COST OVERRUNS AND TIME DELAYS
IN HIGHWAY AND BRIDGE PROJECTS IN
DEVELOPING COUNTRIESEXPERIENCES FROM CAMEROON
By
Bertin Bella Akoa

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
Construction Management
2011

ABSTRACT
COST OVERRUNS AND TIME DELAYS
IN HIGHWAY AND BRIDGE PROJECTS IN
DEVELOPING COUNTRIES EXPERIENCES FROM CAMEROON
By
Bertin Bella Akoa
Cost and time performance is a concern for construction project stake-holders and
specifically for highway and bridge projects, due to the uncertainty that characterizes these
projects. Cost overruns and time delays have been recorded for centuries, and still occur during
projects today. Despite technological innovations in project management, there has been little
improvement in cost and time performance of transportation projects for over eighty years
(Flyvbjerg, 2008).
For developing countries, there is a need for statistically sound studies that describe cost
overruns and time delays from which appropriate solutions can be derived. This research aimed
to contribute to filling this gap, through case-study research at the Ministry of Public Works
(MINTP) in Cameroon.
Literature on cost overruns and time delays was reviewed, historical contract data was
collected, and a survey was administered to construction professionals in Cameroon.
After contract data analysis, it was found that projects funded by foreign aid had the largest
project overrun rates, and small projects had higher project overruns. Project overrun rates
decreased when project size or duration increased. Inadequate site visits during technical studies
and the bidding phase for construction projects were found to be the main causes of cost
overruns and time delays for MINTP. Causes of project overruns were found in all phases of
project development, specifically in the bidding phase.

Copyright by
BERTIN BELLA AKOA
2011

DEDICATION

To the departed ones who left us during the course of my studies at Michigan State
University:


My father, Prof. Engelbert Akoa, who always taught us discipline, hard work, and the

spirit of initiative; and no favoritism. His own children received the grade they deserved in his
class.


My grandmother, Marie Bernadette Mengue, thanks to her blessings, I am now becoming

“Salt and Light”, truly an expert in my professional activities. Her words were: “Whatever you
start searching at noon, you will find it before 2 P.M.”

v

ACKNOWLEDGEMENTS
This research was inspired by H. E. Paul Biya, President of the Republic of Cameroon with
his vision of a “Cameroon of Great Ambitions”. Now, I am more than ready to complete Great
Realizations for Cameroon and for the world.
Countless thanks to H. E. Bernard Messengue Avom, Minister of Public Works, and
“architect” of this work. Nothing would have been done without his goodwill: only the Almighty
One can reward him. Thanks to H. E. Joseph Charles Bienvenu Foe Atangana, Ambassador of
the Republic of Cameroon in the U.S., and to his wife Colette for their permanent and fatherly
support. Thanks to Dr. Medjo Mintom for his assistance.
Thanks to President Lou Anna K. Simon of Michigan State University, who always
encouraged international students to contribute to advance knowledge and transform lives all
over the world; Sincere gratitude to Associate Deans Richard Brandenburg, Tony Nuñez and
Brenda Alston-Mills. Thanks to Prof. Scott Witter, Director of the School of Planning, Design,
and Construction, to Prof. Mark Wilson, our tireless Associate Director, a great planner who
always inspired students about “being strategic”; thanks to Prof. Matt Syal, the CM Program
Coordinator. Thanks to Prof. Tim Mrozowski, my major professor for all the insights and
guidance during this tedious effort. My gratitude is also expressed to my devoted committee
members: Prof. Hinojosa and Dr. El-Gafy, always available in spite of their huge workload.
God is so Good! He made me the son of Bella Genevieve, my exceptional mother who not
only gave me life but also took care of me until now: there are no words good enough to thank
her.
Immense gratitude to anyone else not mentioned here: you are just unforgettable.
I am missing you, Helene and Maeva, now writing these lines; I will soon join you home!
This master’s program was completed with special support from the Government of the Republic
of Cameroon.
vi

TABLE OF CONTENTS
LIST OF TABLES ...................................................................................................................... xii
LIST OF FIGURES .................................................................................................................. xvii
ABBREVIATIONS .................................................................................................................... xix
CHAPTER 1
INTRODUCTION..........................................................................................................................1
1.1 Overview ................................................................................................................................2
1.2 Proposed Research .................................................................................................................4
1.2.1 Need for the Proposed Research......................................................................................4
1.2.2 Overview of Research Questions ....................................................................................5
1.2.3 Research Goal and Objectives .........................................................................................6
1.2.4 Research Scope and Limitations .....................................................................................6
1.2.5 Case-Study of Highway and Bridge projects in Cameroon.............................................7
1.2.5.1 Presentation of the Country .....................................................................................7
1.2.5.2 Overview of the Road Infrastructure Sector of Cameroon .....................................7
1.2.6 Methodology and Deliverables........................................................................................9
1.3 Significance of the Study .....................................................................................................10
1.4 Summary and Organization of the Research ........................................................................10
CHAPTER 2
EXISTING LITERATURE ON COST OVERRUNS AND TIME DELAYS ........................11
2.1 Overview ..............................................................................................................................12
2.2 Selected References ..............................................................................................................14
2.3 Sources of Cost Overruns and Time Delays in Projects ......................................................19
2.3.1 Overview .......................................................................................................................19
2.3.2 Planning and Programming Phases ...............................................................................21
2.3.3 Design Process...............................................................................................................21
2.3.4 Bidding Procedures .......................................................................................................22
2.3.5 Project Implementation .................................................................................................22
2.3.6 Project Control and Evaluation .....................................................................................23
2.4 Descriptive Analysis of Cost Overruns and Time Delays ....................................................24
2.4.1 Overview .......................................................................................................................24
2.4.2 Project Size and Project Duration..................................................................................24
2.4.3 Project Ownership .........................................................................................................24
2.4.4 Competition Level and Difference between the Low Bid and Government Estimate ..25
2.4.5 Construction Type .........................................................................................................25
2.4.6 Geographic Location ....................................................................................................25

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2.4.7 Contractor Familiarity with the Agency ........................................................................26
2.5 Remedies to Cost Overruns and Time Delays ....................................................................27
2.5.1 Alleviation of Cost Overrun and Time Delay Factors...................................................27
2.5.2 Project Governance: Increased Accountability .............................................................27
2.5.3 Reduction Lists ..............................................................................................................28
2.5.4 Lean Methods ................................................................................................................28
2.6 Professional Survey, Data Retrieval and Analysis of Project Cost Overruns and Time
Delays ........................................................................................................................................28
2.6.1 Surveys of Professionals................................................................................................28
2.6.2 Data Retrieval and Analysis ..........................................................................................30
2.7 Summary ..............................................................................................................................31
CHAPTER 3
RESEARCH METHODOLOGY ...............................................................................................32
3.1 Overview ..............................................................................................................................33
3.2 Methodology ........................................................................................................................33
3.3 Literature Review .................................................................................................................35
3.4 Case Study Organization - Cost and Time Issues ................................................................35
3.5 Contract Data Retrieval and Analysis ..................................................................................36
3.5.1 Contract Data Retrieval .................................................................................................36
3.5.1.1 Retrieval Operation ................................................................................................36
3.5.1.2 Sampling ................................................................................................................38
3.5.1.3: Data Categories .....................................................................................................39
3.5.2 Historical Data ..............................................................................................................41
3.5.2.1: Generalities ...........................................................................................................41
3.5.2.2: Data Organization .................................................................................................42
3.5.3 Data Analysis.................................................................................................................43
3.6 Survey of Professionals ........................................................................................................45
3.6.1 Design: Methods and Procedures ..................................................................................45
3.6.2 Sampling ........................................................................................................................51
3.6.2.1 Survey Location .....................................................................................................51
3.6.2.2 Survey Participants ...............................................................................................51
3.6.3 Survey Data Analysis ....................................................................................................54
3.7 Other Sources Retrieved.......................................................................................................54
3.8 Research Questions .............................................................................................................55
3.9 Deliverables ..........................................................................................................................56
3.10 Chapter Summary ...............................................................................................................56

viii

CHAPTER 4
CONTRACT DATA ANALYSIS ...............................................................................................57
4.1 Introduction - Preliminaries .................................................................................................58
4.2 Change Orders ......................................................................................................................63
4.2.1 Overview .......................................................................................................................63
4.2.2 Causes of Change Orders ..............................................................................................64
4.2.3 Purpose of Change Orders Recorded ............................................................................65
4.3 Detailed Analysis of Cost and Time Overruns .....................................................................66
4.3.1 Overview .......................................................................................................................66
4.3.2 Summary of Data for 2001-2002 ...................................................................................67
4.3.3 Project Type ..................................................................................................................70
4.3.3.1 Frequency Distributions of Cost Overrun Rates by Project Type .........................71
4.3.3.2 Summary of Results for Cost Overrun Rates by Project Type .............................75
4.3.3.3 Frequency Distributions of Time Overrun Rates by Project Type ........................75
4.3.3.4 Summary of Results for Time Overrun Rates by Project Type .............................81
4.3.4 Project Ownership .........................................................................................................81
4.3.4.1 Frequency Distributions of Cost Overrun Rates by Project Ownership ................81
4.3.4.2 Summary of Results for Cost Overrun Rates by Project Ownership .....................85
4.3.4.3 Frequency Distributions of Time Overrun Rates by Project Ownership ...............86
4.3.4.4 Summary of Results for Time Overrun Rates by Project Ownership ....................94
4.3.5 Project Size ....................................................................................................................94
4.3.5.1 Relationship between Project Size and Cost Overrun Rate ...................................95
4.3.5.2 Relationship between Project Size and Cost Overrun Size Expressed
in Monetary Value .................................................................................................97
4.3.5.3 Relationship between Project Size and Time Overrun Rate ..................................99
4.3.6 Project Duration...........................................................................................................100
4.3.6.1 Relationship between Project Duration and Cost Overrun Rate ..........................100
4.3.6.2 Relationship between Project Duration and Time Overrun Rate.........................102
4.3.7 Relationship between the Time Delay Rate and the Cost Overrun Rate ....................103
4.4 Summary Analysis of Cost Overruns .................................................................................105
4.4.1 Summary of Cost Overruns by Project Type ..............................................................105
4.4.2 Summary of Cost Overruns by Project Portfolio .......................................................108
4.4.3 Evolution of Cost Overruns During the Period of Study ............................................110
4.5 Contractor Familiarity with the Ministry ..........................................................................113
4.6 Comparison with Other Countries .....................................................................................114
4.7 Chapter Summary ...............................................................................................................116

ix

CHAPTER 5
SURVEY ANALYSIS ................................................................................................................118
5.1 Introduction ........................................................................................................................119
5.2 Data Reporting ...................................................................................................................119
5.3 Overall Responses ..............................................................................................................121
5.4 Cross-Tabulation between Sector and the factor “Negligence of Site Visits
Before/During the Bidding Process- Unknown Site Conditions” ......................................125
5.5 Cross-Tabulation between Profession and the Factor “Negligence of Site Visits
Before/During the Bidding Process- Unknown Site Conditions” ......................................127
5.6 Prioritization of Factors and Project Phases .......................................................................129
5.7 Respondent Comments on Causes and Improvements for Cost Overruns
and Time Delays .................................................................................................................132
5.8 Comparison with Other Countries......................................................................................136
5.9 Chapter Summary ...............................................................................................................138
CHAPTER 6
DISCUSSION AND GUIDELINES FOR IMPROVEMENT ...............................................139
6.1 Overview ............................................................................................................................140
6.2 Discussion of the Contract Data Analysis ..........................................................................140
6.3 Discussion of the Survey Results .......................................................................................144
6.3.1 Issues in Planning and Programming ..........................................................................144
6.3.2 Problems Relating to the Design Process ...................................................................145
6.3.3 Issues Found During Bidding Procedures ...................................................................147
6.3.4 Comments on Project Implementation ........................................................................149
6.3.5 Project Control and Post-implementation Problems ...................................................151
6.3.6 Summary of Factors for the Suggestion of Guidelines ...............................................152
6.4 Guidelines...........................................................................................................................157
6.4.1 Guidelines from the Data Analysis .............................................................................157
6.4.2 Other Guidelines from the Literature .........................................................................162
6.5 Proof of Concepts ...............................................................................................................164
6.6 Chapter Summary ...............................................................................................................164
CHAPTER 7
CONCLUSION ..........................................................................................................................166
7.1 Introduction ........................................................................................................................167
7.2 Research Objectives ...........................................................................................................167
7.3 Summary of the Research ..................................................................................................168
7.4 Further Research ...............................................................................................................171
7.5 Chapter Summary ...............................................................................................................171

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APPENDICES ............................................................................................................................172
Appendix 1 Abstract in French ................................................................................................173
Appendix 2 Socio-Economic Facts of Cameroon ....................................................................175
Appendix 3 Survey Form - English Version ............................................................................178
Appendix 4 Survey Form - French Version .............................................................................183
Appendix 5 Cost and Time Overruns – Details of Regression Analyses .................................188
Appendix 6 Survey Analysis Results –Frequencies .................................................................222
Appendix 7 “Proof of Concept” Package - Suggestions ..........................................................225
Appendix 8 Glossary ................................................................................................................229
BIBLIOGRAPHY ......................................................................................................................232

xi

LIST OF TABLES
Table 1.1

Road Networks of Cameroon...................................................................................7

Table 1.2

Evolution of Highway Ratings.................................................................................8

Table 2.1

Selected References ...............................................................................................15

Table 2.2

Factors of Delay in the U.S. Construction .............................................................20

Table 2.3

Cost Overruns by Project Type and Geographic Location ....................................26

Table 2.4

Surveys of Construction Professionals in the Literature........................................29

Table 3.1

Survey Structure.....................................................................................................46

Table 3.2

Sources of the Factors in the Questionnaire ..........................................................46

Table 3.3

Respondents’ Coding for Data Input .....................................................................48

Table 3.4

Respondents’ Coding for Data Analysis ...............................................................49

Table 3.5

Software Coding of Factors ...................................................................................50

Table 3.6

Sampling- Potential Respondents of the Survey....................................................53

Table 4.1

Volume of the Contracts Registered ......................................................................59

Table 4.2

Volume of Contracts with Cost and Time Overruns .............................................62

Table 4.3

Overall Change Order Volume in the Database by Project Ownership .................63

Table 4.4

General Purposes of Change Orders Recorded at MINTP ...................................66

Table 4.5

Cost and Time Overrun Rates for All Contracts - Year 2001-2002 ......................68

Table 4.6

Means and Standard Deviations of Cost Overrun Rates by Project Type .............75

Table 4.7

Means and Standard Deviations of Time Overrun Rates by Project Type ...........81

Table 4.8

Means and Standard Deviations of Cost Overrun Rates by Project Ownership ....86

Table 4.9

Means and Standard Deviations of Time Overrun Rates by Project Ownership ...94

Table 4.10 Project Size and Cost Overrun Rates– Means, Standard Deviations, and
Linear Regressions ................................................................................................96
Table 4.11 Project Size and Cost Overrun Size– Means, Standard Deviations, and
Linear Regressions ................................................................................................98
Table 4.12 Project Size and Time Overrun Rate – Means, Standard Deviations, and
Linear Regressions ................................................................................................99
Table 4.13 Cost Overrun Rates Classified by Project Duration- Means,
Standard Deviations, Linear Regressions ............................................................101
Table 4.14 Time Overrun Rates Classified by Project Duration- Means, Standard
Deviations, Linear Regressions ............................................................................102

xii

Table 4.15 Linear Regression Results of the Relationship Between Cost Overrun
Rates and Time Overrun Rates .............................................................................104
Table 4.16 Overall Cost Overruns by Project Type for the Period of Study .........................106
Table 4.17 Project Portfolio Cost Overruns ...........................................................................108
Table 4.18 Evolution of Overall Project Cost Overruns for the Period of Study ..................110
Table 4.19 Frequency of Change Orders for Contractors ......................................................113
Table 4.20 Comparison Between Cost Overrun Rates in Cameroon and
Other Regions and Countries .............................................................................115
Table 4.21 Summary of Cost and Time Overrun Rates by Project Categories .....................117
Table 5.1

Response Rate for the Survey ..............................................................................119

Table 5.2

Cross-tabulation of the Sector and Profession Variables .....................................120

Table 5.3

Prioritization of Survey Factors by the Sum of Respondents Who
“Strongly Agreed” and “Agreed” .........................................................................122

Table 5.4

Cross-tabulation of the variable Sector and the Factor “Negligence of Site
Visits Before/During the Bidding Process- Unknown Site Conditions”..............126

Table 5.5

Directional Measures for the Cross-tabulation Between the Sector and the
Factor “Negligence of Site Visits Before/During the Bidding ProcessUnknown Site Conditions”....................................................................................127

Table 5.6

Cross-tabulation of the Profession and the Factor “Negligence of Site Visits
Before/During the Bidding Process- Unknown Site Conditions” .......................128

Table 5.7

Directional Measures for the Cross-tabulation Between the Profession
and the Factor “Negligence of Site Visits Before/During the Bidding ProcessUnknown Site Conditions”...................................................................................129

Table 5.8

Classification of Factors by Priority Groups .......................................................130

Table 5.9

Prioritization of Project Phases ............................................................................132

Table 5.10 Comments From Survey Respondents .................................................................133
Table 5.11 Comparison Between Construction Professionals Surveys .................................137
Table 6.1

Amounts of MDOT Force Account Projects for Past Years................................145

Table 6.2

Percent of US DOT Competition in Contracting for 2006-2008 .........................146

Table 6.3

Summary of Factors to Consider for Guidelines .................................................153

Table A5.1 Correlation - Significance for the Relationship between Project Size and
Cost Overrun Rate - Project Size under 100,000,000 XAF ................................189

xiii

Table A5.2 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Rate - Project Size between 100,000,000-250,000,000 XAF ................190
Table A5.3 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Rate - Project Size between 250,000,000-700,000,000 XAF ................191
Table A5.4 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Rate - Project Size between 700,000,000-2,000,000,000 XAF .............192
Table A5.5 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Rate - Project Size between 2,000,000,000- 5,000,000,000 XAF .........193
Table A5.6 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Rate - Project Size over 5,000,000,000 XAF ........................................194
Table A5.7 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Rate - All Project Sizes ..........................................................................195
Table A5.8 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Size - Project Size under 100,000,000 XAF .........................................196
Table A5.9 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Size - Project Size between 100,000,000-250,000,000 XAF ...............197
Table A5.10 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Size - Project Size between 250,000,000-700,000,000 XAF ...............198
Table A5.11 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Size - Project Size between 700,000,000-2,000,000,000 XAF ............199
Table A5.12 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Size - Project Size between 2,000,000,000-5,000,000,000 XAF .........200
Table A5.13 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Size - Project Size over 5,000,000,000 XAF ........................................201
Table A5.14 Correlation - Significance for the Relationship between Project Size and Cost
Overrun Size - All Project Sizes .........................................................................202
Table A5.15 Correlation - Significance for the Relationship between Project Size and Time
Overrun Rate - Project Size under 100,000,000 XAF ........................................203
Table A5.16 Correlation - Significance for the Relationship between Project Size and Time
Overrun Rate - Project Size between 100,000,000-250,000,000 XAF ...............204

xiv

Table A5.17 Correlation - Significance for the Relationship between Project Size and Time
Overrun Rate - Project Size between 250,000,000-700,000,000 XAF ...............205
Table A5.18 Correlation - Significance for the Relationship between Project Size and Time
Overrun Rate - Project Size between 700,000,000-2,000,000,000 XAF ............206
Table A5.19 Correlation - Significance for the Relationship between Project Size and Time
Overrun Rate - Project Size between 2,000,000,000-5,000,000,000 XAF .........207
Table A5.20 Correlation - Significance for the Relationship between Project Size and Time
Overrun Rate - Project Size over 5,000,000,000 XAF .......................................208
Table A5.21 Correlation - Significance for the Relationship between Project Size and Time
Overrun Rate - All Project Sizes .........................................................................209
Table A5.22 Correlation - Significance for the Relationship between Project Duration and
Cost Overrun Rate - Project Duration Under 6 Months .....................................210
Table A5.23 Correlation - Significance for the Relationship between Project Duration and
Cost Overrun Rate - Project Duration between 6 Months - 12 Months ..............211
Table A5.24 Correlation - Significance for the Relationship between Project Duration and Cost
Overrun Rate - Project Duration between 12 Months - 24 Months ....................212
Table A5.25 Correlation - Significance for the Relationship between Project Duration and Cost
Overrun Rate - Project Duration between 24 Months - 36 Months ....................213
Table A5.26 Correlation - Significance for the Relationship between Project Duration and Cost
Overrun Rate - Project Duration over 36 Months ...............................................214
Table A5.27 Correlation - Significance for the Relationship between Project Duration and Cost
Overrun Rate - All Project Durations .................................................................215
Table A5.28 Correlation - Significance for the Relationship between Project Duration
and Time Overrun Rate - Project Duration under 6 Months ..............................216
Table A5.29 Correlation - Significance for the Relationship between Project Duration
and Time Overrun Rate - Project Duration between 6 Months - 12 Months ......217
Table A5.30 Correlation - Significance for the Relationship between Project Duration
and Time Overrun Rate - Project Duration between 6 Months - 12 Months ......218
Table A5.31 Correlation - Significance for the Relationship between Project Duration
and Time Overrun Rate - Project Duration between 24 Months - 36 Months ....219

xv

Table A5.32 Correlation - Significance for the Relationship between Project Duration
and Time Overrun Rate - Project Duration over 36 Months ..............................220
Table A5.33 Correlation - Significance for the Relationship between Project Duration
and Time Overrun Rate - All Project Durations .................................................221
Table A6.1 SPSS Output – Overview of Valid Responses ....................................................223
Table A6.2 SPSS Output - Frequencies for the Variable “Profession” ..................................223
Table A6.3 SPSS Output – Frequencies for the Variable “Sector” ........................................223
Table A6.4 SPSS Output – SPSS Output – Frequencies for the Variable “Lack of Project
Planning/Programming” ......................................................................................224
Table A6.5 SPSS Output – Frequencies for the Variable “Inadequate Project Planning
Programming” ......................................................................................................224
Table A6.6 SPSS Output – Frequencies for the Variable “Weaknesses during the Land
Taking Process” ...................................................................................................224

xvi

LIST OF FIGURES
Figure 1.1

Transportation Project Development ......................................................................4

Figure 2.1

Hierarchical Organization of the Literature Review ..............................................13

Figure 3.1

Hierarchical Organization of the Research Methodology .....................................34

Figure 4.1

Repartition of Contract Global Amount by Project Type ......................................62

Figure 4.2

Repartition of Change Orders in the Database (XAF Amount) By
Funding Source ......................................................................................................64

Figure 4.3

Frequency Distribution of Cost Overrun Rates - Road
Construction and Maintenance ...............................................................................72

Figure 4.4

Frequency Distribution of Cost Overrun Rates – Bridges and Structures .............73

Figure 4.5

Frequency Distribution of Cost Overrun Rates – Work Supervision ....................73

Figure 4.6

Frequency Distribution of Cost Overrun Rates – Design/Technical Studies,
Technical Assistance .............................................................................................74

Figure 4.7

Frequency Distribution of Cost Overrun Rates – Mowing Roadsides ..................74

Figure 4.8

Frequency Distribution of Time Overrun Rates – Road
Construction/Maintenance .....................................................................................76

Figure 4.9

Frequency Distribution of Time Overrun Rates – Bridges and Structures ............77

Figure 4.10 Frequency Distribution of Time Overrun Rates – Work Supervision ...................78
Figure 4.11 Frequency Distribution of Time Overrun Rates – Design/Technical Studies,
Technical Assistance .............................................................................................79
Figure 4.12 Frequency Distribution of Time Overrun Rates – Mowing Roadsides .................80
Figure 4.13 Frequency Distribution of Cost Overrun Rates – Project Co-Funded by
the African Dev. Bank ..........................................................................................82
Figure 4.14 Frequency Distribution of Cost Overrun Rates – Project Co-Funded by the
European Union.....................................................................................................82
Figure 4.15 Frequency Distribution of Cost Overrun Rates – Project Co-Funded by
France - AFD .........................................................................................................83
Figure 4.16 Frequency Distribution of Cost Overrun Rates – Project Co-Funded by Islamic
Dev. Bank, OPEC Funds, Koweitian Funds, Saudian Funds .................................83
4.17 Frequency Distribution of Cost Overrun Rates – Project Co-Funded by HIPC Funds .....84
Figure 4.18 Frequency Distribution of Cost Overrun Rates – Project Co-Funded by Overall
Foreign Aid ............................................................................................................84
Figure 4.19 Frequency Distribution of Cost Overrun Rates – Project Funded by
Government Only ..................................................................................................85
xvii

Figure 4.20 Frequency Distribution of Time Overrun Rates – African Dev. Bank
Co-Funded Projects ...............................................................................................87
Figure 4.21 Frequency Distribution of Time Overrun Rates – European Union
Co-Funded Projects ................................................................................................88
Figure 4.22 Frequency Distribution of Time Overrun Rates – France-AFD
Co-Funded Projects ................................................................................................89
Figure 4.23 Frequency Distribution of Time Overrun Rates – HIPC Co-Funded Projects ......90
Figure 4.24 Frequency Distribution of Time Overrun Rates – Islamic Dev. Bank,
OPEC Funds, Koweitian Funds, Saudian Funds Co-Funded Projects ..................91
Figure 4.25 Frequency Distribution of Time Overrun Rates – Project Co-Funded by Overall
Foreign Aid ............................................................................................................92
Figure 4.26 Frequency Distribution of Time Overrun Rates – Project Funded by
Government Only ...................................................................................................93
Figure 4.27 Scatterplot of the Relationship Between Project Size and Cost Overrun
Rate (110 cases) .....................................................................................................97
Figure 4.28 Project Size and Cost Overrun Size – Linear Regression ......................................98
Figure 4.29 Scatterplot of the Relationship between Project Size and Time Overrun
Rate for Contract Amounts between Two and Five Billion XAF ........................100
Figure 4.30 Scatterplot of the Relationship between Project Duration and Cost
Overrun Rate for Contract Durations between 24 and 36 Months .......................101
Figure 4.31 Scatterplot of the Relationship between Project Duration and Time
Overrun Rate for Contract Durations between 6 and 12 Months .........................103
Figure 4.32 Illustration of the Relationship between the Time Overrun Rate and the
Cost Overrun Rate ...............................................................................................105
Figure 4.33 Overall Cost Overruns by Project Type for the Period of Study .........................107
Figure 4.34 Portfolio Project Cost Overruns for the Period of Study .....................................109
Figure 4.35 Comparison of Cost Overruns by Project Type over the Period of Study ...........111
Figure 4.36 Frequencies of Constructors and Consultants with Change Orders and
Number of Years .................................................................................................114
Figure A2.1 Map of Cameroon and Socio Economic Facts ...................................................176

xviii

ABBREVIATIONS
AFD

Agence Française de Développement (French Cooperation)

EU

European Union

FAD

African Development Fund

GOV

Government

HIPC

Highly Indebted and Poor Countries Initiative

IDA

International Development Association (World Bank Group)

IDB

Islamic Development Fund

IMF

International Monetary Fund

KFW

Kreditanstalt für Wiederaufbau (German Cooperation)

MDOT

Michigan Department of Transportation

MINTP

Ministry of Public Works, Republic of Cameroon

PRC

Presidency of the Republic of Cameroon

SPM

Prime Minister’s Office of the Republic of Cameroon

USDOT

United States Department of Transportation

XAF

CFA Franc

xix

CHAPTER 1
INTRODUCTION

1

1.1 Overview
Transportation infrastructure, specifically road infrastructure, is the backbone of economic
and social development of countries. It is useful for communication and trade exchanges locally
and internationally. In addition, there is a long process from project conception to completion
and availability for taxpayer use. Successful road infrastructure projects are delivered with
reduced cost, on time, and in accordance with technical specifications for an optimal economic
return. Unfortunately, many road infrastructure projects, such as highways and bridges, do not
meet cost and time performance requirements: cost overruns and time delays are a worldwide
phenomenon to the detriment of economic development and taxpayers (Flyvbjerg et al., 2004).
Less infrastructure development occurs when ongoing projects run over budget and consume
resources, initially scheduled for other projects.
The causes of cost overruns and time delays are often attributed to the constructor and the
construction environment. However, project implementation is only one phase of project
development; the entire process needs to be investigated to detect weaknesses which lead to cost
overruns and time delays during project implementation. The present study addresses the project
development phases illustrated in Figure 1.1.
During planning, a vision and long term goals are defined. Socioeconomic studies are held
including public participation and right-of-way estimation. Funding opportunities are also
discussed. As an outcome of preliminary planning, a project is transformed from an idea to a
preliminary design consisting of a conceptual cost estimate, environmental studies, project
parameters, geometry design and preliminary plans and layouts (Anderson et al., 2008). In
general, once funding is available, projects are programmed on a case by case basis.
Programs, sometimes referred to as Capital Improvement Programs, cover a period of years
during which final designs are developed, land is acquired, and engineering cost estimates and
2

schedules are approved. In a traditional project delivery approach, projects are procured through
advertisement and bid processes. Then contracts are awarded and construction or maintenance
operations follow under inspection of the project owner or its representatives. Before occupancy
or delivery to users, contracts are closed-out. In some organizations, contract administration is
delegated to third parties, generally private consultants, who supervise the work until
completion.
Through a participatory approach, project stake-holders were surveyed, and contract data was
collected and analyzed in a case-study organization from Cameroon: the Ministry of Public
Works (MINTP). This study developed recommendations for reducing cost overruns and time
delays for projects in developing countries, and addresses all project development phases.

3

Construction/Maintenance
• Project Bidding
• Contract Awards: Bidder
Estimates
• Project Implementation and
Completion- Close Out,
Occupancy

Projects1 to 3 years

Programming
• Project selection
• Project Design
• Funding Available
• Detailed cost estimates and
schedules

Programs
(Transportation
Improvement
Programs)

- Periods of 5
years

Planning
•Vision and Goals
•Socio Economic Studies
•Project definitions
•Preliminary Cost Estimates

Transportation Plan 15 years

Figure 1.1 Transportation Project Development
1.2 Proposed Research
1.2.1 Need for the Proposed Research
Cost and time performance has not significantly improved over time; little learning seemed
to have occurred in eight decades (Flyvbjerg, 2008). Few studies provide data on cost overruns,
and only one study by Flyvbjerg and co-authors was statistically sound (Gamez and Touran ,
2010), (Jergeas and Ruwanpura, 2009), (Jin-Kyung, L., 2008) . Flyvbjerg’s study focused on 258
transportation projects implemented in 20 nations, mainly in Europe and North America from
1925 to 2000. For developing nations, there is a lack of data. Only research using interviews and
surveys of construction professionals was found, which addressed cost overruns and time delays

4

in construction projects. Flyvbjerg found that cost underestimation was expected to be more
pronounced in developing countries than in North America and Europe (Flyvbjerg et al, 2003).
Since the 1990s, economic difficulties led many developing countries worldwide to reform
and modernize their transportation sectors. With the fall of the Berlin Wall, liberalization was
adopted, and privatization was implemented in many developing nations. Cameroon, Ethiopia,
Togo, Malawi, Kenya, Tanzania, Zambia, and Ghana, as well as many others in Africa and
developing countries in other continents, created Road Funds to secure stable funding for road
projects. They also adopted Design-Bid-Build as their project delivery method (World Bank,
1997). However, it is well known that cost overruns and time delays (or time overruns) are major
factors affecting construction projects in spite of reforms. Many transportation infrastructure
projects in developing countries were added with supplemental financial resources in recent
years. These projects were characterized by slowness and time delay during implementation
(World Bank, 2009). In Botswana, Chinese contractors were instructed to deliver Government
projects of a quality that were durable, on time and on budget (Kebadiretse, 2010). The issue of
cost and time performance had to be solved to ensure delivery of efficient projects to taxpayers.
1.2.2 Overview of Research Questions
This research investigated the causes of cost overruns and time delays during all project
development phases; additionally the influence of project characteristics on cost overruns and
time delays were explored.

5

1.2.3 Research Goal and Objectives
The goals of the research were to examine cost overruns and time delays in highway and
bridge projects in developing countries, and to provide relevant recommendations for
substantially alleviating these problems. The objectives of the study were:


To develop a database of historical contract data and conduct statistical data analyses to

obtain cost and time overrun rates for the case-study organization and to find relevant
relationships for cost and time overruns


To conduct a survey of construction professionals to obtain their perceptions on the main

causes of cost overruns and time delays for their organizations


To develop recommendations which would help improve organizations and their contracting

processes with regard to cost overruns and time delays for road infrastructure projects
1.2.4 Research Scope and Limitations
This study was limited to highway and bridge projects in Cameroon, and considered the casestudy country as a single geographic location. In addition, only controllable cost overrun factors
affecting contract costs were analyzed: optimism bias in cost estimates was not studied. The
initial construction contract amount was used as the basis for overrun measurements: for
simplicity, engineering estimates were not considered. The study did not consider the awardestimate difference factor: only the award amount was considered.
In addition, time delays were limited to excused delays for which contractors received time
extensions through change orders; unexcused delays were not documented in the data collected.
Time overrun or time delay rate was computed as the total time extension divided by the initial
contract duration, or project duration.

