment to meet cost quality and time of

project.

9. Adequacy and effective management of project financial and

material resources.

10. Training the human resources in the skills demanded by the

project.

11. Leadership, monitoring, coordinating and organizing

manager skills of project manager.

12. Permanent presence of project manager in project site.

13. Availability of enough staff in project site according to works

requirements.

14. Top management support for project workers.

15. Collaborative team work environment.

16. Mutual trust and understanding between project participants.

17. Social relationships and coordination between project

participants.

244

#.


Critical factor

Very


Low

important

Not

important

18. Annual organized meetings related to project activities for all

participants.

19. Timely and effective conflict resolution.

20. Effective project control , such as monitoring, updating

plans and feedback.

21. Control and monitoring subcontractors works.

22. Annual measuring of KPIs.

23. Effective well established information and communication

routines.

24. The project is part of a well-documented or understood

strategy

25. Effective knowledge processing and management systems.

26. Natural climates like winds, rains and high temperature.

27. Consultant and contractor commitment to continuous

improvement.

28. Client changes in plans and goals during execution.

29. Client approvals and Payment method.

30. Availability and execution of material handling plans.

31. Using applicable construction methods.

32. Continuous revision of project shop drawings and approve

them fast.

33. Saving as built drawings of the project.

34. Consultant and contractors involvement in project operating

and maintenance plan after project execution.

Thank you for your participation

Appendix III: Questionnaire (Arabic)

غزة - الإسلامية الجامعة

العليا الدراسات عمادة

الماجستير برنامج - الهندسة كلية

مشاريع هندسية إدارة

استبانة في موضوع

كحالة عوامل النجاح التي تؤثر على مشاريع الإنشاءات العامة وعلاقتها بالأداء؛ )فلسطين

دراسية(

The success factors that affecting public construction projects and their relation to

key performance indicators; Palestine as case study

السادة الكرام /

السلام عليكم ورحمة الله وبركاته ،،،

بداية أتقدم لكم بالشكر والامتنان على إعطاء جزء من وقتكم الثمين لتعبئة هذه الاستبانة التي تعد جززء أساسزيا

من الدراسة البحثية المطلوبة لنيل درجة الماجستير في إدارة المشروعات الهندسية بالجامعزة الإسزلامية وهزي

ات العامززة وعلاقتهززا بززافداء نفلسززطين كحالززة عوامززل النجززات التززي تززمشر علززى مشززاريع الإنشززاءبعنززوان

دراسية( .

الهدف من الدراسة هو معرفة أهم ممشرات قياس أداء المشزاريع الإنشزاةية العامزة و تحديزد أهزم العوامزل التزي

تمشر على نجات تلك المشاريع. كما وتهدف لتقييم العلاقة بين عوامل النجات وأداء مشاريع الإنشزاءات العامزة.

مشاريع الإنشاءات العامة المستهدفة من الدراسة مشاريع الإسكان والبنيزة التحتيزة كزالطر و ازدمات وتشمل

كالمدارس والمشافي والمباني العامة وغيرها من المشاريع التي تنفذها الجهات المختلفة.

القطزا العزام وتستهدف هذه الدراسزة فئزة الخبزراء والاستشزاريين فزي مجزاا الإنشزاءات وااازة العزاملين فزي

والممسسات الدولية والمكاتب الاستشارية الهندسية. ولتحقيق أهداف هذه الدراسة تم ااتيزار سزيادتكم مزن اجزل

دقيقة لتعبئتها مع العلم انه سزيتم اسزتخدام البيانزات التزي سزتجمع 15تعبئة الاستبانة التي يتوقع أن تحتاج لقرابة

فغراض البحث العلمي فقط.

ر والتقدير على مساهمتكم في دعم البحث العلمي.ولكم كل الشك

الباحثة

سيرين البحيصي

إشراف

أ.د. عدنان انشااي

مكونات الاستبانة:

تتكون هذه الاستبانة من شلاشة أجزاء وهم:

:معلومات عامة ومعلومات حوا المشاريع التي تابعتها ممسستكم. الجزء الأول

:ممشرات قياس أداء المشاريع. الجزء الثاني

:العوامل الممشرة على نجات مشاريع الإنشاءات التابعة للقطا العام. الجزء الثالث

:معلومات عامةالجزء الأول:

مقابل الخيار الذي ترونه مناسبا ونرجو مراعاة وضعها أمام ايار واحد فقط.√ الرجاء وضع إشارة

مكان الإقامة

قطا غزة الضفة الغربية

حاليا نوع المؤسسة التي تعملون بها

ممسسة حكومية مكتب استشاري أارى، حدد............ ممسسة غير حكومية.....

حجم المشاريع التي تابعتها مؤسستكم خلال الخمس سنوات الأخيرة

مليون دولار 5أقل من مليون دولار10 -5من مليون دولار20 -11من مليون دولار 20أكثر من

نيمكن ااتيار أكثر من ايار(مجالات عمل المؤسسة التي تعملون بها حاليا

مشاريع

سكنية مباني

مشاريع

مباني حكومية

مشاريع ادمات عامة

نمدارس، مستشفيات،..(

مشاريع

إزالة أنقاض

مشاريع

طر

أارى، حدد............

الحالي لمن يقوم بتعبئة الاستبانة المسمى الوظيفي

استشاري تصميم استشاري إشراف غير ذلك . حدد .... مدير مشاريع.....

سنوات الخبرة في قطاع الإنشاءات لمن يقوم بتعبئة الاستبانة

سنوات 10- 5من سنة 15 -11من سنة 20-16من سنة 20أكثر من

نبرجاء كتابة عدد السنوات في الصندو (برجاء تحديد سنوات خبرتكم العملية الخاصة في المجالات التالية

ابرة حكومية

هندسية

ابرة بمكاتب

استشارية

ابرة في شركات

المقاولات

ابرة في

ممسسات ممولة

ابرات أارى،

حدد............

المشاريع.ممشرات قياس أداء الجزء الثاني:

Keyالااتيارات في هذا الجدوا تتعلق بتحديد أهم الممشرات التي قد تستخدم لقياس أداء المشاريع ن

Performance Indicators "KPI's") أم لا نلذا في كل فقرة وذلك لمعرفة إن كان المشرو ناجحا

من وجهة نظرك√ نرجو وضع إشارة دورية – درجة الأهميةم لكل من عند الخيار الذي تجدونه مناسبا

(تقييمكم لأداء مشاريع الإنشاءات العامة المنفذة بمتابعتكم – قياس المؤشر

مؤشر القياس م.

درجة الأهميةيتم قياس المؤشر خلال أو بعد

تنفيذ المشروع

تقييمكم بالمجمل لأداء المشاريع

العامة التي نفذت بمتابعتكم من حيث

كل مؤشر مقارنتها بالمخطط حسب

داجم ها

امه

ط ستوم

يةهملأا

ض خفمن

يةهملأا

ام هر غي

ما ائد

با الغ

نا ياحأ

را ادن

قا طلم

ة فعرتم

دا ج

عة تفمر

ية اوسم

قلأ

ير كث بلأق

1. تكاليف المشرو الحقيقية مقارنة

بالتقديرات افولية.

2. مدة تنفيذ المشرو الحقيقية

مقارنة بالجدوا الزمني المقدر.

3. الكفاءة المالية للمالك والمقاوا

لتغطية تكاليف المشرو .

4.

أربات المشرو للمقاوا مقارنة

مع مشاريع أارى في نفس

المجاا.

5. مراعاة المشرو لمعايير الجودة

والمواافات الفنية.

6. مراعاة معايير الاستدامة أشناء

التنفيذ.

7. مراعاة معايير حماية البيئة أشناء

التنفيذ.

8. عدد الحوادث والإاابات في

المشرو .

عدد وتكلفة افوامر التغييرية. .9

عدد وحجم القضايا والنزاعات. .10

11. تأشر سمعة منفذي المشرو من

مقاوا واستشاري.

12. درجة رضا أطراف تنفيذ

المشرو .

13. مدى رضا المستفيدين على تأدية

المشرو للوظيفة المحددة له.

العوامل الممشرة على نجات مشاريع الإنشاءات التابعة للقطا العام.الجزء الثالث:

يعتبر المشرو ناجحا عندما تكون ممشرات قياس افداء المذكورة في الجزء الثاني من هذه الاستبانة مقاربة

في تحقيق ذلك وتسمى تسهم إلى حد كبير لما اطط له في بداية المشرو . وهناك العديد من العوامل التي

عوامل النجات المحتملة في الجدوا وقد تم سرد عدد من (Success Factorsهذه العوامل بعوامل النجات ن

التالي. وقد تم تقسيم هذه العوامل بناء على دورة حياة المشرو حيث يمر المشرو بعدة مراحل.

الااتيارات في الجدوا التالي تتمثل في تحديد أهمية كل عامل من العوامل المذكورة لنجات المشرو نلذا في

الذي تجدونه مناسبا من وجهة نظركم(.عند الخيار √ كل سماا نرجو وضع إشارة

م. درجة أهميته في التأثير على نجاح المشروع

هام هام جدا العوامل المؤثرةمتوسط

الأهمية

منخفض

الأهمية

غير

هام

أولا : العوامل المتعلقة بمرحلة التحضير والاستعداد للمشروع

المشرو بالنسبة للمجتمع.دراسة جدوى و قيمة وأولوية .1

2. وضع أهداف محددة وواضحة وواقعية للمشرو ومشاركة جميع

افطراف في وضعها.

تحديد حجم المشرو متمثلا في مقدار موازنته المطلوبة. .3

4. تحديد نو المشرو من حيث أنه مشرو جديد أو ايانة أو

استكماا مشرو قاةم أو إزالة أنقاض.

تحديد طبيعة مشرو الإنشاءات نسكني، بنية تحتية، مبنى عام،...(. .5

6. تحديد مدى اعوبة تصميم وتنفيذ المشرو مقارنة بما تم تنفيذه سابقا

من مشاريع.

العمل على تقليل تأشر المشرو بحالات عدم الاستقرار السياسي. .7

8. بموقع المشرو لتنفيذه في دراسة رضا المجتمع المحلي المحيط

المكان.