6

1.2.5 Case-Study of Highway and Bridge projects in Cameroon
1.2.5.1 Presentation of the Country
Called “Africa in miniature” because of its diversity of peoples, cultures, and natural
environment, Cameroon is an interesting case to study for general issues. In addition to French
and English, official languages of the country, 240 African languages are spoken there. The
figure in Appendix 1 presents socioeconomic facts for Cameroon.
1.2.5.2 Overview of the Road Infrastructure Sector of Cameroon
In Cameroon, only 5,000 km of highways are paved; 12,000 km are unpaved and need more
frequent maintenance compared to paved highways. The country has approximately 1200 bridges
and structures (MINTP, 2008). There are no freeways, no cable stayed bridges and no suspended
bridges. For management of its road infrastructure, MINTP has geographically divided the
country into three networks as presented below.
Road Network Name
South Network
West Network

Northern Network

Regions Covered
Centre, South, East
Littoral, West, South West,
North West
Adamaoua, North, Far
Northern

Table 1.1 Road Networks of Cameroon
Fifteen years ago, the Ministry of Public Works, in charge of highways and bridges was
reformed and adopted privatization for project delivery and work supervision. Unit-price
contracts were used in MINTP. Design-Bid-Build was introduced as a delivery method for better
project efficiency. However, a study carried out by a private consultancy firm unveiled that there

7

have been no improvements since 1997 in project delivery or management reform (CRTV,
2010a, 2010b, 2010c). The findings of that study indicated:


The organization was incoherent in spite of the adoption of multi-annual contracts and a

Road Fund


There was a lack of equipment



Contracts were awarded solely on the basis of bidding declarations by contractors and the

Public Contract Code did not allow the awarding of contracts solely to competent contractors


Highways ratings had degraded:
Highway nature
Paved

Unpaved

Year

Ratings

1995

1/2 in good condition

2007

1/3 in good condition

1995

10% in good condition

2007

6% in good condition

Table 1.2 Evolution of Highway Ratings (CRTV, 2010a)


The cost of unpaved roads had tripled and the cost of paved roads has doubled in the same

period.
In addition, contractors frequently requested change orders for time extensions and cost
overruns. Furthermore, 32 contracts out of 244 signed in 2006 were cancelled by the Ministry
during their implementation because of contractor abandonment or lateness (MINTP, 2008).
Similarly, other studies found that since 1996, road maintenance costs were increasing year after
year; meanwhile the road network still seemed to deteriorate (Okole , 2009c). The Ministry had
also emphasized the necessity of building lasting infrastructure that costs less in relation to its
quality control (Bainkong, 2009). Time delays during project implementation were common in

8

Cameroon and many highway infrastructure projects were often delayed for years after their
beginning (Okole, 2009a, 2009b).
1.2.6 Methodology and Deliverables
Informal discussions were held with the management of MINTP, to help shape this research.
After initial planning, the following steps were established for carrying out the research.
1. Literature review on cost overrun and time delay in construction projects
2. Research data collection steps
2.1 Contract Data
2.1.1 Planning for collection of contract data in Cameroon
2.1.2 Implementation of contract data collection in Cameroon
2.1.3 Development of a historical contract database
2.2 Survey of Construction Professionals
2.2.1 Development of a survey targeted to construction professionals
2.2.2 Identification of subject groups
2.2.3 Submission of an IRB application
2.2.4 Implementation of the survey in Cameroon
2.2.5 Development of a survey response database
3. Statistical analysis of data
4. Development and presentation of the results, recommendations and proof of concepts.
This study presents statistical analyses of cost overruns and time delays in Cameroon, as a
case-study for developing countries. It also suggests recommendations to solve these problems.

9

1.3 Significance of the Study
This research helps reduce the lack of statistically sound studies in the literature on cost
overruns and time delays by statistically describing their magnitude, causes and proposed
remedies for the case study of Cameroon, for all project development phases including: Planning
and Programming, Design, Bidding, Implementation, and post-implementation.
1.4 Summary and Organization of the Research
This chapter introduced the research and the organization of the thesis.
The thesis is organized in six chapters, in addition to the introduction. The literature review is
addressed in Chapter Two, and focused on the existing research on cost overruns and time
delays.
Chapter Three presents the methodology for the research and identifies the steps conducted
during the study. Chapter Four presents the contract data and its analysis. Chapter Five presents
the survey data. Chapter Six presents the results and guidelines for helping to solve cost overruns
and time delays in developing countries, mainly for the case-study organization, as well as a
suggested proof of concept approach. Chapter Seven concludes the study and makes suggestions
for further areas of research.

10

CHAPTER 2
EXISTING LITERATURE ON
COST OVERRUNS AND TIME DELAYS

11

2.1 Overview
There is an abundance of literature on cost overruns and time delays in infrastructure
projects. Flyvbjerg, in several papers with co-authors, provided the most relevant research, and
some of the only statistically sound research in the area to date (Gamez and Touran, 2010),
(Jergeas and Ruwanpura, 2009), (Jin-Kyung, L. 2008). Other studies (Hinze and Selstead, 1991),
(Bordat et al., 2004), and (Merewitz, 1973) also contributed to knowledge of cost overruns. In
addition, research has been conducted worldwide which investigates the causes of cost overruns
and time delays through surveys. Researchers have attempted to provide remedies for this
seminal problem.
The state of the existing literature on cost overruns and time delays was reviewed to date, and
is illustrated in Figure 2.1.

12

Cost
Overruns and
Time Delays

Research
Methods Used

Remedies





Professional
surveys
Data Retrieval and
Analysis

Description of
Cost Overrun/
Time Delay





Alleviation of Cost
Overrun and Time
Delay Factors
Projects’ Governance:
Increased
Accountability
Reduction Lists
Lean methods










Project Size
Project Duration
Project Ownership
Competition Level
Difference Between the
Low Bid & the Government
Estimate
Construction Type
Geographic Location
Contractor Familiarity with
the Agency

Figure 2.1 Hierarchical Organization of the Literature Review

13

Sources







Planning & Programming
Phases
Design Process
Bidding Procedures
Project Implementation
Project Control &
Evaluation

2.2 Selected References
The key words Cost Overruns and Time Delays were used in searching electronic resources
and journals and books which addressed cost overruns and time delays were reviewed. The Web
of Science and Proquest were used, as well as daily Google Alerts. Relevant research was
reviewed and classified by the methodology and related geographical area. The literature is
presented in Table 2.1.

14

No

1

2

3

4

Author(s)/Year
(Abd El-Razek et al., 2008); (LeHoai et al., 2008); (Lo et al.,
2006); (Sambasivan and Soon,
2007), (Abdul-Rahman et al.,
2006); (Ajibade and Odeyinka,
2006), (Mansfield et al., 1994),
(Okpala and Aniekwu, 1988);
(Frimpong et al., 2003)

Description of the Study

Research Method

Country

Observations

The papers reviewed project
delays/cost overruns causes from
the literature, adopted and ranked
those which are common in the
case- study country. Remedies
were proposed.

Interviews and
Survey Analysis.

Egypt,
Vietnam,
Hong Kong,
Malaysia,
Nigeria,
Ghana.

The studies were
limited to
participants’
opinions.

(Bramble and Callahan, 2000)

 Delay claims in the construction
industry. Identified factors of time
delays were classified between the
owner, designer, contractor and
delays out of the control of these
parties.
 Consequences and remedies to
delays were also discussed.

Case-law based
analysis of
construction
projects that are
delayed.

(Creedy et al., 2010)

The paper presented results from
231 highway projects which were
investigated to determine their
cost overrun factors, from historic
highway data.

Interviews, Data
collection and
analysis, expert
elicitation.

(Cui and Olsson, 2008)

The paper presented “reduction
lists” prepared ahead of the
beginning of a project. They were
defined as the list of cost items
which could be reduced if other
parts of a project were actually
more costly than planned.

Data collection
and analysis

Table 2.1 Selected References

15

U.S.A.

Covers time
overruns for all
project phases.

Australia
(State of
Queensland)

Mitigated
correlation found
between project
characteristics
and cost
overruns.

Northway

Reduction lists
were used to
avoid cost
overruns before
project
implementation.

Table 2.1 Selected References (Cont’d)
No

Author(s)/Year

5

(Flyvbjerg, 2008),
(Flyvbjerg et al, 2004),
(Flyvbjerg and COWI,
2004), (Flyvbjerg et al,
2004), (Flyvbjerg et al,
2003)

6

(Gamez and Touran,
2010)

Description of the Study
 The studies statistically analyzed 258
rail, bridge, tunnel and road projects to
determine the factors of cost escalation in
transport infrastructure projects.
 Findings were that not only the
duration of project implementation, the
size of the project were factors of cost
escalation, but also optimism
bias. This later is mainly due to the
political or self-interest economic factors
through deceptive, biased costs
underestimated and benefits
overestimated : a strategic
misrepresentation to obtain decisionmakers’ approval or to make profits.
However, private ownership has no effect
on cost escalation. Solutions were
proposed.
 The paper analyzed the cost, schedule
and scope performance metrics of 89
transportation projects founded by the
World Bank.
 Findings were that costs were
overestimated, and schedules were
optimistic. However, no improvement in
these performances was observed during
the period of study, 1991-2007.

16

Research Method

Country

Observations

Europe, North
Lengthy historical America, Japan
data collection and
and 10
statistical analysis
developing
nations.

Covers the
planning phase
of projects, with
an emphasis on
the influence of
politics on
planners.

Historical data
collection and
statistical analysis

This study had
optimistic results
about project
cost and
schedule
performance,
compared to
others.

International

Table 2.1 Selected References (Cont’d)
No

7

8

9

10

11

Author(s)/Year

(Hinze and
Selstead, 1991)

(Jahren and Ashe,
1990)

(Jergeas and
Ruwanpura, 2009)

(Jin-Kyung, L.,
2008)

(Merewitz,
L.,1973)

Description of the Study
 Review of 433 unit price contracts of
WSDOT*.
 Findings were that the number of bids
received, project size and type, geographic
location, frequency of awarding WSDOT
contracts to a contractor were factors which
impacted construction cost overruns.
The authors suggested that change order and
cost overrun factors were similar. Therefore,
these factors which were known for change
orders were relevant to investigate cost
overruns.
The authors found cost and schedule overruns’
causes in inaccurate cost estimates and
schedules, inadequate scope definition and
project strategies, poor project management.
The paper presented cost overrun rates for 161
projects of roads, rails, airports and ports in
South Korea. The causes and remedies of cost
overruns in South Korea were suggested.
 The study evoked the “bias” in cost estimates,
and classified cost overrun reasons in
controllable and uncontrollable factors.
 Comparative analysis of cost estimates for
200 large projects of water resources,
highways, buildings, rapid transit and ad hoc
public works.

17

Research Method
Interviews of
WSDOT
engineers, data
collection and
statistical analysis

Focused on the
literature

Professionals’
survey

Country

Observations

U.S.A.

Local study
focusing on
contract
characteristics.

U.S.A.

The paper
introduced
factors which
can be used to
forecast cost
overruns

Canada

The statistical
analysis was not
available.

Data retrieval

South Korea

Data collection
and statistical
analysis

International

No statistical
analysis or
survey was
performed.
Aimed to
compare the 45%
cost overruns of
the San Francisco
Rapid Transit
project to other
project cost
overruns

Table 2.1 Selected References (Cont’d)

12

13

(Shane et al., 2009)

 This study found 18 primary factors classified
as internal or external to the agency/owner, for
transportation project cost overruns.

Focused on a
literature review
and interviews of
state highway
agencies

(Siemiatycki, M.,
2009)

 The author compared the results of
transportation project cost overruns between
two groups: academics and independent
government auditors. The first hardly had
access to data compared to the second, and the
explanations of cost overruns differed for both
groups
 The paper also suggested remedies to cost
overruns

Focused on the
literature and
retrieved auditors’
studies of cost
overruns

(*)WSDOT: Washington State Department of Transportation.

18

U.S.A.

General causes of
cost overruns are
listed in the study

International:
Europe, South
Korea, USA

The paper
summarized the
studies on
transportation
cost overruns

2.3 Sources of Cost Overruns and Time Delays in Projects
2.3.1 Overview
There are various causes or factors of cost overruns and time delays in projects identified in
the literature. The definition of cost overrun varies depending on the project phase considered by
researchers; however, from a construction management perspective, it is perceived to be the
difference between the final project cost and the original contract amount (Hinze and Selstead,
1991). Others consider the difference between the actual project cost and the original engineer’s
(or owner’s) estimate. For government agencies, cost overrun also means the escalation of
project cost over time. Cost overruns and time delays affect all project development phases, from
project initial concept to construction and maintenance. For MINTP, there are contracts with
consultants and design firms for preliminary studies and design, contracts with builders to
perform the work, and contracts with consultants for work supervision. Some lending agencies
require that the same consultant does the design, assists the owner in the bidding process and
supervises the work later. This means that any delay in the bidding process would be costly to
MINTP even before the work starts or the contractor is selected. Often extra cost is due to the
consultant being paid for a longer period. “Time delay” for such an owner is more a matter of a
“project delay” rather than a “contract delay.” The delivery of one physical project consists of
different types of contracts.
In general, Bramble and Callahan (2000) defined delay as the time period during which some
part of the construction project has been extended beyond the initial time, or the incident
affecting the performance of an activity of the project. Delay factors from a litigation perspective
in the U.S. construction industry are summarized in Table 2.2.

19

Owner
Designer
Access to project site
Design defects, errors, and omissions
Right-of-Way
Slow correction of defects
Utility relocation delays
Tardy shop drawings review
Unidentified utilities
Delayed testing and inspection
Demolition of existing structures
Poor contract administration
Differing site conditions
Contractor
Relocation of tenants
Failure to evaluate site
Approvals from governing authorities
Failure to evaluate design
Payment delays
Underbidding
Project financing
Management failures
Design defects
Inadequacy of labor force
Defective specifications
Scheduling and planning
Tardy shop drawing processing
Coordination and subcontractors
Inspection delays
Subcontractor delays
Delayed notice to proceed/contract
Material procurement
award
Equipment failures
Inappropriate stop work orders
Financial resources
Owner-furnished items
Construction defects
Over inspection
Changes
Constructive changes
Owner interference
Failure to coordinate multiple prime
contractors
Delays that may be beyond the control of the parties
Unusual weather
Unusual delays in transportation
Labor disputes
Floods
Unavoidable calamities
Governmental acts
Acts of God
Vandalism
Fire
Table 2.2 Factors of Delay in the U.S. Construction (Source: Bramble & Callahan, 2000)

Because costs generally are related to time in projects, time delays directly affect projects,
and lead to cost overruns. Responsible parties of a delay will frequently have to compensate the
affected parties. As illustration, “Time is of the Essence” is a common clause in U.S. contracts
which indicate that time provisions are contractual requirements, instead of mere guidelines.
During this research, the factors were classified according to project cycle: phases of planning

20

and programming, design process, bidding procedures, project implementation, project control,
and ex post evaluation which helped to understand how time delays or mistakes during one
phase, could affect others.
2.3.2 Planning and Programming Phases
Insufficient planning and programming of projects is one cause of cost overruns and delays.
Poor planning methods or unplanned projects have a high risk of cost overruns or project failure.
Anderson et al. (2008) identified right-of-way costs as a crucial factor of cost escalation in
highway projects. Specifically, Flyvbjerg and co-authors pointed out the use of deception and
lying, to be sources of cost overruns during transportation project planning. Under the influence
of politicians, or to increase project stake-holders revenues and profits, project planners
deliberately underestimate project costs and overestimate the potential benefits. Such a “strategic
misrepresentation” will quickly convince decision makers to authorize projects, implying
increased economic self-interest of consultants and contractors to the detriment of taxpayers or
funding agencies. However, de-biasing cost estimates can lead to the problem of higher costs
which would prevent projects from being undertaken and cause slow economic development
(Merewitz, 1973). According to this point of view, “technical” optimism or low estimating
would be better than correct cost estimating.
2.3.3 Design Process
At the project design stage, Jergeas (2009) pointed out poor project implementation strategies
that impacted the actual costs of projects in Canadian mega oil sand projects. In Nigeria, Okpala
and Aniekwu (1998) indicated that mistakes and discrepancies in documents caused cost
overruns. Similarly from Jergeas’ (2009) research, another factor is under-estimating. In South
Korea, Jin-Kyung (2008) wrote that unreasonable underestimation in the adjustments of project
costs caused overrun issues during implementation. Furthermore, Ajibade and Odeyinka(2006),
21

Anderson et al. (2007), Creedy et al.(2010) presented the design process as a potential source of
cost overruns and time delays in projects. For illustration, Sweet and Schneier (2009) presented
the case Stanley Consultants, Inc. v. H. Kalicak Construction Co., where the design professional
of a sixty-one-unit housing project in Zaire (Now Democratic Republic of Congo, Africa) did not
use Zaire’s data during his studies. As a result, the only bid submitted was double that of the
design cost estimate.
2.3.4 Bidding Procedures
Site conditions need to be known by project counterparts at all phases, mainly during the
bidding phase for contractors (Bramble and Callahan, 2000). Visits should be mandatory (Pratt,
2004). The consequences of misunderstanding due to lack of site visits are cost escalation or
abandonment. A key factor outlined by Okpala and Aniekwu (1998) seems to be the period of
bidding, which often takes a long time for highway projects in developing countries. Site
conditions can change noticeably between the time of bidding and contract award.
Furthermore, the level of competition based on the number of bidders and the difference
between low bids and engineering estimates impact construction cost overruns. Projects in which
low bids are less than the engineering estimates are prone to increased cost overruns (Hinze and
Selstead 1991). In South Korea, Jin-Kyung (2008) criticized the lowest bid price system where
irrational estimating occurred by the winning contractor, who might not efficiently complete the
contract.
2.3.5 Project Implementation
Merewitz (1973) presented inflation, which is not controllable by contract parties, as a factor
in cost overruns. Unforeseen scope changes can also affect project costs. The following excerpt
from Merewitz presents “controllable cost overruns”:

22

Controllable overruns are due to poor administration of projects,
starting with incomplete surveys of engineering, financial and legal
problem which might have been anticipated ahead of time. Poor
administration may also include overly complex organizational
structures for planning and constructing projects, poor contracting
practices, unnecessary scope changes, and simple inexperience of
personnel for the type of project or the area in which the project is
undertaken.

Other factors introduced by Anderson et al (2007) are delivery and procurement methods,
scope creep, faulty execution, ambiguous contract provisions and conflicting contract
documents. Moreover, according to Jergeas (2009), poor communication is another reason for
cost overruns. Okpala and Aniekwu (1998) provided additional points from Nigeria’s experience
including preparation and approval of shop drawings, shortage of materials, payment methods,
lack of equipment and materials that were imported, construction errors, on-site test approval,
unethical attitudes and kickbacks. Weather conditions also needed to be considered given the
growing influence of climate change, although they did not consider the influence of weather in
Nigerian projects. The studies of Naoum(1994), Ajibade and Odeyinka(2006), Tumi et al. (2009)
and Sambasivan (2006) also focused on comparable problems to explain cost overruns and time
delays.
2.3.6 Project Control and Evaluation
Few authors focused on work evaluation in their research. Jin-Kyung (2008) indicated that
periodic reports on contract progress from contractors were not sufficiently studied by owners to
detect causes of cost overruns and to solve problems: the consequence was cost escalation.
Similarly, Okpala and Aniekwu (1998), Tumi et al. (2009) indicated that the period of inspection
and testing after project completion could also influence costs.

23

Political risk can be found in all project phases above and can be critical when it is ignored.
Political tensions and insecurity can dramatically affect project cost and time (Akinci and
Fischer, 1998).
2.4 Descriptive Analysis of Cost Overruns and Time Delays
2.4.1 Overview
Change orders and project overruns are closely related. Preventing change orders in projects
and reducing the time for change-order processing were objectives defined to limit project cost
overruns in a study for Michigan State University (Mrozowski et al., 2004). Factors known to
affect change order rates were used to investigate cost overruns: project size, difference between
the low bid and government estimate, the type of construction and the level of competition
(Jahren and Ashe, 1990).
2.4.2 Project Size and Project Duration
Flyvbjerg and co-authors in diverse papers, and Hinze and Selstead (1991) found through
statistical analyses that large projects were prone to higher cost overruns. Also, Flyvbjerg studied
the influence of project duration and project sluggishness: a large implementation phase can lead
to larger cost overruns. Specifically, the scope of road projects was found to increase overtime.
2.4.3 Project Ownership
The private sector, characterized by competition and seeking performance, is generally said
to be more disciplined and efficient than the public sector. In an attempt to investigate whether
the private sector had better cost performance than the public sector, Flyvbjerg and co-authors
found no statistical evidence. Instead, cost overrun rates of some privately-owned projects were
larger than average.

24

2.4.4 Competition Level and Difference between the Low Bid and Government Estimate
A greater number of bidders often leads to low, underestimated bids. Hinze and Selstead
(1991) found the difference between the high bid and low bid to be a main factor of cost
overruns. A bid winner with an estimate lower than the engineer’s estimate would attempt to
recover the difference through all sorts of claims and change requests.
2.4.5 Construction Type
In the literature, cost overrun rates varied with the type of construction such as buildings,
roads, fixed links which are bridges or tunnels, and rails. Studies provided different rates and
ranking of cost overruns according to the type of construction. However, Flyvbjerg and coauthors attributed the lowest cost overrun rates to road projects, in the context of Europe and
North America.
2.4.6 Geographic Location
Hinze and Selstead (1991) working in the state of Washington did not find any evidence
between cost overruns and the geographic district or project location. However, Flyvbjerg and
co-authors at a worldwide level found that geography accounts for cost escalation: the highest
rates were supposedly found in developing countries. It also appears that more data is needed and
studies conducted to explain the geographical variations of cost overruns.
Table 2.3 summarizes cost overruns by project type and geographic location.

25

Region

Europe

North America

USA (State of
Washington)

South Korea

Project type
Rail
Fixed links
Roads
Rail
Fixed links
Roads
Highways:
New
construction
Resurfacing
Bridge only
Safety
Improvement

Period
covered by
the study

Average cost overrun
rate (%)

Author(s)

1927-1998

34.2
43.4
22.4
40.8
25.7
8.4

(Flyvbjerg et
al, 2003)

9.23
1985-1989

3.90
8.20

(Hinze and
Selstead,
1991)

2.98

Min. Avrg.(**) Max.
Roads
<0 *
10.7
85
(Jin-Kyung,
1985-2005
Rails
<0
47.64
65.34
L. , 2008)
Airports
16.2
60.4
64.5
Ports
8.3
36.3
182.5
(*) <0 means cost underruns, (**) Derived from Jin-Kyung’s study .
Table 2.3 Cost Overruns by Project Type and Geographic Location

However, Gamez and Touran (2010) found contradictory results to the ones of Flyvbjerg and
co-authors for developing countries. In a study of 89 transportation projects funded by the World
Bank in developing countries, Gamez and Touran (2010) found that costs were overestimated
and schedules were optimistic. In addition, project duration did not influence project
performance. The reason given was that project environments in developing countries are
different from those in developed countries, which was the focus of Flyvbjerg’s work.
2.4.7 Contractor Familiarity with the Agency
While investigating if specific contractors working with WSDOT were prone to file claims
and request additional compensation, Hinze and Selstead (1991) found no statistical evidence
that contractor familiarity and working relationship with an agency increased cost overruns.

26

2.5 Remedies to Cost Overruns and Time Delays
2.5.1 Alleviation of Cost Overrun and Time Delay Factors
In the literature, the main objectives of studies were to present cost overrun and time delay
factors at all project phases to stake-holders. This would help to prevent the occurrence of these
factors in project planning and implementation. Among other suggestions, the lowest bid system
needed to be improved by considering potential for project overruns during the work. Anderson
et al. (2007) studied right-of-way (ROW) estimation to prevent cost escalation in highway
projects, and developed a process flowchart for ROW estimate improvements. Also, Sweet and
Schneier (2009) studied the introduction of cost conditions in consultant contracts, so that design
professionals would produce more accurate cost predictions.
2.5.2 Project Governance: Increased Accountability
A relevant remedy to project overruns was the application of good governance in
transportation projects. Flyvbjerg and co-authors proposed increased focus on transparency and
public control for public sector accountability. Similarly, competition and market control were
necessary for accountability in the private sector. Transparency is achieved when required
documents and information are available to the public. Flyvbjerg (2008) summarized
accountability as follows:
The project organization may be a company or not, public or private, or
a mixture. What is important is that this organization enforces
accountability vis-à-vis contractors, operators, etc., and that in turn, the
directors of the organization are held accountable for any cost overrun,
benefits shortfall, faulty designs, unmitigated risks, etc. that may occur
during project planning, implementation and operations. The
governance framework should discourage organizational entrenchment,
i.e., the existence of the organization for longer than it is needed. If the
institutions with responsibility for developing and building major
infrastructure projects effectively implemented, embedded and enforced
such measures of accountability, then the misrepresentation in cost,
benefits and risk estimates, which is widespread today, would be

27

mitigated. If this is not done, misrepresentation is likely to continue, and
the allocation of funds for infrastructure projects is likely to continue to
be wasteful and undemocratic.

2.5.3 Reduction Lists
Ahead of project implementation, Cui and Olsson’s (2008) paper presented “reduction lists”,
i. e. the list of cost items which could be reduced if other items of a project were actually more
costly than estimated. This would help to prevent cost overruns; however projects would have a
“reduced” quality.
2.5.4 Lean Methods
Invented by Toyota, the lean production system is a technique of project improvement based
on six principles: productivity, quality, cost, delivery, safety, and employee morale. The
introduction of lean methods in other industrial sectors, such as construction, could improve
project performance (Patty and Denton, 2010).
2.6 Professional Survey, Data Retrieval and Analysis of Project Cost Overruns and Time
Delays
2.6.1 Surveys of Professionals
Most of the studies on cost overrun and time delay factors were based on surveys of industry
professionals. The following table summarizes the results of these studies.

28

Author(s)/Year

Country

Number of
Respondents

Number of
factors
studied

(Creedy et al.,
2010)

Australia

8

37

(Tumi et al. ,
2009)

Libya

N/A

43

(Abd El-Razek
et al., 2008)

Egypt

74

32

(Le-Hoai et al.,
2008)

Vietnam

87

21

(Sambasivan
and Soon, 2007)

Malaysia

150

28

(Abdul-Rahman
et al., 2006)

Malaysia

204

20

(Ajibade and
Odeyinka,
2006)

Nigeria

102

44

(Lo et al., 2006)

Hong
Kong

151

30

(Frimpong et
al., 2003)

Ghana

72

26

Major causes(or factors) of cost
overruns/ time delays
1. Design and scope change
2. Insufficient investigations and
latent conditions
3. Deficient documentation
(specification and design)
1. Improper planning
2. Lack of effective communication
3. Design errors
1. Financing by contractor during
construction
2. Delays in contractor’s payment
by owner
3. Design changes by owner or his
agent during construction
1. Poor site management and
supervision
2. Poor project management
assistance
3. Financial difficulties of owner
1. Improper planning
2. Site management
3. Inadequate contractor experience
1. Additional work
2. Labor shortage and lack of skills
3. Poor planning and scheduling
1. Contractors’ financial difficulties
2. Clients’ cash flow problems
3. Architects’ incomplete drawings
1.Inadequate resources due to
contractor lack of capital
2.Unforeseen ground conditions
3.Exceptionally low bids
1.Monthly payment difficulties
from agencies for completed work
2.Poor contractor management
3.Material procurement

Table 2.4 Surveys of Construction Professionals in the Literature

29

Table 2.4 Surveys of Construction Professionals in the Literature (Cont’d)

(Mansfield et
al., 1994)

Nigeria

37

23

(Okpala and
Aniekwu, 1988)

Nigeria

192

27

(Merewitz, L.,
1973)

U.S.A.

N/A

N/A

1. Poor contract management
2. Financing and payment of
completed work
3. Changes in site conditions
1. Shortage of materials
2. Finance and payment for
completed works
3. Poor contract management
1.Price level increases
2.Scope changes
3.Unforeseen conditions and
structural modifications

Likert scales were typically used during these studies and statistical analyses performed to
check sample adequacy and to find associations and correlations among data. Statistical
approaches used for these studies are listed below.


The Kendall’s coefficient of concordance was utilized to test whether the factors could be

prioritized (Frimpong et al. 2003). Similarly, Barlett’s test of sphericity tested the suitability of
data and the Kaiser-Meyer-Olkin test was used for sampling adequacy test (Le-Hoai et al., 2008),
(Creedy and co-authors, 2010).


The Spearman’s coefficient of rank correlation was used to evaluate the agreement or

disagreement between two groups of survey respondents (Le-Hoai et al., 2008).
2.6.2 Data Retrieval and Analysis
Flyvbjerg et al. (2004), Bordat et al. (2004), Hinze and Sealstead (1991), and Merewitz
(1973) used the statistical techniques listed below for data analysis during their studies on cost
overruns.


Histograms, data mean, median, mode, standard deviation and confidence intervals



Chi-square test to check data goodness of fit

30



R2, the coefficient of multiple determination, was necessary to choose the right model for

data analysis


Pearson’s correlation test and tailed statistical level of significance



Multiple regression analysis, scatter plots, box-and-whisker plots



T-tests utilized to check the statistical significance of hypothesis, and p-value for the

level of significance
2.7 Summary
The literature on cost overruns and time delays in construction projects, specifically in
highway and bridge projects, was summarized in this chapter. In addition, research methods and
statistical models used in the literature to study cost and time performance of projects were
reviewed. These studies stated the current knowledge about cost and time overruns, and the
studies also unveiled a gap concerning statistically sound research in this area about developing
countries. This literature review was the starting point for the research about cost and time
overruns for developing countries, by the illustration of approaches and methodologies used by
researchers. The intent of this research is to fulfill the gap observed in the literature for
developing countries, by providing a related statistically sound study on cost overruns and time
delays. As innovation, causes of cost and time overruns through the project cycle and overrun
rates and sizes were sought along with their influence on the project type, project ownership or
project source of funding, project size, and project duration.
Factors which may contribute to cost overruns and time delays were identified and presented
in Table 2.2. These factors were used as the basis for a survey of industry professionals described
in Chapter Three.

31

CHAPTER 3
RESEARCH METHODOLOGY

32

3.1 Overview
This chapter lays out the steps which were used for this research. The goals of the project
were presented in Chapter One, and the literature review presented in Chapter Two was
conducted to assess the current knowledge and research regarding cost overruns and time delays
in construction projects. After approval of the project, highway and bridge contract data were
collected for statistical analysis. In addition, a survey of construction professionals was
conducted addressing the causes of cost overruns and time delays. From the results,
recommendations were developed to help reduce cost and time overruns for infrastructure
projects in developing countries.
3.2 Methodology
The methodology proposed for this research is shown in Figure 3.1. To study cost overruns
and time delays in highway and bridge projects, the Ministry of Public Works of Cameroon was
chosen as a case study organization. Prior to the development of the research proposal,
preliminary discussions were held in MINTP for the design of the survey and guidelines for
contract data collection. Survey responses and contract data were collected and then statistically
examined. The study attempted to help fill the gap found in the literature between developing
countries, and cost overruns and time delays.

33

Preliminary
Discussions
with MINTP
Literature Review
Cost Overruns and Time Delays during:
• Planning and Programming,
• Design Process,
• Bidding Phase,
• Project Implementation,
• Project Control and ex post Evaluation

IRB
Approval

Identify
Subject
Groups

Survey
Design

Contract Data
Collection Design

Survey in
Cameroon

Contract
Data
Collection
in
Cameroon

Survey
Response
Database

Historical
Contract
Database

Statistical
Analysis

Discussion,
Recommendations,
Proof of Concepts

Figure 3.1 Hierarchical Organization of the Research Methodology

34

3.3 Literature Review
A variety of sources were surveyed during the literature review. Electronic resources were
extensively used such as Web of Science and daily Google Alerts using the key words Cost
Overruns and Time Delays. A number of journal articles were found and the most relevant ones
were selected. In addition, secondary sources consisted of books, conference proceedings,
newspapers, doctoral dissertations and master’s theses. The sources were classified according to
project development phases including: planning and programming, design process, bidding
phase, project implementation, project control and ex post evaluation. The literature was
reviewed to obtain the state of the knowledge about cost overruns and time delays in
construction, and to identify gaps for developing countries.
3.4 Case Study Organization - Cost and Time Issues
The initial step for this study was to apply for its authorization from MINTP. An application
file consisting of a letter, a literature review, and the research timeline was sent to MINTP. The
research was approved and a contract data collection as well as a construction project stake–
holder survey were authorized based on the documents presented. Informal discussions were
held with MINTP to design the survey according to the local practices of project development.
It was said that in Cameroon, weaknesses during land acquisition frequently caused people to
protest and interrupt site work (Okole, 2009). Such situations influenced negatively cost and
time. Weak and insufficient technical studies were also presented as causes of cost overruns in
Cameroon’s highways projects (Cameroon Tribune archives, 2009). Furthermore, the
displacement of existing networks (Cameroon Tribune archives, 2009) and supervisor and
contractor claims and disputes delayed projects, as well as the period of bidding. All these were
time-consuming for highway projects in Cameroon (Okole, 2009a). Similarly, bidding

35

procedures were complicated and negatively influenced project implementation. These studies
helped to motivate this research.
In addition, available reports from MINTP and past or ongoing studies related to the research
were utilized.
3.5 Contract Data Retrieval and Analysis
3.5.1 Contract Data Retrieval
Along with the survey of construction professionals, contract data was retrieved to
qualitatively determine cost overruns and time delays in MINTP.
3.5.1.1 Retrieval Operation
Bidding operations and contract services of MINTP were mainly centralized at the Ministry
headquarters in Yaounde. Some highway and bridge projects were also contracted at the local
level, in Cameroon’s regions. Periodically, local delegations sent reports on the implementation
of delegated projects to the Ministry’s headquarters. Therefore, contract data covering the whole
country was only collected at the Ministry headquarters. Key departments involved in highway
and bridge projects provided relevant documentation including contract registers, field reports
and annual project reports for use in this research.
The concerned units were the following:


Department of Highway Investment and Maintenance



Department of Rural Roads



Department of General Affairs



Department of Planning



Department of Road Protection and Environment

36

Only publicly available sources were considered for the present study. Electronic contract
files were requested for a faster retrieval for 2009, and physical documents or contract registers
were used for other years; about five thousands contracting agreements were retrieved.
In addition, sources of funding for projects were considered important because rules vary
according to budgetary items or lender policies. Two main groups were considered for funding:
projects funded by Cameroon’s government only and projects co-funded by donors. Projects
owned by Cameroon’s government only were funded through the Road Funds, the Public
Investment Budget and other budgetary items. For this last group, MINTP funded all the taxes
and a percent of project costs before taxes such as 25%, 50% or 75% of project amounts. Cofunded projects were implemented following the rules of the lender.
The main lending agencies which cooperated with MINTP were the following:


European Union



African Development Bank



Islamic Development Bank



Organization of the Petroleum Exporting Countries (OPEC) Funds



Highly Indebted and Poor Countries Initiative (HIPC) Funds, a multilateral source of
funds



World Bank, through its International Development Agency (IDA)



Koweitian Funds



Saudian Funds



Belgium



France, through its cooperation agency (AFD)



Germany, by its cooperation agency (KFW)

37

3.5.1.2 Sampling
For a statistically significant analysis, a large set of historical contract data covering more
than ten years was retrieved backwards from 2009; contracts signed in 2009 were not studied
because many of them were not yet closed-out at the time of this study. The data was selected
based on its availability. Year by year, all contracts were retrieved, even those without change
orders, or with no cost overruns or time delays. Contracts which were not directly related to
highway and bridge projects were excluded during data analysis. The research considered
recorded change orders and cost and time overruns for contracts at the cut-off date of January 8,
2010, and started in January 1994.
Only a portion of contracts experienced change orders signed into agreement between
MINTP and contractors over the past decade. In Cameroon, change orders were signed in
agreement only for changes greater than thirty percent of any cost item as specified in the
contract general provisions. Change orders were also signed for changes that necessitated new
cost items, because the contractor could not perform any work that was not in the contract; or
any work destined to be performed in new locations that were not stated in the initial contract.
However, change orders were not issued for changes affecting cost items for less than thirty
percent. These changes were typically documented in a daily diary of the job site for construction
or maintenance projects, or in progress reports for other types of contracts.
Overall, the files used in this study contained about 5,000 contracts and change orders and
consisted of about 4,000 contracts and 1,000 change orders. Only 394 recorded contracts relating
to highway and bridge projects experienced cost overruns or time delays. These 394 were used in
this research.

38

3.5.1.3: Data Categories
Contracts and change orders signed from 1994 to 2009 were categorized as follows: contract
code, nature of agreement, object of agreement, agreement amount, project type, funding source,
contract duration, date of signature, contractor identification, agreement date for each contract or
change order, contractor identification for change orders, project type, contract type,
contract/change order amount, contract/change order duration, and source of funding. The object
or purpose of each change order where available was also included for further analysis. For data
analysis, a codification for contractors and consultants with cost overruns was used:
CONTR_XX for constructors and CONSLT_XX for consultants. XX refers to an ordinal
number.
Contract Code: The contract code used by MINTP was recorded for contracts which incurred
change orders. This variable was initialized as a string of characters. It consisted of the contract
number, year, nature of contract, bidding board or call for bid reference and the ministry as
owner.
Nature of Agreement: The nature of the agreement was defined as a string of characters taking
three values respectively for regular contracts, small size contracts, and change orders. MINTP
has two classification sizes for contracts: small size contracts have an amount ranging between
5,000,000 XAF and 30,000,000 XAF and regular contracts start above 30,000,000 XAF. No
contract is needed for projects below 5,000,000 XAF, and they were not included in this study.
Object of Agreement: The purpose of a project was retrieved only for change orders under this
entry, and it was recorded as a string of characters.
Amount: This variable was set up to input the amount of each contract or change order.

39

Project Type: This category was defined as a string of characters and recorded the type of project
for each agreement as follows:


Road Construction or Maintenance



Road Signs and Markings



Bridges and Structures



Equipment Renting



Material Supplies



Design or Technical Studies



Mowing Roadsides



Geotechnical Testing



Technical Assistance, this specific item referred to agreements signed between MINTP

and consultants to assist the ministry for specific missions, mostly for the management of
projects co-funded by foreign lenders.


Work Supervision, MINTP systematically recruited consultants to insure contract

administration; these consultants had separate contracts to supervise highway and bridge
construction or maintenance projects.


Other types of projects, although recorded, were discarded from data analysis because

they were not directly related to highways or bridges. Examples of projects not considered
include: buildings, office furniture and supplies, water supply infrastructure, and other equipment
for general use such as cars.
Funding Source: The source of funding was recorded as a string of characters for the following
entities:


Government Only Funding

40



European Union



African Development Bank



Islamic Development Bank



Organization of the Petroleum Exporting Countries (OPEC) Funds



Highly Indebted and Poor Countries Initiative (HIPC)



World Bank (IDA)



Koweitian Funds



Saudian Funds



Belgium



France (AFD)



Germany (KFW)

Contract Duration: The duration of each agreement was recorded and expressed in months.
Signature: For each agreement, the signature date by the Minister of Public Works was recorded.
Contractor Identification: The contractor’s name was included as a string of characters for
change orders and related contracts.
3.5.2 Historical Data
3.5.2.1: Generalities
Yearly, each contract or change order had a unique number for identification in the Ministry
which was also used for this study. Microsoft (MS) Excel was the software used to organize the
data and for statistical analysis. During this process, data coherence was tested as well as input
errors using MS Excel tools for checking duplicates, searching and sorting strings of characters.

41

3.5.2.2: Data Organization
Data were classified in worksheets by fiscal year which varied from 1994-1995 to 2009. The
inputs were reviewed several times by the researcher to detect mistakes in the typing and sorted
by amount, type of contract, type of work, source of funding. Duplicates were identified from the
contract registers and corrected. Beginning by year 2009, for each change order, the original
contract was sought using criteria such as the date of signature, contract amount, contractor
name, and contract code. Once the original contract was found, all corresponding change orders
were pasted next to it for further analysis. Both contract registers and electronic files were used
to match contracts and related change orders.
For some projects, design and work supervision were combined, and one design-build project
was identified. These cases were classified as “Work Supervision” because design studies
continued during work supervision. The design – build project was considered a construction
project because most of its activities related to construction. Also, retaining walls, bridges and
car-ferries maintenance projects were grouped together, in some parts of Cameroon, car-ferries
are used on rivers to bridge portions of roads.
Also, change orders without an initial contract in the registers were not considered for cost
and time overrun calculations. This happened mostly for contracts dated in the 1990s which were
not handled by MINTP, before reforms which intervened about 1995. Those change orders were
only used in this study for comparisons between the sources of funding, and reporting of their
purposes.
The cost overrun rate for a contract was extracted as the total amount of its aggregated
change orders divided by the original contract amount. Similarly, time overrun rates were taken
by dividing the total value of time overruns from corresponding aggregated change orders, by the

42

initial contract time duration. Contractor cost overruns or time delays which were not excused by
the owner, such as for terminated contracts, were not considered. They were not documented in
the contract registers. For overrun rates the primary source of funding of the initial contract was
considered as the project funding source: For one contract, different change orders could have
different sources of funding. Furthermore, the final cost of contracts was assumed to be the
addition of the initial contract amounts and all change orders; the consequence is that contracts
with cost or time underruns were not studied.
After calculating the contract cost and time overrun (or time delay) rates, studies were
conducted by project funding and type from 1998 to 2008 because of data availability. Before
1997-98, funding sources were not detailed in the contract registers and contract amounts were
aggregated for all sources.
3.5.3 Data Analysis
Aided by Microsoft Excel and SPSS Statistics, data was analyzed to find frequency
distributions, means, standard deviations, correlations and associations between cost and time
overruns and contract categories in the case study organization. Histograms, tables, pie charts,
scatter plots and line graphs were used. The method of data analysis was based on the following
guidelines:
Because of experimental and other errors of measurement, the
points shown on the scatter diagram will not fall precisely on a
smooth curve. For this reason the task of the analyst becomes
threefold: to hypothesize the mathematical form of the relationship
between the two variables (model postulation), to estimate the
parameters of the model based on the experimental data (model
calibration), and to determine how well the calibrated relationship
explains the observed data (goodness of fit).
(Papacostas and Prevedouros, 2001)

43

For overrun rates, data reporting was broken down by contract categories. The categories
were project type, project ownership, project size, and project duration. Frequency distributions
for each category were plotted following interval groups of cost or time overrun rates, then
means and standard deviations were calculated. Categories of project size and project duration
were broken down in sub-categories for analysis, according to MINTP current practices for
contract classifications. For project size, sub-categories were as follows:


Contract amounts under 100,000,000 XAF



Contract amounts between 100,000,000 – 250,000,000 XAF



Contract amounts between 250,000,000 – 700,000,000 XAF



Contract amounts between 700,000,000 – 2,000,000,000 XAF



Contract amounts between 2,000,000,000 – 5,000,000,000 XAF



Contract amounts over 5,000,000,000 XAF
Sub-categories for project duration were:



Contract duration under 6 Months



Contract duration between 6 Months - 12 Months



Contract duration between 12 Months - 24 Months



Contract duration between 24 Months - 36 Months



Contract duration over 36 Months
After calculating means and standard deviations, linear regression analyses were performed

to find relevant relationships between project size, project duration and the project overrun rates.
Cost overrun rates or amounts, and time overrun rates were the dependent variables, which were
examined in relation to the independent variable, the initial contract amount, or initial contract
duration. The coefficient of determination R indicated the strength of correlation among

44

variables and p-value were calculated for the level of significance of linear regressions. Linear
regression was conducted to find the relationship between cost overrun rates and time overrun
rates.
Seeking the influence of contractor familiarity with the agency on cost and time overruns, the
frequency of occurrence of at least one change order for contractors during a given year of the
period of study was also analyzed. In the case of joint venture, each contractor was counted
separately. This frequency possibly ranged from one, for contractors who obtained only one
change order, to fifteen for contractors who received at least one change order, each year, in the
considered period. Relationships were then investigated for the resulting classifications.
3.6 Survey of Professionals
3.6.1 Design: Methods and Procedures
A survey was designed and implemented in Cameroon to collect perceptions of construction
professionals about cost overruns and time delays.
Survey design
The survey began by a statement to explain the research to the subject and to obtain his or her
consent to participate. It was anonymous, neither name nor signature were required. However,
the respondent indicated his or her profession and sector in the construction industry.
After this introduction, the survey presented the main factors of cost overruns and time delays
identified from the literature. Factors were classified by source of cost overruns and time delays
for each project phase including: Planning and Programming, Design Process, Bidding, Project
Implementation, Project Control and ex post Evaluation. The following table summarizes the
organization of survey factors.

45

No

Part

No of Questions(Factors)

1

Planning and
Programming

5

2
3
4
5

4

Design Process

4

Bidding Phase
Project
Implementation
Project Control and
ex post Evaluation
Total

17
4
34

Table 3.1 Survey Structure
Specific factors were derived from the literature and discussions with MINTP staff. Table 3.2
presents the factors and their related sources.
Factors
Planning and Programming
Lack of Project Planning/Programming
Inadequate Project
Planning/Programming
Weaknesses during the land takings
process
Expropriation costs
Legal environmental requirements
Design Process

Sources
Merewitz (1973)
Flyvbjerg (2008)
Okole (2009a)
Jergeas (2009), Anderson et al. (2008)
Jergeas (2009), Anderson et al. (2008)

Weak and insufficient technical studies

Ajibade and Odeyinka(2006), Anderson
et al. (2007), Creedy et
al.(2010),Cameroon-Tribune Archives
(2009)

Underestimating of cost estimates and
schedules/ Overestimating of Benefits

Flyvbjerg et al. (2004)

Poor project implementation strategies

Jergeas (2009), Anderson et al (2007),
Shane et al. (2009)

Mistakes and discrepancies in
documents

Okpala and Aniekwu (1998)

Table 3.2 Sources of the Factors in the Questionnaire

46

Table 3.2 Sources of the Factors in the Questionnaire (Cont’d)
Factors
Bidding Phase
Bidding Procedures
Duration of the Period of Bidding
The Lowest Bid Price System:
Unreasonable adjustment of project cost
by contractors
Project Implementation
Negligence of Site Visits Before/During
the Bidding Process- Unknown Site
Conditions.
Mismanagement Due to Inexperienced
Supervisors.
Supervisor and Contractor Claims and
Disputes
Many Stakeholders
Poor Communication Among Contract
Stakeholders
Unethical Activities And Kickbacks
Equivocal/Unclear Contracts
Changes in Scope of Contracts
The Displacement of Existing Networks
Construction Errors and On Site Testing
Approval
Building on unexpected archaeological
sites
Shortages of Materials
Material Price Fluctuation
Methods of Payment
Lack of Equipment
Weather Conditions
Political Tensions/Insecurity

Sources
MINTP Specific
Okpala and Aniekwu (1998)
Hinze and Selstead (1991),Jin-Kyung
(2008), Lo et al. (2006), Frimpong et al.
(2003)
Jin-Kyung (2008)

Pratt (2004), Sweet and Schneier (2009),
Lo et al. (2006)
Merewitz (1973), Le-Hoai et al. (2008),
Mansfield et al. (1994), Jergeas (2009)
Abd El-Razek et al. (2008)
Abd El-Razek et al. (2008)
Tumi et al. (2009), Le-Hoai et al.
(2008), Sambasivan and Soon (2007),
Jergeas (2009)
Okpala and Aniekwu (1998)
Anderson et al (2007), Shane et al.
(2009)
Merewitz (1973), Anderson et al (2007)
Cameroon-Tribune Archives (2009)
Anderson et al (2007), Okpala and
Aniekwu (1998)
Lo et al. (2006), Le-Hoai et al. (2008),
Abd El-Razek et al. (2008)
Okpala and Aniekwu (1998), Abd ElRazek et al. (2008)
Merewitz (1973), Le-Hoai et al. (2008),
Frimpong et al. (2003)
Okpala and Aniekwu (1998)
Okpala and Aniekwu (1998), Abd ElRazek et al. (2008)
Bramble and Callahan (2000), Abd ElRazek et al. (2008), Le-Hoai et al.
(2008), Okpala and Aniekwu (1998)
Akinci and Fischer (1998)

47

Table 3.2 Sources of the Factors in the Questionnaire (Cont’d)
Factors
Project Control and ex post
Evaluation
No Action Taken After Contract’
Progress Reports
Periods of Inspection and Testing After
Contract Completion
Lack of Contract ex post Evaluation
Negligence of Past Experiences

Sources

Jin-Kyung (2008)
Okpala and Aniekwu (1998), Tumi et al.
(2009), Mansfield et al. (1994)
Jin-Kyung (2008)
MINTP Specific

Questions were closed-ended for quick responses and pre-coded to allow statistical analysis.
The last question was open ended and asked the respondent to provide his or her suggestions for
solutions. On a five-category Likert scale varying from 1(Strongly Agree) to 5(Strongly
Disagree), respondents rated each factor based on their experience. The survey took ten to fifteen
minutes on average to complete. It also had a French version.
In addition to the use of a Likert scale, because respondents were anonymous during the
survey, the following coding process was used to record each respondent’s characteristics:
PPP_CCCC_XX. The table below explains this coding for each respondent:

PPP
CCCC
XX

The first three letters of the
profession.
The first four letters of the
sector in construction.
Two digits representing the
numbering of each
questionnaire.

Table 3.3 Respondents’ Coding for Data Input
In order to organize the set of data, variables were coded as presented in Table 3.4 and Table
3.5 for software statistical analysis.

48

No

Variable
Characteristics of Respondents

1

Profession of the Respondent

2

Sector in the industry

Code

Type

Profession

String

Sector

String

Values
 Man = “Manager”
 Eng= “Engineer”
 Acc= “Accountant”
 Oth= “Other”
 Cons =”Consultant”
 Cont= “Constructor”
 Dono= “Donor”
 Fina= “Finance”
 Gove= “Government”

Table 3.4 Respondents’ Coding for Data Analysis

49

No

Variable

Code

Type

Values
1= “Strongly
Agree”
2= “Agree”
3= “Neither”
4= “Disagree”
5= “Strongly
Disagree”

Lack_Pl_Prog

Ordinal

1,2,3,4,5

Inad_Plan_Prog

Ordinal

1,2,3,4,5

Weakness_Takings

Ordinal

1,2,3,4,5

Expropriation_Costs

Ordinal

1,2,3,4,5

legal_Envir_Req

Ordinal

1,2,3,4,5

Weak_Tech_Stud

Ordinal

1,2,3,4,5

Underestimating_Cost_ove
r_benf

Ordinal

1,2,3,4,5

Poor_Impl_Stratg

Ordinal

1,2,3,4,5

Mistakes_Discrep

Ordinal

1,2,3,4,5

Bidding_proced

Ordinal

1,2,3,4,5

Duration_Bidd

Ordinal

1,2,3,4,5

Lowest_Bid_Sys

Ordinal

1,2,3,4,5

Unreasonnable_Adjust

Ordinal

1,2,3,4,5

Negligence_Site_visits

Ordinal

1,2,3,4,5

Mismanagt_Inexp_Supv

Ordinal

1,2,3,4,5

Supv_Contr_Claims

Ordinal

1,2,3,4,5

Many_Stakeholders

Ordinal

1,2,3,4,5

Poor_Communicat

Ordinal

1,2,3,4,5

Responses of Respondents

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.

14.

15.
16.
17.
18.

Lack of Project
Planning/Programming
Inadequate Project
Planning/Programming
Weaknesses during the land
takings process
Expropriation costs
Legal environmental
requirements
Weak and insufficient technical
studies
Underestimating of cost
estimates and schedules/
Overestimating of Benefits
Poor project implementation
strategies
Mistakes and discrepancies in
documents
Bidding Procedures
Duration of the Period of
Bidding
The Lowest Bid Price System:
Unreasonable adjustment of
project cost by contractors
Negligence of Site Visits
Before/During the Bidding
Process- Unknown Site
Conditions.
Mismanagement Due to
Inexperienced Supervisors
Supervisor and Contractor
Claims and Disputes
Many Stakeholders
Poor Communication Among
Contract Stakeholders

Table 3.5 Software Coding of Factors

50

Table 3.5 Software Coding of Factors (Cont’d)
No
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.

Variable
Unethical Activities And
Kickbacks
Equivocal/Unclear Contracts
Changes in Scope of Contracts
The Displacement of Existing
Networks
Construction Errors and On Site
Testing Approval
Building on unexpected
archaeological sites
Shortages of Materials
Material Price Fluctuation
Methods of Payment
Lack of Equipment
Weather Conditions
Political Tensions/Insecurity
No Action Taken After
Contract Progress Reports
Periods of Inspection and
Testing After Contract
Completion
Lack of Contract ex post
Evaluation
Negligence of Past Experiences

Code

Type

Values

Unethical_Actvties

Ordinal

1,2,3,4,5

Equivocl_Contracts
Change_Scope

Ordinal
Ordinal

1,2,3,4,5
1,2,3,4,5

Displacement_Networks

Ordinal

1,2,3,4,5

Constr_Errors

Ordinal

1,2,3,4,5

Unexpted_Archeolg_Sites

Ordinal

1,2,3,4,5

Shortage_Materials
Materials_Price_Fluct
Payment_Method
Equipment_Lack
Weather
Politic_Tensions

Ordinal
Ordinal
Ordinal
Ordinal
Ordinal
Ordinal

1,2,3,4,5
1,2,3,4,5
1,2,3,4,5
1,2,3,4,5
1,2,3,4,5
1,2,3,4,5

No_Action_Reports

Ordinal

1,2,3,4,5

Period_Inspect_Test

Ordinal

1,2,3,4,5

Ordinal

1,2,3,4,5

Ordinal

1,2,3,4,5

Lack_Post_Impl
Lack_Pl_Prog
Negl_Past_Expces

Survey versions in English and French are presented in appendices.
3.6.2 Sampling
3.6.2.1 Survey Location
The survey was conducted at the capital city, Yaounde, where the central services of MINTP
and most of all other agencies involved in transportation projects are based.
3.6.2.2 Survey Participants
The investigator focused on technical and administrative departments of MINTP and its
partners, involved with highway and bridge project management. For the ministry, they were:

51



The Department of Highway Investments and Maintenance



The Sub Department of Contracts and Bidding (General Affairs Department)



The Department of Rural Roads



The Department of Planning



The Regional Delegation of Public Works for the Centre region
MINTP had hundreds of engineers, and in addition, 137 contractors and 35 consultants

partnering with the ministry in 2007 (MINTP, 2008). Participants completed the survey in their
offices. A balance between government agencies, contractors, consultants, funding agencies and
donors was sought. The size and local classification of contractors and consultants was also
considered.
The investigator had informative telephone meetings with top managers of the ministry
departments to request participation of their unit in the survey. Approximately five heads of
department at MINTP participated, along with the five to ten experienced project engineers,
managers or accountants within their respective departments. The forms were electronically sent
by email to the departments, printed and distributed to targeted participants in an envelope or left
with the secretary of the department if the targeted respondents were not available. Participants
returned their responses in a sealed envelope provided with the survey. Responses were collected
daily by agents of the MINTP Mailing Service, where the responses were gathered and mailed by
express means to the investigator at MSU. These agents usually tour the Ministry and its
partnering organizations many times daily to distribute or collect mail and internal documents
from one service to the other.
For donors, only those having projects with MINTP were surveyed: the respondents were
preferably project managers or accountants.

52

Lastly, contractors and consultants who were active, i.e. have ongoing contracts with MINTP
were targeted. The heads of departments of the ministry were asked to provide shortlists of
contractors and consultants who could be surveyed. Field engineers, superintendents, field
supervisors and project managers were targeted for the survey. Most public works contractors
and consultants working countrywide are based in Yaounde or have an agency there. In total, 30
out of 137 contractors were scheduled for the survey for a rate of 22%; and eleven consultants
out of 35 as well, and the forecasted survey rate was 31 % for the latter group. Overall 41
respondents from contractors and consultants, and 59 respondents from Government and funding
agencies were sought. A response rate greater than 40% was targeted for an acceptable bias
(Moser and Kalton, 1972). Therefore, about one hundred survey forms were printed and
administered to construction professionals during a three to four week period.
Table 3.6 presents the stratified sampling considered for this survey.

No

1

Location(City)
Yaounde

Department(SubDepartment)

Agency

MINTP Central services

Highway
Investment and
Maintenance
General
Affairs(Contracts&
Bidding)
Rural Roads
Planning

Donors and Lenders: European
Union Delegation, World Bank ,
African Development Bank
Road Fund
Consultants/Supervisors
Contractors
MINTP Regional Delegation of Centre
Total
Table 3.6 Sampling- Potential Respondents of the Survey

53

No of
Targeted
Respondents
15

10
15
8
5
2
11
30
4
100

3.6.3 Survey Data Analysis
After receiving the data in hard copies, using the Statistical Package for the Social Sciences
(SPSS) and Microsoft Excel, data were computerized using the coding presented previously.
Missing values for each variable were identified and all corresponding responses were discarded
from the survey analysis. Then, valid responses were analyzed using descriptive statistics.
Variables were ranked according to the response frequencies for each possibility from one to
five. Cross-tabulation was also performed to study associations and correlations among
variables. Overall ranking of responses was first performed; for each variable, the frequencies of
respondents for the values “Strongly Agree” and “Agree” were summed and the score used for
ranking. Variables were ranked in decreasing order from the highest score to the lowest.
The statistical models of Lambda and Goodman and Kruskal tau were automatically performed
to evaluate correlation among the variables used for cross-tabulation.
3.7 Other Sources Retrieved
Along with contract data, other documents were received, for a better understanding of cost
and time issues in MINTP, and its contracting process. The most relevant were:


The public contract code of Cameroon, and related by-laws and circular letters



The decree organizing MINTP signed on April 29 2011



Typical call for bids electronic files



MINTP Annual Reports for 2004, 2006,2007,2008 and 2009



Project and field reports for road funds and public investment budget, European Union

funded road rehabilitation and maintenance programs, project reports of the African
Development Bank, and an implementation completion report of the Transport Sector Project of
the World Bank

54



Work Supervision Report for the Construction of Ayos - Bonis road (June 2008)



Work Supervision Final Report for the construction of Ngaoundere-Touboro-Chad

frontier road(March 2007)


Final report on the study to obtain standardized costs for road projects, technical studies,

and work supervision in Cameroon (MINTP, 2009a)


Final report on the study to analyze problems related to the bidding of public contracts of

MINTP (MINTP, 2008b)


Twenty recent contracts and change orders for road and bridge construction and

maintenance, work supervision, socio-economic studies and preliminary design, detailed design,
mowing roadsides, traffic studies.
These sources were used help substantiate conclusions drawn from the survey and contract
data analysis and formulate guidelines and recommendations.
3.8 Research Questions
The following research questions were investigated, during the present study:


There are causes of cost overrun and time delay in the planning/programming phases of

projects that are identifiable


Design processes and bidding influence cost overrun and time delay during project

implementation


During project implementation, there are identifiable factors of cost overruns and time

delays


Deficiencies in project post evaluation impact future projects cost overrun and time delay



The project type, project size, project ownership, project duration, and contractor

familiarity with the case study organization are factors of the cost overrun rate

55



The cost overrun rate and time overrun rate are related to each other

3.9 Deliverables
Discussion in the thesis included the survey results, project overrun rates and their statistical
inferences. It also considered past studies and legal and administrative documents relating to cost
overruns and time delays, which were collected at MINTP along with data.
This research unveiled cost overrun rates, their relationships to project categories, and
perceptions of their causes by industry professionals in highway and bridge projects in
Cameroon, as a case study for developing countries. Furthermore, it contributed to the literature
in helping to identify the main factors of cost overruns and time delays in Cameroon. Guidelines
to overcome cost overruns and time delays were developed for the case study agency, which
would have application in other countries with similar conditions. As proof of concepts, the
researcher has a broad knowledge of the case-study organization and these guidelines considered
the diverse solutions proposed by the management of the MINTP and other survey respondents
to solve the issues of cost overruns and time delays.
3.10 Chapter Summary
Based on the background studies presented in Chapter Two, the methodology used for this
research was described in this chapter. Research questions and projected outcomes of the study
were also presented.

56

CHAPTER 4
CONTRACT DATA ANALYSIS

57

4.1 Introduction - Preliminaries
This chapter presents the results of the contract data analysis. After contracts and change
orders were entered in the database, a detailed analysis was performed to determine project
overruns for MINTP. The arithmetic mean and standard deviation of cost and time overrun rates
were performed for each of the project categories. Then, a linear regression model was used to
investigate relationships among the data.
MINTP consumes important budgetary resources of the Republic of Cameroon, for highway
infrastructure construction and maintenance. Each year since the mid-1990s, hundreds of
contracts were signed since the mid-1990s. The currency of Cameroon is the CFA Franc (XAF).
It has an invariable constant exchange rate with the Euro: Euro 1 = 655.96 XAF; on August 1
2011, US$1= 460 XAF. Monetary amounts were not adjusted for inflation.
Time was measured in months for all contracts; few projects had durations less than one
month. The definitions of cost overrun and time overrun presented in the glossary for contracts
are similar for programs or projects which consist of many contracts. The cost or time overrun
rates represent the ratio between the cost or time overrun and the initial contract, project,
program amount or duration. Rates are expressed as percentages of the initial contract, project or
program cost or duration.
Table 4.1 summarizes the volume of contracts during the time period considered for the
research.

58

Year (Period)
Number
of
Contracts
Signed
for
highway and
bridge
projects
Total Amount
of Contracts
Signed (XAF)
Number
of
Change
Orders Signed
Total Amount
of
Correspondin
g
Change
Orders
and
others(*)
(XAF)
(*) “Others”:
Change Orders
for initial
contract not in
the database

1994-95

1995-96

1996-97

1997-1999

99-2000

2001-02

196

140

712

374

403

331

7,790,548,570

5,908,371,918

27,005,131,550

37,680,119,941

52,321,414,289

167,171,541,572

4

5

18

80

132

162

102,409,944

124,048,147

154,405,872

26,909,853,066

4,561,362,799

35,252,289,594

Table 4.1 Volume of the Contracts Registered

59

Table 4.1 Volume of the Contracts Registered (Cont’d)
Year (Period)
Number of Contracts
Signed for highway
and bridge projects
Total
Amount
of
Contracts
Signed
(XAF)
Number of Change
Orders Signed

Total
Amount
of
Corresponding Change
Orders and others(*)
(XAF)

2003

2004

2005

2006

190

222

355

202

51,750,458,562

72,854,036,091

106,592,532,115

132,311,964,847

90

65

67

33

10,300,632,952

11,141,968,415

11,967,037,403

3,379,832,674

(*) “Others” are Change
Orders for initial
contract not in the
database

60

Table 4.1 Volume of the Contracts Registered (Cont’d)
2007

2008

2009

77

267

399

Total Amount of Contracts
Signed (XAF)

52,080,242,217

160,656,817,485

280,771,098,989.2

Number of Change Orders
Signed

13

26

5

1,476,655,360

421,635,611

0

Year (Period)
Number
of
Contracts
Signed for highway and
bridge projects

Total
Amount
of
Corresponding
Change
Orders
and
others(*)
(XAF)
Overall Number of
Contracts (1994-2009)
Overall Number of Change
Orders(1994-2009)
(*) “Others” are Change
Orders for initial contract not
in the database

3868
700

61

Table 4.2 and Figure 4.1 below summarize the volume of contracts and change orders for the
period of study, by project type.
Total Contract
Amounts

Total Cost
Overruns

Global Amount by
Project Type

545,472,244,192.00

57,294,182,778.00

602,766,426,970.00

48,700,487,193.00

12,237,193,407.00

60,937,680,600.00

Bridges and Structures

41,394,727,818.00

560,974,087.00

41,955,701,905.00

Design/Technical Studies,
Technical Assistance

17,517,937,055.00

1,196,632,317.00

18,714,569,372.00

Mowing Roadsides

14,700,432,431.00

168,701,672.00

14,869,134,103.00

TOTAL

667,785,828,689.00

71,457,684,261.00

739,243,512,950.00

Type
Road
Construction/Maintenance
Work Supervision

Table 4.2 Volume of Contracts with Cost and Time Overruns (1994-2009)
Design/Technic.
Studies,
Technical
Assistance
2%
Bridges and
Structures
6%

Mowing
Roadsides
2%
Road
Construction/
Maintenance
82%

Work
Supervision
8%

Global Amount by Project Type

Figure 4.1 Repartition of Contract Global Amount by Project Type (1994 – 2009)

62

4.2 Change Orders
4.2.1 Overview
Change orders recorded during the overall period of study were broken-down as follows
between the diverse sources of funding, for MINTP activities. Projects funded by foreign donors
or lenders incorporated government contributions, in the form of taxes or a percentage of the
estimated costs. However, for simplicity, they are considered owned by the corresponding donor
or lending agencies because the rules of these organizations applied for project implementation.
The volume of change orders varied for each source of funding as presented in Table 4.3 below.
Overall Change Order Volume in the
Database (XAF Amount)
605,583,744.00
23,790,596,830.00
28,525,280,749.00
8,883,417,840.00
30,790,525,005.00

Organization
African Dev. Bank
World Bank (IDA)
Cameroon’s Government Only
France-AFD
European Union
Islamic Dev. Bank(IDB), OPEC
Funds, Koweitian Funds, Saudian
Funds
HIPC Funds

4,502,686,423.00
8,391,873,683.00
105,489,964,274.00

TOTAL

Table 4.3 Overall Change Order Volume in the Database by Project Ownership (1994-2009)

63

Change Order Volume in the Database (XAF Amount)
African Dev.
Islamic Dev.
HIPC Funds
Bank
Bank(IDB),
8%
World Bank
1%
OPEC Funds,
(IDA)
Koweitian Funds,
23%
Saoudian Funds
4%
European Union
29%

Govt Only
27%
France-AFD
8%

Figure 4.2 Repartition of Change Orders in the Database (XAF Amount) By
Funding Source (1994-2009)
4.2.2 Causes of Change Orders
From MINTP and donors reports (MINTP, 2009a), (MINTP, 2008b), (MINTP, 2008c),
MINTP, 2007a), (Groupe de la Banque Africaine de Développement, 2008), some causes of
change orders which impacted cost and time for large projects were indicated, among which
were listed:


Interruption of work because funds were exhausted before contract completion, this

situation mainly concerned projects co-funded by foreign aid, and many times MINTP had to
finance related change orders itself

64



The practice of cash advances by MINTP: on some large projects, contractors required

cash advances before starting work, and they sometimes ended with high cost overruns and time
extensions


Acts of God and vandalism



Lateness of MINTP in the issuance of contractual documents



Lateness of MINTP in land expropriation and “right-of-way” processing



Displacement of aerial or underground networks



Wrong design studies which had to be re-done at the beginning of work implementation.

Some contracts experienced cost overruns from the period of the notice to proceed


Processing of taxes and customs exemption for international contractors working on co-

funded projects


Defective equipment



Extraordinary lengthy bidding and payment procedures, involving donor agreement at

each step
Such causes did not appear in the contract registers, when only the intent of each change
order was recorded.
4.2.3 Purpose of Change Orders Recorded
Change orders in the database could be broken down in four groups:


Change orders with no impact on cost and time



Change orders with cost overruns only



Change orders with time overruns only



Change orders with both cost and time overruns

65

However, these change orders could have a similar purpose, regardless of their group. Table 4.4
below summarizes the 37 purposes of change orders which were recorded in the contract files.
Changing Contractor’s Bank Account
Modifying the Contract’s Budgetary
Item

Modifying the Scope of Work

Changing the Method of Payment

Extension of the Work Supervision Period

Changing Unit Prices

Time Extension for Work

Update of Design Studies

Extra Work

Paying Contractor’s Extra Work

Paying Cost Overruns due to Work
Interruption because of Insecurity

Extra Work Supervision

Paying Cost Overruns due to Asphalt Shortage

Extra Design Studies During Work
Supervision
Paying a Consultant for Assistance
during Bidding Procedures
Correcting Contract’s Duration
Approving New Prices for the
Contract’s estimate
Extra Technical Assistance
Modification of Project Itinerary
Extra Geotechnical Studies
Change of Work Scheduling
Environmental Impact Studies during
Work Supervision

Modifying Some Contract Provisions

Adjusting Prices
Change of Contractor’s Name
Refund of Some Taxes to Contractor
Extra costs for Work Supervision due to
Contractor Lateness
Modifying Repartition of Funding
Adjustment for New Value Added Taxes
Replacing Deceased Contractor Manager by
Legal Representative
Correction of Mistakes on Estimate Errors
Modification of Definitions and Attributions

Extension of Design Studies Proposal

Cancellation of Parts of Work

Modification of Budgetary Year

Modification of Work Supervision Contract
following Increases in Construction Costs

Change of Construction Site

Table 4.4 General Purposes of Change Orders Recorded at MINTP
4.3 Detailed Analysis of Cost and Time Overruns
4.3.1 Overview
Cost and time overrun rates were reported depending on data availability year after year, and
then summarized for the whole period of study. Cost overrun and time delay rates were

66

investigated by project type, project ownership, project size, and project duration. The
relationship between cost overrun rates and time overrun rates was also sought. The sample of
394 contracts was used for regression analysis, which was performed at 90% for the level of
significance. These 394 contracts were selected because they had either cost overruns or time
delays.
4.3.2 Summary of Data for 2001-2002
Contracts signed in 2001-2002 had the largest number of change orders for the period studied,
therefore this fiscal year was chosen for illustration since it has the most significance on cost
overruns and time delays for MINTP.
Table 4.5 indicates contract amounts and their cost and time overrun rates for 2001-2002 by
project type and by source of funding. These project overrun rates for all contracts for 2001-2002
are classified by ascending cost overrun rates.