دراسة المخاطر والحوادث التي قد تنجم عن طبيعة المشرو . .9

11. فهم وتوفر ابرة سابقة لدى المالك/ من يمثله لطبيعة المشرو وتحديد

أولويات تنفيذه بوضوت.

إعطاء فترة زمنية مناسبة لمرحلة التخطيط والتصميم. .11

الاستعانة باستشاري في كافة مراحل المشرو . .12

العوامل المتعلقة بمرحلة التخطيط والتصميمثانيا :

1. التنسيق مع الجهات الرسمية ذات العلاقة بلديات، شركة الكهرباء،

.الوزارات المختصة، ...إلخ(

2. مساهمة المالك/ من يمثله الفعالة في مراحل التصميم والتخطيط

للمشرو .



الأهمية

منخفض

الأهمية

غير

هام

توفر ابرة سابقة ذات علاقة لدى استشاري المشرو . .3

وجود قدرة لدى أطراف المشرو على توليد افكار الاقة. .4

وضع معايير الجودة المطلوبة للمشرو بحيث يمكن قياسها بسهولة. .5

6.

وجود كودات ومواافات واضحة ومحدشة لصناعة الإنشاءات

الجهات المنظمة كجمعيات المهندسين واتحادات معتمدة من

الصناعات.

كفاءة القدرات الفنية للاستشاري مثل وجود طواقم ومصممين مهرة. .7

8. الدقة في التصميم والاستناد فحدث الكودات والمعايير لتلافي

افاطاء التي قد تنجم.

9. مرحلة الإدارة والصيانة افاذ بالحسبان عند إعداد الخطط والتصاميم

والتشغيل للمشرو .

11. مراعاة العوامل الثقافية والاجتماعية والبيئية وتأشيرها على نو

وتصميم وتخطيط المشرو .

11. مراعاة العوامل الفيزيقية للمشرو مثل نموقعه، أعماا التربة، وجود

بنى تحتية محيطة بالمشرو ،...(.

12. تصاريح وتراايص عمل المشرو وما يتعلق به سهولة استخراج

من اعتمادات من قبل الممسسات الحكومية ذات العلاقة.

13. توفر البيئة القانونية من قوانين تشجيع وسرعة حل النزاعات

وغيرها.

14. وجود اطة مفصلة ومتكاملة لكل من مراحل التصميم والإنشاء مع

المشرو .تحديثها الداةم وفق مستجدات

15. مشاركة جميع ذوي العلاقة والمعنيين بوضع اطط المشرو كل في

مجاا ااتصااه وابرته.

التنبم الدقيق للوقت المطلوب للمشرو والجدولة الزمنية له. .16

17. وجود هيكل تنظيمي واضح وشامل وناظم لجميع افطراف ذات

العلاقة بالمشرو .

18. التي قد تواجه المشرو وسبل إدارتها مع تحديد تحديد المخاطر

واضح لمسئوليات ودور الجهات المختلفة لتجاوزها.

19. مشاركة ذوي العلاقة مثل ممثلين عن المجتمع المحلي والمستفيدين

من المشرو والمتضررين في رسم سياساته والتخطيط له.

والتعاقداتثالثا : العوامل المتعلقة بمرحلة المناقصات

وجود آلية لإدارة المناقصة من قبل المالك/ من يمثله. .1

2. وجود معايير شفافة وعادلة تتوافق مع أنظمة وقوانين العطاءات

المعموا بها.



الأهمية

منخفض

الأهمية

غير

هام

اعتبار معايير السمعة وافداء المسبق من ضمن معايير الترسية. .3

4. ترسية عطاءات وعقود وجود تجربة سابقة للمالك / من يمثله في

مشابهه.

5. وجود تجربة سابقة للاستشاري في المشاركة بعطاءات وعقود

مشابهه.

وجود تجربة سابقة للمقاوا في المشاركة بعطاءات وعقود مشابهه. .6

7. وجود آلية لإدارة المقاوا أو الاستشاري لمناقصة المشرو وقدرتهم

على المنافسة.

8. المالك / من يمثله لكافة متطلبات المشرو وشرت لموقعه توضيح

الاا الاجتما التمهيدي للمناقصات.

9. توشيق كافة النقاط المتفق عليها بالتفصيل الاا الاجتماعات التمهيدية

للمناقصات.

11. زيارة كافة الاستشاريين / المقاولين لموقع المشرو قبل تعبئة نموذج

العطاء.

إعطاء وقت كاف للمقاوا/ الاستشاري لتعبئة العطاء. .11

12. مشاركة الجهات ذات العلاقة كالاستشاري في تقييم العروض ماليا

وفنيا.

13. الإدارة الفعالة للعقود ودقة اياغتها و توشيقها وتفصيل بنودها من

حيث العقوبات والضمانات والحوافز وغيره.

بالنسبة للمقاوا والاستشاري.ربحية المشرو .14

15. البيئة الاقتصادية المتعلقة في وجود معابر لداوا المواد وأسعار مواد

البناء وقيمة العملة المحلية وغيرها.

تفويض وتحديد الصلاحيات والمسئوليات للعاملين في المشرو . .16


العوامل المؤثرة هام هام جدا

متوسط

الأهمية

منخفض

الأهمية

غير

هام

رابعا : العوامل المتعلقة بمرحلة التنفيذ

متابعة المالك/ من يمثله بشكل منتظم لمرحلة تنفيذ للمشرو . .1

علاقة لدى مقاوا المشرو .توفر ابرة سابقة ذات .2

اتخاذ التدابير المتعلقة بافمان والسلامة أشناء تنفيذ المشرو . .3

وجود اطة محدشة فعماا إدارة موقع المشرو والإشراف عليه. .4

5. إعداد وتطبيق اطط تراعي الوضع البيئي ويشمل ذلك أعماا

المشرو .التخلص من المخلفات التي قد تنتج عن

التزام جميع طاقم العمل بخطط وأهداف المشرو . .6

7. سلاسة ووضوت سلطة وآلية اتخاذ القرارات من القاةمين على

المشرو سواء المالك أو الاستشاري أو المقاوا.


العوامل المؤثرة هام هام جدا

متوسط

الأهمية

منخفض

الأهمية

غير

هام

8. التزام مدير المشرو بإنهاء المشرو ضمن الموازنة والوقت

والجودة المحددة للمشرو .

توفير و إدارة الموارد المالية والمادية للمشرو بشكل ممنهج. .9

تدريب الموارد البشرية على المهارات اللازمة للمشرو . .11

11. تعيين مدير المشرو بحيث يمتلك المهارات الإدارية المتمثلة في

.قدرته على القيادة والرقابة والتنسيق والتوجيه

المشرو الداةم في المشرو .تواجد مدير .12

تواجد طاقم المشرو بشكل كاف في موقع المشرو . .13

دعم الإدارة العليا للعاملين في المشرو . .14

وجود بيئة تعاونية بين فر العمل في المشرو . .15

وجود شقة متبادلة وتفاهم بين العاملين في المشرو . .16

اجتماعية وتنسيق داةم بين العاملين في المشرو .وجود علاقات .17

18. دورية الاجتماعات المنظمة المتعلقة بأنشطة المشرو يشارك بها

جميع ذوي العلاقة.

سرعة حل النزاعات التي قد تنشأ بمسئولية ووفق اطة مدروسة. .19

21. عبر التغذية التحكم الفعاا في المشرو والرقابة عليه وتحديث بياناته

الراجعة.

21. الرقابة والتحكم بأعماا مقاولي الباطن باعتبارها جزء متكاملا من

المشرو .

22. قياس أداء المشرو أولا بأوا وفق ممشرات القياس الموضوعية

الدالة على نجات المشرو من عدمه.

المشرو .وجود نظام فعاا للتواال وتبادا المعلومات بين أطراف .23

توشيق أعماا وأنشطة المشرو بشكل واضح وعبر تقارير دورية. .24

وجود نظام فعاا لإدارة معلومات وبيانات المشرو ومعالجتها. .25

العوامل الطبيعية من ريات وأمطار وارتفا في درجات الحرارة. .26

باستمرار.قيام الاستشاري والمقاوا بتطوير وتحسين قدراتهم .27

28. وجود أوامر تغيرية التي يحدشها المالك/ من يمثله في اطط وأهداف

وتصميم المشرو أشناء التنفيذ.

29. سرعة اعتماد المالك / من يمثله للمستخلصات والدفعات وارفها

وفق التعاقد.

وجود وتنفيذ اطة لتخزين المواد اللازمة للمشرو . .31

تنفيذ للمشرو قابلة للتطبيق. ااتيار طر .31

( وسرعة اعتمادها.shop drawingsتدقيق ومراجعة مستمرة لل ن .32

.As built drawingsحفظ مخططات تنفيذ المشرو مع وجود .33

34. مشاركة المقاوا والاستشاري بإعداد اطة وتعليمات التشغيل

والصيانة للمشرو بعد الانتهاء من تنفيذه.

نشكر ونقدر تعاونكم معنا لإنجاح هذا البحث العلمي

Appendix IV: Criterion and structural validity of the questionnaire

254

Table A 4: Internal validity of the questionnaire

Domain Item no.

Correlation

coefficient (r)

between items

and domain

Correlation

coefficient (r)

between items

and whole

questionnaire

Item

no.

Correlation

coefficient (r)

between items

and domain

Correlation

coefficient (r)

between items and

whole questionnaire

Correlation

coefficient (r)

between domain

and whole

questionnaire

KPIs

1 0.848** 0.716** 8 0.766** 0.522*

0.874**

2 0.824** 0.645** 9 0.734** 0.486*

3 0.712** 0.822** 10 0.636** 0.515*

4 0.767** 0.527* 11 0.583** 0.621**

5 0.607** 0.722** 12 0.705** 0.479*

6 0.5* 0.605** 13 0.652** 0.545**

7 0.694** 0.506*

Factors related to

conceptualizing and

preparation phase

1 0.678** 0.568** 7 0.581** 0.536*

0.812**

2 0.474* 0.706** 8 0.564** 0.781**

3 0.507* 0.654** 9 0.587** 0.545**

4 0.535* 0.54** 10 0.516* 0.82**

5 0.809** 0.664** 11 0.76** 0.717**

6 0.716** 0.498* 12 0.463* 0.61**

Factors related to

planning and

designing phase

1 0.435* 0.489* 11 0.787** 0.78**

0.794**

2 0.548** 0.474* 12 0.818** 0.446*

3 0.784** 0.635** 13 0.452* 0.51*

4 0.559** 0.634** 14 0.757** 0.44*

5 0.725** 0.461* 15 0.844** 0.568**

6 0.463* 0.53* 16 0.503* 0.631**

7 0.578** 0.643** 17 0.797** 0.64**

255


Domain Item no.