67

No
1.
2.

Cost
Time
Overrun Overrun
Rates
Rates
11,945,358,369.00(*) 0.00%
0.00%
347,462,795.00
0.00%
33.33%
195,532,605.00
0.00%
25.00%
Contract
Amounts

Type

Funding

All
Bridge & Structure
Construction/Maintenance

All
Gov
Gov

3.

398,695,495.00

0.00%

50.00%

Construction/Maintenance

HIPC

4.
5.
6.
7.
8.

411,499,838.00
412,927,672.00
423,902,152.00
428,813,462.00
454,638,423.00

0.00%
0.00%
0.00%
0.00%
0.00%

50.00%
50.00%
50.00%
50.00%
50.00%

Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance

Gov
HIPC
HIPC
HIPC
HIPC

9.

480,867,316.00

0.00%

50.00%

Construction/Maintenance

HIPC

10.
11.
12.
13.
14.
15.
16.
17.

6,034,808,829.00
2,849,972,793.00
2,750,414,002.00
4,006,281,419.00
3,446,267,827.00
171,354,070.00
569,757,145.00
774,911,963.00

0.33%
1.28%
1.38%
1.63%
1.74%
2.35%
2.96%
2.97%

22.22%
0.00%
0.00%
0.00%
0.00%
8.33%
0.00%
8.33%

Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Technical studies

Gov
EU
EU
EU
EU
Gov
EU
HIPC

18.

4,357,805,562.00

2.99%

5.56%

Construction/Maintenance

Gov

19.
20.
21.
22.
23.

1,087,683,356.00
737,320,934.00
921,712,897.00
1,029,439,154.00
812,147,317.00

3.31%
3.39%
3.81%
4.21%
4.39%

0.00%
0.00%
0.00%
0.00%
0.00%

Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance

EU
EU
EU
EU
EU

24.

939,954,150.00

4.70%

0.00%

Construction/Maintenance

EU

693,152,006.00
4.89%
0.00%
Construction/Maintenance
4,143,625,414.00
5.76%
2.78%
Construction/Maintenance
99,520,568.00
8.27%
4.17%
Mowing
64,941,786.00
10.48%
16.67%
Mowing
31,542,318.00
10.59%
25.00%
Mowing
2,728,524,578.00
15.55%
4.17%
Construction/Maintenance
(*) Aggregated amount for contracts without cost or time overruns

EU
Gov
Gov
Gov
Gov
EU

25.
26.
27.
28.
29.
30.

Table 4.5 Cost and Time Overrun Rates for All Contracts - Year 2001-2002

68

Table 4.5 Cost and Time Overrun Rates for All Contracts - Year 2001-2002 (Cont’d)
No
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.

Cost
Overrun
Rate
302,112,293.00
16.26%
247,652,825.00
17.02%
889,591,215.00
18.79%
261,680,865.00
21.25%
209,821,492.00
21.67%
374,182,758.00
21.97%
616,763,099.00
22.65%
107,687,816.00
25.64%
30,999,492.00
25.66%
645,585,085.00
26.43%
875,365,071.00
26.58%
70,017,755.00
28.47%
163,395,564.00
28.58%
3,437,290,860.00 29.00%
70,325,994.00
29.87%
58,094,154.00
29.88%
63,374,470.00
29.90%
45,723,240.00
29.94%
74,624,593.00
29.99%
161,832,945.00
31.54%
138,039,791.00
31.94%
96,925,483.00
32.38%
449,917,916.00
34.00%
173,058,807.00
34.18%
24,388,276.00
34.71%
418,790,178.00
35.91%
117,366,168.00
37.23%
109,240,396.00
37.63%
106,103,444.00
38.99%
121,137,018.00
39.39%
74,904,446.00
39.88%
86,739,953.00
41.64%
111,109,743.00
41.81%
317,771,770.00
44.12%
58,754,386,191.00 44.76%
464,417,577.00
45.93%
Contract
Amounts

Time
Overrun
Rate
0.00%
0.00%
38.89%
8.33%
8.33%
44.44%
44.44%
0.00%
0.00%
44.44%
44.44%
100.00%
8.33%
34.91%
100.00%
100.00%
100.00%
100.00%
100.00%
0.00%
41.67%
0.00%
30.00%
0.00%
170.00%
145.45%
41.67%
41.67%
41.67%
0.00%
41.67%
41.67%
41.67%
31.58%
36.36%
19.44%

69

Type

Funding

Construction/Maintenance
Construction/Maintenance
Work supervision
Construction/Maintenance
Construction/Maintenance
Work supervision
Work supervision
Construction/Maintenance
Mowing
Work supervision
Work supervision
Technical studies
Construction/Maintenance
Work supervision
Technical studies
Technical studies
Technical studies
Technical studies
Technical studies
Construction/Maintenance
Work supervision
Bridge & Structure
Construction/Maintenance
Construction/Maintenance
Bridge & Structure
Work supervision
Work supervision
Work supervision
Work supervision
Technical studies
Work supervision
Work supervision
Work supervision
Work supervision
Construction/Maintenance
Work supervision

Gov
Gov
EU
Gov
Gov
EU
EU
Gov
Gov
EU
EU
Gov
Gov
EU
Gov
Gov
Gov
Gov
Gov
Gov
Gov
Gov
Gov
Gov
Gov
EU
Gov
Gov
Gov
Gov
Gov
Gov
Gov
Gov
EU
EU

Table 4.5 Cost and Time Overrun Rates for all contracts, Year 2001-2002(Cont’d)
No

Contract
Amounts

67.
68.
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.

118,292,871.00
846,435,450.00
71,696,909.00
410,200,849.00
101,090,437.00
29,960,405.00
417,589,673.00
52,799,618.00
530,345,339.00
173,592,815.00
29,932,491.00
47,628,606.00
91,610,878.00
547,413,543.00
138,077,751.00
110,034,636.00
572,959,572.00
558,510,801.00
73,792,941.00
96,085,246.00
27,528,904.00
101,159,738.00
78,756,688.00
125,601,293.00
164,281,690.00
122,486,530.00
74,582,178.00
26,122,186.00

Cost
Overrun
Rate
47.43%
47.76%
47.90%
47.91%
49.49%
50.07%
50.13%
50.73%
53.04%
57.24%
60.08%
62.07%
62.45%
65.79%
67.00%
67.69%
69.13%
70.85%
72.14%
83.61%
92.27%
98.68%
100.00%
100.00%
110.62%
140.41%
155.01%
284.18%

Time
Overrun
Rate
12.50%
44.44%
0.00%
47.22%
25.00%
66.67%
8.33%
50.00%
47.22%
101.82%
66.67%
40.00%
0.00%
19.44%
12.50%
12.50%
20.83%
20.83%
141.67%
0.00%
50.00%
8.33%
75.00%
12.50%
143.64%
41.67%
8.33%
100.00%

Type

Funding

Construction/Maintenance
Work supervision
Construction/Maintenance
Work supervision
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Work supervision
Work supervision
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Work supervision
Construction/Maintenance
Construction/Maintenance
Work supervision
Work supervision
Work supervision
Construction/Maintenance
Construction/Maintenance
Construction/Maintenance
Technical studies
Construction/Maintenance
Work supervision
Work supervision
Technical studies
Construction/Maintenance

Gov
EU
Gov
EU
Gov
Gov
Gov
Gov
EU
IDB
Gov
Gov
Gov
EU
Gov
Gov
EU
EU
Gov
Gov
Gov
Gov
Gov
Gov
IDB
Gov
AFD
Gov

Table 4.5 Cost and Time Overrun Rates for all contracts, Year 2001-2002 (Cont’d)
4.3.3 Project Type
Contracts were first classified by project type, as presented in table 4.2.: road construction
and maintenance, work supervision, bridges and structures, design/technical studies and

70

technical assistance, and mowing roadsides. For each type, the frequency distribution of cost
overruns and time delays was plotted, and then means and standard deviations calculated.
4.3.3.1 Frequency Distributions of Cost Overrun Rates by Project Type

Frequency distributions of cost overrun rates varied with project type. The largest number of
contracts was recorded for road construction and maintenance. Regardless of project type, most
contracts had no change orders recorded for them in the database. Cost overrun rates ranged from
0% to 284%. Work supervision had the highest frequency of cost overrun rates, and bridge and
structure projects recorded the lowest frequency of cost overrun rates. Corresponding
distributions are plotted in the Figures 4.3- 4.7.

71

Frequencies of Cost Overrun Rates for Road
Construction/Maintenance
Frequencies of Cost Overrun Rates for Road Construction/Maintenance

Number of Contracts

963

85
1

1

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

20 10 9 14 21 17 9 13 8 6 6 9 6
3 3 2 2 2 2 2

Cost Overrun Rates
Figure 4.3 Frequency Distribution of Cost Overrun Rates - Road Construction and
Maintenance (1994-2009)

72

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

Number of Contracts
0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

Number of Contracts

Frequencies of Cost Overrun Rates for Bridges & Structures
Frequencies of Cost Overrun Rates for Bridges & Structures

230

1

3
1 1 1 2

10
11 9
6
4
1

8
3 3 1 1 1 2 2 1 2

73
2 1

1

Cost Overrun Rates

Figure 4.4 Frequency Distribution of Cost Overrun Rates – Bridges and Structures (1994-2009)
Frequencies of Cost Overrun Rates for Work Supervision

71
Frequencies of Cost Overrun Rates for Work Supervision

17
3 1
1 1

Cost Overrun Rates

Figure 4.5 Frequency Distribution of Cost Overrun Rates – Work Supervision (1994-2009)

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

Number of Contracts
0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

Number of Contracts

Frequencies of Cost Overrun Rates for Design/Technical Studies,
Technical Assistance

148
Frequencies of Cost Overrun Rates for Design/Technical Studies, Technical
Assistance

2 2 1 1 2 7 0 1 1

2 5 4 1 5 3
1
1

74

1

Cost Overrun Rates

Figure 4.6 Frequency Distribution of Cost Overrun Rates –
Design/Technical Studies, Technical Assistance (1994-2009)

Frequencies of Cost Overrun Rates for Mowing Roadsides

568
Frequencies of Cost Overrun Rates for Mowing Roadsides

2

Cost Overrun Rates

Figure 4.7 Frequency Distribution of Cost Overrun Rates – Mowing Roadsides (1994-2009)

4.3.3.2 Summary of Results for Cost Overrun Rates by Project Type

All types of projects had low average cost overrun rates below six percent except work
supervision with averaged 21.23%. Table 4.6 shows the mean of cost overrun rates for each
project type, along with standard deviations. These rates look lower than rates of developed
countries. The scarcity of financial resources in developing countries is a possible reason for
this situation. These lower rates do not necessarily imply a better project management in the
case study organization however.

Project Type

Cases

Mean (%)

Standard Deviation
(%)

Road
Construction/Maintenance

1214

5.50

17.66

Bridges & Structures

238

1.69

13.04

Work Supervision

164

21.23

30.63

168

4.13

16.51

590

0.67

4.16

Design/Technical Studies,
Technical Assistance
Mowing Roadsides

Table 4.6 Means and Standard Deviations of Cost Overrun Rates by Project Type
4.3.3.3 Frequency Distributions of Time Overrun Rates by Project Type

Similar to cost overrun rates, frequency distributions of time overrun rates varied with project
type. Again, irrespective of project type, the majority of contracts had a zero percent time
overrun rate. In general, the range of time overrun rates is greater than the range of cost overrun
rates. Time overrun rates ranged from 0% to 270%. The frequency distributions of time overrun
rates are shown in Figures 4.8 - 4.12.

75

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
160 to 170%
170% to 180%
180% to 190%
200% to 210%
216.00%
231%
260 to 270%

Number of Contracts

Frequencies of Time Overrun Rates for Road Construction/Maintenance

963
Frequencies of Time Overrun Rates for Road Construction/Maintenance

44
14 11 12 6 12 36 7 8 1 19 3 2 14 2 8 3 1 1

76

7 15 6 4 2
2 1 1 7

Time Overrun Rates

Figure 4.8 Frequency Distribution of Time Overrun Rates – Road Construction/Maintenance (1994-2009)
1 1

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
160 to 170%
170% to 180%
180% to 190%
200% to 210%
216.00%
231%
260 to 270%

Number of Contracts

Frequencies of Time Overrun Rates for Bridges & Structures
Frequencies of Time Overrun Rates for Bridges & Structures

230

1 1
1
1 2
1

Time Overrun Rates

Figure 4.9 Frequency Distribution of Time Overrun Rates – Bridges and Structures (1994-2009)

77

1

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
160 to 170%
170% to 180%
180% to 190%
200% to 210%
216.00%
231%
260 to 270%

Number of Contracts

Frequencies of Time Overrun Rates for Work Supervision
Frequencies of Time Overrun Rates for Work Supervision

71

13
14

5

1
12
15

5 6
3
5
2 1
2
2

78

2
3

Time Overrun Rates

Figure 4.10 Frequency Distribution of Time Overrun Rates – Work Supervision (1994-2009)
1
1

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
160 to 170%
170% to 180%
180% to 190%
200% to 210%
216.00%
231%
260 to 270%

Number of Contracts

Frequencies of Time Overrun Rates for design/Technical Studies, Technical Assistance
Frequencies of Time Overrun Rates for design/Technical Studies, Technical Assistance

148

3 3
2 1
1
1 1
1
6

79

1

Time Overrun Rates

Figure 4.11 Frequency Distribution of Time Overrun Rates – Design/Technical Studies, Technical Assistance (1994-2009)

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
160 to 170%
170% to 180%
180% to 190%
200% to 210%
216.00%
231%
260 to 270%

Number of Contracts

Frequencies of Time Overrun Rates for Mowing Roadsides
Frequencies of Time Overrun Rates for Mowing Roadsides

568

16 2
1 2
1

Time Overrun Rates

Figure 4.12 Frequency Distribution of Time Overrun Rates – Mowing Roadsides (1994-2009)

80

4.3.3.4 Summary of Results for Time Overrun Rates by Project Type
The means of time overrun rates had greater values compared to those for cost overrun rates
when classified by project type, except for mowing roadsides. Work supervision had the highest
time overrun rate at 22.93%. Standard deviations were larger than for cost overruns.

Project Type
Road
Construction/Maintenance
Bridges & Structures
Work Supervision
Design/Technical Studies,
Technical Assistance
Mowing Roadsides

Cases

Mean (%)

Standard
Deviation
(%)

1214

10.43

31.01

238

2.81

21.72

164

22.93

37.25

168

6.39

22.52

590

0.17

1.57

Table 4.7 Means and Standard Deviations of Time Overrun Rates by Project Type (1994-2009)
4.3.4 Project Ownership
To investigate if project ownership, or source of funding influenced cost overruns and time
delays, contracts were studied by source of funding. For each source of funding, frequency
distributions of cost overrun rates and time delays were graphed, and means and standard
deviations computed. Results are illustrated in the Figures 4.13-4.19.
4.3.4.1 Frequency Distributions of Cost Overrun Rates by Project Ownership

When classified by project ownership, frequency distributions of cost overrun rates varied
with the project type classification. For several sources of funding, most projects had a cost
overrun rate greater than zero. Most contracts funded by Government only had lower rates or no
time overruns.

81

Number of Contracts
0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%
0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

Number of Contracts

Frequencies of Cost Overrun Rates for the African Dev. Bank

6
Frequencies of Cost Overrun Rates for the African Dev. Bank

2

1
1

20

5

4

3

4

5

3
1

Cost Overrun Rates

Figure 4.13 Frequency Distribution of Cost Overrun Rates –
Project Co-Funded by the African Dev. Bank (1994-2009)

Frequencies of Cost Overrun Rates for the European Union
Frequencies of Cost Overrun Rates for the European Union

14

4

1

3

1 1

2

82
1 1 1

2

1

2

1

Cost Overrun Rates

Figure 4.14 Frequency Distribution of Cost Overrun Rates –
Project Co-Funded by the European Union (1994-2009)
1

Frequencies of Cost Overrun Rates for France-AFD
Frequencies of Cost Overrun Rates for France-AFD
Number of Contracts

27

3 4

2

1

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

1

Cost Overrun Rates
Figure 4.15 Frequency Distribution of Cost Overrun Rates –
Project Co-Funded by France – AFD (1994-2009)
Frequencies of Cost Overrun Rates for Islamic Dev. Bank,OPEC
Funds, Koweitian Funds, Saudian Funds

3
2
1

1

1

1

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

Number of Contracts

Frequencies of Cost Overrun Rates for Islamic Dev. Bank,OPEC Funds, Koweitian
Funds, Saudian Funds
6

Cost Overrun Rates
Figure 4.16 Frequency Distribution of Cost Overrun Rates – Project Co-Funded by Islamic Dev.
Bank, OPEC Funds, Koweitian Funds, Saudian Funds (1994-2009)

83

Number of Contracts
0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%
0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

Number of Contracts
89
Frequencies of Cost Overrun Rates for the HIPC Funds
Frequencies of Cost Overrun Rates for the HIPC Funds

7

31
1 1
1
6
1

Cost Overrun Rates

Figure 4.17 Frequency Distribution of Cost Overrun Rates – Project Co-Funded by
HIPC Funds (1994-2009)
Frequencies of Cost Overrun Rates for Total Foreign Aid
Frequencies of Cost Overrun Rates for Total Foreign Aid

145

10 5 3 7 17 6 4
1 3 1 2 1 2 1 1 2

84
2 1

3 1

Cost Overrun Rates

Figure 4.18 Frequency Distribution of Cost Overrun Rates –
Project Co-Funded by Overall Foreign Aid (1994-2009)
2

Frequencies of Cost Overrun Rates for Projects Funded by
Government Only
Frequencies of Cost Overrun Rates for Projects Funded by Government Only

62 27 16 20 24 32 17 14 16 10 6 6 9 6 4 3 2 2 2 2 4

1

1 1 1

0%
0 to 5%
5 to 10%
10 to 15 %
15 to 20%
20 to 25%
25% to 30%
30% to 35%
35 to 40%
40 to 45%
45% to 50%
50 to 55%
55% to 60%
60% to 65%
65% to 70%
70% to 75 %
75% to 80%
80% to 85%
85% to 90%
90% to 95%
95% to 100%
100 to 110%
110 to 120%
120 to 130%
130 to 140%
140 to 150%
150 to 160%
284.18%

Number of Contracts

1494

Cost Overrun Rates
Figure 4.19 Frequency Distribution of Cost Overrun Rates –
Project Funded by Government Only (1994-2009)
4.3.4.2 Summary of Results for Cost Overrun Rates by Project Ownership

Projects funded by HIPC Funds had the lowest mean cost overrun rates, and the European
Union co-funded projects had the highest. Overall, foreign aid projects had higher mean cost
overrun rates than projects funded by government only. The related ratio of means was 2.60.
There were a large number of both government and foreign aid projects in the dataset so that the
computed means can be considered reliable.

85

Cases

Mean (%)

Standard Deviation
(%)

African Dev. Bank

11

13.57

20.66

Belgium
European Union
France-AFD
HIPC Funds
Islamic Dev. Bank(IDB),OPEC
Funds, Koweitian Funds,
Saudian Funds
Total Foreign Aid
Government Only

1
80
38
106

22.68
26.51
8.75
2.27

35.04
28.63
8.44

15

18.9

30.7

251
1782

12.42
4.77

26.62
16.47

Project Ownership

Table 4.8 Means and Standard Deviations of Cost Overrun Rates by
Project Ownership (1994-2009)
4.3.4.3 Frequency Distributions of Time Overrun Rates by Project Ownership

Contracts funded by Government only and HIPC contracts had the largest number of cases
with zero time overruns. On the other extreme, European Union contracts had more time
overruns compared to others. Frequency distributions of time overrun rates by project ownership
are shown in Figures 4.20-4.26.

86

1
1

87
110 to 120%

260 to 270%

231%

216.00%

200% to…

180% to…

170% to…

160 to 170%

140 to 150%

130 to 140%

120 to 130%

1

100 to 110%

90% to 95%

85% to 90%

80% to 85%

75% to 80%

70% to 75 %

65% to 70%

60% to 65%

1

55% to 60%

50 to 55%

45% to 50%

1

40 to 45%

35 to 40%

30% to 35%

25% to 30%

20 to 25%

15 to 20%

10 to 15 %

5 to 10%

0 to 5%

0%

Number of Contracts
6
Frequencies of Time Overrun Rates for the African Dev. Bank
Frequencies of Time Overrun Rates for the African Dev. Bank

Time Overrun Rates
Figure 4.20 Frequency Distribution of Time Overrun Rates – African Dev. Bank Co-Funded Projects (1994-2009)

3
2
1

65% to 70%

88

1

Time Overrun Rates

Figure 4.21 Frequency Distribution of Time Overrun Rates – European Union Co-Funded Projects (1994-2009)
260 to 270%

231%

1
216.00%

200% to 210%

180% to 190%

170% to 180%

160 to 170%

2

140 to 150%

130 to 140%

120 to 130%

110 to 120%

100 to 110%

90% to 95%

3

85% to 90%

80% to 85%

4

75% to 80%

70% to 75 %

1

60% to 65%

50 to 55%
1

55% to 60%

2

45% to 50%

40 to 45%

35 to 40%

2
3

30% to 35%

4

25% to 30%

1

20 to 25%

15 to 20%

10 to 15 %

5 to 10%

0 to 5%

0%

Number of Contracts

Frequencies of Time Overrun Rates for the European Union
Frequencies of Time Overrun Rates for the European Union

22

20

6

1

2
2

89

160 to 170%

140 to 150%

130 to 140%

120 to 130%

110 to 120%

100 to 110%

90% to 95%

85% to 90%

Figure 4.22 Frequency Distribution of Time Overrun Rates – France-AFD Co-Funded Projects (1994-2009)
260 to 270%

231%

216.00%

200% to 210%

180% to 190%

170% to 180%

Time Overrun Rates
80% to 85%

75% to 80%

70% to 75 %

1

65% to 70%

60% to 65%

55% to 60%

50 to 55%

45% to 50%

1

40 to 45%

35 to 40%

1

30% to 35%

25% to 30%

20 to 25%

2

15 to 20%

1

10 to 15 %

5 to 10%

0 to 5%

0%

Number of Contracts

Frequencies of Time Overrun Rates for France-AFD

27
Frequencies of Time Overrun Rates for France-AFD

1

3

5 to 10%

1
2

90
80% to 85%

160 to 170%

140 to 150%

130 to 140%

120 to 130%

110 to 120%

100 to 110%

90% to 95%

Figure 4.23 Frequency Distribution of Time Overrun Rates – HIPC Co-Funded Projects (1994-2009)
260 to 270%

231%

216.00%

200% to 210%

180% to 190%

170% to 180%

Time Overrun Rates
85% to 90%

1

75% to 80%

70% to 75 %

65% to 70%

60% to 65%

55% to 60%

50 to 55%

45% to 50%

40 to 45%

35 to 40%

30% to 35%

25% to 30%

20 to 25%

15 to 20%

10 to 15 %

1

0 to 5%

0%

Number of Contracts

Frequencies of Time Overrun Rates for the HIPC Funds
Frequencies of Time Overrun Rates for the HIPC Funds

89

9

Frequencies of Time Overrun Rates for Islamic Dev. Bank, OPEC Funds, Koweitian Funds,
Saudian Funds
Frequencies of Time Overrun Rates for Islamic Dev. Bank, OPEC Funds, Koweitian Funds, Saudian Funds
3

2

Figure 4.24 Frequency Distribution of Time Overrun Rates – Islamic Dev. Bank,
OPEC Funds, Koweitian Funds, Saudian Funds Co-Funded Projects (1994-2009)

91

260 to 270%

231%

216.00%

200% to 210%

180% to 190%

1

160 to 170%

140 to 150%

1

130 to 140%

120 to 130%

110 to 120%

100 to 110%

90% to 95%

1

2

170% to 180%

Time Overrun Rates

1

85% to 90%

75% to 80%

70% to 75 %

65% to 70%

60% to 65%

55% to 60%

50 to 55%

45% to 50%

40 to 45%

35 to 40%

1

30% to 35%

25% to 30%

20 to 25%

15 to 20%

10 to 15 %

5 to 10%

0 to 5%

0%

1

80% to 85%

Number of Contracts

2

3

10 to 15 %

4
4
4

30% to 35%
35 to 40%
2
2
3

60% to 65%
65% to 70%

11
5
2

92

80% to 85%
85% to 90%

2
1

100 to 110%
110 to 120%
120 to 130%

2
2

140 to 150%
160 to 170%

130 to 140%

1
1
1

200% to 210%
216.00%
260 to 270%

231%

2

180% to 190%

170% to 180%

Time Overrun Rates
90% to 95%

2

75% to 80%

70% to 75 %

1

55% to 60%

50 to 55%

8

45% to 50%

145

40 to 45%

3

25% to 30%

7

20 to 25%

15 to 20%

2

5 to 10%

0 to 5%

0%

Number of Contracts

Frequencies of Time Overrun Rates for Total Foreign Aid

Frequencies of Time Overrun Rates forTotal Foreign Aid

30

1

Figure 4.25 Frequency Distribution of Time Overrun Rates – Project Co-Funded by Overall Foreign Aid (1994-2009)

Frequencies of Time Overrun Rates for Projects Funded by Government Only
Frequencies of Time Overrun Rates for Projects Funded by Government Only

1

2

231%

260 to 270%

216.00%

200% to 210%

180% to 190%

170% to 180%

90% to 95%

5

2

160 to 170%

85% to 90%

3

140 to 150%

80% to 85%

Time Overrun Rates

4

130 to 140%

1 13 15 5

120 to 130%

1

110 to 120%

1

100 to 110%

6

75% to 80%

70% to 75 %

65% to 70%

60% to 65%

55% to 60%

50 to 55%

45% to 50%

40 to 45%

35 to 40%

30% to 35%

25% to 30%

20 to 25%

15 to 20%

10 to 15 %

4 14 2

5 to 10%

0%

47 17 11 12 17 23 39 9 15
2 14 3

0 to 5%

Number of Contracts

1494

Figure 4.26 Frequency Distribution of Time Overrun Rates – Project Funded by Government Only (1994-2009)

93

4.3.4.4 Summary of Results for Time Overrun Rates by Project Ownership
Similarly to the analysis of contracts by project type, the mean time overrun rates were
higher overall when compared to cost overrun rates. However, the trends were different; AFD
projects had the lowest time overrun rates, and IDB related projects had the highest. Globally,
foreign aid projects experienced larger time overrun rates compared to projects funded by
Government only. The corresponding ratio of means is 2.56, which is close to the 2.60 ratio
found above when comparing cost overrun rates for the two types of ownership.
Project Ownership

Cases

Mean (%)

Standard Deviation (%)

African Dev. Bank

11

28.53

43.72

Belgium
European Union
France-AFD
HIPC Funds
Islamic Dev. Bank(IDB),OPEC
Funds, Koweitian Funds,
Saudian Funds
Total Foreign Aid
Government Only

1
80
38
106

18.42
26.49
5.98
7.12

44.83
14.01
19.34

15

93.30

82.12

251
1782

19.26
7.54

41.40
25.90

Table 4.9 Means and Standard Deviations of Time Overrun Rates
by Project Ownership (1994-2009)
4.3.5 Project Size
Project size, measured in monetary value, may have an influence on cost overrun and time
delay rates. This was the third assumption, which was tested by the researcher. Contracts were
classified in six classes from the smallest amounts to the largest ones. Small size contracts,
which had an amount less than 100,000,000 XAF constituted 64.20% of the number of contracts
studied. The number of contracts in each group decreased gradually when project size increased.
The largest contracts, which had an amount greater than five billion XAF, represented 0.67% of

94

the number of contracts studied. For each group, means and standard deviations were calculated,
and linear regression was performed to find the relationship between project size, and cost and
time overrun rates. Results are presented below.
4.3.5.1 Relationship between Project Size and Cost Overrun Rate

No clear relationship could be directly observed between the size of project, in monetary
value and cost overrun rates as shown in Table 4.10. No trend was observed with correlation and
statistical significance for all data. However, the general trend is that cost overrun rates decrease
when project size increases: this relation was observed with statistical significance, for contract
amounts between 100,000,000 XAF and 250,000,000 XAF. These results are presented in Table
4.10 and Figure 4.27. The low mean value for projects under 1000,000,000 XAF might be due to
“mowing projects” which are not generally a part of heavy construction projects.
Because these results did not agree with the literature, which showed cost overruns
increasing along with project size, the researcher conducted testing to determine the relationship
between project size and cost overrun size, and to compare results to the literature.

95

Project Size
(XAF)
Under 100,000,000
100,000,000 –
250,000,000
250,000,000 –
700,000,000
700,000,000–
2,000,000,000
2,000,000,000–
5,000,000,000
Over
5,000,000,000
All

Mean
Linear Regression
Cost
Standard
Cases Overrun
X
R
Level of
Deviation
Rate
Coefficient Square Significance
(%)
1538
2.70
14.05
-1.17E-09
0.0047
0.4742
349

11.79

26.12

-2.5E-09

0.0826

0.0024

293

6.93

16.54

5.57E-11

0.0010

0.7753

164

6.24

13.92

-1.7E-11

0.0010

0.8113

36

4.85

9.57

-1.262E-11

0.0072

0.7458

16

9.17

15.25

5.32E-12

0.4980

0.1832

2396

4.85

16.89

-3.4E-12

0.0012

0.4940

Table 4.10 Project Size and Cost Overrun Rates– Means,
Standard Deviations, and Linear Regressions (1994-2009)

96

Cost Overrun Rates for Projects between 100,000-250,000 - p=0.0024
180.00%
160.00%
140.00%
120.00%
Cost Overrun Rates for
Projects Between 100,000250,000
Linear (Cost Overrun
Rates for Projects Between
100,000-250,000)

100.00%

Cost Overrun Rates

80.00%
60.00%
40.00%
20.00%
0.00%
0.00

100,000.00 200,000.00 300,000.00 Thousands
Project Amount (Size)
Figure 4.27 Scatter plot of the Relationship between
Project Size and Cost Overrun Rate (110 cases, 1994-2009)

4.3.5.2 Relationship between Project Size and Cost Overrun Size Expressed in Monetary Value

It was observed that means of the size of cost overruns increased when project size increased.
Overall, linear regressions confirmed this relationship and were statistically significant, except
for project sizes between 100,000,000 XAF and 250,000,000 XAF, which showed a different
trend. However, this later group had the lowest significance level. It was therefore inferred that
cost overrun size, expressed in monetary value, increased along with project size.
In conclusion, this analysis suggests that the cost overrun rate and the cost overrun size for a
project are distinct, and the relationship between them will vary. Table 4.11 and Figure 4.28
summarize the analysis.

97

Linear Regression
X
R
Level of
Coefficient Square Significance

Cases

Standard
Deviation

1,565.00

8,083.27

0.3117

0.1042

0.0005

349

17,477.00

37,661.43

-0.0711

0.0035

0.5398

293

29,154.20

71,467.50

0.2620

0.1109

0.0015

164

65,488.61

160,973.25

0.1148

0.0298

0.1914

36

151,602.40

300,598.10

0.1228

0.0746

0.2728

16

2,433,592.5

6,578,859.00

0.4847

0.9930

1.847E-05

2396

Under
100,000,000
100,000,000 –
250,000,000
250,000,000 –
700,000,000
700,000,000 –
2,000,000,000
2,000,000,000–
5,000,000,000
Over
5,000,000,000
All

Mean Cost
Overrun
Size (XAF)

1538

Project Size
(XAF)

30,126.53

560,780.10

0.4080

0.9383

2.815E-239

Table 4.11 Project Size and Cost Overrun Size–
Means, Standard Deviations, and Linear Regressions

Cost Overruns in Monetary Value (XAF) - p=1.847E-05
1,600,000,000.00
1,400,000,000.00
1,200,000,000.00
Cost Overrun Rates

1,000,000,000.00
Cost Overruns in
Monetary Value
(XAF)

800,000,000.00
600,000,000.00
400,000,000.00
200,000,000.00
0.00
0.00

2,000,000,000.00 4,000,000,000.00
Project Amount (Size)

Figure 4.28 Project Size and Cost Overrun Size – Linear Regression (376 cases, 1994-2009)

98

4.3.5.3 Relationship between Project Size and Time Overrun Rate
The relationship between project size and time overrun rate was investigated. Means,
standard deviations and linear regression were performed for each category of project size.
However, there was no obvious inference from the analysis. Only the group of contracts between
two and five billion XAF showed that time overrun rate decreased when project size increased,
with statistical significance. The results are shown in Table 4.12 and Figure 4.29.

Cases

Project Size
(XAF)
Under
100,000,000
100,000,000 –
250,000,000
250,000,000 –
700,000,000
700,000,000 –
2,000,000,000
2,000,000,000–
5,000,000,000
Over
5,000,000,000
All

Mean
Time
Overrun
Rate (%)

Linear Regression
Standard
Deviation

1538

3.59

349

X
Coefficient

R square

Level of
Significance

18.45

-2.5E-09

0.0128

0.2326

17.28

39.49

2.03E-09

0.0236

0.1090

293

13.32

32.01

-4.5E-10

0.0171

0.2246

164

9.51

24.17

7.69E-11

0.0058

0.5675

36

23.93

51.90

-3.4E-10

0.1852

0.0746

16

24.45

52.92

-8.6E-14

5.882E-06

0.9964

2396

7.62

26.47

1.4E-12

8.468E-05

0.8556

Table 4.12 Project Size and Time Overrun Rate –
Means, Standard Deviations, and Linear Regressions (1994-2009)

99

Time Overrun Rates for Projects between 2,000,000,000 and
5,000,000,000 - p=0.0746
200.00%

Time Overrun Rates for
Projects Between
2,000,000,000 and
5,000,000,000
Linear (Time Overrun
Rates for Projects Between
2,000,000,000 and
5,000,000,000 )

Time Overrun Rates

150.00%
100.00%
50.00%
0.00%
0.00
-50.00%

2,000,000.00
4,000,000.00
Project Amount (Size)

6,000,000.00 Thousands

Figure 4.29 Scatter plot of the Relationship between Project Size and Time Overrun Rate for
Contract Amounts between Two and Five Billion XAF (18 cases, 1994-2009)

4.3.6 Project Duration
The last project characteristic investigated in this study was project duration. For this
analysis, contracts were broken down in five groups ranging from contracts with short durations,
under six months, to contracts with durations greater than 36 months. Most of the projects in the
database had durations less than twelve months. Only eleven contracts in the study had durations
greater than 36 months.
4.3.6.1 Relationship between Project Duration and Cost Overrun Rate

The linear regression for all project durations suggests that cost overrun rates decrease when
project durations increase, with statistical significance. However, the opposite trend is observed
for project durations under six months, between six and twelve months and over 36 months; this
trend was rejected because of the very poor associated level of significance. Details are shown in
Table 4.13 below, and the scatter plot in Figure 4.30 illustrates the relationship between project
duration and cost overrun rate for contract durations between 24 and 36 months.

100

Project
Duration in
Months
Under 6
Months
6 Months 12 Months
12 Months 24 Months
24 Months 36 Months
Over 36
Months
All

Cases

Mean
Cost
Standard
X
Overrun
Deviation Coefficient
Rate
(%)

R Square

Level of
Significance

676

3.26

17.06

0.010214

0.0008489

0.8251

644

9.45

22.01

0.000193

7.158E-07

0.9907

325

4.38

13.88

-0.01007

0.0068302

0.5642

377

4.80

15.24

-0.01594

0.0542447

0.0320

11

10.97

16.51

0.002748

0.0091611

0.8569

2033

5.73

18.22

-0.00434

0.0273126

0.0010

Table 4.13 Cost Overrun Rates Classified by Project DurationMeans, Standard Deviations, Linear Regressions (1994-2009)

180.00%

Cost Overrun Rates for Project Duration between 24 and 36 Months p=0.0320

160.00%

Cost Overrun Rates

140.00%
Cost Overrun Rates for
Project Durations Between
24 and 36 Months

120.00%
100.00%
80.00%

Linear (Cost Overrun
Rates for Project
Durations Between 24 and
36 Months)

60.00%
40.00%
20.00%
0.00%
0.00

10.00
20.00
30.00
Project Duration (Months)

40.00

Figure 4.30 Scatter plot of the Relationship between Project Duration and Cost Overrun Rate for
Contract Durations between 24 and 36 Months (85 cases, 1994-2009)

101

4.3.6.2 Relationship between Project Duration and Time Overrun Rate
It was observed that there was a strong relationship between project duration and time
overrun rate, with high statistical significance. For all groups of project durations, the time
overrun rate decreased when the project duration increased. Table 4.14 and Figure 4.31 below
illustrate this relationship.
Project
Duration in
Months
Under 6 Months
6 Months - 12
Months
12 Months - 24
Months
24 Months - 36
Months
Over 36 Months
All

Mean
Time
Cases
Overrun
Rate (%)
676
6.47

Standard
Deviation

X
Coefficient

R
Square

Level of
Significance

25.87

-0.0620

0.0238

0.2388

644

17.17

39.17

-0.0489

0.0150

0.0910

325

3.86

13.33

-0.0856

0.0067

0.5681

377

3.80

15.34

-0.0244

0.1043

0.0026

11
2033

13.17
8.98

17.29
28.53

-0.0021
-0.0155

0.0060
0.1420

0.8846
1.052E-14

Table 4.14 Time Overrun Rates Classified by Project DurationMeans, Standard Deviations, Linear Regressions (1994-2009)

102

Time Overrun Rates for Project Duration between 6 and 12 Months p=0.0910

300.00%
250.00%

Time Overrun Rates for
Project Durations Between
6 and 12 Months

Time Overrun Rates

200.00%
150.00%

Linear (Time Overrun
Rates for Project
Durations Between 6 and
12 Months)

100.00%
50.00%
0.00%
0

5
10
Project Duration (Months)

15

Figure 4.31 Scatter plot of the Relationship between Project Duration and Time Overrun Rate for
Contract Durations between 6 and 12 Months (192 cases, 1994-2009)

4.3.7 Relationship between the Time Delay Rate and the Cost Overrun Rate
A regression analysis was performed to study the relationship between the time overrun rate
as the dependent variable, and the cost overrun rate as the independent variable. A positive trend
was observed with high significance: the cost overrun rate increased along with the time overrun
rate. The p-value, p=5.99773E-06 showed a high significance for the relationship. The summary
output of the linear regression is presented in Table 4.15 and Figure 4.32.

103

SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.22581
R Square
0.05099
Adjusted R
Square
0.04857
Standard Error
0.31013
Observations
394
ANOVA
df
Regression
Residual
Total

1
392
393
Coefficients

Intercept
X Variable 1

0.22866
0.14442

Significance
SS
MS
F
F
2.025665 2.02566497 21.061265 5.99773E-06
37.70242 0.09617964
39.728085
Standard
t Stat
P-value
Lower 95% Upper 95%
Error
0.0213758 10.6970181 1.328E-23 0.186631406 0.27068235
0.0314702 4.5892554 5.998E-06 0.08255326 0.20629618

Lower
90.0%
0.2
0.1

Upper 90.0%
0.263900159
0.196311188

Table 4.15 Linear Regression Results of the Relationship between Cost Overrun Rates and Time Overrun Rates

104

Relationship between Cost Overrun Rates and Time Overrun Rates p=5.998E-06

300.00%

Relationship Between
Cost Overrun Rates and
Time Overrun Rates

250.00%
200.00%

Linear (Relationship
Between Cost Overrun
Rates and Time Overrun
Rates)

Cost Overrun Rates

150.00%
100.00%
50.00%
0.00%
0.00%

100.00%
200.00%
Time Overrun Rates

300.00%

Figure 4.32 Illustration of the Relationship between the
Time Overrun Rate and the Cost Overrun Rate (394 cases, 1994-2009)

4.4 Summary Analysis of Cost Overruns
Section 4.3 presented a detailed analysis of cost overruns, studied for the contracts in the
database. A summary analysis provided global results with contracts first aggregated by project
type, and secondly by project ownership or project portfolio.
4.4.1 Summary of Cost Overruns by Project Type
For each project type, the overall cost overrun rate is the ratio between total cost overruns
and total contract amounts for the period of study. Table 4.16 presents the results of this
synthesis, which are also illustrated in Figure 4.32. Work supervision had the highest cost
overrun rate, and mowing roadsides had the smallest.

105

Type
Road
Construction/Maintenance
Work Supervision
Bridges and Structures
Design/Technical Studies,
Technical Assistance
Mowing Roadsides

Overall Cost
Total
Amounts
Total Cost
Overrun Rates by
(XAF)
Overruns (XAF) Project Type for the
Period of Study
545,472,244,192.0 57,294,182,778.0
10.50%
0
0
12,237,193,407.0
48,700,487,193.00
25.13%
0
41,394,727,818.00
560,974,087.00
1.36%
17,517,937,055.00

1,196,632,317.00

6.83%

14,700,432,431.00

168,701,672.00

1.15%

Table 4.16 Overall Cost Overruns by Project Type for the Period of Study (1994-2009)

106

Overall Cost Overrun Rates by Project Type for the Period of Study
Overall Cost Overrun Rates by Project Type
25.13%

10.50%
6.83%

1.36%

1.15%

Figure 4.33 Overall Cost Overruns by Project Type for the Period of Study (1994-2009)
107

4.4.2 Summary of Cost Overruns by Project Portfolio
Table 4.17 and Figure 4.34 below summarize the cost overrun rates by project portfolio for
the period of study. The Government project portfolio had the lowest percent cost overrun. The
highest cost overrun rates were related to the African Development Bank and the European
Union portfolios.

Portfolio Cost Overrun Rates
Organization
European Union
Government Only
African Dev. Bank
France-AFD
Islamic Dev. Bank(IDB),OPEC
Funds, Koweitian Funds,
Saudian Funds
HIPC Funds
Belgium

Total Contract
Amounts

Total Cost
Overruns

111,517,937,606.00
310,890,418,836.00
16,443,708,799.00
42,618,056,497.00

32,874,738,136.00
17,582,747,825.24
5,371,590,630.00
2,661,161,150.00

Portfolio
Percent Cost
Overruns
29.48%
5.66%
32.67%
6.24%

83,409,197,507.00

6,921,239,748.00

8.30%

32,697,173,970.00
4,591,066,091.00

3,003,433,571.00
1,041,149,412.00

9.19%
22.68%

Table 4.17 Project Portfolio Cost Overruns (1994-2009)

108

Project Portfolio Cost Overruns for the Period of Study
Project Portflio Cost Overruns
32.67%
29.48%
22.68%

8.30%
5.66%

European
Union(80
Contracts)

Government
Only(1782
Contracts)

African Dev. France-AFD
Bank(11
(38
Contracts)
Contracts)

9.19%

6.24%

IDB,OPEC
Funds,
Koweitian
Funds,
Saudian
Funds(15
Contracts)

HIPC
Funds(106
Contracts)

Belgium( 1
Contract)

Figure 4.34 Portfolio Project Cost Overruns for the Period of Study (1994-2009)

109

4.4.3 Evolution of Cost Overruns During the Period of Study
Contracts were aggregated by project type, and cost overrun rates were broken down year by
year to scrutinize the evolution of cost overrun rates for the period of study. Only years with cost
overrun data were considered for this analysis. Table 4.18 and Figure 4.35 show the cost overrun
rates by year and project type.
Year
(Period)
Overall Cost
Overruns

19971999
6.69
%

Work
Supervision
Road
Construction
and
maintenance
Bridges and
Structures
Design/
Technical
Studies,
Technical
Assistance
Mowing
Roadsides

992000

200102

2003

2004

2005

2006

2007-08

8.29%

20.67% 19.90%

8.47%

8.93%

2.19%

2.84%

69.63
%

33.87
%

34.92% 36.58%

3.11%

18.95
%

5.85%

13.33%

2.52
%

7.14%

20.04% 27.21%

9.19%

8.98%

2.17%

2.80%

-

41.40
%

1.01%

0.00%

8.84%

2.81%

0.05%

0.00%

-

8.28%

11.08%

0.00%

14.99%

1.28%

0.00%

4.66%

-

2.06%

2.90%

0.00%

0.15%

0.42%

0.00%

-

Table 4.18 Evolution of Overall Project Cost Overruns for the Period of Study (1994-2009)

110

Evolution of Overall Project Cost Overrun Rates
80.00%
70.00%
60.00%

Percent Overrun

Overall Cost Overrun Rates
50.00%

Road Construction and
maintenance

40.00%

Work Supervision

30.00%

Bridges and Structures

20.00%

Design/Technical Studies,
Technical Assistance
Mowing Roadsides

10.00%
0.00%

Figure 4.35 Comparison of Cost Overruns by Project Type over the Period of Study (1994-2009)

111

Many reasons could explain the variations observed year after year for cost overrun rates
such as:


Improvement in the management at MINTP



Institutional reforms in Cameroon such as the adoption of a public contract code in 2004.

This new code limits cost overruns to 30% of the initial contract amount. Before 2004, higher
cost overrun rates were observed. However, with the application of this new code fewer projects
were implemented, because of lengthy processes.

112

4.5 Contractor Familiarity with the Ministry
No evidence could be found between contractor familiarity with the Ministry and change
orders. To study if the more contractors worked with the ministry, the more they received change
orders, a regression model was prepared. For each contractor with a change order impacting cost
or time in the database, the number of years for which they received at least one change order
was sought. It was found that the majority of contractors received one or more change orders
during one year only. The quantity of change orders received ranged from one for most of the
contractors to 25 for one of the consultant firms.
For constructors, 106 received their change order(s) in a single year for the lowest frequency,
and one constructor received at least one change order per year, during eight years. Fourteen
consultants received their change order(s), only in one year, and two consultants repeatedly
received change order(s) for nine years. Table 4.19 and Figure 4.36 illustrate the results.
Number of
Years at least
one Change
1
2
3
4
5
6
7
8
9
order was
Year Years Years Years Years Years Years Years Years
received over
the period of
Study
Frequency of
106
44
9
7
2
5
2
1
0
Constructors
Frequency of
14
4
4
3
1
0
0
0
2
Consultants
Table 4.19 Frequency of Change Orders for Contractors

113

Frequencies of Constructors and Consultants Who Had Change Orders

Frequency of Constructors

Frequency of Consultants

Number of Contractors

106

44

14
9
4
1

2

4
3

7

3
4

2 1

5

5
6
Number of Years

0

2 0

1 0

0 2

7

8

9

Figure 4.36 Frequencies of Constructors and Consultants with
Change Orders and Number of Years

4.6 Comparison with Other Countries
Table 4.20 was developed and shown below in order to compare cost overrun rates obtained
for Cameroon from the contract data analysis, and others in the world as indicated in the
literature.

114

Region

Project type

Road
Construction/Maintenance
Work Supervision
Cameroon
(This
Bridges and Structures
Research)
Design/Technical Studies,
Technical Assistance
Mowing Roadsides
Rail
Europe
Fixed links
Roads
Rail
North America Fixed links
Roads
Highways:
New construction
USA (State of
Resurfacing
Washington)
Bridge only
Safety Improvement

South Korea

Period
covered by
the study

Average cost
overrun rate (%)*

Author(s)

5.50(10.43)
1997-2007

21.23(22.93)
1.69(2.81)
4.13(6.39)

1927-1998

1985-1989

0.67(0.17)
34.2
43.4
22.4
40.8
25.7
8.4
9.23
3.90
8.20
2.98
Avrg.

Bella Akoa
(This
Research)

Flyvbjerg et
al(2003)

Hinze and
Selstead
(1991)

Min.
Max.
Roads
<0
10.7
85
**
Jin-Kyung,
1985-2005
Rails
<0
47.64 65.34
L. (2008)
Airports
16.2 60.4 64.5
Ports
8.3
36.3 182.5
(*) Time overrun rates are shown in parenthesis for Cameroon
(**) <0 means cost underruns
Table 4.20 Comparison between Cost Overrun Rates in Cameroon
and Other Regions and Countries

Road construction and maintenance projects in Cameroon had a lower average cost overrun
rate, when compared to North America and South Korea, which were all close to 10%. Bridges
and structures in Cameroon had a low rate too, probably because most of the related projects
were maintenance projects. Other studies did not present cost overruns for consultancy projects,
which were considered in the case of Cameroon and had the highest cost overrun rate for work
supervision. Chapter Six incorporates the results of the contract data analysis into
recommendations and guidelines for measures to reduce cost and time overruns.
115

4.7 Chapter Summary
This study confirmed that cost overruns and time delays depend on many factors such as
project type, project ownership, project size and project duration. In addition, cost overrun rates
and time overall are related, the first increases along with the second.
Contractor familiarity with the ministry was not proven to be determinant for cost and time
overruns. However, compared to other studies, the difference was that small projects had greater
overrun percent rates or relative overrun values, compared to larger ones with various
significance levels. Furthermore, in absolute values or in monetary amount, cost overruns
increased with project size, with high significance. Odeck (2004) also found that small projects
had more cost overruns compared to larger ones in Norway. However, Frisby (1989) found both
cost and schedule overruns growing in percent and absolute values with project size.
Table 4.21 summarizes the results of Chapter 4. Project characteristics are ranked in
descending order of cost overrun rates. Project characteristics with the largest overruns were
given priority in establishing guidelines for reducing cost overruns and time delays.
Some key findings were that work supervision had the highest cost overrun rate, projects
funded by donors experienced larger cost overrun rates. Small projects showed the lowest cost
overrun rates, and large projects had larger cost overrun rates. Project amounts between
100,000,000 and 250,000,000 XAF had the highest cost overrun rates, and projects with the
largest durations had the largest cost overrun rates.

116

Project Type

Project
Ownership

Project Size

Project
Duration

Average Cost
Overrun Rate (%)
21.23

Average Time
Overrun Rate (%)
22.93

5.50

10.43

4.13

6.39

1.69

2.81

Mowing Roadsides

Factors

0.67

0.17

European Union
Islamic Dev.
Bank(IDB),OPEC Funds,
Koweitian Funds, Saudian
Funds
African Dev. Bank
France-AFD
Government Only
HIPC Funds
Between 100,000,000 –
250,000,000 XAF
Over 5,000,000,000XAF
Between 250,000,000 –
700,000,000XAF
Between 700,000,000 –
2,000,000,000XAF
Between 2,000,000,000 –
5,000,000,000XAF
Under 100,000,000
Over 36 Months
Between 6 Months - 12
Months
Between 24 Months - 36
Months
Between 12 Months - 24
Months
Under 6 Months

26.51

26.49

18.9

93.30

13.57
8.75
4.77
2.27

28.53
5.98
7.54
7.12

11.79

17.28

9.17

24.45

6.93

13.32

6.24

9.51

4.85

23.93

2.70
10.97

3.59
13.17

9.45

17.17

4.80

3.80

4.38

3.86

3.26

6.47

Characteristics
Work Supervision
Road
Construction/Maintenance
Design/Technical Studies,
Technical Assistance
Bridges & Structures

Table 4.21 Summary of Cost and Time Overrun Rates by Project Categories (1994-2009)

117

CHAPTER 5
SURVEY ANALYSIS

118

5.1 Introduction
A survey of the professionals who were involved in project development of the contracts
analyzed in Chapter Four was conducted to help identify sources of cost overruns and time
delays. Limited information in the contract files did not allow for determination of causes
directly. This chapter reports the results of the survey.
5.2 Data Reporting
The survey was completed in 2011 in the city of Yaounde, Cameroon. Response rates for the
survey are presented in table 5.1 below.
Number of Questionnaires Sent
Non Response
Incomplete Responses
Completed Questionnaires
Total Valid Responses
Overall Response Rate

100
4
12
84
84
84%

Table 5.1 Response Rate for the Survey
Valid responses were analyzed using the Statistical Package for the Social Sciences (SPSS).
Response frequencies for each variable were determined. Examples of the SPSS frequency tables
are presented in Appendix 5. To study the stratification of respondents, depending upon their
sector and profession in the field of construction, a SPSS cross-tabulation analysis using both
variables was performed and results are shown in Table 5.2.

119

Sector * Profession Cross-tabulation
Profession
Accountant Engineer Manager
Sector(*) Consul- Count
tant
% within Sector

0

7

.0%

77.8%

% within
Profession

.0%

11.9%

% of Total

.0%

1

Other
1

Total
9

11.1% 11.1% 100.0%

8.3%

1.2%

1.2%

10.7%

0

6

3

0

9

% within Sector

.0%

66.7%

33.3%

.0% 100.0%

.0%

10.2%

16.7%

.0%

10.7%

% of Total

.0%

7.1%

3.6%

.0%

10.7%

0

2

1

2

5

% within Sector

.0%

40.0%

% within
Profession

.0%

3.4%

5.6% 66.7%

6.0%

% of Total

.0%

2.4%

1.2%

2.4%

6.0%

2

0

0

0

2

100.0%

.0%

.0%

.0% 100.0%

% within
Profession

50.0%

.0%

.0%

.0%

2.4%

% of Total

Donor

10.7%

% within
Profession

Constructor

5.6% 33.3%

2.4%

.0%

.0%

.0%

2.4%

2

44

13

0

59

3.4%

74.6%

22.0%

.0% 100.0%

50.0%

74.6%

72.2%

.0%

Count

Count

Finance Count
% within Sector

Govern- Count
ment
% within Sector
% within
Profession

% of Total
2.4%
52.4%
Total
Count
4
59
% within Sector
4.8%
70.2%
% within
100.0% 100.0%
Profession
% of Total
4.8%
70.2%
(*) Refer to Table 3.4 for the Definition of Variables

20.0% 40.0% 100.0%

15.5%
.0% 70.2%
18
3
84
21.4% 3.6% 100.0%
100.0% 100.0% 100.0%
21.4%

3.6% 100.0%

Table 5.2 Cross-tabulation of the Sector and Profession Variables
120

70.2%

For the construction sector, the majority (22.2%) of respondents were government employees
followed by constructors (10.7%), and consultants (10.7%). Engineers and managers constituted
the largest professional segments surveyed at 70.2% and 21.4% respectively. These sectors and
professions influenced the results because they made up a large number of the respondents.
5.3 Overall Responses
Respondent frequencies were reported for factors found in the literature to find its influence
on cost overruns and time delays according to survey respondents (refer to Chapter 3 for a
discussion of the factors). For the purpose of ranking, the respondent frequencies for “Strongly
Agree” and “Agree” were summed for each factor. The score was used to classify the factors
from the most critical, with the highest score, to the least critical, which recorded the lowest
score. The most critical causes of cost overruns and time delays are shown in table 5.3 below;
“Negligence of Site Visits Before/During the Bidding Process- Unknown Site Conditions” was
identified most frequently (61 respondents) as a cause of cost overruns and time delays.

121

1Strongly
Agree

2Agree

29
(34.52%)

32
(38.10%)

12
(14.29%
)

31
(36.90%)

28
(33.33%)

8
(9.52%)

22
(26.19%)

35
(41.67%)

10
(11.90%
)

18
(21.43%)

39
(46.43%)

17
(20.24%
)

Lack of Equipment

29
(34.52%)

26
(30.95%)

Bidding Procedures

27
(32.14%)

28
(33.33%)

Duration of the
Period of Bidding

26
(30.95%)

28
(33.33%)

Material Price
Fluctuation

19
(22.62%)

35
(41.67%)

Negligence of Past
Experiences

25
(29.76%)

28
(33.33%)

The Lowest Bid Price 28
System
(33.33%)

23
(27.38%)

Factors

Negligence of Site
Visits Before/During
the Bidding ProcessUnknown Site
Conditions.
Weak and
insufficient technical
studies
Lack of Project
Planning/Programming
Underestimating of
cost estimates and
schedules/
Overestimating of
Benefits

534Strongly
Neither Disagree
Disagree

20
(23.81%
)
13
(15.48%
)
14
(16.67%
)
14
(16.67%
)
18
(21.43%
)
14
(16.67%
)

8
(9.52%)

3
(3.57%)*

61

1
(1.19%)

59

1
(1.19%)

57

8
(9.52%)

2
(2.38%)

57

6(7.14%
)

3
(3.57%)

55

3
(3.57%)

55

3
(3.57%)

54

2
(2.38%)

54

0
(0.00%)

53

4
(4.76%)

51

16
(19.05%
)
16
(19.05%
)

13
(15.48%
)
13
(15.48%
)
14
(16.67%
)
13
(15.48%
)
15
(17.86%
)

(*) Percentage of respondents
Table 5.3 Prioritization of Survey Factors by the Sum of Respondents
Who “Strongly Agreed” and “Agreed”

122

Respondents
"Agreeing
"&
“Strongly
Agreeing”

Table 5.3 Prioritization of Survey Factors by the Sum of Respondents
Who “Strongly Agreed” and “Agreed” (Cont’d)

Factors

1Strongly
Agree

2Agree

3Neither

Methods of Payment

23
(27.38%)

28
(33.33%)

15
(17.86%)

Inadequate Project
Planning/Programming

15
(17.86%)

36
(42.86%)

14
(16.67%)

The Displacement of
Existing Networks

11
(13.10%)

40
(47.62%)

22
(26.19%)

Poor project
implementation
strategies

17
(20.24%)

33
(39.29%)

18
(21.43%)

Changes in Scope of
Contracts

10
(11.90%)

39
(46.43%)

16
(19.05%)

12
(14.29%)

35
(41.67%)

20
(23.81%)

13
(15.48%)

33
(39.29%)

18
(21.43%)

12
(14.29%)

34
(40.48%)

21
(25.00%)

8
(9.52%)

38
(45.24%)

25
(29.76%)

14
(16.67%)

30
(35.71%)

19
(22.62%)

6
(7.14%)

38
(45.24%)

24
(28.57%)

Poor
Communication
Among Contract
Stakeholders
Unreasonable
adjustment of project
cost by contractors
Lack of Contract ex
post Evaluation
Weaknesses during
the land takings
process
Supervisor and
Contractor Claims
and Disputes
Construction Errors
and On Site Testing
Approval

123

Respondents
54"Agreeing"
Strongly
Disagree
&
Disagree
“Strongly
Agreeing”
16
2
(19.05%
51
(2.38%)
)
17
2
(20.24%
51
(2.38%)
)
11
0
(13.10%
51
(0.00%)
)
16
0
(19.05%
50
(0.00%)
)
16
3
(19.05%
49
(3.57%)
)
15
(17.86%
)
19
(22.62%
)
15
(17.86%
)
12
(14.29%
)
20
(23.81%
)
14
(16.67%
)

2
(2.38%)

47

1
(1.19%)

46

2
(2.38%)

46

1
(1.19%)

46

1
(1.19%)

44

2
(2.38%)

44

Table 5.3 Prioritization of Survey Factors by the Sum of Respondents
Who “Strongly Agreed” and “Agreed” (Cont’d)

Factors

Many Stakeholders
Weather Conditions
Unethical Activities
And Kickbacks
No Action Taken
After Contract
Progress Reports
Mistakes and
discrepancies in
documents
Expropriation costs
Shortages of
Materials
Mismanagement
Due to
Inexperienced
Supervisors.
Periods of
Inspection and
Testing After
Contract Completion
Political
Tensions/Insecurity
Equivocal/Unclear
Contracts
Building on
unexpected
archaeological sites
Legal environmental
requirements

1Strongly
Agree

2Agree

3Neither

12
(14.29%)
11
(13.10%)
13
(15.48%)

31
(36.90%)
32
(38.10%)
28
(33.33%)

19
(22.62%)
18
(21.43%)
27
(32.14%)

Respondents
54"Agreeing"
Strongly
Disagree
&
Disagree
“Strongly
Agreeing”
19(22.62 3
43
%)
(3.57%)
21(25.00 2
43
%)
(2.38%)
14(16.67 2
41
%)
(2.38%)

9
(10.71%)

32
(38.10%)

26
(30.95%)

11(13.10 6
%)
(7.14%)

41

12
(14.29%)

25
(29.76%)

21
(25.00%)

24(28.57 2
%)
(2.38%)

37

10
(11.90%)
7
(8.33%)

24
(28.57%)
27
(32.14%)

29
(34.52%)
19
(22.62%)

15(17.86
%)
27(32.14
%)

2
(2.38%)

32
(38.10%)

24
(28.57%)

23(27.38 3
%)
(3.57%)

34

9
(10.71%)

21
(25.00%)

31
(36.90%)

19(22.62 4
%)
(4.76%)

30

8
(9.52%)
3
(3.57%)

19
(22.62%)
24
(28.57%)

14
(16.67%)
20
(23.81%)

29(34.52
%)
31(36.90
%)

10
(11.90%)

13
(11.90%)

33
(39.29%)

22(26.19 6
%)
(7.14%)

23

4
(4.76%)

19
(22.62%)

27
(32.14%)

32(38.10 2
%)
(2.38%)

23

124

6
(7.14%)
4
(4.76%)

14(16.67
%)
6
(7.14%)

34
34

27
27

Cross-tabulations were performed to analyze the scoring for “Negligence of Site Visits
Before/During the Bidding Process- Unknown Site Conditions” by sector, and then by profession
as shown below.
5.4 Cross-Tabulation between the Sector and the Factor “Negligence of Site Visits
Before/During the Bidding Process- Unknown Site Conditions”
Table 5.4 below shows that the factor “Negligence of Site Visits Before/During the Bidding
Process- Unknown Site Conditions” 72.6% of all respondents agreed (38.1%) and strongly
agreed (34.5%) that this factor was a cause of cost overruns and time delays. This scoring was
broken down by sectors as follows: 78% of respondents in government, 80% for donors, 88.8%
for constructors, 33.3% for consultants, and 0% for respondents in the finance sector. The low
result for the finance sector was probably due to the limited number of participants from this
sector, only two respondents. Overall, it was inferred that all sectors agreed that this factor is a
cause of cost overruns and time delays.

125

Negligence_Site_visits
1:
5:
2:
3:
4:
Strongly
Strongly
Agree Neither Disagree
Agree
Disagree
Sec Cons Count
2
1
3
tor
% within Sector
22.2% 11.1% 33.3%
% within
6.9% 3.1% 25.0%
Negligence_Site_visits
% of Total
2.4% 1.2%
3.6%
Cont Count
4
4
1
% within Sector
44.4% 44.4% 11.1%
% within
13.8% 12.5%
8.3%
Negligence_Site_visits
% of Total
4.8% 4.8%
1.2%
Dono Count
2
2
1
% within Sector
40.0% 40.0% 20.0%
% within
6.9% 6.3%
8.3%
Negligence_Site_visits
% of Total
2.4% 2.4%
1.2%
Fina Count
0
0
1
% within Sector
.0% .0% 50.0%
% within
.0% .0%
8.3%
Negligence_Site_visits
% of Total
.0% .0%
1.2%
Gove Count
21
25
6
% within Sector
35.6% 42.4% 10.2%
% within
72.4% 78.1% 50.0%
Negligence_Site_visits
% of Total
25.0% 29.8%
7.1%
Total Count
29
32
12
% within Sector
34.5% 38.1% 14.3%
% within
100.0% 100.0 100.0%
Negligence_Site_visits
%
% of Total
34.5% 38.1% 14.3%

Total

3
33.3%
37.5%

0
9
.0% 100.0%
.0% 10.7%

3.6%
0
.0%
.0%

.0% 10.7%
0
9
.0% 100.0%
.0% 10.7%

.0%
0
.0%
.0%

.0% 10.7%
0
5
.0% 100.0%
.0%
6.0%

.0%
1
50.0%
12.5%

.0%
6.0%
0
2
.0% 100.0%
.0%
2.4%

1.2%
4
6.8%
50.0%

.0%
2.4%
3
59
5.1% 100.0%
100.0% 70.2%

4.8%
8
9.5%
100.0%

3.6% 70.2%
3
84
3.6% 100.0%
100.0% 100.0%

9.5%

3.6% 100.0%

Table 5.4 Cross-tabulation of the variable Sector and the Factor “Negligence of Site Visits
Before/During the Bidding Process- Unknown Site Conditions”

126

Table 5.5 provides the Lambda and Goodman and Kruskal tau, for the cross-tabulation
above; their weak values suggest a weak relationship between the two variables. The sector did
not influence the responses for the “Negligence_Site_visits” variable.
Value
Nominal by
Nominal

Lambda

Goodman and Kruskal
tau

Symmetric
Sector Dependent
Negligence_Site_visits
Dependent
Sector Dependent
Negligence_Site_visits
Dependent

Asymp. Std.
Errora

.039
.000
.058

.052
.000
.077

.068
.056

.039
.021

a. Not assuming the null hypothesis.
Table 5.5 Directional Measures for the Cross-tabulation Between the Sector and the factor
“Negligence of Site Visits Before/During the Bidding Process- Unknown Site Conditions”
5.5 Cross-Tabulation between Profession and the Factor “Negligence of Site Visits
Before/During the Bidding Process- Unknown Site Conditions”
Among the respondents who strongly agreed and agreed that the factor “Negligence of Site
Visits Before/During the Bidding Process- Unknown Site Conditions” was a cause of cost
overruns and time delays, were 72.9% of engineers, 77.8% of managers, 50% of accountants,
and 66.6% of others. The majority of all professions considered this factor to be critical for cost
overruns and time delays. The cross-tabulation by profession is shown in Table 5.6.

127

Negligence_Site_visits
1:
5:
2:
3:
4:
Strongly
Strongly
Agree Neither Disagree
Agree
Disagree
Profes Acc Count
2
0
1
sion
% within Profession
50.0% .0% 25.0%
% within
6.9% .0% 8.3%
Negligence_Site_visits
% of Total
2.4% .0% 1.2%
Eng Count
22
21
6
% within Profession
37.3% 35.6% 10.2%
% within
75.9% 65.6% 50.0%
Negligence_Site_visits
% of Total
26.2% 25.0% 7.1%
Man Count
4
10
4
% within Profession
22.2% 55.6% 22.2%
% within
13.8% 31.3% 33.3%
Negligence_Site_visits
% of Total
4.8% 11.9% 4.8%
Oth Count
1
1
1
% within Profession
33.3% 33.3% 33.3%
% within
3.4% 3.1% 8.3%
Negligence_Site_visits
% of Total
1.2% 1.2% 1.2%
Total
Count
29
32
12
% within Profession
34.5% 38.1% 14.3%
% within
100.0% 100.0 100.0%
Negligence_Site_visits
%
% of Total
34.5% 38.1% 14.3%

Total

1
25.0%
12.5%

0
.0%
.0%

4
100.0%
4.8%

1.2%
7
11.9%
87.5%

.0%
3
5.1%
100.0%

4.8%
59
100.0%
70.2%

8.3%
0
.0%
.0%

3.6%
0
.0%
.0%

70.2%
18
100.0%
21.4%

.0%
0
.0%
.0%

.0%
0
.0%
.0%

21.4%
3
100.0%
3.6%

.0%
8
9.5%
100.0%

.0%
3
3.6%
100.0%

3.6%
84
100.0%
100.0%

9.5%

3.6%

100.0%

Table 5.6 Cross-tabulation of the Profession and the Factor “Negligence of Site Visits
Before/During the Bidding Process- Unknown Site Conditions”

The weakness of the Lambda and Goodman and Kruskal tau values in Table 5.7 below
implied a poor association between the two variables of the cross-tabulation above. The
profession did not influence the responses for the “Negligence_Site_Visits” variable.

128

Value
Nominal by
Nominal

Lambda

Goodman and Kruskal
tau

Symmetric
Profession Dependent
Negligence_Site_visits
Dependent
Profession Dependent
Negligence_Site_visits
Dependent

Asymp. Std.
Errora

.039
.000
.058

.087
.000
.128

.065
.039

.034
.020

a. Not assuming the null hypothesis
Table 5.7 Directional Measures for the Cross-tabulation Between the Variable Profession and the
factor “Negligence of Site Visits Before/During the Bidding Process- Unknown Site Conditions”
5.6 Prioritization of Factors and Project Phases
Table 5.3 places factors in decreasing order. It also showed the factors, which seemed most
critical as well as the less significant ones regarding cost overruns and time delays. Since scores
were relatively close, it was difficult to determine which factors were important. Consequently, a
supplementary table was developed to separate factors into quartiles as shown in table 5.8.