Correlation

coefficient (r)

between items

and domain

Correlation

coefficient (r)

between items

and whole

questionnaire

Item

no.

Correlation

coefficient (r)

between items

and domain

Correlation

coefficient (r)

between items and

whole questionnaire

Correlation

coefficient (r)

between domain

and whole

questionnaire

8 0.696** 0.478* 18 0.808** 0.492*

9 0.474* 0.514* 19 0.488* 0.56**

10 0.539** 0.672**

Factors related to

tendering and

contracting phase

1 0.565** 0.587** 9 0.444* 0.528*

0.851**

2 0.606** 0.61** 10 0.457* 0.537**

3 0.512* 0.753** 11 0.514* 0.474*

4 0.642** 0.736** 12 0.475* 0.604**

5 0.57** 0.479* 13 0.748** 0.577**

6 0.654** 0.761** 14 0.841** 0.82**

7 0.49* 0.499* 15 0.596** 0.466*

8 0.596** 0.79** 16 0.62** 0.448*

Factors related to

implementation

phase

1 0.591** 0.721** 18 0.826** 0.521*

0.882**

2 0.541** 0.49* 19 0.538** 0.794**

3 0.541** 0.452* 20 0.681** 0.619**

4 0.665** 0.749** 21 0.72** 0.458*

5 0.615** 0.492* 22 0.796** 0.67**

6 0.637** 0.667** 23 0.643** 0.5*

7 0.729** 0.551** 24 0.612** 0.63**

8 0.492* 0.646** 25 0.834** 0.534*

9 0.471* 0.732** 26 0.627** 0.45*

10 0.817** 0.535* 27 0.522* 0.801**

256


Domain Item no.

Correlation

coefficient (r)

between items

and domain

Correlation

coefficient (r)

between items

and whole

questionnaire

Item

no.

Correlation

coefficient (r)

between items

and domain

Correlation

coefficient (r)

between items and

whole questionnaire

Correlation

coefficient (r)

between domain

and whole

questionnaire

11 0.635** 0.536* 28 0.614** 0.671**

12 0.571** 0.833** 29 0.505* 0.841**

13 0.727** 0.797** 30 0.649** 0.649**

14 0.77** 0.46* 31 0.701** 0.79**

15 0.806** 0.705** 32 0.786** 0.566**

16 0.806** 0.654** 33 0.836** 0.621**

17 0.562** 0.453* 34 0.823** 0.449*

Appendix V: Summary of selected and omitted KPIs and CSFs

258

Table A 5: Summary of selected KPIs

No. Indicators from literature Resource Notes New Indicator

1 Schedule indicators

Shenhar et al (2001); Chan et al (2002);

Dvir et al (2003); Frimpong et al

(2003); Dvir and Lechler (2004); Chan

and Chan (2004); Chan et al (2004a);

Hughes et al (2004); Bryde and

Robinson (2005); Wang and Huang

(2006); Sambasivan and Soon (2007);

Ko and Cheng (2007); Ahadzie et al

(2008); Lam et al (2007); Enshassi et al

(2009a); Yeung et al (2009); Cho et al

(2009); Ling and Bui (2010); Ahsan and

Gunawan (2010); Yang et al (2011); Al-

Tmeemy et al. (2011); Meng (2012); Ng

et al (2012); LI et al (2012); Chou et al

(2013); Hwang et al (2013); Alzahrani

and Emsley (2013); Cserháti and Szabó

(2014); Alias et al (2014); Locatelli et al

(2014).

Modified Actual project duration compared

with planned duration.

2 Cost indicators


Dvir et al (2003); Frimpong et al

(2003); Dvir and Lechler (2004); Chan

and Chan (2004); Chan et al (2004a);

Hughes et al (2004); Bryde and

Robinson (2005); Wang and Huang

(2006); Sambasivan and Soon (2007);

Ko and Cheng (2007); Ahadzie et al

(2008); Lam et al (2007); Enshassi et al

(2009a); Yeung et al (2009); Cho et al

(2009); Ling and Bui (2010); Ahsan and

Gunawan (2010); Yang et al (2011); Al-

Tmeemy et al. (2011); Meng (2012); Ng

Modified Actual project costs compared with

planned budget.

259



et al (2012); LI et al (2012); Chou et al

(2013); Ali et al (2013); Alzahrani and

Emsley (2013); Alias et al (2014);

Locatelli et al (2014).

3 Satisfying the customers' needs


Dvir et al (2003); Dvir and Lechler

(2004); Chan and Chan (2004); Chan et

al (2004a); Hughes et al (2004); Bryde

and Robinson (2005); Lam et al (2007);

Enshassi et al (2009a); Yeung et al

(2009); ); Ling and Bui (2010); Yang et

al (2011); Al-Tmeemy et al. (2011);

Chou et al (2013); Ali et al (2013);

Alias et al (2014).

Modified Beneficiaries satisfaction on project

functionality.

4 Satisfying stakeholders (other

than customer)

Chan et al (2002); Chan and Chan

(2004); Chan et al (2004a); Hughes et al

(2004); Bryde and Robinson (2005);

Lam et al (2007); Ahadzie et al (2008);

Enshassi et al (2009a); Cho et al (2009);

Ling and Bui (2010); Yang et al (2011);

Chou et al (2013); Mir and Pinnington

(2014); Cserháti and Szabó (2014)

Modified Project parties satisfaction.

5 Quality of service and work


(2004); Hughes et al (2004); Wang and

Huang (2006); Lam et al (2007);

Ahadzie et al (2008); Yeung et al

(2009); Enshassi et al (2009a); Ling and

Bui (2010); Cho et al (2009); Yang et al

(2011); Al-Tmeemy et al. (2011); Meng

(2012); Ng et al (2012); LI et al (2012);

Chou et al (2013); Hwang et al (2013);

Modified Project conformity to quality and


260



Ali et al (2013); Alzahrani and Emsley

(2013); Alias et al (2014)

6 Safety (accident rate)

Chan and Chan (2004); Hughes et al

(2004); Ko and Cheng (2007); Enshassi

et al (2009a); Yeung et al (2009); Ali et

al (2013); Alzahrani and Emsley (2013)

Modified Accidents and injures number in the

project.

7 Financial stability

Chan et al (2002); Ali et al (2013);

Alzahrani and Emsley (2013); Mir and

Pinnington (2014)

Modified

Financial ability for both owner and

contractor to cover project

expenditures

8 Reputation “professional image”

Chan et al (2002); Dvir et al (2003);

Lam et al (2007); Al-Tmeemy et al.

(2011); Cserháti and Szabó (2014)

Modified Contractor and consultant reputation .

9 Benchmarks Lam et al (2007); Shehata and El-

Gohary (2012); Ali et al (2013) Modified

Project profitability for contractor

comparing with other related projects

10 Cost of change orders Ko and Cheng (2007); LI et al (2012) Modified Quantity and costs of variation orders.

11 Environmental impact


(2004); Hughes et al (2004); Ahadzie et

al (2008); Enshassi et al (2009a);

Alzahrani and Emsley (2013)

Modified Project conformity to environment


12 Disputes, arbitrations and

litigations

Chan et al (2002); Chan et al (2004a);

Sambasivan and Soon (2007); Chen and

Chen (2007); Lam et al (2007); LI et al

(2012)

Modified Number and size of disputes,

litigations.

13

Added Project conformity to sustainability

criteria.

14 Profitability

Chan et al (2002); Dvir et al (2003);

Chan and Chan (2004); Ling and Bui

(2010); Al-Tmeemy et al (2011); Ng et

al (2012); Ali et al (2013); Alzahrani

and Emsley (2013); Mir and Pinnington

(2014).

Merged

261



15 Meeting the technical

specification


Dvir et al (2003); Chan and Chan

(2004); Bryde andRobinson (2005);

Ling and Bui (2010); Al-Tmeemy et al.

(2011); Alzahrani and Emsley (2013)

Merged

16 Efficiency

Chan et al (2002); Chen and Chen

(2007); Lam et al (2007); LI et al

(2012); Ali et al (2013); Mir and

Pinnington (2014)

Merged

17 Impact on Long Term Benefits

Shenhar et al (2001); Mir and

Pinnington (2014); Cserháti and Szabó

(2014

Merged

18 Functional requirements


Dvir et al (2003); Chan and Chan

(2004); Lam et al (2007); Al-Tmeemy

et al. (2011)

Merged

19 Design team satisfaction Chan et al (2002); Chan and Chan

(2004) Merged

20 Construction team’s satisfaction Chan et al (2002); Chan and Chan

(2004) Merged

21 Quantity of change orders Ko and Cheng (2007); LI et al (2012) Merged

22 Overall performance Wang and Huang (2006); Sambasivan

and Soon (2007) Merged

23 Effectiveness of planning Ali et al (2013); Locatelli et al (2014) Cancelled

24 Growth/ market share

Shenhar et al (2001); Dvir et al (2003);

Cho et al (2009); Al-Tmeemy et al.

(2011); Ali et al (2013); Alzahrani and

Emsley (2013); Mir and Pinnington

(2014)

Cancelled

25 productivity Chan et al (2002); Ko and Cheng

(2007); Enshassi et al (2009a); Shehata Cancelled

262



and El-Gohary (2012)

26 Aesthetics Chan et al (2002); Lam et al (2007);

Yeung et al (2009); Chou et al (2013) Cancelled

27 Risk Chou et al (2013) Cancelled

28 Human resources Chou et al (2013) Cancelled

29 Communication Wang and Huang (2006); Yeung et al

(2009); Chou et al (2013) Cancelled

30 Procurement Dvir et al (2003); Chou et al (2013) Cancelled

31 Pre-contract costs LI et al (2012) Cancelled

32 Learning value Lam et al (2007); Enshassi et al

(2009a); Yeung et al (2009) Cancelled

263

Table A 6: Summary of selected and modified CSFs

No. Factor Resource Notes New factor

1. Accidents and hazards

Park (2009); Gudienė et al (2013); Gudienė et al

(2014); Marzouk and El-Rasas (2014);

Zavadskas et al (2014).