First quartile, very high priority, for factors with respondent frequencies strongly

agreeing and agreeing between 75% and 100%


Second quartile, high priority, for factors with respondent frequencies strongly agreeing

and agreeing between 50% and 75%


Third quartile, low priority, similarly, for respondent frequencies between 25% and 50%



Fourth quartile, very low priority, lastly for respondent frequencies lower than 25%

Based on this definition, there were no factors that fell in the first quartile.
Corresponding results are presented in table 5.8.

129

Frequency
Respondents
Strongly Agreeing
and Agreeing
Between 84 (100%)
and 63 (75%)

Between 63(75%)
and 42 (50%)

Priority

Corresponding Factors

Very
High

None

High

Negligence of Site Visits Before/During the Bidding
Process-Unknown Site Conditions
Weak and Insufficient Technical Studies
Lack of Project Planning/Programming
Underestimating of Cost Estimates and Schedules/
Overestimating of Benefits
Lack of Equipment
Bidding Procedures
Duration of the Period of Bidding
Material Price Fluctuation
Negligence of Past Experiences
The Lowest Bid Price System
Methods of Payment
Inadequate Project Planning/Programming
The Displacement of Existing Networks
Poor Project Implementation Strategies
Changes in Scope of Contracts
Poor Communication among Contract Stakeholders
Unreasonable Adjustment of Project Cost by
Contractors
Lack of Contract ex post Evaluation
Weaknesses during the Land Taking Process
Supervisor and Contractor Claims and Disputes
Construction Errors and On Site Testing Approval
Many Stakeholders
Weather Conditions

Table 5.8 Classification of Factors by Priority Groups

130

Table 5.8 Classification of Factors by Priority Groups (Cont’d)
Frequency
Respondents
Strongly Agreeing
and Agreeing

Priority

Between 42 (50%)
and 21 (25%)

Low

Between 21(25%)
and 0 (0%)

Very
Low

Corresponding Factors
Unethical Activities And Kickbacks
No Action Taken After Contract Progress Reports
Mistakes and discrepancies in documents
Expropriation costs
Shortages of Materials
Mismanagement Due to Inexperienced Supervisors
Periods of Inspection and Testing After Contract
Completion
Political Tensions/Insecurity
Equivocal/Unclear Contracts
Building on unexpected archaeological sites
Legal environmental requirements
None

Based on Table 5.8, the researcher attempted to prioritize project phases. The objective was
to classify project phases, according to their influence on cost overruns and time delays. Project
phases with a high number of high priority factors were also considered critical for cost overruns
and time delays. High priority factors were found in all project development phases, with the
distribution presented in table 5.9. The bidding phase was the most critical, with all four factors
classified in the high priority group. Project implementation, with 59% of high priority factors,
seemed to be of slightly less concern for cost overruns and time delays.

131

Project Phase

Bidding Phase
Design Process
Planning and Programming
Project Implementation
Project Control and ex post
Evaluation

Number of
High
Priority
Factors
4

Total
Number of
Factors

3

4

3

5

10

17

2

4

4

Observations
All factors have high priority
(100%)
75% of factors are high priority
60% of factors are high priority
59% of factors are high priority
50% of factors are high priority

Table 5.9 Prioritization of Project Phases

5.7 Respondent Comments on Causes and Improvements for Cost Overruns and Time
Delays
The following comments were received from respondents, in the open-ended portion of the
survey. Participants were asked to suggest solutions to cost overruns and time delays.
An author’s translation for comments in French is italicized after each French response. These
suggestions are considered in Chapter Six in discussion of guidelines developed in the study.

132

Respondent No

Verbatim Comments

1

1: Accidents on job sites

2

2:Financement des Travaux
2: Funding of Work.

3

4

1: Deficit de personnel Experimenté
1: Lack of experienced personnel
Réaliser des bonnes études préalablement au lancement de l’appel
d’offres, Améliorer le système de passation des marchés, Mieux
programmer la période de démarrage des travaux, Prendre des dispositions
pour le déplacement des réseaux à temps.
Conduct good studies before calling for bids, improve the public contract
system, better scheduling of the beginning of work, displacement of
networks on time

5

Main issues lie along procurements and implementation phases. Another
concern is the selection of contractors who are not well equipped/qualified:
false declarations of competencies.

6

Assouplir les procédures de passation des marches, Améliorer la qualité
des études, Equiper ou renforcer l'équipement du pays en matériel des TP
(engins de génie civil), réduire le nombre de parties prenantes au marché,
renforcer les capacités de gestion administrative, technique et financière
des entreprises locales.
To ease the process of bidding contracts, improve the quality of design
studies, providing the country with heavy construction equipment, fewer
contract stakeholders, improve management, technical, and financial
capabilities of local enterprises.

7

Par la maturation des projets.
By a deep study of projects.

8

Disposer de bonnes études, Acceptation du projet par les riverains, Bonne
sélection des acteurs (entreprise, BET contrôle…), Renforcement des
capacités des services du maitre d'ouvrage vis-à-vis de la gestion des
projets et la nécessité de réaliser la qualité dans les délais.
Having good studies, the project should be adopted by riparians, good
selection of the project team (constructor, work supervisor,…), improve
owner capabilities for project management and the need to implement
project of good quality on time.
Table 5.10 Comments from Survey Respondents

133

Table 5.10 Comments from Survey Respondents (Cont’d)
Respondent
No

9

10

11

12

Verbatim Comments
S'assurer que des études sont bien faites avant le lancement des appel d'offres,
S'assurer que le financement des travaux existe et conduira le projet à terme,
Réduire autant que possible les intervenants dans les procédures de passation du
marché, S'assurer que la mission de contrôle choisie sera à la hauteur de la tâche
de même que l'entreprise en charge des travaux, Respecter les exigences des
contrats et les plannings arrêtés.
Verifying that design studies are available before call for bids, Verifying that
funding is available until project close-out. Reduction of stakeholders during the
bidding process, verifying that the chosen work supervisor will be capable to
perform efficiently, as well as the chosen constructor, abide to contract
requirements and planning established.
Pour réduire les surcouts et les projets hors délais, il faut: une programmation
rigoureuse des travaux, à temps; Des études bien menées avec une interprétation
de celles-ci; Des couts bien maitrises et reflétant la réalité du marché; Une bonne
stratégie d'exécution des travaux avec prise de décision à temps; Une attribution
des marches aux entreprises performantes et suivies.
To diminish cost overruns and time delays, a strict scheduling of work, on time ;
good design studies along with their good interpretation, mastering contract
costs, a good project implementation strategy and timely decision making,
contract award to successful enterprises are needed.
Pour réduire les surcouts et les projets hors délais: Démarrer les études à temps
(Programmation), Commander les études approfondies, Réduire le nombre
d'intervenants dans les procédures de passation.
To reduce cost overruns and time delays, start design studies on time, order
detailed design, reduce stakeholders on bidding processes.
Pour les grands projets, prévoir une assistance à la maitrise d'ouvrage, ou une
maitrise d'ouvrage déléguée: trop de grands projets, surtout sur financements
nationaux, sont mal conduits ou pas conduits du tout. Les projets d'entretien
doivent être suivis par l'ingénieur du MINTP le plus proche du site: le
subdivisionnaire ou le Délégué Régional. La centralisation à Yaounde n'est pas
pertinente pour ce type de travaux. Programmation, passation de marche et
supervision de la mission de contrôle en tant que représentant du maitre de
l’ouvrage, le MINTP.
For large projects the owner needs assistance, or needs to delegate a
representative : many large projects, mainly those funded locally, are poorly or
not managed at all. Maintenance projects should be followed up by the MINTP
engineer closer to the site : the divisional or regional delegate. Yaounde’s
centralization is not pertinent for such work, programming, bidding the contract
and supervising the work by a consultant, as MINTP’s representative.

134

Table 5.10 Comments from Survey Respondents (Cont’d)
Respondent No

13

Verbatim Comments
Réhabilitation du MATGENIE, Plus d'objectivité dans le choix des
entreprises et MDC, Diminuer les entreprises présentant des offres
anormalement basses.
Rehabilitation of MATGENIE (public company for heavy equipment), more
objectivity in choosing constructors and contractors. Diminish enterprises
with too low bids.

14

La réussite d'un projet est fortement liée à son cout et à ses délais
d'exécution qui devraient être optimises au maximum. Connaissant les
cycles d'un projet, il serait indiqué pour son exécution, et ce, de son
instruction à son évaluation ex post, de mobiliser des ressources humaines
bien outillées en matière de suivi-évaluation et en gestion des contrats.
A successful project is strongly linked to its cost and implementation time
which should be optimized to the maximum extent. Knowing project cycles,
human resources skilled in contract administration and project
management should be mobilized from project inception to post
implementation.

15

The time between the feasibility studies and the award of contracts should
not be too long.

16

Faire de bonnes études jusqu'à l'APD, Retenir des entreprises citoyennes
pour l’exécution des travaux, Mettre en place une équipe de suivi de projet
intègre et compétente, Gérer efficacement les expropriations et les
déplacements de réseaux.
Good design studies, awarding contracts to responsible contractors,
putting in place a competent and transparent project team, efficiently
manage expropriations and network displacements.

17

18

In Cameroon, we have to stress on the design of the project, ensure that
technical studies and the cost of the project are well evaluated. With this,
execution will be perfect but we also have to stress on maintenance, when
the project is finished, everything has to be done to keep the project from
degrading.
Améliorer la planification et la programmation, Approfondir les TDR des
études afin de minimiser les risques de variation des quantités, Améliorer
les conditions de travail des différents intervenants dans la chaine.
Improve planning and programming, deepening studies terms of references
to reduce quantity variations, improve stakeholders’ work conditions.

135

Table 5.10 Comments from Survey Respondents (Cont’d)
Respondent No

Verbatim Comments

20

Passer les marchés d'études techniques en maitrise d'œuvre complète et
fixer les dates dans les contrats.
Bid a single contract for design and work supervision, and set up dates in
contracts.
R.A.S.
Nothing To Report

21

By objectivities in decisions taking by both parties involve.

19

5.8 Comparison with Other Countries
Table 5.11 was shown in Chapter Two and is repeated here for discussion of the results
concerning Cameroon. The literature showed the design phase and site conditions were critical
causes for project overruns in other countries. This research showed this in the case for
Cameroon as well. The lack of planning was reported by other studies, and also was a common
factor for cost overruns and time delays in Cameroon.

136

Author(s)/
Year

Country

Number of
Respondents

Number of
Factors
Studied

Bella Akoa
(2011)

Cameroon

84

34

Creedy et al.
(2010)

Australia

8

37

Tumi et al.
(2009)

Libya

N/A

43

Abd ElRazek et al.
(2008);

Egypt

74

32

Le-Hoai et
al. (2008)

Vietnam

87

21

Sambasivan
and Soon
(2007)

Malaysia

150

28

Lo et al.
(2006)

Hong
Kong

151

30

Malaysia

204

20

Nigeria

102

44

AbdulRahman et
al.(2006)
Ajibade and
Odeyinka
(2006)

Major Causes(or factors) of Cost
Overrun/ Time Delay
1. Negligence of Site Visits
Before/During the Bidding Process Unknown Site Conditions
2. Weak and insufficient technical
studies
3. Lack of Project
Planning/Programming
1. Design and scope change
2. Insufficient investigations and
latent conditions
3. Deficient documentation
(specification and design)
1.Improper planning
2.Lack of effective communication
3.Design errors
1. Financing by contractor during
construction
2. Delays in contractor’s payment by
owner
3. Design changes by owner or his
agent during construction
1. Poor site management and
supervision
2. Poor project management
assistance
3. Financial difficulties of owner
1. Improper planning
2. Site management
3. Inadequate contractor experience
1. Inadequate resources due to
contractor lack of capital
2. Unforeseen ground conditions
3. Exceptionally low bids
1. Additional work
2. Labor shortage and lack of skills
3. Poor planning and scheduling
1. Contractors’ financial difficulties
2. Clients’ cash flow problems
3. Architects’ incomplete drawings

Table 5.11 Comparison between Construction Professional Surveys

137

Table 5.11 Comparison between Construction Professional Surveys (Cont’d)
Author(s)/
Year

Country

Number of
Respondents

Number of
Factors
Studied

Frimpong et
al. (2003)

Ghana

72

26

Mansfield et
al. (1994)

Nigeria

37

23

Okpala and
Aniekwu
(1988)

Nigeria

192

27

Merewitz,
L. (1973)

U.S.A.

N/A

N/A

Major Causes(or factors) of Cost
Overrun/ Time Delay
1. Monthly payment difficulties from
agencies for completed work
2. Poor contractor management
3. Material procurement
1. Poor contract management
2. Financing and payment of
completed work
3. Changes in site conditions
1.Shortage of materials
2.Finance and payment for completed
works
3.Poor contract management
1. Price level increases
2. Scope changes
3. Unforeseen conditions and
structural modifications

5.9 Chapter Summary
Chapter Five presented the results of the survey of construction professionals in Cameroon.
Using SPSS software, statistical data analyses were performed. The factors identified as causes
of cost overruns and time delays were classified by degree of importance, for further analysis.
“Negligence of Site Visits Before/During the Bidding Process- Unknown Site Conditions” was
found to be the most frequently cited cause of cost overruns and time delays, and the bidding
phase was the most critical. Comparing the survey results obtained in Cameroon to those in other
countries, similarities were observed. Suggestions by survey participants for methods to improve
cost and time overruns are used in the development of recommendations and guidelines
presented in Chapter Six.

138

CHAPTER 6
DISCUSSION AND GUIDELINES FOR IMPROVEMENT

139

6.1 Overview
This research uses three principal sources of data in addition to the literature review, which
included:


The statistical analysis of cost overruns and time delays from contract data.



The survey of construction professionals in Cameroon, which identified the causes of

cost overruns and time delays.


Documents obtained at MINTP during data collection. These documents presented in

section 3.7 explain not only regulations used by the ministry, but also describe project
development activities at MINTP for the years covered by this study. They contribute to the
research because they present discussion of the MINTP organization, potential flaws in project
management, detail on causes of change orders, and proposed measures to avoid project overruns
in the future.
6.2 Discussion of the Contract Data Analysis
Contract data analysis showed that cost overruns and time delays were predominant for the
following project sub-categories:


Work supervision



Foreign aid projects



Small projects between 100,000,000 XAF and 250,000,000 XAF, and larger projects

greater than 5,000,000,000 XAF


Projects scheduled for more than 36 months

140

Work Supervision
The adoption of work supervision for highway and bridge construction or maintenance contracts
at MINTP was problematic, considering the high project overrun rates recorded, compared to
more complicated contracts such as those using heavy equipment. Adding to the complexity of
contracting, work supervision was not only very expensive, but also inefficient for project
management. Work supervision accounted for eight percent or about 61 billion XAF of contract
expenditures during 1997-2007. If MINTP chose to administer contracts itself, such contract
funds could have been used to pave more highways and build more bridges in Cameroon. Such
situations were described by Schumacher (1973): “Poor countries slip-and are pushed –into the
adoption of production methods and consumption standards which destroys the possibilities of
self-reliance and self-help. The results are unintentional neocolonialism and hopelessness for the
poor”.
In addition, high wages and fringes were recorded in consultant contracts for work supervision.
During MINTP project implementation, both construction and supervision contracts were linked
such that cost overruns for the first contract would affect the second one, creating a multiplier
effect. The same situation was observed for time delays. When constructors stopped work or
were late for mobilization, work supervisors were still paid (MINTP, 2009b). Similarly, when
work supervisors were not mobilized at scheduled contract start, constructors who were delayed
received time extensions. Furthermore, small projects, which were frequent at MINTP, were said
to have high work supervision costs (BCEOM, CEBTP, 1991).
In 2009, poor results were recorded at the ministry for road maintenance. However, the
responsibility was shifted to work supervisors instead of constructors (Abomo, 2010).

141

This confusion between responsibilities did not only happen between constructors and
supervisors; contract data analysis showed that a consultant in some instances had contracts
providing both work supervision and technical assistance to MINTP for project management,
meaning that the consultant was simultaneously contractor and owner representative on related
projects. Such situations pose ethical problems.
Foreign Aid Projects
Contracts involving donors from outside countries were presumed by the researcher to be better
prepared, better implemented, and would experience fewer project overruns compared to those
funded only by MINTP because donors involved experts and specialists from developed
countries. Unexpectedly, the results of this study showed the opposite; Seeking explanations for
this finding, the researcher investigated foreign aid practices, specifically for Africa.
Foreign aid started after World War II, with the creation of multilateral agencies such as the
World Bank, IMF and bilateral cooperation agencies supported by individual countries. Many
successful projects were implemented with foreign aid in developing countries, and specifically
infrastructure projects. Without foreign assistance, many countries could not achieve
development goals: MINTP for instance could only fund about 50% of its highway and bridge
projects, the rest came from donor contributions in the form of grants or loans. In general,
assistance is provided through programme aid, technical assistance, and aid to build capacity of
institutions in recipient countries (Ridell, 2007).
However, the balance-sheet of foreign aid is limited in the literature. For the past decades,
foreign aid increased significantly in poor countries; meanwhile economic growth was declining
in the same period (Easterly, 2006). Multiple causes contributed to this situation such as a lack of
project planning and coordination (Van de Walle, 1996), political, strategic and commercial

142

interests of donors (Ridell, 2009), and governance issues from the recipient countries (Calderisi,
2006).
Hancock (1989) illustrated an example of a highway project in Somalia, externally funded
and built in 1983 by an international contractor: the highway was only serviceable for five years,
meanwhile that country had to pay the loan for that project until 2023. Brunel (1993) went
further indicating that the French aid agency was squandering French resources. According to
her, only 5% of French aid effectively contributed to development in assisted countries, the rest
was distributed to French companies through fruitful contracts, and for an excessive technical
assistance. Foreign aid policies need to be improved for win-win partnerships between donors
and recipient countries.
Project Size
Poor technical studies (MINTP, 2007a, 2008c) and delays in bidding were cited in reports for
causing cost and time overruns for large projects. According to these sources, bidding processes
for large projects, which often involved foreign lenders, were lengthier and more complicated
than those of medium and small size projects (Banque Mondiale 2005; MINTP, 2008b). At the
point of notice to proceed for some contracts, design studies needed to be updated. In addition,
the sub-contracting processes were limited such that at the ministry work was not divided into
sub-contracts for more efficiency, as is typical in the U.S.
Project Duration
Project durations at MINTP were controlled by the ministry through notices to start or to stop
the work; these durations seemed approximate in many contracts because they were based on bar
charts without activities being clearly defined. Large durations were not necessarily linked to
large projects. Small projects such as mowing projects were scheduled for three years, however

143

the work was actually completed during three to four months each year. Mowing projects
showed smaller project overruns during the contract data analysis. Weaknesses during design
studies also suggested little detail for durations, which may increase during project
implementation.
6.3 Discussion of the Survey Results
According to the survey of construction professionals in Cameroon, the top six causes of cost
overruns and time delays in highway and bridge projects were:
1.

Negligence of Site Visits Before/During the Bidding Process-Unknown Site Conditions

2.

Weak and Insufficient Technical Studies

3.

Lack of Project Planning/Programming

4.

Underestimating of Cost Estimates and Schedules/ Overestimating of Benefits

5.

Lack of Equipment

6.

Bidding Procedures

These six factors, as well as others, are discussed below.
6.3.1 Issues in Planning and Programming
From MINTP documents, transportation planning and planning in general seemed to be
secondary activities within the ministry. The planning department was created in the mid-2000s,
and seemed to have limited involvement in the activities of the ministry. Several units supervised
programming activities within the ministry. However, no transportation improvement program
was available at MINTP. Many projects were decided during budgetary sessions with
parliamentarians (Njoh-Mouelle, 2001). Such unplanned projects were likely to experience large
cost and time overruns. Project teams would face many unexpected situations, starting with

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expropriations. That seemed to be the case for small contracts which had the highest project
overrun rates.
6.3.2 Problems Relating to the Design Process
Project Implementation Strategies
After studying the documents collected at MINTP, including contract samples, it seemed that
MINTP may have project implementation strategies that were not well suited to its socio
economic situation.
Without having companies available to ensure its field duties, MINTP totally privatized its
project implementation in the 1990s, and adopted work supervision by private parties for
contract administration (World Bank, 2004) although it had personnel for such tasks. In addition,
all contracts were awarded through a complicated and lengthy bidding system created in the
same period: all the work was carried out and supervised by private parties (Banque Mondiale,
2005 ; MINTP, 2008b). By comparison in the United States, construction and consultant
companies have existed for centuries and are competitive, along with use of force account for
specific projects (Refer to thesis definition of force account in the glossary). As illustration, table
6.1 shows for the past five years, the value of force account projects by the Michigan Department
of Transportation (MDOT).
Year

Amount (US$)

2009

18,936,762

2008

15,895,652

2007

24,033,713

2006

17,054,685

2005

2,664,971.00

Table 6.1 Amounts of MDOT Force Account Projects for
Past Years (Source: www.michigan.gov)

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Furthermore, table 6.2 shows the United States Department of Transportation had
competition in contracting ranging from 61% to 82% of its projects from 2006 to 2008.
Year

Competition in Contracting

2008

82%

2007

76%

2006

61%

Table 6.2 Percent of US DOT Competition in Contracting for 2006-2008
(Source: www.recovery.gov)
These tables demonstrate that possibly, Cameroon has outsourced its public work activities, more
than in the U.S., which is strange for a developing country.
Weak and Insufficient Technical Studies
Before work was implemented, studies were carried out from socio-economic analysis to
detailed design. Contract analysis conducted during this research showed that the design process
had a critical influence on cost and time overruns. Weak and Insufficient Technical Studies were
found to be the second most common cause, cited in the survey of professionals. The scope of
projects was defined by technical studies. In some instances, weak studies were not detailed
enough to clearly allow the project team to build a project. Insufficient technical studies required
more design effort from the project team during design, and cost projects extra time and money.
From the contract analysis, it was found that MINTP spent 2% of project resources from
1997 to 2007 for design and technical studies and technical assistance. Poor technical and design
studies were described negatively. Wrong, incoherent, or irrational technical studies were
dismissed many times at the beginning of construction or maintenance work (MINTP, 2007a ;
MINTP, 2008c ). In addition, the purposes of some change orders for work supervision were to

146

implement environmental studies during the work. However, environmental studies had to be
carried out before project approval. The common practice for project development is to schedule
project implementation only when environmental impact studies are approved.
Advanced cost and time management are needed to improve project performance. Instead of
using simple bar charts which were found in the contract analysis conducted during this research.
None of the contract specifications reviewed defined scheduling activities or networks; leading
to weak technical studies. Design contracts should be improved, in order to hold design
consultants accountable for their work.
6.3.3 Issues Found During Bidding Procedures
The bidding phase was found to be the most critical for cost overruns and time delays.
The factors related to the bidding phase included bidding procedures, the duration of the period
for bidding, the lowest bid price system, and unreasonable adjustment of project costs by
contractors were cited as important causes in Chapter Five for their impact on project overruns.
A final report by MINTP (MINTP, 2008b) for a study of problems related to bidding of public
contracts at MINTP pointed out many issues which included: malfunctions between MINTP
services and between MINTP and other public institutions involved in bidding processes, as well
as problems related to public contract regulation. As a result, bidding processes wasted resources
and time, and were detrimental to project implementation.
The public contract code of Cameroon adopted in 2004 shows many issues which were
identified by the researcher, as indicated below:


The project owner, who is the minister of MINTP, has no final decision in the bidding

process. A specialized bidding board reviews bid awards and would possibly reverse the
minister’s decisions, adding more time to bidding procedures (MINTP, 2008b).

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

The project owner awards contracts after propositions from an internal bidding board. The

bidding board itself proposes contract awards after bid analysis by a separate board, designated
as “sub-board for bid analysis”. In addition, the sub-board works under the scrutiny of an
“independent observer” who is a consultant recruited by the authority for public contracts. For
projects with external funding, the donor has to formally approve the awards: this last step can
take months.


The procedures above are used for all contracts, even for simple projects such as regular

maintenance or the mowing of roadsides.
With such rules, the volume of work is so huge that MINTP created four bidding boards for
its various types of contracts. In spite of that, bidding procedures take so long that site conditions
have frequently changed or deteriorated by the time of contract implementation. Change orders
are needed to solve such problems (MINTP, 2009a ; MINTP, 2008b).
Another noteworthy issue in the public contract code is that, it does not apply to international
conventions between Cameroon and other countries or donors, as stated in its article four. The
researcher believes such disposition unfair and inequitable to local contractors, and does not
promote good governance. In general, lenders or donors funding projects also brought
contractors from their countries. Not only was the pricing of such contracts high because of
limited competition, but also international contractors received exemptions on taxes and customs
duties to import equipment and buy materials for project implementation (MINTP, 2009a). This
equipment was later used for other contracts awarded to those international companies in the
country (MINTP, 2009a). Local contractors did not have such advantages and were
automatically excluded from the bidding of large contracts which require an extended use of
heavy equipment. Here again, limited competition leads to high pricing and cost escalation.

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6.3.4 Comments on Project Implementation
“Negligence of Site Visits Before/During the Bidding Process- Unknown Site Conditions”,
and “Lack of Equipment” were ranked as the first and fifth causes of project overruns in the
survey of MINTP staff and partners.
Site visits are required for contractors during the bidding phase. Many change orders
potentially flow lack of knowledge of site conditions by contractors such as changed plans,
increased costs to account for added tasks, and changes in scope of work. Consultants who did
not conduct site visits provided inadequate design studies. Similarly, due to remoteness of
project sites, short bidding periods and limits on bidding expenses, constructors would rely
solely on bidding documents for their offers. As previously written, these design documents were
not always reliable.
In many cases, contractors were responsible to conduct site visits; however, change orders
resulted from differences between bidding documents and actual conditions which could have
been observed. Site conditions also changed significantly between the bidding phase and the
contract award or notice to proceed, when actual bidding periods were longer than expected.
Change orders were necessary to update contract documents for actual site conditions.
In addition, MINTP solved the issue of congestion of bidding boards from a large number of
contracts for award, by bidding multi-annual contracts lasting for typically three years, for
maintenance activities. However, change orders were sometimes needed for the last years
because of changed site conditions. This was also the case for contracts, which were awarded
several months or even a year ahead of the notice to proceed. To update contract quantities,
MINTP adopted its contract procedures, to include an initial site visit by the project team, after

149

the notice to proceed for contractors. However, in the author’s opinion, this practice needs to be
abandoned because it usually modifies the initial contract quantities above acceptable limits,
favoring irrational estimating by contractors during the bidding process, mindful that their
estimates will be corrected and change orders executed, after they will receive the notice to
proceed with work.
Lack of Equipment: Substantial project costs are due to the use of heavy equipment (Sears et Al.,
2008). This was a crucial problem for MINTP, since this equipment had to be imported and the
equipment was not affordable for most contractors. When privatization was adopted by the
ministry in the early 1990s, all MINTP owned equipment, mostly depreciated, was sold to the
new private companies or transferred to MATGENIE, the public agency for heavy equipment
rental, which had economic difficulties since its inception. From 1995-2010, obsolete equipment
frequently failed on job sites. In 2010, new equipment was purchased for MATGENIE.
Methods of Payment: Some change orders were due to contractor delays, because they were
waiting for cash advances from the ministry (Groupe de la Banque Africaine de Développement,
2008). MINTP took financial risks, by allowing advances to contractors which were repaid
without interest charges. Similarly, retainage could be replaced by a bond from a bank. This was
another risk, due to the instability of contractors and banks. Furthermore, bonding agencies did
not exist in Cameroon, so contract bonds were merely signed by banks.
Unethical Activities and Kickbacks: This factor was not perceived by the survey respondents as a
source of cost overruns and time delays at MINTP, it was classified as “Low Priority”. However
Njoh-Mouelle (2001), a member of the Cameroon’s parliament reported that in his region, a
contractor was totally paid for work not even started on site, attempted to process two change
orders on that fictitious project, while claiming a third change order for more “compensation”.

150

Another concern was raised after scrutiny of MINTP’s contracts, considering large disparities
between the wages of constructors, consultants and government employees. For workers with
similar qualifications, some earned up to ten times the salaries of others from the same employer
(MINTP). This was unsustainable, and could lead the lower paid employees, mostly from
government to look for compensation from private counterparts. It was an issue for ethics and
good governance which could impact project costs because contractors would attempt to recover
extra spending through change orders. These would be rapidly validated by agents who received
kickbacks. For such problems, the President of the Republic of Cameroon, Paul Biya (1987)
wrote:
“ Since the building of our country is inevitably a collective task, an enormous
task to which each citizen makes a contribution according to his means and
abilities, it would be injustice of the highest order to institutionalize inequalities
between effort and remuneration among workers. Such injustice existed and is
still widespread in our society, leading to a great deal of frustration, complexes
and eventually resignation …the salary gap between the private and semi-private
sector and the public sector must be reduced considerably.…The lesson will be
applied rigorously in both sectors since harmonized or equal pay will mean that
the same skills, the same efficiency and the same output will be expected of
everybody. Laxity and the shirking of duty by the post-colonial administration led
to the popular conclusion that state employees were incompetent, inefficient and
consequently deserved their low remuneration. I do not think that such
shortcomings are inherent in government employees or that their case is a
hopeless one. On the contrary, through a global policy based on social justice, we
hope to eliminate such shortcomings as well as the presumed causes of salary and
wage disparities. ”

6.3.5 Project Control and Post-implementation Problems
In developing countries, Government agencies may lack contract administration skills. At
MINTP, some change orders seemed to be to the detriment of the ministry. Valid explanations
were not found by the researcher, for change orders which looked inappropriate for their purpose
(MINTP, 2007a). As examples, the following were found:

151



Time extension and financial compensation through price updating, for contractors who

deliberately delayed the work, demanding cash advances before starting to work


Financial compensation to contractors for some shortage of materials, or for damages to

the work due to contractor’s negligence


Financial compensation for diverse MINTP(owner) lateness in addition to time

extensions
Appropriate project controls and contract terms would have helped to prevent such change
orders.
Improvements were taken by the public contract authority to regulate price updating (SPM,
2011a) in order to limit costly change orders which occurred when projects were delayed for a
long period. Overall, more improvements are needed: MINTP implemented project strategies
which were already identified as costly and inefficient. Costs of the development project system
seemed to largely surpass their benefits. Periodic ex post evaluation of the system would
contribute to reduce cost and time overruns, for the interest of taxpayers.
6.3.6 Summary of Factors for the Suggestion of Guidelines
Table 6.3 was developed from the discussion above along with Chapter Five of this thesis, in
an attempt to select important factors for the thesis recommendations.

152

Literature
Evidence

Factors
Planning and
Programming
Lack of Project
Planning/Program
ming
Inadequate Project
Planning/Program
ming

Survey
Data

(Merewitz ,1973)

High

(Flyvbjerg, 2008)

High

Weaknesses during
the land takings
(Okole, 2009a)
process

High

(Jergeas , 2009),
Expropriation costs (Anderson et al.,
2008)
Legal
(Jergeas , 2009),
environmental
(Anderson et al.,
requirements
2008)
Design Process
(Ajibade and
Odeyinka,2006),
Weak and
(Anderson et al.,
insufficient
2007), (Creedy et
technical studies
al.,2010),(Camero
on-Tribune
Archives, 2009)
Underestimating of
cost estimates and
(Flyvbjerg et al.,
schedules/
2004)
Overestimating of
Benefits
(Jergeas, 2009),
Poor project
(Anderson et al,
implementation
2007), (Shane et
strategies
al., 2009)
Mistakes and
(Okpala and
discrepancies in
Aniekwu, 1998)
documents

Low

MINTP
Reports and
Studies

High
(MINTP,2008b,
2009c)
Low
(MINTP,2009a,
2007a)
Low
(MINTP,2008b)
,
(MINTP,2009c,
2007a)
Low
(MINTP,2009c,
2007c)

Priority for
Guidelines

Yes

No

No

No

Low

Low
(MINTP,2009c)

No

High

High
(MINTP,2009a,
2009b,2009c,20
08b,2007a)

Yes

High

High
(MINTP,2009a,
2009b,2007a)

Yes

High

High
(MINTP,2009a;
PRC,2004)

Yes

Low

Low, No
Evidence

No

Table 6.3 Summary of Factors to Consider for Guidelines

153

Table 6.3 Summary of Factors to Consider for Guidelines (Cont’d)

Factors

Literature
Evidence

Survey Data

MINTP
Reports and
Studies

Priority for
Guidelines

Bidding Phase
Bidding
Procedures

MINTP
Specific

Duration of the
Period of Bidding

(Okpala and
Aniekwu, 1998)
(Hinze and
Selstead, 1991),
(Jin-Kyung,
2008), (Lo et
al., 2006),
(Frimpong et
al., 2003)

The Lowest Bid
Price System

High
High

Very High
(MINTP,
2009a, 2008b)
Very High
(MINTP,2008b)

Yes
Yes

High

High
(MINTP,2009a)

Yes

(Jin-Kyung ,
2008)

High

High
(MINTP,2009a)

Yes

(Pratt, 2004),
(Sweet and
Schneier, 2009),
(Lo et al., 2006)

High

High (MINTP,
2009c, 2007a)

Yes

Mismanagement
Due to
Inexperienced
Supervisors

(Merewitz
,1973), (LeHoai et al.,
2008),
(Mansfield et
al., 1994),
(Jergeas, 2009)

Low

Low
(MINTP,2009c)

No

Supervisor and
Contractor Claims
and Disputes

(Abd El-Razek
et al., 2008)

High

Low, No
Evidence

No

Many Stakeholders

(Abd El-Razek
et al., 2008)

High

High
(MINTP,2008b)

Yes

Unreasonable
adjustment of
project cost by
contractors
Project
Implementation
Negligence of Site
Visits
Before/During the
Bidding ProcessUnknown Site
Conditions

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Table 6.3 Summary of Factors to Consider for Guidelines (Cont’d)

Survey Data

MINTP
Reports and
Studies

Priority for
Guidelines

Factors

Literature
Evidence

Poor
Communication
Among Contract
Stakeholders

(Tumi et al.,
2009), (Le-Hoai
et al., 2008),
(Sambasivan
and Soon,
2007), (Jergeas
, 2009),

High

Low, No
Evidence

No

Unethical
Activities And
Kickbacks

(Okpala and
Aniekwu, 1998)

Low

High
(MINTP,2009a)

No

Low

Very High
(MINTP,2009e,
2009f,2009h,20
09i,2009j,2007a
,2007b,2005a,2
005b,2005c,
2004)

Yes

Low

High
(MINTP,2007a)

No

High

Low
(MINTP,2009c)

No

High

Low, No
Evidence

No

Low

Low
(MINTP,2007a)

No

Low

Low, No
Evidence

No

Equivocal/Unclear
Contracts

Changes in Scope
of Contracts
The Displacement
of Existing
Networks
Construction
Errors and On Site
Testing Approval
Building on
unexpected
archaeological
sites

Shortages of
Materials

(Anderson et al
, 2007), (Shane
et al., 2009)

(Merewitz ,
1973),
(Anderson et al,
2007)
(CameroonTribune
Archives, 2009)
(Anderson et al,
2007), (Okpala
and Aniekwu,
1998)
(Lo et al.,
2006), (Le-Hoai
et al., 2008),
(Abd El-Razek
et al., 2008)
(Okpala and
Aniekwu,
1998), (Abd ElRazek et al.,
2008);

155

Table 6.3 Summary of Factors to Consider for Guidelines (Cont’d)

Factors

Literature
Evidence

Material Price
Fluctuation

(Merewitz,
1973), (Le-Hoai
et al., 2008),
(Frimpong et
al., 2003)

Methods of
Payment

(Okpala and
Aniekwu, 1998)

(Okpala and
Aniekwu ,
Lack of Equipment 1998), (Abd ElRazek et al.,
2008)
(Bramble and
Callahan,
2000), (Abd ElRazek et al.,
Weather Conditions
2008), (Le-Hoai
et al., 2008),
(Okpala and
Aniekwu, 1998)
Political
(Akinci and
Tensions/Insecurity Fischer, 1998)
Project Control
and ex post
Evaluation
No Action Taken
(Jin-Kyung,
After Contract
2008)
Progress Reports
(Okpala and
Periods of
Aniekwu,
Inspection and
1998), (Tumi et
Testing After
al., 2009),
Contract
(Mansfield et
Completion
al., 1994)
Lack of Contract ex (Jin-Kyung,
post Evaluation
2008)
Negligence of Past MINTP
Experiences
Specific

Survey Data

MINTP
Reports and
Studies

Priority for
Guidelines

High

Low
(MINTP,2007a)

No

High

Low
(MINTP,2009a,
2009c)

No

High

High
(MINTP,2009a)

Yes

High

High
(MINTP,2009a,
2009c)

Yes

Low

Low
(MINTP,2007a)

No

Low

Low, No
Evidence

No

Low

Low
(MINTP,2009c)

No

High
High

156

Low, No
Evidence
High
(MINTP,2009a)

No
Yes

6.4 Guidelines
Chapter Four unveiled cost and time overruns in the project contract files, which undermined
highway and bridge projects in Cameroon. The magnitude of this problem was also described in
the same chapter. Next, Chapter Five discussed perceptions of causes of cost overruns and time
delays from survey respondents for the case study organization. Additionally, causes identified in
the literature or in MINTP reports were considered in identifying factors for development of
guidelines. Recommendations or guidelines emerging from the research are presented below.
6.4.1 Guidelines from the Data Analysis
The previous discussion showed that optimizing time management at all project phases is
fundamental in reducing impacts on costs of labor, equipment and materials. Guidelines are
suggested for each factor of project overruns selected from Table 6.3.
Lack of Project Planning/Programming
In order to help MINTP improve the planning process, it is necessary to organize seminars on
transportation planning. Progressively, planning should be implemented in the ministry and its
importance emphasized. In April 2011, a new organization was adopted for MINTP; although it
still has a planning division, environmental studies are carried out by another division (PRC,
2011). Socio-economic studies, preliminary design, and environmental studies are planning
activities. Once projects receive environmental clearance, they are programmed and detailed
design proceeds within programming units, along with expropriation studies which would be
completed before work starts. The author also believes that the ministry’s road plan needs
updating, and a transportation improvement program adopted. However, detailed transportation
planning is out of the scope of this study.