Modified 1. Preparing safety and

health plans..

2. Change in goals plans and

orders

Davies (2002); Dvir and Lechler (2004); Hughes

et al (2004); Fortune and White (2006); Orangi et

al (2011); Lehtiranta et al (2012); Yong and

Mustaffa (2013); Hwang et al (2013); Marzouk

and El-Rasas (2014); Wibowo and Alfen (2014);

Yang et al (2015).

Modified

2. Client changes in plans

and goals during

execution.

3. Commitment to continuous

improvement

Davies (2002); Chen and Chen (2007); Meng

(2012); Cserháti and Szabó (2014); Yang et al

(2015)

Modified

3. Consultant and

contractor commitment

to continuous

improvement.

4. Knowledge management Davies (2002); Yang et al (2012); Zou et al

(2014). Modified

4. Effective knowledge

processing and

management systems.

5.

Performance measurement

(Management for successful

outcome).

Davies (2002); Omran and Mamat (2011); Yu

and Kwon (2011); Zawawi et al (2011); Meng

(2012); Mir and Pinnington (2014); Cserháti and


Modified 5. Annual measuring of

KPIs.

6. Control of subcontractor

works

Sambasivan and Soon (2007); Ling and Bui

(2010); Orangi et al (2011); LI et al (2012);

Yong and Mustaffa (2013).

Modified 6. Control and monitoring

subcontractors works.

7.

The project has a clear and

well-planned agenda of

meetings for all participants

Dvir et al (2003); Nguyen et al (2004); Andersen

et al (2006); Iyer and Jha ( 2006); Chen et al

(2012); Garbharran et al (2012).

Modified

7. Annual organized

meetings related to

project activities for all

participants.

8. Parties relationships and

coordination

Chan et al (2004); Meeampol and Ogunlana

(2006); Wang and Huang (2006); Iyer and Jha (

2006); Lu et al (2008); Ng et al (2009); Park

(2009); Tan and Ghazali (2011); Omran and

Modified

8. Social relationships and

coordination between


264



Mamat (2011); Yu and Kwon (2011); Meng

(2012); Hwang et al (2013); Molenaar et al

(2013); Yong and Mustaffa (2013); Cserháti and


9. Team members number and

performance

Wang and Huang (2006); Zavadskas et al (2014);

Ihuah et al (2014); Yang et al (2015). Modified

9. Availability of enough

staff in project site

according to works

requirements.

10. Project nature Chan et al (2004); Cho et al (2009); Yong and

Mustaffa (2013); Shehu et al (2014). Modified

10. Determining the


nature (housing,

infrastructure, public

building, …)

11.

Leadership, monitoring,

coordinating, organizing

manager skills for both

contractor PM and owner

Bourne et al (2002); Dvir et al (2003); Turner

and Müller (2005); Iyer and Jha ( 2006);

Andersen et al (2006); Fortune and White

(2006); Lu et al (2008); Ng et al (2009); Park

(2009); Tan and Ghazali (2011); Yang et al

(2011); Omran and Mamat (2011); Zawawi et al

(2011); Lehtiranta et al (2012); Ismail et al

(2012); Alzahrani and Emsley (2013); Gudienė et

al (2013); Zhao et al (2013); Gudienė et al

(2014); Alias et al (2014); Mir and Pinnington

(2014).

Modified

11. Leadership,

monitoring,

coordinating and

organizing manager

skills of project

manager.

12. Decision-making

effectiveness

Frimpong et al (2003); Dvir et al (2003); Iyer

and Jha ( 2006); Park (2009); Tan and Ghazali

(2011); Yu and Kwon (2011); Meng (2012);

Lehtiranta et al (2012); Gudienė et al (2013);

Gudienė et al (2014); Ihuah et al (2014).

Modified

12. Clear and effective

decision making

mechanism.

13. Commitment of all project

participants

Bourne et al (2002); Chan et al (2004a); Nguyen

et al (2004); Hughes et al (2004); Iyer and Jha (

2006); Wang and Huang (2006); Chen and Chen

Modified

13. Commitment of team

members on project

plans and objectives.

265



(2007); Aksorn and Hadikusumo (2008); Chan et

al (2010); Omran and Mamat (2011); Tan and

Ghazali (2011);Chen et al (2012); Garbharran et

al (2012); Lehtiranta et al. (2012); Ismail et al

(2012); Ng et al (2012); Yong and Mustaffa

(2013); Cserháti and Szabó (2014); Alias et al

(2014); Zou et al (2014).

14. Environmental plan and

methods during construction

Fortune and White (2006); Lu et al (2008); Ng et

al (2009); Park (2009); Lu and Yuan et al

(2010); Ismail et al (2012); Alzahrani and

Emsley (2013); Son and Kim (2014); Wibowo

and Alfen (2014); Zavadskas et al (2014).

Modified

14. Preparing and

implementing

environmental plans

included project waste

management works.

15. Safety issues

Chan et al (2004); Hughes et al (2004); Lu et al

(2008); Aksorn and Hadikusumo (2008); Ng et al

(2009); Park (2009); Alhaadir and

Panuwatwanich (2011); Gudienė et al (2013);

Yong and Mustaffa (2013); Gudienė et al (2014);

Son and Kim (2014).

Modified

15. Appropriate safety

practices during project

execution.

16. Profitability

Ng et al (2009); Park (2009); Ng et al (2012);

Famakin et al (2012); Gudienė et al (2013); Zhao

et al (2013); Gudienė et al (2014); Zavadskas et

al (2014).

Modified

16. Project profitability for

consultant and

contractor

17.

Contract management and

documentation include

penalties, bonds, incentives,

..etc

Frimpong et al (2003); Dvir et al (2003); Nguyen

et al (2004); Chan et al (2004a); Hughes et al

(2004); Wang and Huang (2006); Lu et al

(2008); Ng et al (2009); Park (2009); Tan and

Ghazali (2011); Abdul-Aziz and Kassim (2011);

Chen et al (2012); LI et al (2012); Famakin et al

(2012); Ng et al (2012); Garbharran et al (2012);

Lehtiranta et al (2012); Verburg et al (2013);

Gudienė et al (2013); Yong and Mustaffa (2013);

Alzahrani and Emsley (2013); Gudienė et al

Modified

17. Effective contract

management included

precise formulation,

documentation and

enough detailed

incentives, bonds,

penalties, …etc.

266



(2014); Marzouk and El-Rasas (2014).

18. Subcontractor and contractor

Involvement

Chan et al (2004); Ng et al (2009); Park (2009);

Tan and Ghazali (2011); LI et al (2012). Modified

18. Participating of related

project parties in

financial and technical

evaluation of tenders.

19. Project type

Chan et al (2004); Yang et al (2011); Cho et al

(2009); Gudienė et al (2013); Gudienė et al

(2014); Locatelli et al (2014); Shehu et al (2014);

Yang et al (2015).

Modified

19. Project type (new,

maintenance,

completion for existing

one or rubble removal

project)

20. Reputation Ng et al (2009); Abdul-Aziz and Kassim (2011);

Verburg et al (2013) Modified

20. Consider consultant and

contractor past

performance and

reputation as awarding

criteria.

21. Transparent and efficient

procurement method

Frimpong et al (2003); Dvir et al (2003); Chan

et al (2004); Wang and Huang (2006); Lu et al

(2008); Ng et al (2009); Chan et al (2010); Ling

and Bui (2010); Tan and Ghazali (2011);

Garbharran et al (2012); Gudienė et al (2013);

Yong and Mustaffa (2013); Windapo and Cattell

(2013); Gudienė et al (2014); Shehu et al (2014);

Son and Kim (2014); Wibowo and Alfen (2014).

Modified

21. Transparent and

efficient procurement

criteria depends on

applicable laws and

regulations.

22. Size

Chan et al (2004); Fortune and White (2006); Lu

et al (2008); Cho et al (2009); Ng et al (2012);

Gudienė et al (2013); Gudienė et al (2014);

Shehu et al (2014); Yang et al (2015).

Modified 22. Predetermining of

project size and budget.

23. Legal environment

Lu et al (2008); Chan et al (2010); Yu and Kwon

(2011); Ng et al (2012); Gudienė et al (2013);

Zhao et al (2013)Gudienė et al (2014); Wibowo

and Alfen (2014).

Modified

23. Availability of

organized legal

environment i.e. (laws

of industry

encouragement, conflict

267



resolution, litigations,

…etc).

24. Design management change

and mistakes

Dvir et al (2003); Ahsan and Gunawan (2010);

Lu and Yuan et al (2010); Tan and Ghazali

(2011); Orangi et al (2011); Lehtiranta et al

(2012); LI et al (2012); Yong and Mustaffa

(2013); Son and Kim (2014); Marzouk and El-

Rasas (2014);

Modified

24. Designing project

according to updated

codes and standards in

order to eliminate

possible errors.

25. Clear and realistic and

sharable multi-benefit goals

vision and mission of projects

Bourne et al (2002); Dvir et al (2003); Nguyen et

al (2004); ); Hughes et al (2004); Chan et al

(2004a); Iyer and Jha ( 2006); Fortune and White

(2006); Andersen et al (2006); Chen and Chen

(2007); Aksorn and Hadikusumo (2008); Lu et al

(2008); Toor et al (2008); Yang et al (2009);

Ahsan and Gunawan (2010); Chan et al (2010);

Alhaadir and Panuwatwanich (2011); Tan and

Ghazali (2011); Garbharran et al (2012);

Lehtiranta et al. (2012); Ng et al (2012);

Famakin et al (2012); Gudienė et al (2013);

Molenaar et al (2013); Yong and Mustaffa

(2013); Verburg et al (2013); Gudienė et al

(2014); Ihuah et al (2014); Son and Kim (2014);


Modified

25. Deterministic, clear,

sharable and realistic

project objectives.

26. Technical capability

(contractor and managers)

Chan et al (2004); Iyer and Jha ( 2006); Wang

and Huang (2006); Chen and Chen (2007); Lu et

al (2008); Ng et al (2009); Tan and Ghazali

(2011); Gudienė et al (2013); Alzahrani and

Emsley (2013); Gudienė et al (2014).

Modified

26. Efficient technical

capability of consultant

for example existence

of skilled team and

designers.

27. Quality standards and criteria

Tan and Ghazali (2011); Gudienė et al (2013);


Son and Kim (2014); Yang et al (2015).

Modified

27. Specific and

measurable project

quality standards.

28. Consultant recruitment and Bourne et al (2002); Fortune and White (2006); Modified 28. Consultant recruitment

268



involvement in budgeting and

supervision

Wang and Huang (2006); Ahsan and Gunawan

(2010); Jagboro et al. (2012); Molenaar et al

(2013); Yong and Mustaffa (2013).

and involvement in all

project activities.

29. Design completed before

work on site Park (2009). Modified

29. Suitable and enough

time for project

planning and designing.

30. Value

Dvir et al (2003); Dvir and Lechler (2004); Cho

et al (2009); Ng et al (2012); Gudienė et al

(2013); Zhao et al (2013); Gudienė et al (2014);

Son and Kim (2014); Yang et al (2015).

Modified 30. Project feasibility and

priority for society.

31. Financial security and

stability (contractor, owner)

Frimpong et al (2003); Nguyen et al (2004);

Chan et al (2004); Chen and Chen (2007); Lu et

al (2008); Ng et al (2009); Park (2009); Chen et

al (2012); Famakin et al (2012); Ng et al (2012);

Hwang et al (2013); Zhao et al (2013); Gudienė

et al (2013); Gudienė et al (2014); Marzouk and

El-Rasas (2014); Wibowo and Alfen (2014).

Modified

31. Adequacy and effective

management of project

financial and material

resources.

32. Project team leader

involvement and authority

Chan et al (2004); Turner and Müller (2005);

Andersen et al (2006); Iyer and Jha ( 2006); Tan

and Ghazali (2011); Yong and Mustaffa (2013);

Ihuah et al (2014).

Modified

32. Delegation and

authority allocation of

project workers.

33. Construction regulations

Chan et al (2004); Park (2009); Lu and Yuan et

al (2010); Zhao et al (2013); Gudienė et al

(2013); Windapo and Cattell (2013); Gudienė et

al (2014); Ihuah et al (2014); Son and Kim

(2014); Wibowo and Alfen (2014).

Modified

33. Approved, clear and

updated codes,

specifications and

regulations for


34. Cultural issues

Bourne et al (2002); Chen and Chen (2007);

Ahsan and Gunawan (2010); Orangi et al (2011);

Zawawi et al (2011); Chen et al (2012); Gudienė

et al (2013); Gudienė et al (2014); Ihuah et al

(2014).

Modified

34. Social, cultural and

environmental impacts

on project type, design

and planning.

35. Community, international Fortune and White (2006); Chen and Chen Modified 35. Involvement of local

269



and end user involvement (2007); Orangi et al (2011); Yang et al (2011);

Garbharran et al (2012); Ng et al (2012); Ihuah

et al (2014).

community, project

beneficiaries and the

affected parties in

project plans and

policies.

36. Depreciation/devaluation of

local currency

Hughes et al (2004); Ahsan and Gunawan

(2010); Gudienė et al (2014). Modified

36. Economic environment

in terms of materials

quantity, quality, and

price, local currency

value, …etc.

37. Clear prioritization of project

goals by the client

Chan et al (2004); Toor et al (2008); Yang et al

(2009); Ling and Bui (2010); Yang et al (2011);



Modified

37. Client understanding of

project nature priorities

and needs.

38. Political influence

Chan et al (2004); Chan et al (2004a); Iyer and

Jha ( 2006); Fortune and White (2006); Ng et al

(2009); Chan et al (2010); Abdul-Aziz and

Kassim (2011); Tan and Ghazali (2011);

Garbharran et al (2012); Ng et al (2012); Yong

and Mustaffa (2013); Zhao et al (2013); Gudienė

et al (2013); Gudienė et al (2014).

Modified

38. Recognizing political

influence on the

project.

39. Natural calamities

Frimpong et al (2003); Iyer and Jha ( 2006);

Ahsan and Gunawan (2010); Orangi et al (2011);



Modified

39. Natural climates like

winds, rains and high

temperature.


understanding

Gudienė et al (2014); Gudienė et al (2013); Chan

et al (2004); Chan et al (2004a); Chen et al

(2012); Famakin et al (2012); Park (2009); Tan

and Ghazali (2011); Verburg et al (2013); Chen

and Chen (2007); Yong and Mustaffa (2013)

Modified


understanding between


41. Collaborative team culture Chan et al (2004a); Iyer and Jha ( 2006); Aksorn

and Hadikusumo (2008); Lu et al (2008); Ng et Modified

41. Collaborative team

working environment.

270



al (2009); Park (2009); Yang et al (2009);

Alhaadir and Panuwatwanich (2011); Yang et al

(2011); Chen et al (2012); Meng (2012);

Famakin et al (2012); Ismail et al (2012);

Verburg et al (2013); Yang et al (2015).

42. Management support

Bourne et al (2002); Chan et al (2004a); Nguyen

et al (2004); Iyer and Jha ( 2006); Andersen et al

(2006); Fortune and White (2006); Aksorn and

Hadikusumo (2008); Lu et al (2008); Alhaadir

and Panuwatwanich (2011); Garbharran et al

(2012); Gudienė et al (2013); Yong and

Mustaffa (2013); Gudienė et al (2014); Alias et

al (2014); Chen et al (2012); Ihuah et al (2014);


Modified

42. Top management

support for project

workers.

43. Physical environment (civil

works, location, weather,

..etc)

Frimpong et al (2003); Chan et al (2004); Lu et

al (2008); Ahsan and Gunawan (2010); Tan and

Ghazali (2011); Zawawi et al (2011); Windapo

and Cattell (2013); Gudienė et al (2013);

Gudienė et al (2014); Ihuah et al (2014); Shehu

et al (2014); Son and Kim (2014); Marzouk and

El-Rasas (2014); Wibowo and Alfen (2014).

Modified

43. Project physical

environment of project

like (location, soil

works, availability of

surrounding

infrastructure, … etc.)

44. Realistic time forecasting and

schedule management

Bourne et al (2002); Dvir et al (2003); Fortune

and White (2006); Andersen et al (2006);

Meeampol and Ogunlana (2006); Lu et al (2008);

Ng et al (2009); Park (2009); Abdul-Aziz and

Kassim (2011); Famakin et al (2012); Hwang et

al (2013); Gudienė et al (2013); Molenaar et al

(2013); Gudienė et al (2014); Ihuah et al (2014);

Marzouk and El-Rasas (2014); Zavadskas et al

(2014)

Modified

44. Effective schedule

management and

realistic forecasting of

project duration.

45. Ability to Generate

Innovative Ideas

Chan et al (2004a); Lu et al (2008); Lu and Yuan

et al (2010); Ng et al (2012); Gudienė et al Modified

45. Ability of project

parties to generate

271



(2013); Gudienė et al (2014). innovative ideas.

46. Close relationship with

suppliers Orangi et al (2011); Ismail et al (2012). Merged

Availability and

execution of material

handling plans.

47. Client approvals and

Payment method

Frimpong et al (2003); Sambasivan and Soon

(2007); Ng et al (2009); Orangi et al (2011); LI

et al (2012); Marzouk and El-Rasas (2014).

Selected 46. Client approvals and

Payment method.

48. The project has effective well

established information and

communication routines

Bourne et al (2002); Dvir et al (2003); Nguyen et

al (2004); Chan et al (2004); Meeampol and

Ogunlana (2006); Wang and Huang (2006);

Fortune and White (2006); Iyer and Jha ( 2006);

Chen and Chen (2007); Sambasivan and Soon

(2007); Lu et al (2008); Aksorn and Hadikusumo

(2008); Park (2009); Yang et al (2009); Chan et

al (2010); Lu and Yuan et al (2010); Alhaadir

and Panuwatwanich (2011); Yang et al (2011);

Tan and Ghazali (2011); Omran and Mamat

(2011); Yu and Kwon (2011); Abdul-Aziz and

Kassim (2011); Orangi et al (2011) ; Chen et al

(2012); Alias et al (2014); Gudienė et al (2014);

Cho et al (2009); Famakin et al (2012);

Garbharran et al (2012); Ismail et al (2012);

Meng (2012); Lehtiranta et al. (2012); Molenaar

et al (2013); Yong and Mustaffa (2013); Gudienė

et al (2013); Verburg et al (2013); Ihuah et al

(2014); Cserháti and Szabó (2014); Zou et al

(2014).

Selected

47. Effective well

established information

and communication

routines.

49. Effective and timely conflict

resolution

Chan et al (2004a); Chan et al (2004); Iyer and

Jha ( 2006); Lu et al (2008); Park (2009); Cho et

al (2009); Yang et al (2009); Yu and Kwon

(2011); Famakin et al (2012); Gudienė et al

(2013); Gudienė et al (2014).

Selected 48. Timely and effective

conflict resolution.

272



50. Complexity and uniqueness

Chan et al (2004); Hughes et al (2004);

Meeampol and Ogunlana (2006); Fortune and

White (2006); Cho et al (2009); Park (2009); Tan

and Ghazali (2011); Yang et al (2011); LI et al

(2012); Gudienė et al (2013); Yong and Mustaffa

(2013); Gudienė et al (2014).

Selected 49. Project complexity and

uniqueness.


management and allocation

Davies (2002); Dvir et al (2003); Chan et al

(2004a); Fortune and White (2006); Lu et al

(2008); Park (2009); Chan et al (2010); Ismail et

al (2012); LI et al (2012); Lehtiranta et al

(2012); Ng et al (2012); Meng (2012); Yong and

Mustaffa (2013); Gudienė et al (2013); Gudienė

et al (2014); Ihuah et al (2014); Son and Kim

(2014); Zavadskas et al (2014).

Selected


management and

allocation.

52. Applicable Construction

methods

Bourne et al (2002); Meeampol and Ogunlana

(2006); Park (2009); Chan et al (2010);

Lehtiranta et al (2012); Hwang et al (2013);

Alzahrani and Emsley (2013); Gudienė et al

(2013); Gudienė et al (2014).