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Weak and insufficient technical studies and Underestimating of cost estimates and schedules/
Overestimating of Benefits


The introduction of cost conditions (Sweet and Schneier, 2009) in consultant contracts

for technical studies, so that design professionals would produce more accurate cost estimates is
proposed. In addition, these contracts could also include retainage and possible warranty
provisions.


To streamline cost estimating, labor costs could be standardized for all trades and

equipment, so that the differences among bids would be determined by the costs of materials.
Establishing prevailing wages would be an important step toward such standardization.


Seminars on cost estimating and project scheduling would also allow design

professionals to efficiently estimate costs and time needed to implement projects.


Large projects should be scheduled through networks of activities.



Sub-contracting should be developed.

Project Implementation Strategies


MINTP should use its own forces first, to execute its main projects. Then, the remaining

projects can be entrusted to private parties; force account should be restored. More efficiency can
be attained through reducing procedures and hence corresponding spending for professionalism.
Outside work supervision should not be used unless projects are very specialized so that experts
are needed to provide solutions. Such projects should be large and include many constructors.
Relieved from the burden of work supervision, consultants would therefore focus on technical
studies, to significantly improve them. Similarly mowing projects, rural road maintenance, and
unpaved road maintenance are proposed for force account which would not only increase the
volume of projects, but would also reduce the burden on bidding boards and create jobs in rural

158

areas. Such measures would help in achieving timely project implementation. Adopting a project
management approach for force account projects and training of MINTP personnel to improve
contract administration are highly recommended. Increased accountability at MINTP is a prerequisite for the success of such guidelines.


An important innovation suggested for MINTP is to develop the subcontracting process,

to start small, reduce costs and promote professionalism. A plan to develop public work
subcontractors over the entire country is needed. The plan could cover a period of fifteen years.


It is also suggested that MINTP stops delivering cash advances to contractors. Such

financial activities should be reserved to banks, and the ministry employees should concentrate
on technical questions. A plan should also be proposed for the development of bonding
companies in Cameroon, able to carry out the work in lieu of their ‘principal debtors”.


To reduce endless spending on costly and deteriorating unpaved roads, MINTP should

think about a program of road pavement, based on savings from the cancellation of external work
supervision and increased force account. Lastly, using its own forces would also mean relying on
its own resources. This path was shown in 2010 when the government sold treasury bonds
locally to fund infrastructure projects (Teke, 2011). If MINTP improves its project management,
increased productivity will allow the development of more projects funded locally, and fewer
projects would use outside donors.
Biding Phase: Bidding Procedures, Duration of the Period of Bidding, The Lowest Bid Price
System, Unreasonable adjustment of project cost by contractors
It is proposed to revise the public contract code of Cameroon in several ways including:
 Introducing prevailing wages to reduce wages disparities such as in the U.S. (Fisk, 1997)

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 Streamlining bidding procedures by cancelling the special boards and limiting the
“independent observer” to a sample of projects per year, providing more responsibility to
project owners (MINTP, 2008b)
 Award contracts to the lowest responsible and responsive bidder (Sweet and Schneier, 2009)
 Accounting for cancellation of external work supervision
 Use of force account for more efficient project delivery
 Including project start and end dates in contracts, as suggested in the survey responses
 Introducing a “time is of the essence” provision in contracts, to emphasize the importance of
time. Liquidated damages could also be prescribed, in lieu of the current “late fee penalties”
prescribed by the contract code.
When contractors are delayed by MINTP, or the project owner, the only possible
compensation should be time extensions for completing the work (Wickwire et al., 2003). This
would help protect public funds.
Negligence of Site Visits Before/During the Bidding Process- Unknown Site Conditions


Site visits by bidders should be mandatory during the bidding phase. For this purpose, more

value should be given to site visits for the evaluation of bids. More than simple statements of site
visit should be required. Pictures showing specific details of the site along with the date could be
required for each bid. Forms can also be provided to bidders, who will confirm the locations and
quantities of the job to be performed in comparison to the bidding documents.


Cost conditions and requirements for retainage were previously proposed for design

contracts. Such measures will help to insure that consultants provide technical studies, consistent
with field conditions.

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Many Stakeholders
Reducing the number of participants in project development would help reduce waste in cost
and time. Specifically, the project owner should have more responsibility during bidding
approval procedures as previously proposed. Reducing outside work supervision would reduce
the confusion over work performance: the contractor instead of the work supervisor should be
solely responsible for the quality of its work.
Equivocal/Unclear Contracts
Revisions to the public contract code and adoption of coherent project implementation
strategies as previously suggested will provide MINTP with contracts with high standards. Such
contracts could reduce possibilities for project overruns.
Lack of Equipment
Heavy equipment available in the country should be directed to paving projects and for
important bridges. Labor intensive methods by local people would be preferable for unpaved
roads, according to Schumacher’s philosophy.
Weather Conditions
Appropriate time management is crucial to reduce the impact of weather conditions on
project implementation. Except for exceptional weather, which occurs unexpectedly, project
overruns due to weather conditions would be avoided if MINTP becomes successful in time
management. The rainy season would not interfere with the scheduled work.
Lessons learned from Past Experiences
Acquiring information systems for project controls is suggested to help MINTP manage
projects and keep track of records. Evaluating projects at post implementation would assist the
ministry in focusing on the right directions and take advantage of lessons learned from past

161

experiences. Databases for storing and analyzing construction project cost and schedule
information are necessary for MINTP and its partners.
6.4.2 Other Guidelines from the Literature
Remedies for reducing cost overrun and time delay factors from the literature presented in
section 2.5 are discussed below for the case-study of MINTP. Project governance, reduction lists
and lean methods, and foreign aid are considered.


Project Governance: Increased Accountability
Good governance requires the development of projects for public interest, which follow the

principles of merit and equal opportunity for all. The public needs to be aware of the processes of
project development for achievement of transparency and increased accountability. Under the
scrutiny of taxpayers, project teams should provide their best efforts to keep projects on budget
and time. Whistleblowers, who are persons who report misconduct or mismanagement observed
during the activities of a public agency, would help in improving project governance.
Whistleblowers should be protected by public authorities and by laws protecting them from any
sort of retaliation, such as in the U.S.


Reduction lists and lean methods
One reason for lower project overrun rates in Cameroon compared to other countries could

be the reduction of contract scope by project teams, when unexpected field conditions were
observed during project implementation. However, such practices raise problems of fairness to
bidders who were disqualified and favored irrational low bids, as well as reductions in project
quality.

162

Lean methods would have a high impact in reducing project overruns in developing countries
such as Cameroon; however, basic improvements in contract administration and project
management in general are required.


Foreign Aid
It was noted that external funding could be more beneficial to MINTP. Propositions to

reform foreign aid in the literature were:


An increased accountability of public funds in recipient countries



The merging of donor programs for more coherence and uniqueness of procedures



Improving donor-recipient relationships, with “discrete” donors not directly

involving themselves in projects.
Overall, the philosophy of Schumacher (1973), which is still relevant, was found relevant for
successful projects in developing countries, which would keep budget and time in scope.
Suggested guidelines from Schumacher are summarized as follows:


Building adapted, human scale systems, which can be understood and efficiently run by

concerned people


Encouraging the formation of workplaces employing large numbers of people, where they

live


Promoting simple methods of production from local materials



Relative variations of wages and fringes within organizations should range between 1 to 7

between the lowest and highest ones, regardless of race, age, sex, function or experience.
In a few words, it is a matter of starting small, organizing, streamlining and standardizing
processes. For the case study of Cameroon and similar developing countries, privatization may
have gone too far, even further than the U.S. as shown in the discussion. Poor results observed

163

should not be a surprise. Schumacher’s philosophy would suggest that only projects which are
worth competition should be bid and only projects needing private work supervision should be
supervised that way. In addition, the bidding systems should be simplified to allow timely project
implementation. Doing so would save resources, and time would be used more efficiently to
complete more successful projects.
6.5 Proof of Concepts
The guidelines and recommendations suggested in this study will have to be discussed and
validated by the case study organization. The researcher has prepared suggestions for a “proof of
concept” process which is included in Appendix 6. The suggested approach includes a survey or
interview approach to gain feedback from MINTP staff of the accuracy and usefulness of the
recommendations and barriers and opportunities for their implementation. Any “proof of
concept” study should include appropriate Human Subjects Review procedures from the hosting
organization. A sample of five to ten managers should be selected for this survey. A similar
process can be undertaken in other agencies in developing countries, for the adoption of relevant
thesis guidelines for their organizations. Due to reorganization processes being undertaken in
MINTP during conclusions of the research, this was not possible during completion of the thesis.
6.6 Chapter Summary
The purpose of Chapter Six was to suggest guidelines developed from the research data
analysis, the literature and documents collected from the ministry. Opportunities were identified,
which could result in reducing change orders at MINTP. Foreign aid policies and practice were
also discussed, because the highest volumes of project overruns were found in projects with
foreign aid funds. Guidelines were proposed to correct flaws observed, which if implemented
can help reduce cost overruns and time delays. These guidelines relate to all phases of project
development and will further need to be validated by MINTP, or any other agency willing to
adopt these guidelines. Although the guidelines specifically address MINTP projects, the
164

researcher strongly believes the analysis and guidelines likely have application in other
developing nations. Further research could be conducted to test application of the guidelines in
other nations.

165

CHAPTER 7
CONCLUSION

166

7.1 Introduction
The literature review showed that there was limited statistically sound research on cost
overruns and time delays in construction projects in developing countries. This study attempted
to fill gaps, through the case-study of highway and bridge projects in Cameroon. The study was
both quantitative and qualitative in nature, providing cost and time overrun rates from contract
data and an analysis of their causes through a survey of construction professionals in the casestudy country. Literature review was conducted, research questions established, and data was
collected and analyzed. Results were provided and guidelines suggested for improving cost and
time performance of construction projects in Cameroon and they are believed by the researcher
to apply in other developing nations.
7.2 Research Objectives
This thesis aimed to statistically describe cost overruns and time delays for highway and
bridge projects in Cameroon, determine their major causes and suggest improvements to reduce
project shortcomings. Contract data were collected in Cameroon for the period 1994-2009 and
construction professionals surveyed in the same country.
Literature review was conducted to identify studies of cost overruns and time delays in
construction projects. Studies were found which described surveys of professionals to determine
the causes of cost overruns and time delays, and well as statistical studies of cost overrun rates,
mainly for Europe and North America. The studies suggested remedies for cost and time
overruns.
MS Excel was used to create electronic files for input of 5,000 contracts and change order
references which was initially available in hard copy only. Contracts and change order references
signed by MINTP during the period 1994-2009 were input, sorted, and then change orders were

167

attached to corresponding contracts. Data which was not related to highway and bridge projects
was excluded for analysis. Statistical significance was sought during data analysis.
Similarly, SPSS and MS Excel were used to report and analyze survey data which was used
to classify the causes of cost overruns and time delays in five categories using a Likert scale for
project phases including: Planning and Programming, Design Process, Bidding Phase, Project
Implementation, Project Control and ex post Evaluation. Data was codified to ease electronic
reporting and statistical analysis. Frequency analysis and cross tabulations were performed to
rank the causes and investigate the correlation among variables.
Detailed tables and figures were used to illustrate results found, and guidelines suggested to
improve cost and time performance of highway and bridge projects in Cameroon. These
guidelines likely have application in other countries, and this could be subject of further research.
7.3 Summary of the Research
For this research, a total of 3,868 contracts relating to highway and bridge projects and 700
related change orders were reported, out of which a sample of 394 with cost or time overruns
were studied. It was determined that cost overruns and time delays varied with the type of
project, project ownership or funding source, and project size.
Project Type
Five types of project were studied, including: Road Construction/Maintenance, Work
Supervision, Bridges and Structures, Design/Technical Studies- Technical Assistance, and
Mowing Roadsides. Work supervision had the highest average rate of cost overruns of 22.93%
on average, followed by Road Construction/Maintenance with 10.43%.

168

Project Ownership
The main sources of project funding at MINTP were Cameroon’s Government, African
Development Bank, European Union, World Bank, France, Islamic Development Bank, OPEC
Funds, Koweitian Funds, Saudian Funds, and HIPC Funds. Projects funded by the European
Union had the highest cost overrun rate of 26.51% on average.
Project Size
The research suggested that cost overruns and time delays, in relative value or percentage,
decreased when the project size increased. However, low significance was observed.
Furthermore, the size of cost overruns, in monetary value increased with project size and high
significance was observed in this latter case.
Project Duration
Time overrun rates decreased when project durations increased, with strong significance. The
same result was observed for the relationship between project durations and cost overrun rates.
Contractor Familiarity with Agency
No correlation or model could be established during this study between contractor familiarity
with MINTP and cost overruns, time delays or change orders.
Relationship between Cost Overrun Rates and Time Overrun Rates
It was found that cost overrun rates increased when time overrun rates increased.
Causes of Cost Overruns and Time Delays
Eighty four valid responses out of 100 initially sent to professionals in Cameroon were
received, and analyzed. From the survey analysis, the following factors ranked highest as
important causes of cost overruns and time delays in Cameroon:

169

1. Negligence of Site Visits Before/During the Bidding Process-Unknown Site Conditions
2. Weak and insufficient technical studies
3. Lack of Project Planning/Programming
4. Underestimating of cost estimates and schedules/ Overestimating of Benefits
5. Lack of Equipment
6. Bidding Procedures
Considering project development steps, the bidding phase was found to be most likely
involved with project overruns.
This study neither confirmed expectations that cost overrun rates were higher in developing
countries (Flyvbjerg et al., 2003b) nor that costs were overestimated and schedules were
optimistic as indicated in the literature (Gamez and Touran, 2010). Instead, comparable and even
lower cost and time overruns were found.
Also, this study suggests that project overrun rates and sizes should be differentiated, because
they have different relationships with project size and project duration.
Guidelines
Results from contract data analysis, the survey, the literature and MINTP reports were
discussed, and guidelines were suggested to reduce cost overruns and time delays for highway
and bridge projects in developing countries, and specifically Cameroon.
Given the complexity observed in the project development processes, guidelines were aimed
to streamline processes at MINTP and partnering agencies, and to adapt them to the socioeconomical context of Cameroon. However, the researcher believes that these guidelines have
application in other developing nations.

170

7.4 Further Research
After this study, further research is needed to address its limitations. Some interesting
questions could be investigated, based on the contract files and survey responses. Seeking the
impact of geographic regions in Cameroon on cost and time performance would provide more
insight. In addition, road construction contracts and road maintenance contracts could be split
and studied separately for more precision on their overruns. Similarly, government projects could
be aggregated by budgetary items before study: procedures differ for the Road Fund and other
government budgetary sources.
Furthermore, ranking the survey responses by profession and by sector would provide
interesting findings.
Lastly, further studies examining construction project overrun rates and sizes for other
developing countries and testing the validity of guidelines in other countries would provide more
stepping stones towards the understanding of cost overruns and time delays in developing
countries.
7.5 Chapter Summary
This chapter summarized the research and presented the findings from the data analysis.
Areas for further research were also identified.
Lessons from Cameroon were used to suggest guidelines to streamline processes and to adapt
them to a local context, for reducing cost overruns and time delays in highway and bridge
projects.

171

APPENDICES

172

Appendix 1
Abstract in French

173

RESUME
SURCOUTS ET HORS-DELAIS DANS LES PROJETS D’INFRASTRUCTURES
ROUTIERES ET DE PONTS DANS LES PAYS EN DEVELOPPEMENT EXPERIENCES DU CAMEROUN
Par
Bertin Bella Akoa
La performance en termes de couts et délais est une préoccupation pour les responsables de
projet de construction, particulièrement pour les projets de routes et de ponts à cause de
l’incertitude caractérisant ces derniers. En dépit des innovations technologiques dans le
management des projets, peu d’améliorations ont été enregistrées dans les performances en
termes de couts et délais des projets de transport depuis quatre-vingt ans (Flyvbjerg, 2008).
Pour les pays en développement, des études statistiquement significatives décrivant les
surcouts et hors-délais sont nécessaires, desquelles des solutions appropriées à ce problème
seraient trouvées. Cette recherche a pour but de combler ce vide, à travers l’étude de cas du
Ministère des Travaux Publics (MINTP) du Cameroun. La littérature scientifique sur les surcouts
et hors-délais a été revue, des données de contrats chronologiques collectées, et une enquête
scientifique administrée à des professionnels de la construction au Cameroun.
En résultat, il fut établit que les marchés de contrôle des travaux et les projets financés par
l’aide au développement avaient enregistré les taux les plus élevés de surcouts. Aussi, les projets
les plus larges disposaient des plus volumineux surcouts. Les taux de surcouts ou hors-délais
décroissaient quand les montants ou les durées de projet augmentaient. La négligence des visites
de sites pendant les études techniques et pendant la passation des marchés de travaux était la
principale cause de surcouts et hors-délais pour le MINTP. Les causes de surcouts et hors-délais
ont été trouvées au niveau de toutes les phases de développement des projets, particulièrement au
niveau de l’étape de la passation des marchés.
174

Appendix 2
Socio-Economic Facts of Cameroon

175

CHAD

Maroua
1
0
Garoua
9
NIGERIA

Ngaoundere
7

8

CENTRAL
AFRICAN
REPUBLIC

Bamenda
6
5
Buea

Bafoussam
Bertoua
3

4
Douala

2

Yaounde
1
Ebolowa

EQUATORIAL
GUINEA

GABON

CONGO

Figure A2.1 Map of Cameroon and Socio Economic Facts (Derived from
http://www.prc.cm/index_fr.php?link=b , Accessed 10/28/2010)

176

Legend:
Region’s Limit
Regional City
Large City

(10) Far Northern Region
Population: 2,553,389 inhbt
Area: 34,263 km2
Number of Divisions: 06
Population Density: 74.52 inhbt/km2
Road Network: 5,384 km
(9) North Region
Population: 1,145,038 inhbt
Area: 66,090 km2
Number of Divisions: 04
Population Density: 17.33 inhbt/km2
Road Network: 4,787 km
(8) Adamaoua Region
Population: 681,362 inhbt
Area: 63,701 km2
Number of Divisions: 05
Population Density: 10.7 inhbt/km2
Road Network: 4,255 km

(7) North West Region
Population: 1,702,559 inhbt
Area: 17,300 km2
Number of Divisions: 07
Population Density: 98.41 inhbt/km2
Road Network: 4,504 km
(5) South West Region
Population: 1,153,125 inhbt
Area: 25,410 km2
Number of Divisions: 06
Population Density: 45.38 inhbt/km2
Road Network: 2,991 km

(3) Center Region
Population: 2,272,259 inhbt
Area: 68,953 km2
Number of Divisions: 10
Population Density: 32.96 inhbt/km2
Road Network: 11,036 km
Capital City : Yaounde

(6) West Region
Population: 1,843,518 inhbt
Area: 13,892 km2
Number of Divisions: 08
Population Density: 132.7 inhbt/km2
Road Network: 4,391 km

(2) East Region
Population: 711,651
Area: 109,002 km2
Number of Divisions: 04
Population Density: 6.53 inhbt/km2
Road Network: 4,974 km

(4) Littoral Region
Population: 1,861,463inhbt
Area: 20, 248 km2
Number of Divisions: 04
Population Density: 91.93 inhbt/km2
Road Network: 2,979 km

(1) South Region
Population: 514,336 inhbt
Area: 47,191 km2
Number of Divisions: 04
Population Density: 10.9 inhbt/km2
Road Network: 4,501 km

177

Appendix 3
Survey Form - English Version

178

Michigan State University
School of Planning, Design and Construction
Construction Management Program
PARTICIPANT CONSENT FORM
Construction Professionals
COST OVERRUNS AND TIME DELAYS IN HIGHWAY AND BRIDGE PROJECTS
IN DEVELOPING COUNTRIESEXPERIENCES FROM CAMEROON
Principal Investigator: Tim Mrozowski
Secondary Investigator: Bertin Bella Akoa

Survey
The School of Planning, Design and Construction at Michigan State University is conducting research to
evaluate cost overrun and time delay of highway and bridge projects in developing countries. Cost and time
performances of projects are indicators of efficiency in project development. This research aims to improve cost and
time performances of highway and bridge projects in developing countries, and specifically in the case-study of
Cameroon.
As a participant in this research, you are being asked to complete a survey questionnaire, relating to your
experience in cost overrun and time delay issues in highway and bridge infrastructure projects in Cameroon. You
must be at least 18 years old to participate in this research. Your participation in this research project is completely
voluntary. You have the right to say no. If you are uncomfortable, you may change your mind at any time and
withdraw from the survey. You may choose not to answer specific questions or to stop participating at any time.
Whether you choose to participate or not will have no effect on your grade or evaluation. Your privacy will be
protected to the maximum extent allowable by law. Your name and title will not be asked during this survey and will
not be used in any publication. The estimated time to complete this survey is approximately 15 minutes. As a
participant, you may request a copy of this consent letter for your records.
This research project is not funded. The researchers are employed by Michigan State University and the
data collected will be used for a graduate Master’s thesis.
If you have concerns or questions about this study, such as scientific issues, how to do any part of it, or to
report an injury, please contact:
Tim Mrozowski, A.I.A., LEED® AP
Professor of Construction Management, School of Planning, Design and Construction, Michigan State University,
102B H.E. Bldg., East Lansing, MI-48824, USA, Email: mrozowsk@egr.msu.edu, Phone number : +1
517.353.0781.
Bertin Bella Akoa
Graduate Student, Construction Management Program
School of Planning, Design and Construction, Michigan State University, 112 H.E. Bldg., East Lansing, MI-48824,
USA. Email: akoabert@msu.edu, Phone numbers: +1 517.505.8618, in Cameroon: 99.94.41.73
If you have questions or concerns about your rights as a research participant, please feel free to contact:
Judy McMillan, CIP
IRB Director, Michigan State University, 205B Olds Hall, MI-48824, USA. Email: mcmill12@ora.msu.edu, Phone
number: 517-432-4502
You indicate your voluntary agreement to participate by completing and returning this survey.

179

-

Please, Check your Profession



Manager



Engineer



Accountant



Other, Specify______________________________________________________
-

Your Sector in the Construction Industry



Government



Contractor



Consultant



Finance



Donor



Other,

Specify_____________________________________

180

Please, Circle your Answer to Each
Question
The causes of cost overruns and time
delays in highway and bridge
infrastructure projects in Cameroon are:
Planning and Programming
Lack of Project Planning/Programming
Inadequate Project Planning/Programming
Weaknesses during the land takings process
Expropriation costs
Legal environmental requirements
Design Process
Weak and insufficient technical studies
Underestimating of cost estimates and
schedules/ Overestimating of Benefits
Poor project implementation strategies
Mistakes and discrepancies in documents
Bidding Phase
Bidding Procedures
Duration of the Period of Bidding
The Lowest Bid Price System:
Unreasonable adjustment of project cost by
contractors

Strongly
Agree

Agree

Neither

Disagree

Strongly
Disagree

1
1
1
1
1

2
2
2
2
2

3
3
3
3
3

4
4
4
4
4

5
5
5
5
5

1

2

3

4

5

1

2

3

4

5

1
1

2
2

3
3

4
4

5
5

1
1
1

2
2
2

3
3
3

4
4
4

5
5
5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1
1
1
1

2
2
2
2

3
3
3
3

4
4
4
4

5
5
5
5

1

2

3

4

5

1
1
1
1
1
1

2
2
2
2
2
2

3
3
3
3
3
3

4
4
4
4
4
4

5
5
5
5
5
5

Project Implementation
Negligence of Site Visits Before/During the
Bidding Process- Unknown Site Conditions.
Mismanagement Due to Inexperienced
Supervisors.
Supervisor and Contractor Claims and
Disputes
Many Stakeholders
Poor Communication Among Contract
Stakeholders
Unethical Activities And Kickbacks
Equivocal/Unclear Contracts
Changes in Scope of Contracts
The Displacement of Existing Networks
Construction Errors and On Site Testing
Approval
Building on unexpected archaeological sites
Shortages of Materials
Material Price Fluctuation
Methods of Payment
Lack of Equipment
Weather Conditions

181

Political Tensions/Insecurity
Project Control and ex post Evaluation
No Action Taken After Contract Progress
Reports
Periods of Inspection and Testing After
Contract Completion
Lack of Contract ex post Evaluation
Negligence of Past Experiences

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1
1

2
2

3
3

4
4

5
5

Comments and Others:
How can cost overruns
and time delays be
reduced?

182

Appendix 4
Survey Form - French Version

183

Michigan State University
School of Planning, Design and Construction
Construction Management Program
FORMULAIRE DE CONSENTEMENT DU PARTICIPANT
Professionnels de la Construction
SURCOUTS ET HORS-DELAIS DANS LES PROJETS
D’INFRASTRUCTURE ROUTIERE ET DE PONT DANS LES PAYS EN DEVELOPPEMENTEXPERIENCES DU CAMEROUN
Enquêteur Principal: Tim Mrozowski
Enquêteur Secondaire: Bertin Bella Akoa

Enquête Scientifique
L’Ecole de Planification, Design et Construction du Michigan State University aux Etats-Unis d’Amérique
conduit une recherche pour évaluer les surcoûts et hors-délais dans les projets routiers et de ponts des pays en
développement. Les performances en termes de temps et de coût des projets sont des indicateurs d’efficacité dans le
développement des projets. Le but de cette recherche est d’améliorer les performances de coût et de temps des
projets routiers et de ponts dans les pays en développement, et spécifiquement dans le cas du Cameroun.
En tant que participant à cette recherche, Il vous est demandé de compléter un questionnaire relatif à votre
expérience dans les problèmes de surcoûts et de délais dans les projets routiers et de ponts du Cameroun. Vous
devez avoir au moins 18 ans pour participer à cette recherche. La participation à ce projet de recherche est
complètement volontaire. Vous avez le droit de dire non. Vous pouvez changer d’avis à tout moment et vous retirer
de l’enquête. Vous pouvez choisir de ne pas répondre à des questions spécifiques ou d’arrêter votre participation à
n’importe quel moment. Que vous y participiez ou non n’affectera en rien votre évaluation. Votre confidentialité
sera protégée au maximum possible admissible par la loi. Vos noms et titres ne seront pas demandés pendant cette
enquête et ne seront divulgués dans aucune publication. Compléter ce questionnaire prendra environ 15 minutes. En
tant que participant, vous pouvez demander une copie de ce formulaire de consentement.
Ce projet de recherche n’est pas financé. Les chercheurs sont employés par Michigan State University et
les données collectées seront utilisées pour une thèse de masters.
Si vous avez des inquiétudes ou des questions à propos de cette étude, tels que des problèmes d’ordre
scientifique, comment participer à n’importe laquelle des parties, ou pour reporter une offense, prière de contacter:
Tim Mrozowski, A.I.A., LEED® AP
Professor of Construction Management, School of Planning, Design and Construction, Michigan State University,
102B H.E. Bldg., East Lansing, MI-48824, USA, Courriel: mrozowsk@egr.msu.edu, Télephone: +1 517.353.0781.
Bertin Bella Akoa
Graduate Student, Construction Management Program
School of Planning, Design and Construction, Michigan State University, 112 H.E. Bldg., East Lansing, MI-48824,
USA. Courriel: akoabert@msu.edu, Télephone: +1 517.505.8618, au Cameroon: 99.94.41.73
Si vous avez des questions ou des inquiétudes à propos de vos droits en tant que participant à cette recherche, s’il
vous plaît, soyez libre de contacter:
Judy McMillan, CIP
IRB Director, Michigan State University, 205B Olds Hall, MI-48824, USA. Courriel: mcmill12@ora.msu.edu,
Télephone: 517-432-4502
Vous indiquez votre accord volontaire de participer à cette étude en complétant et en retournant ce questionnaire.

184

-

SVP, Cochez Votre Profession



Coordination/Direction



Ingénieur/Cadre Technique



Comptable /Cadre Financier



Autre, Précisez______________________________________________________
-

Votre secteur dans l’industrie routière :



Administration



Entrepreneur



Consultant



Finance



Bailleur de Fonds,



Autre, Précisez_____________________________________

185

SVP, Encerclez Votre Réponse à Chaque
Question

Entièrement
d’ Accord

D’ Accord

Indécis

Pas
d’Accord

Entièrement
Pas
d’Accord

Les causes de surcoûts et hors délais
dans les projets d’infrastructures
routières et de ponts au Cameroun
sont :
Planification et Programmation
Insuffisance de
Planification/Programmation des projets
Planification/Programmation des projets
non adéquats
Insuffisances Pendant les Processus
d’Expropriation
Coût des Expropriations
Exigences des textes sur la Protection de
l’environnement
Etudes Techniques
Faiblesse et insuffisance des études
techniques
Sous-évaluation des coûts et calendriers
d’activités/Surestimation des bénéfices.
Faibles stratégies d’exécution des projets
Erreurs et incohérences dans les documents
d’exécution
Passation des Marchés
Procédures de passation de marchés
Période de la Passation des marchés
Le système du moins disant
Ajustement des coûts de projets non
raisonnable par les entreprises.
Réalisation des Travaux :
Négligence des Visites de Site
Avant/Pendant la Passation des marchés:
Conditions des sites de projets inconnues.
Inexpérience des missions de contrôle
Plaintes et Disputes des entreprises et
missions de contrôle
Plusieurs Parties Prenantes
Faible communication entre les parties
prenantes des contrats
Activités non éthiques et “retours
d’ascenseur”
Contrats Equivoques/Flous
Changements dans l’étendue des contrats
Déplacement des réseaux existants
Erreurs d’Exécution et tests/approbation
des travaux sur site

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186

Travaux sur des sites archéologiques
inattendus
Manque des matériaux
Variation des prix des matériaux
Méthodes de paiement
Manque d’Engins
Conditions Météorologiques
Tensions Politiques / Insécurité
Suivi et Evaluation ex post des projets
Aucune Action entreprise après les
rapports sur l’évolution des contrats
Période de Contrôle et d’Essai après la
réception provisoire des travaux
Absence d’Evaluation ex post des Travaux
Négligence des Expériences Antérieures

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Commentaires et Autres:
Comment réduire les
surcoûts et les projets
hors délais ?