Selected 51. Using applicable

construction methods.

53. Effective control , such as

monitoring, updating plans

and feedback

Davies (2002); Frimpong et al (2003); Chan et al

(2004a); Nguyen et al (2004); Chan et al

(2004a); Andersen et al (2006); Wang and

Huang (2006); Iyer and Jha ( 2006); Meeampol

and Ogunlana (2006); Fortune and White

(2006); Toor et al (2008); Aksorn and

Hadikusumo (2008); Park (2009); Ahsan and

Gunawan (2010); Abdul-Aziz and Kassim

(2011); Tan and Ghazali (2011); Omran and

Mamat (2011); Chen et al (2012); Ng et al

(2012); Famakin et al (2012); Gudienė et al

(2013); Yong and Mustaffa (2013); Alias et al


Selected

52. Effective project

control , such as

monitoring, updating

plans and feedback

273



Son and Kim (2014); Zavadskas et al (2014).

54. Training the human resources

in the skill demanded by the

project

Fortune and White (2006); Iyer and Jha (2006);

Ng et al (2009); Lu and Yuan et al (2010);


Selected

53. Training the human

resources in the skills

demanded by the

project.

55. Project manager commitment

to meet cost quality and time

of project

Dvir et al (2003); Chan et al (2004); Meeampol

and Ogunlana (2006); Chen and Chen (2007); Lu

et al (2008); Park (2009); Omran and Mamat

(2011); Chen et al (2012); Gudienė et al (2013);

Son and Kim (2014); Cserháti and Szabó (2014).

Selected

54. Project manager

commitment to meet

cost quality and time of

project.

56. The project has a formal

organizational chart covering

the entire project

Chan et al (2004); Andersen et al (2006); Lu et

al (2008); Park (2009); Yu and Kwon (2011);

Zawawi et al (2011); Famakin et al (2012);

Gudienė et al (2013); Tan and Ghazali (2011);

Gudienė et al (2014); Son and Kim (2014);

Cserháti and Szabó (2014);

Selected

55. The project has a

formal organizational

chart covering the

entire project.

57.

All key participants have

participated in the detailed

project planning within their

area of expertise

Hughes et al (2004); Fortune and White (2006);

Andersen et al (2006); Famakin et al (2012);

Lehtiranta et al (2012); Yong and Mustaffa

(2013).

Selected

56. All key participants

have participate in the

detailed project

planning within their

area of expertise.

58. Strong /detailed and updated

integrated planning effort in


Bourne et al (2002); Frimpong et al (2003); Dvir

and Lechler (2004); Nguyen et al (2004); Hughes

et al (2004); Chan et al (2004); Chan et al

(2004a); Andersen et al (2006); Sambasivan and

Soon (2007); Fortune and White (2006); Ng et al

(2009); Cho et al (2009); Yu and Kwon (2011);

Garbharran et al (2012); Lehtiranta et al (2012);

Ismail et al (2012); LI et al (2012); Gudienė et al

(2013); Hwang et al (2013); Alias et al (2014);

Gudienė et al (2014); Ihuah et al (2014);

Locatelli et al (2014); Son and Kim (2014);

Selected

57. Strong, detailed and

updated integrated

planning effort in

design and

construction.

274



Cserháti and Szabó (2014); Marzouk and El-

Rasas (2014).

59. The project is part of a well-

documented or understood

strategy

Davies (2002); Dvir et al (2003); Hughes et al

(2004); Andersen et al (2006); Toor et al (2008);

Park (2009); Yu and Kwon (2011); Lehtiranta et

al (2012); Alzahrani and Emsley (2013); Ihuah et

al (2014); Son and Kim (2014); Mir and

Pinnington (2014); Zavadskas et al (2014).

Selected

58. The project is part of a

well-documented or

understood strategy

60. Parties relevant past

experience

Hughes et al (2004); Nguyen et al (2004); Dvir

and Lechler (2004); Chan et al (2004a); Fortune

and White (2006); Sambasivan and Soon

(2007);Chen et al (2007); Lu et al (2008); Ng et

al (2009); Park (2009); Cho et al (2009); Ling

and Bui (2010); Tan and Ghazali (2011); LI et al

(2012); Chen et al (2012); Famakin et al (2012);

Garbharran et al (2012); Ng et al (2012); Hwang

et al (2013); Alzahrani and Emsley (2013); Yong

and Mustaffa (2013); Zhao et al (2013); Gudienė

et al (2013); Gudienė et al (2014); Marzouk and

El-Rasas (2014).

Splitted

59. Past relevant

experience of

contractor in execution

similar projects.

60. Past relevant

experience of client in

awarding bids and

managing contracts.

61. Past related experience

of consultant in sharing

in similar bids and

contracts.

62. Past related experience

of contractor in sharing

in similar bids and

contracts.

63. Past relevant

experience of

consultant on designing

similar project.

61. Appropriate supervision and

site management

Bourne et al (2002); Meeampol and Ogunlana

(2006); Iyer and Jha ( 2006); Sambasivan and

Soon (2007); Aksorn and Hadikusumo (2008);

Lu and Yuan et al (2010); Orangi et al (2011);

Splitted

64. Updated plan for

supervising and

managing project site.

65. Permanent presence of

275



Alhaadir and Panuwatwanich (2011); Tan and

Ghazali (2011); Hwang et al (2013); Yong and

Mustaffa (2013); Gudienė et al (2013); Gudienė

et al (2014); Marzouk and El-Rasas (2014).

project manager in

project site.

62. Tendering/ bidding strategy

and management

Frimpong et al (2003); Nguyen et al (2004);

Wang and Huang (2006); Lu et al (2008); Toor

et al (2008); Park (2009); Lu and Yuan et al

(2010); Tan and Ghazali (2011); Abdul-Aziz and

Kassim (2011); Molenaar et al (2013); Yong and

Mustaffa (2013); Shehu et al (2014); Marzouk

and El-Rasas (2014).

Splitted

66. The client has a

mechanism to manage

the bids.

67. The consultant and the

contractor have a

mechanism to manage

the tenders and

compete.

63. Client contribution in design

and construction

Chan et al (2004); Chan et al (2004a); Nguyen

et al (2004); Hughes et al (2004); Andersen et al

(2006); Iyer and Jha ( 2006); Toor et al (2008);

Cho et al (2009); Orangi et al (2011); LI et al

(2012); Gudienė et al (2013); Ihuah et al (2014).

Splitted

68. Client contribution on

project designing and

planning.

69. The client follows

project implementation

regularly.

64. Construction permits Tan and Ghazali (2011); Ng et al (2012);

Gudienė et al (2013); Gudienė et al (2014). Splitted

70. Ease of having permits,

licenses and any related

approvals from

governmental

institutions.

71. Coordinating with

related formal parties

such as (municipalities,

electricity companies,

ministries,… etc.)

65. Added

72. Consultant and

contractors involvement

in project operating and

maintenance plan after

276



project execution.

66. Added 73. Saving as built

drawings of the project.

67. Added

74. Local community

acceptance to execute

the project in their

location.

68. Added

75. Continuous revision of

project shop drawings

and approve them fast.

69. Added 76.

70. Added

77. Granting enough time

for consultants and

contractors to fill out

the bid form.

71. Added

78. Visiting project

location by all

consultants and

contractors before

filling out the bid form.

72. Added

79. Documentation the

preparation meetings in

details.

73. Added

80. The client interprets all

project requirements

and location during the

bids preparatory

meeting.

74. Added

81. Considering operation

and maintenance

requirements into

project design.

277



75. Personal motivation

Aksorn and Hadikusumo (2008); Lu et al (2008);

Park (2009); Ahsan and Gunawan (2010);

Gudienė et al (2013); Alias et al (2014); Gudienė

et al (2014).

Canceled

76. Bureaucracy Nguyen et al (2004); Ahsan and Gunawan

(2010). Cancelled

77. The project is well described

and coordinated with other

projects and activities

Bourne et al (2002); Dvir and Lechler (2004);

Andersen et al (2006); Lu et al (2008); Zou et al

(2014).

Cancelled

78. Project ownership Davies (2002); Ihuah et al (2014). Cancelled

79. One major contractor and

consortium Ng et al (2012); Locatelli et al (2014). Cancelled

80. Project insurance Lu et al (2008); Ng et al (2009). Cancelled

81. Responsiveness of

correspondence Molenaar et al (2013). Cancelled

82. Commitment to corruption

eradication

Abdul-Aziz and Kassim (2011); Wibowo and

Alfen (2014). Cancelled

83. An acceptable level of tariff Ng et al (2012) Cancelled

84. Access to affordable

mortgage/credit Windapo and Cattell (2013). Cancelled

85. Critical global

issues/globalization Windapo and Cattell (2013). Cancelled

86. Contingency funds Ahsan and Gunawan (2010) Cancelled

87. Extent of subcontracting LI et al (2012); Gudienė et al (2013); Gudienė et

al (2014). Cancelled

88. Close supervision when new

construction techniques are

employed

Hughes et al (2004); Ling and Bui (2010). Cancelled

89. Willingness to Eliminate

Non-value Added Activities Chan et al (2004); Park (2009). Cancelled

90. Sustainable project design

and construction

Park (2009); Ng et al (2012); Windapo and

Cattell (2013). Cancelled

278



91. Project is not susceptible to

fast-paced change (e.g.

Technological change)

Dvir and Lechler (2004); Ng et al (2012). Cancelled

92. Customer focus competence Fink (2014) Cancelled

93. Fairness of new conditions to

employees Chen and Chen (2007); Ng et al (2012). Cancelled

94. Knowledge transfer Toor et al (2008); Famakin et al (2012); Cserháti

and Szabó (2014) Cancelled

95.

All the organizations

involved in the project effort

have agreed to provide the

project with sufficient

resources

Chan et al (2004); Chen et al (2012); Famakin

et al (2012); Garbharran et al (2012); Alzahrani

and Emsley (2013).

Cancelled

96. Commitment to Win-Win

Attitude (compatibility of

objectives)

Chan et al (2004); Abdul-Aziz and Kassim

(2011); Yu and Kwon (2011); Famakin et al

(2012); Meng (2012).

Cancelled

97. Partnering was started at the

design stage

Chan et al (2004); Chen and Chen (2007); Park

(2009); Chen et al (2012); Ismail et al (2012). Cancelled

98.