187

Appendix 5
Cost and Time Overruns – Details of Regression Analyses

188

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.068308111
R Square
0.004665998
Adjusted R
Square
0.004382493
Standard Error 0.382866589
Observations
112
ANOVA
df
Regression
Residual
Total

Intercept
19104089

Significance
SS
MS
F
F
1 0.075589824 0.07559 0.515666 0.474218786
110 16.12455075 0.146587
111 16.20014057

Standard
Error
t Stat
P-value
Lower 95%
0.10392793 4.216757 5.11E-05 0.232278028
-4.40114E-1.1706E-09 1.63013E-09
-0.7181 0.474219
09

Coefficients
0.438238792

Upper
95%
0.6442
2.06E09

Lower
90.0%
0.265841

Upper
90.0%
0.610637

-3.9E-09

1.53E-09

Table A5.1 Correlation - Significance for the Relationship between Project Size and Cost Overrun Rate Project Size under 100,000,000 XAF

189

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.287399
R Square
0.082598
Adjusted R
Square
0.074025
Standard
Error
0.334771
Observations
109
ANOVA
df
1
107
108

SS
MS
F
1.079672 1.079672 9.633761
11.99167 0.112072
13.07135

Coefficients
Intercept
0.769275
1.01E+08
-2.5E-09

Standard
Error
t Stat
P-value
0.130287 5.904455 4.23E-08
7.95E-10 -3.10383 0.002444

Regression
Residual
Total

Significance
F
0.002444

Upper
Lower 95%
95%
0.510996 1.027554
-4E-09 -8.9E-10

Lower
90.0%
0.5531
-3.8E-09

Upper
90.0%
0.98545
-1.1E-09

Table A5.2 Correlation - Significance for the Relationship between Project Size and Cost Overrun Rate Project Size between 100,000,000-250,000,000 XAF

190

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.031039
R Square
0.000963
Adjusted R
Square
-0.01079
Standard Error
0.234026
Observations
87
ANOVA
df
Regression
Residual
Total

Intercept
2.51E+08

Significance
SS
MS
F
F
1 0.004489217 0.004489217 0.081967384
0.775345
85 4.65530841 0.054768334
86 4.659797627

Standard
Coefficients
Error
t Stat
P-value
0.210172 0.084888649 2.475858118 0.01527549
5.57E-11 1.94684E-10 0.286299466 0.775345406

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.041391 0.378954 0.069 0.351340249
-3.3E-10 4.43E-10 -3E-10 3.79493E-10

Table A5.3 Correlation - Significance for the Relationship between Project Size and Cost Overrun Rate Project Size between 250,000,000-700,000,000 XAF

191

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.032041
R Square
0.001027
Adjusted R
Square
-0.01681
Standard
Error
0.180853
Observations
58
ANOVA
df
Regression
Residual
Total

Significance
SS
MS
F
F
1 0.001882 0.001882 0.057550141 0.811286765
56 1.831633 0.032708
57 1.833515

Standard
Lower
Upper
Coefficients
Error
t Stat
P-value
Lower 95%
Upper 95%
90.0%
90.0%
Intercept
0.184266 0.080016 2.302858 0.025024891 0.023974266 0.344558242 0.050437143 0.318095366
-1.58224E-1.34897E7.01E+08
-1.7E-11 7.05E-11
-0.2399 0.811286765
10 1.24381E-10
10 1.01053E-10
Table A5.4 Correlation - Significance for the Relationship between Project Size and Cost Overrun Rate Project Size between 700,000,000-2,000,000,000 XAF

192

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.08494241
R Square
0.007215213
Adjusted R
Square
0.058970439
Standard
Error
0.122200616
Observations
17
ANOVA
df
Regression
Residual
Total

SS
1 0.001627916
15 0.223994858
16 0.225622774

Coefficients
Intercept
2012608420

Standard
Error

0.143127857 0.125759514
-1.26199E11 3.82221E-11

MS
0.001627916
0.014932991

t Stat

F
0.10901476

P-value

1.138107582 0.272927911
0.330173833 0.745834912

Significance
F
0.745835

Lower 95%

Upper
95%

Lower
90.0%

-0.12492 0.411178 0.07733 0.363590618
-9.4E-11 6.88E-11

-8E-11 5.43853E-11

Table A5.5 Correlation - Significance for the Relationship between Project Size and Cost Overrun Rate Project Size between 2,000,000,000- 5,000,000,000 XAF

193

Upper
90.0%

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.705445253
R Square
0.497653005
Adjusted R
Square
0.330204007
Standard
Error
0.133523903
Observations
5
ANOVA
df
Regression
Residual
Total

1
3
4

SS
MS
F
0.05298612 0.05298612 2.971968
0.053485898 0.017828633
0.106472018

Coefficients

Standard
Error

Intercept

0.157263853

0.08819686 1.783100363

5414904080

5.31817E-12

t Stat

P-value
0.17258

3.08489E-12 1.723939572 0.183188

Significance
F
0.183188

Lower 95%

Upper
95%

Lower
90.0%

-0.12342 0.437946 0.050295412 0.364823
-1.94171E-4.5E-12 1.51E-11
12 1.26E-11

Table A5.6 Correlation - Significance for the Relationship between Project Size and Cost Overrun Rate Project Size over 5,000,000,000 XAF

194

Upper
90.0%

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.034602242
R Square
0.001197315
Adjusted R
Square
0.001357167
Standard Error 0.318215119
Observations
393
ANOVA
df
Regression
Residual
Total

Significance
SS
MS
F
F
1 0.047462121 0.047462 0.468711 0.493986186
391 39.59299691 0.101261
392 39.64045903

Standard
Upper
Coefficients
Error
t Stat
P-value
Lower 95%
95%
Intercept
0.298852578 0.016460313 18.15595 7.26E-54 0.266490785 0.331214
-3.36812E-1.30404E23616872
12 4.91966E-12 -0.68463 0.493986
11 6.3E-12

Lower
90.0%
0.271713

Upper
90.0%
0.325992

-1.1E-11

4.74E-12

Table A5.7 Correlation - Significance for the Relationship between Project Size and Cost Overrun Rate - All Project Sizes

195

SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.322819225
R Square
0.104212252
Adjusted R
Square
0.096142092
Standard
Error
20671371.98
Observations

113

ANOVA
df
Regression
Residual
Total

SS
MS
F
1 5.51792E+15 5.52E+15 12.91328
111 4.74309E+16 4.27E+14
112 5.29488E+16

Coefficients
Intercept
X Variable 1

Standard
Error

2779051.115
0.311677885

5507325.087
0.086733659

Significance
F
0.0004879

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.50461 0.614833 8134081.197 13692183 6355934 11914036
3.593506 0.000488 0.13980935 0.483546 0.167813 0.455543
t Stat

P-value

Table A5.8 Correlation - Significance for the Relationship between Project Size and Cost Overrun Size Project Size under 100,000,000 XAF

196

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.059083
R Square
0.003491
Adjusted R
Square
-0.00574
Standard Error

49166870

Observations
ANOVA

110
df

Regression
Residual
Total

SS

MS

1 9.15E+14 9.15E+14
108 2.61E+17 2.42E+15
109 2.62E+17

Coefficients
Intercept

Standard
Error

66712844 18903538

X Variable 1

-0.07114

0.115657

t Stat
3.529119
-0.61508

F
Significance F
0.37832
9
0.539793

Upper
95%

Lower
90.0%

P-value Lower 95%
0.00061
4
29242751 1.04E+08 35350264
0.53979
3
-0.30039 0.158113 -0.26302

Upper 90.0%
98075424

Table A5.9 Correlation - Significance for the Relationship between Project Size and Cost Overrun Size Project Size between 100,000,000-250,000,000 XAF

197

0.120746

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.332976
R Square
0.110873
Adjusted R
Square
0.100535
Standard
Error
97063396
Observations
88
ANOVA
df
Regression
Residual
Total

SS
1 1.01035E+17
86 8.10232E+17
87 9.11267E+17

Coefficients
Intercept
X Variable 1

-1.2E+07
0.261978

Standard
Error
34749422.91
0.079998916

MS
F
1.01035E+17 10.72412747
9.4213E+15

t Stat

P-value

0.332798124 0.740096577
3.274771361 0.001524862

Significance
F
0.001525

Lower 95%

Upper
95%

-8.1E+07 57515024
0.102946 0.421011

Lower
90.0%

-7E+07 46215597.04
0.129 0.394997593

Table A5.10 Correlation - Significance for the Relationship between Project Size and Cost Overrun Size Project Size between 250,000,000-700,000,000 XAF

198

Upper
90.0%

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.1725
R Square
0.029756
Adjusted R
Square
0.012734
Standard Error
2.25E+08
Observations
59
ANOVA
df
Regression

SS
1

57
58
Coefficient
s

Residual
Total

8.84E+16
2.88E+18
2.97E+18
Standard
Error

MS
8.84E+1
6
5.06E+1
6

F

Significance
F

1.74811842

0.191394734

t Stat

P-value

Lower 95%

0.55274188
3

- 25458
137615890.8 0724.5

0.19139473
4

- 0.2885
0.059038432 20638

Intercept

58482417

97928435

0.59719
5

X Variable 1

0.114741

0.086783

1.32216
4

Upper
95%

Lower
90.0%
1052567
54.7
0.030362
225

Upper
90.0%
222221588.
5
0.25984443
1

Table A5.11 Correlation - Significance for the Relationship between Project Size and Cost Overrun Size Project Size between 700,000,000-2,000,000,000 XAF

199

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.273113514
R Square
0.074590991
Adjusted R
Square
0.016752928
Standard
Error
367507700.6
Observation
s
18
ANOVA
df
Regression
Residual
Total

SS
1
16
17

1.74183E+17
2.16099E+18
2.33517E+18

Coefficients

Standard Error

-81421634.5

349591998.7

X Variable 1 0.122816231

0.108148237

Intercept

MS

F

1.74183E+17 1.289652306
1.35062E+17

t Stat

P-value

Signific
ance F
0.27283
7

Lower
95%

0.232904743 0.818788658 8.2E+08
1.135628595 0.272837476 0.10645

Upper
95%

Lower
90.0%

6.6E+08

-6.9E+08

0.35208

-0.066

Upper
90.0%
528925
329.5
0.3116
30473

Table A5.12 Correlation - Significance for the Relationship between Project Size and Cost Overrun Size Project Size between 2,000,000,000-5,000,000,000 XAF

200

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.996488674
R Square
0.992989678
Adjusted R
Square
0.991237098
Standard
Error
927915252.3
Observations
6
ANOVA
df
Regression
Residual
Total

1
4
5

Intercept
X Variable 1

Coefficients
-2445621113
0.48465726

SS
MS
F
4.87847E+20 4.88E+20 566.5872
3.44411E+18 8.61E+17
4.91291E+20
Standard
Error
t Stat
P-value
533305235.8 -4.58578 0.010139
0.020361105 23.80309 1.85E-05

Significance
F
1.85E-05

Lower 95%
-3.9E+09
0.428126

Upper 95%
-964928401.3
0.541188749

Lower
90.0%
-3.6E+09
0.441251

Table A5.13 Correlation - Significance for the Relationship between Project Size and Cost Overrun Size Project Size over 5,000,000,000 XAF

201

Upper
90.0%
-1.3E+09
0.528064

SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.96868324
R Square
0.938347219
Adjusted R
Square
0.938189942
Standard
Error
341640434.2
Observations
394
ANOVA

Regression
Residual
Total

Intercept
X Variable 1

Significance
df
SS
MS
F
F
1 6.96363E+20 6.96E+20 5966.188 2.8151E-239
392 4.57535E+19 1.17E+17
393 7.42116E+20

Coefficients
118241778.7
0.407948748

Standard
Error
17648512.91
0.005281498

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
-6.69982 7.27E-11 152939357.1 8.4E+07 1.5E+08 8.9E+07
77.24111 2.8E-239 0.397565143 0.418332 0.399241 0.416657
t Stat

P-value

Table A5.14 Correlation - Significance for the Relationship between Project Size and Cost Overrun Size - All Project Sizes

202

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.113201
R Square
0.012815
Adjusted R
Square
0.003921
Standard
Error
0.493304
Observations
113
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
111
112

SS
MS
F
0.350637 0.350637 1.440881
27.01176 0.243349
27.3624

Coefficients
0.636005
-2.5E-09

Standard
Error
t Stat
P-value
0.131428 4.839208 4.24E-06
2.07E-09 -1.20037 0.232552

Significance
F
0.232552

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.375573 0.896438 0.418007 0.854004
-6.6E-09 1.62E-09 -5.9E-09 9.49E-10

Table A5.15 Correlation - Significance for the Relationship between Project Size and Time Overrun Rate Project Size under 100,000,000 XAF

203

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.153642
R Square
0.023606
Adjusted R Square
0.014565
Standard Error
0.534748
Observations
110
ANOVA
df
Regression
Residual
Total

1
108
109

SS
MS
F
0.746649 0.746649 2.611071
30.88316 0.285955
31.62981

Coefficients
Intercept
X Variable 1

Standard
Error

0.22644

0.205598

2.03E-09

t Stat

P-value

Significance
F
0.109038

Lower 95%

Upper
95%

1.10137 0.273184

-0.18109 0.633971

1.26E-09 1.615881 0.109038

-4.6E-10 4.53E-09

Lower
90.0%

Upper
90.0%

0.11467 0.567545
-5.4E11 4.12E-09

Table A5.16 Correlation - Significance for the Relationship between Project Size and Time Overrun Rate Project Size between 100,000,000-250,000,000 XAF

204

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.130775
R Square
0.017102
Adjusted R
Square
0.005673
Standard
Error
0.451198
Observations
88
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
86
87

SS
MS
F
0.30463 0.30463 1.496371
17.50783 0.203579
17.81246

Coefficients
0.632046
-4.5E-10

Standard
Error
t Stat
P-value
0.161532 3.912815 0.000182
3.72E-10 -1.22326 0.224572

Significance
F
0.224572

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.31093 0.953161 0.363455 0.900636
-1.2E-09 2.84E-10 -1.1E-09 1.63E-10

Table A5.17 Correlation - Significance for the Relationship between Project Size and Time Overrun Rate Project Size between 250,000,000-700,000,000 XAF

205

SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations

0.075947
0.005768
-0.01167
0.346506
59

ANOVA
df
Regression
Residual
Total

1
57
58

Coefficients

Significance
SS
MS
F
F
0.039704 0.039704 0.330682
0.567521
6.843802 0.120067
6.883506
Standard
Error

t Stat

P-value

Intercept

0.181459

0.150867 1.202778 0.234035

X Variable 1

7.69E-11

1.34E-10 0.575049 0.567521

Lower 95%

Upper
95%

Lower
90.0%

-0.12065 0.483565 0.07079 0.433713
-1.5E-1.9E-10 3.45E-10
10
3E-10

Table A5.18 Correlation - Significance for the Relationship between Project Size and Cost Overrun Size Project Size between 700,000,000-2,000,000,000 XAF

206

Upper
90.0%

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.430368
R Square
0.185217
Adjusted R
Square
0.134293
Standard Error
0.612391
Observations
18
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

Significance
SS
MS
F
F
1 1.364004089 1.364004 3.637121
0.074622
16 6.000367976 0.375023
17 7.364372066

Standard
Coefficients
Error
t Stat
P-value
1.554991 0.582537639 2.669339 0.016793
-3.4E-10 1.80211E-10

-1.90712 0.074622

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.320066 2.789915 0.537948 2.572033496
-2.90573E-7.3E-10 3.83E-11 -6.6E-10
11

Table A5.19 Correlation - Significance for the Relationship between Project Size and Time Overrun RateProject Size between 2,000,000,000-5,000,000,000 XAF

207

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.002425
R Square
5.88E-06
Adjusted R Square
-0.24999
Standard Error
0.807158
Observations
6
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

Significance
SS
MS
F
F
1 1.53E-05 1.53E-05 2.35E-05
0.996362
4 2.606013 0.651503
5 2.606029

Standard
Coefficients
Error
t Stat
P-value
0.653563 0.463902 1.408839 0.231667
-8.6E-14 1.77E-11

-0.00485 0.996362

Lower 95% Upper 95%
-0.63443 1.941559917
-4.9E-11 4.90886E-11

Lower
Upper
90.0%
90.0%
-0.3354 1.64253
3.77E-3.8E-11
11

Table A5.20 Correlation - Significance for the Relationship between Project Size and Time Overrun Rate Project Size over 5,000,000,000 XAF

208

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.009202
R Square
8.47E-05
Adjusted R
Square
-0.00247
Standard Error
0.497715
Observations
394
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
392
393

Coefficients
0.462517
1.4E-12

Significance
SS
MS
F
F
0.008224 0.008224 0.033199
0.855516
97.10638 0.24772
97.11461
Standard
Error
t Stat
P-value
0.025711 17.98903 3.5E-53
7.69E-12 0.182205 0.855516

Upper
Lower 95%
95%
0.411968 0.513065
-1.4E-11 1.65E-11

Lower
90.0%
0.420126
-1.1E-11

Upper
90.0%
0.504908
1.41E-11

Table A5.21 Correlation - Significance for the Relationship between Project Size and Time Overrun Rate - All Project Sizes

209

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.029136
R Square
0.000849
Adjusted R Square
-0.01638
Standard Error
0.459847
Observations
60
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

Significance
SS
MS
F
F
1 0.01042 0.01042 0.049277
0.825105
58 12.26463 0.211459
59 12.27505

Standard
Coefficients
Error
t Stat
P-value
0.328187 0.185626 1.767999 0.082321
0.010214 0.046013 0.221985 0.825105

Upper
Lower
Lower 95%
95%
90.0%
-0.04338 0.699759 0.017903
-0.08189 0.102319
-0.0667

Upper
90.0%
0.638471
0.087127

Table A5.22 Correlation - Significance for the Relationship between Project Duration and Cost Overrun Rate Project Duration under 6 Months

210

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.000846
R Square
7.16E-07
Adjusted R
Square
-0.00526
Standard
Error
0.304409
Observations
192
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
190
191

SS
MS
F
1.26E-05 1.26E-05 0.000136
17.60635 0.092665
17.60636

Coefficients
0.31573
0.000193

Standard
Error
t Stat
P-value
0.120307 2.62437 0.009387
0.016565 0.011662 0.990708

Significance
F
0.990708

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.078421 0.553039 0.116873 0.514587
-0.03248 0.032868 -0.02719 0.027574

Table A5.23 Correlation - Significance for the Relationship between Project Duration and Cost Overrun Rate Project Duration between 6 Months - 12 Months

211

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.082645
R Square
0.00683
Adjusted R Square
-0.01344
Standard Error
0.242178
Observations
51
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
49
50

Coefficients
0.408532
-0.01007

SS
MS
F
0.019764 0.019764 0.336982
2.873855 0.05865
2.893619
Standard
Error
0.225446
0.017354

t Stat
P-value
1.81211 0.076099
-0.5805 0.564237

Significance
F
0.564237

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
-0.04452 0.861582 0.030561 0.786504
-0.04495
0.0248 -0.03917 0.019021

Table A5.24 Correlation - Significance for the Relationship between Project Duration and Cost Overrun Rate Project Duration between 12 Months - 24 Months

212

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.232905
R Square
0.054245
Adjusted R Square
0.04285
Standard Error
0.255902
Observations
85
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
83
84

Coefficients
0.756906
-0.01594

Significance
SS
MS
F
F
0.311749 0.311749 4.760544
0.031947
5.435339 0.065486
5.747088
Standard
Error
0.250816
0.007304

t Stat
P-value
3.01778 0.003381
-2.18187 0.031947

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.258044 1.255768 0.339695 1.174118
-0.03046 -0.00141 -0.02809 -0.00379

Table A5.25 Correlation - Significance for the Relationship between Project Duration and Cost Overrun Rate Project Duration between 24 Months - 36 Months

213

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.095714
R Square
0.009161
Adjusted R Square
-0.23855
Standard Error
0.200452
Observations
6
ANOVA
df
Regression
Residual
Total

1
4
5

Coefficients
Intercept
X Variable 1

Significance
SS
MS
F
F
0.001486 0.001486 0.036983
0.856868
0.160724 0.040181
0.16221
Standard
Error

t Stat

P-value

Lower 95%

Upper
95%

0.07786

0.64577

0.12057 0.909846

-1.71508 1.870805

0.002748

0.014288

0.19231 0.856868

-0.03692 0.042417

Lower
90.0%

Upper
90.0%

1.29882 1.454543
0.02771 0.033207

Table A5.26 Correlation - Significance for the Relationship between Project Duration and Cost Overrun Rate
- Project Duration over 36 Months

214

SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations

0.165265
0.027313
0.024831
0.313973
394

ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

SS
MS
F
1 1.085077 1.085077 11.00717
392 38.64301 0.098579
393 39.72809

Standard
Coefficients
Error
t Stat
P-value
0.355423 0.023985 14.81858 9.19E-40
-0.00434 0.001309 -3.31771 0.000992

Significance
F
0.000992

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.308268 0.402579 0.315878 0.394969
-0.00692 -0.00177
-0.0065 -0.00219

Table A5.27 Correlation - Significance for the Relationship between Project Duration and Cost Overrun Rate All Project Durations

215

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.154424
R Square
0.023847
Adjusted R Square
0.007017
Standard Error
0.520506
Observations
60
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

SS
MS
1 0.383878 0.383878
58 15.71371 0.270926
59 16.09759

Significance
F
F
1.41691
0.238762

Standard
Coefficients
Error
t Stat
P-value
0.966158 0.210112 4.598289 2.36E-05
-0.062 0.052083 -1.19034 0.238762

Upper
Lower
Lower 95%
95%
90.0%
0.545572 1.386744 0.614944
-0.16625 0.042259 -0.14906

Upper
90.0%
1.317372
0.025063

Table A5.28 Correlation - Significance for the Relationship between Project Duration and Time Overrun Rate Project Duration under 6 Months

216

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.122327
R Square
0.014964
Adjusted R Square
0.009779
Standard Error
0.528897
Observations
192
ANOVA

Regression
Residual
Total

Intercept
X Variable 1

Significance
df
SS
MS
F
F
1 0.807396 0.807396 2.886315
0.090972
190 53.14917 0.279732
191 53.95656
Standard
Coefficients
Error
t Stat
P-value
0.92514 0.209028 4.425915 1.62E-05
-0.0489 0.028781 -1.69892 0.090972

Upper
Lower
Lower 95%
95%
90.0%
0.512826 1.337454 0.579635
-0.10567 0.007875 -0.09647

Upper
90.0%
1.270645
-0.00132

Table A5.29 Correlation - Significance for the Relationship between Project Duration and Time Overrun Rate Project Duration between 6 Months - 12 Months

217

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.081822
R Square
0.006695
Adjusted R Square
-0.01358
Standard Error
0.253168
Observations
51
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
49
50

Coefficients
0.269608
-0.08553

Significance
SS
MS
F
F
0.021167 0.021167 0.330255
0.568138
3.140605 0.064094
3.161772
Standard
Error
t Stat
P-value
0.054615 4.936523 9.61E-06
0.148829 -0.57468 0.568138

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.159855 0.37936 0.178043 0.361172
-0.38461 0.213554 -0.33505 0.163991

Table A5.30 Correlation - Significance for the Relationship between Project Duration and Time Overrun Rate Project Duration between 12 Months - 24 Months

218

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.322939
R Square
0.10429
Adjusted R Square
0.093498
Standard Error
0.274437
Observations
85
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
83
84

Coefficients
0.999483
-0.02435

Significance
SS
MS
F
F
0.727845 0.727845 9.663904
0.002574
6.251217 0.075316
6.979063
Standard
Error
t Stat
P-value
0.268982 3.715796 0.000366
0.007833 -3.10868 0.002574

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.464488 1.534478 0.552053 1.446913
-0.03993 -0.00877 -0.03738 -0.01132

Table A5.31 Correlation - Significance for the Relationship between Project Duration and Time Overrun Rate Project Duration between 24 Months - 36 Months

219

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.077119
R Square
0.005947
Adjusted R Square
-0.24257
Standard Error
0.186561
Observations
6
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
4
5

Coefficients
0.333678
-0.00206

Significance
SS
MS
F
F
0.000833 0.000833 0.023932
0.884551
0.13922 0.034805
0.140052
Standard
Error
t Stat
P-value
0.601018 0.555189 0.608349
0.013298

-0.1547 0.884551

Upper
Lower 95%
95%
-1.33501 2.002371
-0.03898 0.034863

Lower
Upper
90.0%
90.0%
-0.9476 1.614956
0.03041 0.026291

Table A5.32 Correlation - Significance for the Relationship between Project Duration and Cost Overrun Rate Project Duration over 36 Months

220

SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations

0.376352
0.141641
0.139451
0.461141
394

ANOVA

Regression
Residual
Total

Intercept
X Variable 1

Significance
df
SS
MS
F
F
1 13.75541 13.75541 64.68537
1.05E-14
392 83.3592 0.212651
393 97.11461
Standard
Coefficients
Error
t Stat
P-value
0.676533 0.035227 19.20472 2.06E-58
-0.01547 0.001923 -8.04272 1.05E-14

Upper
Lower
Upper
Lower 95%
95%
90.0%
90.0%
0.607274 0.745791 0.618451 0.734614
-0.01925 -0.01169 -0.01864
-0.0123

Table A5.33 Correlation - Significance for the Relationship between Project Duration and Time Overrun Rate All Project Durations

221

Appendix 6
Survey Analysis Results –Frequencies

222

Valid Responses
Statistics
Profession
N

Valid

Inad_Plan_Pr
Lack_Pl_Prog
og
Weakness_Takings

Sector

84

84

84

84

0

Missing

84
0

0

0

0

Underestimati
Expropriation legal_Envir_R Weak_Tech_ ng_Cost_over Poor_Impl_St
_Costs
eq
Stud
_benf
ratg
N

Valid

84

84

84

84

0

Missing

84
0

0

0

0

Table A6.1 SPSS Output – Overview of Valid Responses
Frequency Tables
Profession
Cumulative
Frequency Percent Valid Percent
Percent
Valid Acc

4

4.8

4.8

4.8

Eng

59

70.2

70.2

75.0

Man

18

21.4

21.4

96.4

Oth

3

3.6

3.6

100.0

84

100.0

100.0

Total

Table A6.2 SPSS Output – Frequencies for the Variable “Profession”
Sector
Frequency Percent Valid Percent

Cumulative
Percent

Valid Cons

9

10.7

10.7

10.7

Cont

9

10.7

10.7

21.4

Dono

5

6.0

6.0

27.4

Fina

2

2.4

2.4

29.8

Gove

59

70.2

70.2

100.0

Total

84

100.0

100.0

Table A6.3 SPSS Output – Frequencies for the Variable “Sector”

223

Lack_Pl_Prog
Frequency Percent Valid Percent

Cumulative
Percent

Valid 1

22

26.2

26.2

26.2

2

35

41.7

41.7

67.9

3

10

11.9

11.9

79.8

4

16

19.0

19.0

98.8

5

1

1.2

1.2

100.0

84

100.0

100.0

Total

Table A6.4 SPSS Output – Frequencies for the Variable “Lack of Project
Planning/Programming”
Inad_Plan_Prog
Frequency Percent Valid Percent

Cumulative
Percent

Valid 1

15

17.9

17.9

17.9

2

36

42.9

42.9

60.7

3

14

16.7

16.7

77.4

4

17

20.2

20.2

97.6

5

2

2.4

2.4

100.0

84

100.0

100.0

Total

Table A6.5 SPSS Output – Frequencies for the Variable “Inadequate Project Planning
Programming”
Weakness_Takings
Cumulative
Frequency Percent Valid Percent
Percent
Valid 1

8

9.5

9.5

9.5

2

38

45.2

45.2

54.8

3

25

29.8

29.8

84.5

4

12

14.3

14.3

98.8

5

1

1.2

1.2

100.0

84

100.0

100.0

Total

Table A6.6 SPSS Output – Frequencies for the Variable “Weaknesses during the Land Taking
Process”

224

Appendix 7
“Proof of Concepts” Package - Suggestions

225

Proof of Concept-Validating Results
Introduction
Generally, when thesis research leads to suggested recommendations, guidelines or frameworks,
those suggestions should be tested in the context of the real world. The process of testing
suggestions is sometimes referred to as “Proof of Concept” or validation. Efforts to evaluate
proposed recommendations, frameworks or guidelines often use follow-up interviews, surveys,
questionnaires or focus groups to obtain feedback about the accuracy, usefulness, effectiveness
of recommendations or barriers and opportunities to their implementation. Once feedback is
obtained the researcher can then consider the feedback and decide whether to add, delete or
modify any original recommendations, guidelines or frameworks.
Due to reorganization occurring in MINTP during completion of the research on cost and time
overruns, it was not possible to conduct these “Proof of Concept” efforts. In the thesis the
researcher indicates that the recommendations suggested in this study should be discussed and
validated by the case study organization and suggests a sample of five to ten managers be
selected for obtaining feedback. The researcher also suggests a similar process can be undertaken
in developing countries’ other agencies, for the adoption of relevant thesis recommendations for
their organizations.
“Proof of concept” efforts should be conducted with qualified individuals who have the
experience and background with the subject, including the recommendations, guidelines, or
frameworks, being evaluated, to be effective.
“Proof of Concept” components should include:
1. An introductory background statement which summarizes the research sufficiently to
provide enough background to the respondent or interviewee so that they can effectively
evaluate the recommendations, guidelines or frameworks
2. Clear statement of the guidelines
3. A human subjects’ review from a qualified institutional review board to ensure proper
protections are in place for anyone who participates
4. A consent statement with proper protections from the sponsoring agency
5. Selection of qualified subjects for effective review
6. The survey instrument or questionnaire
7. Processes to administer, collect and analyze the data
Since the “Proof of Concept” process was not conducted during this research. Any Human
Subjects’ review process should be from the Human Subjects Institutional Review Board of any
subsequent sponsoring agency.

226

Suggested Proof of Concept Components
1. Consent form and Human Subjects Protections
The MINTP should prepare a consent form and appropriate protections for participating
respondents.
2. Background statement such as the following:
Research was conducted which targeted reducing cost overruns and time delays in
construction projects in developing countries. The research led to guidelines and
recommendations for measures which may help to reduce these overruns. Toward this
end you are being asked to review the guidelines and recommendations to gain your view
of their usefulness, appropriateness, identification of barriers, or opportunities for their
implementation and suggestions for improvement.
3. Listing of key recommendations:

R1

Organize and conduct seminars on transportation planning to help MINTP
improve the planning process

R2

Update MINTP’s road plan, and adoption of a transportation improvement
program

R3

Increase accountability at MINTP project managers

R4

Introduce cost conditions in consultant contracts for technical studies

R5

Include provisions for retainage and warranties in consultant contracts

R6

Standardize labor rates for all trades and equipment, so that the differences
among bids would be determined by the costs of materials

R7

Organize and conduct seminars on cost estimating and project scheduling

R8

Formalize scheduling of large projects through use of networks of activities

R9

Develop the use of sub-contracting for projects

R10

Use of force account utilizing the owner’s own forces for routine projects

R11

Adopt a project management approach for force account projects

R12

Provide training of MINTP personnel to improve contract administration

227

R13

Use force account for mowing projects, rural road maintenance, and unpaved
road maintenance

R14

Use outside work supervision only for projects which are very specialized or
large and when the benefits warrant its cost

4. To test the recommendations include the following, similar but not limited to survey or
interview questions.
Suggested Questions
1.

How well do you understand these recommendations for measures to help reduce
cost and time overruns on MITPP projects? (Cite specific recommendations.)

2.

Which recommendations would be most helpful in helping to reduce cost and
time overruns on projects? Explain.

3.

Which recommendations would be least helpful in helping to reduce cost and time
overruns on projects? Explain.

4.

What are the barriers for implementation of these recommendations during
project closeout in your organization? (Please refer to specific recommendations)
Explain.

5.

What organizational factors may influence implementation of these
recommendations?

6.

How helpful are these recommendations for your organization?

7.

Rank the importance of recommendations in helping to reduce cost and time
Overruns
o
o
o
o

8.

Very helpful
Very helpful
Less helpful
Not very helpful

Do you have any additional suggestions for improvement?

228

Appendix 8
Glossary

229

Glossary
Change Order: A change order is defined as a formal change to a contract which usually includes
an increase in work scope and in cost. The time scheduled to perform the work can also be
modified (O’Brien, 1998).
Contract Administration: It relates to the conduct of the project-related parties to a contract such
as relations with the contractor, communications, procedures, authority, duties of all the parties,
construction operations, coordination, planning and scheduling, payments, change orders,
disputes and claims, project closeout, final cleanup, administrative closeout. (Fisk, 1997)
Cost Condition: A stipulated statement in a design contract, to hold the design firm responsible
of the accuracy of the predicted cost of a project.
Cost Overrun: Also called “cost escalation,” it is the difference in cost between the final contract
cost and the contract award amount (Jahren and Ashe, 1990). In the long term, “cost overrun”
refers to the general increase of contract costs.
Constructor: Someone or a business entity who can physically build a facility or a manufacturer
who fabricates ordered objects (Pritchett, 2006).
Consultant: The architect or engineer, in general, who perform design or design related services
(Pritchett, 2006).
Contractor: “A business entity that enters into contracts to provide goods or services to another
party” (Pritchett, 2006).
Donor or lender: Organization making loans or donate funds to other parties.
Faulty Execution: Inability of agency’s or owner’s representatives to take appropriate decisions
for the implementation of the project, or to effectively coordinate the work (Jahren and Ashe,
1990).
Force-account system: A method of construction where the owner acts as a constructor, instead
of hiring a professional contractor to perform the work (Sears et al., 2008).
Optimism Bias: Tendency to expect the best about project outcomes in the decision-making
process, lowering cost estimates which would later result in higher actual costs than planned
(Flyvbjerg et al., 2002).
Plan: Adopted statement of policy, represented as text, maps, and graphics, used to guide public
and private actions impacting on the future. It helps decision makers to take informed decisions
which influence the long-range social, economic, and physical growth of a community
(Anderson L. T. et al., 2006).

230

Program: A set of projects to be implemented in a specified period, generally five years with
determined funding(s).
Project: An undertaking to construct a specific enhancement at a determined location or locations
(Anderson et al., 2008).
Right-of-Way: A linear corridor of land, generally taken from private owners, and destined to
transportation infrastructure such as roads, railways and other facilities (Anderson et al., 2008).
Scope Creep: Increase of project costs due to the tendency to accumulate many minor scope
changes (Shane et al., 2009).
Time Delay: Time period during which some part of the construction project has been extended
beyond the initial time, or the incident affecting the performance of an activity of the project
(Bramble and Callahan, 2000). For this study, time delay or time overrun is the total time
extension received by a contractor, compared to the initial contract duration.

231

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232

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