Open exchange and

consideration of ideas were

promoted during the

partnering process

Chan et al (2004a); Andersen et al (2006); Wang

and Huang (2006); Yang et al (2009); Chen et al

(2012).

Cancelled

99. A list of partner selection

criteria was developed

Chan et al (2004); Famakin et al (2012);

Verburg et al (2013). Cancelled

100. Strong and good private

consortium Chan et al (2010); Cserháti and Szabó (2014). Cancelled

101. Public -sector capacity Ng et al (2012); Windapo and Cattell (2013). Cancelled

102. Partnerships with local and

national stakeholders Ng et al (2012); Cserháti and Szabó (2014). Cancelled

103. Profit-sharing Abdul-Aziz and Kassim (2011); Meng (2012). Cancelled

104. Identifying stakeholders Yang et al (2009) Cancelled

105. Social environment Chan et al (2004); Iyer and Jha ( 2006); Park Merged

279



(2009); Yang et al (2009); Chan et al (2010);

Abdul-Aziz and Kassim (2011); Tan and Ghazali

(2011); Gudienė et al (2013); Yong and Mustaffa

(2013); Gudienė et al (2014).

106. Troubleshooting Gudienė et al (2013); Alias et al (2014); Gudienė

et al (2014). Merged

107. Project management was

systematic and methodical

Davies (2002); Frimpong et al (2003); Nguyen et

al (2004); Fortune and White (2006); Wang and

Huang (2006); Ng et al (2009); Park (2009); Yu

and Kwon (2011); Lehtiranta et al (2012); Son

and Kim (2014).

Merged

108. Transaction cost economics

(preplanning)

Park (2009); LI et al (2012); Son and Kim

(2014). Merged

109.

Service quality can be easily

defined and objectively

measured

Ng et al (2012); Marzouk and El-Rasas (2014);

Yang et al (2015). Merged

110. Product and service

certification Gudienė et al (2013); Gudienė et al (2014). Merged

111. Technological environment

Bourne et al (2002); Davies (2002); Dvir and

Lechler (2004); Nguyen et al (2004); Chan et al

(2004); Fortune and White (2006); Lu et al

(2008); Park (2009); Lu and Yuan et al (2010);

Tan and Ghazali (2011); Omran and Mamat

(2011); Garbharran et al (2012); Gudienė et al

(2013); Yong and Mustaffa (2013); Zhao et al

(2013); Verburg et al (2013); Windapo and

Cattell (2013); Alzahrani and Emsley (2013);

Gudienė et al (2014); Son and Kim (2014).

Merged

112. Skilled designers

Aksorn and Hadikusumo (2008); Park (2009);

Tan and Ghazali (2011);Gudienė et al (2014);

Locatelli et al (2014).

Merged

113. Staff qualification and skills Fortune and White (2006); Ng et al (2009); Park Merged

280



(2009); Tan and Ghazali (2011); Chen et al

(2012); Lehtiranta et al. (2012); LI et al (2012);

Yong and Mustaffa (2013); Alzahrani and

Emsley (2013); Verburg et al (2013); Windapo

and Cattell (2013); Cserháti and Szabó (2014);

Wibowo and Alfen (2014).

114. Rework due to errors during

construction

Sambasivan and Soon (2007); Orangi et al

(2011); Molenaar et al (2013); Marzouk and El-

Rasas (2014); Zavadskas et al (2014);

Merged

115. Litigation, disputes and

arbitrating tendency

Lu et al (2008); Park (2009); Molenaar et al

(2013); Alzahrani and Emsley (2013). Merged

116.

The detailed project plans are

understood and accepted by

all project team members

Andersen et al (2006); Iyer and Jha ( 2006);

Chen and Chen (2007); Toor et al (2008); Park

(2009).

Merged

117. Foreign (external) Experts’

Participation in Projects

Chan et al (2004a); Ling and Bui (2010); Chen et

al (2012). Merged

118. Having an explicit

competitive strategy Davies (2002); Lu et al (2008); Park (2009). Merged

119. Competition

Hughes et al (2004); Park (2009); Ahsan and

Gunawan (2010); Abdul-Aziz and Kassim

(2011); LI et al (2012); Ng et al (2012); Ihuah et

al (2014); Son and Kim (2014).

Merged

120. The costs of building

materials

Frimpong et al (2003); Windapo and Cattell

(2013). Merged

121. Delegation and allocation of

authority and responsibility

Chan et al (2004a); Andersen et al (2006); ); Iyer

and Jha ( 2006); Aksorn and Hadikusumo

(2008); Lu et al (2008); Park (2009); Chan et al

(2010); Alhaadir and Panuwatwanich (2011);

Omran and Mamat (2011); Zawawi et al (2011);

Lehtiranta et al. (2012); Alzahrani and Emsley

(2013); Gudienė et al (2013); Verburg et al

(2013); Gudienė et al (2014); Cserháti and Szabó

Merged

281



(2014); Zou et al (2014).

122. Sufficient resource allocation

Chan et al (2004b); Fortune and White (2006);

Aksorn and Hadikusumo (2008); Park (2009);

Alhaadir and Panuwatwanich (2011); Gudienė et

al (2014).

Merged

123. Waste management system Lu and Yuan et al (2010); Son and Kim (2014); Merged

124. Personal competency

Nguyen et al (2004); Fortune and White (2006);

Toor et al (2008); Aksorn and Hadikusumo

(2008); Ahsan and Gunawan (2010); Omran and

Mamat (2011); Tan and Ghazali (2011);

Garbharran et al (2012); Lehtiranta et al. (2012);


Gudienė et al (2014); Ihuah et al (2014); Cserháti

and Szabó (2014).

Merged

125.

Selection of PM with proven

track record at an early stage

by top management

Iyer and Jha ( 2006); Omran and Mamat (2011). Merged

126. Personal attitude and issues

Bourne et al (2002); Dvir and Lechler (2004);

Iyer and Jha ( 2006); Aksorn and Hadikusumo

(2008); Alhaadir and Panuwatwanich (2011);

Omran and Mamat (2011); Gudienė et al (2013);

Verburg et al (2013);Gudienė et al (2014).

Merged

127. Good governance

(government policy)

Ng et al (2009); Chan et al (2010); Ng et al

(2012); Wibowo and Alfen (2014). Merged

128. Research and development

Davies (2002); Lu et al (2008); Ng et al (2009);

Lu and Yuan et al (2010); Chan et al (2010);

Ismail et al (2012).

Merged

129.

A team leader or champion

was appointed to ensure that

partnering principles did not

slip out of focus

Chan et al (2004a) Merged

130. Government Officers’ Hughes et al (2004); Ling and Bui (2010); Chan Merged

282



Participation in Projects et al (2010); Locatelli et al (2014); Wibowo and

Alfen (2014).

131. Adequate and clear financial

budget

Bourne et al (2002); Dvir et al (2003); Frimpong

et al (2003); Wang and Huang (2006); Fortune

and White (2006); Andersen et al (2006);

Meeampol and Ogunlana (2006); Park (2009);

Ahsan and Gunawan (2010); Chan et al (2010);

Tan and Ghazali (2011); Yang et al (2011);

Garbharran et al (2012); Chen et al (2012);

Yong and Mustaffa (2013); Alzahrani and

Emsley (2013); Gudienė et al (2013); Alias et al


Locatelli et al (2014); Son and Kim (2014);

Zavadskas et al (2014);.

Merged

132. Economic viability

environment

Chan et al (2004); Iyer and Jha ( 2006); Enshassi

et al (2009); Chan et al (2010); Ahsan and

Gunawan (2010); Tan and Ghazali (2011); Ng et

al (2012); Windapo and Cattell (2013); Gudienė

et al (2013); Yong and Mustaffa (2013); Zhao et

al (2013); Gudienė et al (2014); Son and Kim

(2014); Wibowo and Alfen (2014);

Merged

133. Adequacy and management

of resources

Frimpong et al (2003); Dvir et al (2003); Nguyen

et al (2004); Hughes et al (2004); Iyer and Jha (

2006); Meeampol and Ogunlana (2006);

Sambasivan and Soon (2007); Chen and Chen

(2007); Lu et al (2008); Ng et al (2009); Lu and

Yuan et al (2010); Omran and Mamat (2011);

Orangi et al (2011); Garbharran et al (2012);

Ismail et al (2012); LI et al (2012); Chen et al

(2012); Lehtiranta et al (2012); Gudienė et al

(2013); Alzahrani and Emsley (2013); Yong and

Mustaffa (2013); Verburg et al (2013); Hwang et

Merged

283



al (2013); Memon et al (2013); Gudienė et al

(2014); Ihuah et al (2014); Son and Kim (2014);

Mir and Pinnington (2014); Marzouk and El-

Rasas (2014); Yang et al (2015).

134. Adaptability to changes,

management of Changes

Dvir et al (2003); Chan et al (2004); Andersen et

al (2006); Fortune and White (2006); Chen and

Chen (2007); Cho et al (2009); Ng et al (2009);

Chen et al (2012); Gudienė et al (2013); Yong

and Mustaffa (2013); Gudienė et al (2014);

Yang et al (2015).

Merged

135. Client ability on brief, define

roles and make decisions

Chan et al (2004); Iyer and Jha ( 2006); Cho et

al (2009); Tan and Ghazali (2011); Lehtiranta et

al (2012); Gudienė et al (2013); Hwang et al

(2013); Gudienė et al (2014); Son and Kim

(2014); Marzouk and El-Rasas (2014);

Merged

Appendix VI: RII, means, SD and rank of CSFs

285

Table A 7: RII, means, SD and ranks of CSFs

Item Mean S.D RII

Test

value

P-value

(Sig.)

Total

rank

Phase 1 Factors related to project conceptualizing and preparation phase 4.22 0.47 84.42 43.13 0.000* (3)**

CSF 1 Project feasibility and priority for the society. 4.63 0.59 92.55 45.56 0.000* 1

CSF 2 Deterministic, clear, sharable and realistic project objectives 4.38 0.67 87.69 34.07 0.000* 17

CSF 3 Predetermining of project size and budget. 4.38 0.67 87.53 34.04 0.000* 21

CSF 4 Project type (new, maintenance, completion for existing one or rubble removal

project). 4.19 0.79 83.85 24.65 0.000* 51

CSF 5 Determining the construction project nature (housing, infrastructure, public

building, …) 4.21 0.86 84.1 23.08 0.000* 48

CSF 6 Project complexity and uniqueness. 3.96 0.8 79.26 19.96 0.000* 74

CSF 7 Recognizing political influence on the project. 3.95 0.8 79.25 19.8 0.000* 75

CSF 8 Local community acceptance to execute the project in their location. 3.89 0.88 77.8 16.71 0.000* 77

CSF 9 Preparing safety and health plans. 4.13 0.79 82.64 23.57 0.000* 61

CSF 10 Client understanding of project nature priorities and needs 4.13 0.86 82.51 21.65 0.000* 62

CSF 11 Granting suitable and enough time for project planning and designing 4.35 0.88 86.96 25.35 0.000* 25

CSF 12 Consultant recruitment and involvement in all project activities. 4.2 0.96 83.96 20.59 0.000* 50

Phase 2 Factors related to project planning and designing phase 4.2 0.49 83.99 40.68 0.000* (4)**

CSF 13 Coordinating with related formal parties such as (municipalities, electricity

companies, ministries,… etc.). 4.57 0.61 91.43 42.64 0.000* 2

CSF 14 Client contribution on project designing and planning. 4.23 0.77 84.63 26.24 0.000* 46

CSF 15 Past relevant experience of consultant on designing similar project. 4.44 0.68 88.79 35.05 0.000* 9

286


Item Mean S.D RII

Test

value

P-value

(Sig.)

Total

rank

CSF 16 Ability of project parties to generate innovative ideas. 4.06 0.72 81.17 24.29 0.000* 69

CSF 17 Specific and measurable project quality standards. 4.31 0.7 86.1 30.88 0.000* 34

CSF 18 Approved, clear and updated codes, specifications and regulations for

construction industry. 4.38 0.7 87.69 32.52 0.000* 18

CSF 19 Efficient technical capability of consultant for example existence of skilled

team and designers. 4.44 0.72 88.79 33.24 0.000* 10

CSF 20 Designing project according to updated codes and standards in order to

eliminate possible errors. 4.45 0.72 89.08 33.53 0.000* 7

CSF 21 Considering operation and maintenance requirements into project design. 4.26 0.81 85.15 25.73 0.000* 37

CSF 22 Social, cultural and environmental impacts on project type, design and

planning. 3.88 0.88 77.65 16.6 0.000* 78

CSF 23 Project physical environment of project like (location, soil works, availability

of surrounding infrastructure, … etc.). 4.24 0.78 84.84 26.26 0.000* 43

CSF 24 Ease of having permits, licenses and any related approvals from governmental

institutions. 4.16 0.73 83.22 26.11 0.000* 58

CSF 25 Availability of organized legal environment i.e. (laws of industry

encouragement, conflict resolution, litigations, …etc). 3.9 0.86 78.02 17.35 0.000* 76

CSF 26 Strong, detailed and updated integrated planning effort in design and

construction. 4.25 0.75 85.05 27.55 0.000* 40

CSF 27 All key participants have participate in the detailed project planning within

their area of expertise. 4.07 0.78 81.4 22.57 0.000* 67

CSF 28 Effective schedule management and realistic forecasting of project duration. 4.07 0.8 81.47 22.27 0.000* 66

CSF 29 The project has a formal organizational chart covering the entire project. 4.12 0.79 82.49 23.52 0.000* 63

CSF 30 Risk identification management and allocation. 4.14 0.78 82.78 24.04 0.000* 60

CSF 31 Involvement of local community, project beneficiaries and the affected parties

in project plans and policies. 3.81 0.9 76.12 14.71 0.000* 80

287


Item Mean S.D RII

Test

value

P-value

(Sig.)

Total

rank

Phase 3 Factors related to project tendering and contracting phase 4.28 0.46 85.53 45.43 0.000* (1)**

CSF 32 The client has a mechanism to manage the bids. 4.37 0.66 87.43 34.08 0.000* 22

CSF 33 Transparent and efficient procurement criteria depends on applicable laws and

regulations. 4.46 0.67 89.23 36.08 0.000* 6

CSF 34 Consider consultant and contractor past performance and reputation as

awarding criteria. 4.18 0.84 83.59 23.18 0.000* 55

CSF 35 Past relevant experience of client in awarding bids and managing contracts. 4.02 0.85 80.44 19.9 0.000* 72

CSF 36 Past related experience of consultant in sharing in similar bids and contracts. 4.28 0.77 85.64 27.68 0.000* 36

CSF 37 Past related experience of contractor in sharing in similar bids and contracts. 4.24 0.68 84.87 30.22 0.000* 42

CSF 38 The consultant and the contractor have a mechanism to manage the tenders

and compete. 4.2 0.7 84.04 28.42 0.000* 49

CSF 39 The client interprets all project requirements and location during the bids

preparatory meeting. 4.33 0.73 86.59 30.16 0.000* 29

CSF 40 Documentation the preparation meetings in details. 4.53 0.7 90.62 36.32 0.000* 3

CSF 41 Visiting project location by all consultants and contractors before filling out

the bid form. 4.33 0.74 86.67 29.6 0.000* 27

CSF 42 Granting enough time for consultants and contractors to fill out the bid form. 4.18 0.75 83.59 25.88 0.000* 54

CSF 43 Participating of related project parties in financial and technical evaluation of

tenders. 4.25 0.8 85.07 25.84 0.000* 38

CSF 44 Effective contract management included precise formulation, documentation

and enough detailed incentives, bonds, penalties, …etc. 4.38 0.79 87.57 28.71 0.000* 20

CSF 45 Project profitability for consultant and contractor 4.08 0.77 81.69 23.2 0.000* 65

CSF 46 Economic environment in terms of materials quantity, quality, and price, local

currency value, …etc. 4.32 0.81 86.45 27.04 0.000* 31

288


Item Mean S.D RII

Test

value

P-value

(Sig.)

Total

rank

CSF 47 Delegation and authority allocation of project workers. 4.25 0.8 85.07 25.99 0.000* 39

Phase 4 Factors related to implementation phase 4.25 0.48 85.01 43.02 0.000* (2)**

CSF 48 The client follows project implementation regularly. 4.46 0.66 89.26 36.32 0.000* 5

CSF 49 Past relevant experience of contractor in execution similar projects. 4.4 0.7 87.99 33.25 0.000* 16

CSF 50 Appropriate safety practices during project execution. 4.42 0.71 88.38 33.01 0.000* 12

CSF 51 Updated plan for supervising and managing project site. 4.34 0.73 86.74 30.26 0.000* 26

CSF 52 Preparing and implementing environmental plans included project waste

management works. 4.07 0.85 81.32 20.81 0.000* 68

CSF 53 Commitment of team members on project plans and objectives. 4.37 0.71 87.33 32 0.000* 24

CSF 54 Clear and effective decision making mechanism. 4.4 0.67 88.01 34.53 0.000* 15

CSF 55 Project manager commitment to meet cost quality and time of project. 4.46 0.62 89.26 39.02 0.000* 4

CSF 56 Adequacy and effective management of project financial and material

resources. 4.45 0.62 89.04 38.41 0.000* 8

CSF 57 Training the human resources in the skills demanded by the project. 4.16 0.71 83.25 27.08 0.000* 57

CSF 58 Leadership, monitoring, coordinating and organizing manager skills of

project manager. 4.44 0.74 88.71 32.07 0.000* 11

CSF 59 Permanent presence of project manager in project site. 4.19 0.77 83.82 25.56 0.000* 52

CSF 60 Availability of enough staff in project site according to works requirements. 4.41 0.72 88.16 32.34 0.000* 14

CSF 61 Top management support for project workers. 4.18 0.76 83.6 25.48 0.000* 53

CSF 62 Collaborative team work environment. 4.31 0.72 86.25 29.86 0.000* 32

289


Item Mean S.D RII

Test

value

P-value

(Sig.)

Total

rank

CSF 63 Mutual trust and understanding between project participants. 4.31 0.74 86.25 29.25 0.000* 33

CSF 64 Social relationships and coordination between project participants. 3.78 0.93 75.51 13.73 0.000* 81

CSF 65 Annual organized meetings related to project activities for all participants. 4.03 0.84 80.66 20.31 0.000* 70

CSF 66 Timely and effective conflict resolution. 4.25 0.77 85 26.75 0.000* 41

CSF 67 Effective project control , such as monitoring, updating plans and feedback. 4.21 0.74 84.19 26.9 0.000* 47

CSF 68 Control and monitoring subcontractors works. 4.32 0.77 86.49 28.2 0.000* 30

CSF 69 Annual measuring of KPIs. 4.24 0.81 84.72 25 0.000* 44

CSF 70 Effective well established information and communication routines. 4.23 0.69 84.63 29.51 0.000* 45

CSF 71 The project is part of a well-documented or understood strategy 4.37 0.75 87.43 30.25 0.000* 23

CSF 72 Effective knowledge processing and management systems. 4.17 0.79 83.49 24.42 0.000* 56

CSF 73 Natural climates like winds, rains and high temperature. 3.87 0.9 77.35 15.98 0.000* 79

CSF 74 Consultant and contractor commitment to continuous improvement. 4.02 0.74 80.44 22.67 0.000* 71

CSF 75 Client changes in plans and goals during execution. 3.98 0.86 79.56 18.62 0.000* 73

CSF 76 Client approvals and Payment method. 4.28 0.71 85.66 29.96 0.000* 35

CSF 77 Availability and execution of material handling plans. 4.15 0.83 83.1 22.82 0.000* 59

CSF 78 Using applicable construction methods. 4.33 0.71 86.59 30.77 0.000* 28

CSF 79 Continuous revision of project shop drawings and approve them fast. 4.41 0.77 88.27 30.25 0.000* 13

290


Item Mean S.D RII

Test

value

P-value

(Sig.)

Total

rank

CSF 80 Saving as built drawings of the project. 4.38 0.77 87.65 29.47 0.000* 19

CSF 81 Consultant and contractors involvement in project operating and maintenance

plan after project execution. 4.1 0.8 81.99 22.74 0.000* 64

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