Analysis of Causes for Schedule Delay and Cost Overrun with Their Relationship in Bangladesh Construction Projects
- Alternative Title
- 방글라데시 건설 사업의 일정지연 및 비용초과 원인과 상호관계 분석
- Abstract
- 건설 산업은 국가 경제의 발전을 위한 중요한 요소를 제공하는 핵심 부문이지만 다양한 문제에 영향을 받는다. 건설 프로젝트에서 지연문제는 프로젝트 수행과 홍보 및 건설프로젝트에 악영향을 미치며 건설사업을 방해하는 전세계적인 중요한 문제이다. 특히, 일정지연은 공기, 공사비, 품질 및 안전등 건설사업에 부정적인 영향을 미치므로 일정지연의 원인과 적정공기 및 공사비추정은 사업의 타당성분석 등을 위한 건설프로젝트 초기단계에서 대단히 중요하다.
따라서 이번 연구는 (1) 방글라데시에서 현 건설 사업 일정 지연 및 비용초과에 대한 탐색적 연구를 하고, (2) 건설 프로젝트의 수행비용에 크다란 영향을 주는 일정지연의 주요 원인을 규명하고, (3) 프로젝트 참여그룹, 형식 및 규모 관점에서 일정지연원인을 연구하고, (4) 일정지연과 발생원인간의 잠재적 관계를 조사하고, (5) 일부선정 된 국가의 상위 5개 지연지연원인에 대한 비교 연구를 수행 하고, (6) 건설프로젝트에서 타당성분석도구로 사용하고자 시간-비용모형개발 을 하고, (7) 일부 선택된 국가들과의 시간-비용의 관계에 대한 비교 연구를 수행하는데 목적을 두었다.
이를 위하여 방글라데시에서 건설 프로젝트 관리 경험이 있는 전문가들에게 설문조사를 수행하였으며 수집된 48설문자료중 불완전한 자료는 일관성 높이기 위하여 삭제한 후 35개 변수를 분석하였다.
분석결과는 건설업계의 전문가들은 일정지연과 비용초과를 아주 중요하게 인식하는 것으로 나타났다. 빈도 및 심각도 지표를 통해 산출된 중요도에 기초하여 지연 원인의 순위에 따라 도출된 7 대 지연 원인은 (1) F2 단기간 건축 자재의 가격상승, (2) F33 정치 상황 (혁명 / 대중 파업), (3) F4 숙련되지 않은 노동자, (4) F21 ' 시공사의 현장 및 감독 미흡', (5) F23 '경쟁력 없는 미숙한 협력업체', (6) F12 '시공사에 대한 운영자금 지불지연 및 발주자의 재정적 어려움 및 (7) F20 '시공사의 프로젝트 자금 문제로 나타났다. 전체적인 분석 결과 일곱가지 중요한 지연 원인 중 ; 세가지 원인은 시공사에게, 하나의 원인은 발주자에게 ; 하나의 원인은 건설재료; 하나의 원인은 인력과 장비; 하나의 원인은 외부범주에 속하는 것으로 나타났다. 이번 연구결과에 의하면 , 하나의 당사자가 건설 지연에 대한 책임이 있다고 결론 지을 수 없다. 이는 어떤 단계에서 일정지연을 방지하거나 지연을 완화하기 위해서는 공동으로 노력하거나 팀워크를 기반으로 하여야 한다는 것을 의미한다. 또한 이 번 연구는 프로젝트 당사자, 프로젝트형식 및 프로젝트 규모에 따른 일정지연에 대하여 연구하였다. 요인 분석을 바탕으로, 35개의 일정지연변수로부터 분산의 76.80%를 나타내는 8개 요인을 추출하였다.
다른 국가들과의 지연원인 비교에 대해 비교한 결과 가나, 나이지리아, 베닌, 이집트, 쿠웨이트, 인도 등 대부분의 개발 도상국에서 서는 ‘경제적 어려움’이 공동적인 일정지연원인으로 나타났다. 방글라데시와 팔레스타인에서는 ‘정치상황’이 가장 영향력 있는 건설 지연 원인 중 하나로 나타났다. 따라서 건설에서 일정지연원인은 건설 산업 수행 관리 뿐만 아니라 국가의 경제적, 정치적 안정성과 관련이 있음을 보여준다.
이 연구에서 일정지연과 비용초과 관계 뿐만 아니라 Bromilow 방정식에 기초한 시간-비용에 대한 수학적 회귀모형에 대한 연구를 수행하였다.
연구결과, 일정지연과 비용초과 관계에서 MAPE (Mean Absolute Percent Error) 값이 24.24 % 로 계산 되었고 R2 의 값은 0.456이다. 따라서, 일정지연과 비용초과는 타당성 조사 단계에서 이용 될 수 있는 것으로 나타났다. 또한, 각 프로젝트 특성에 따라 개발된 Bromilow 시간-비용(BTC) 2차회귀식(QUA) 모형은 상당히 높은 결정계수 (R2 = 45.6 to 70.2%)를 나타내고, 상대적으로 작은 MAPE 값 ( 6.93 - 11.57%)으로 나타났다. 이러한 결과는 수치모형에 의해 도출된 방정식이 프로젝트 비용으로 프로젝트 기간을 예측 가능성이 있음을 보여준다. 그 중, 발주자에 따른 시간과 비용에 대한 예측 모델이 가장 적합한 모델이다. 이것은 BTC 모델을 방글라데시에서 시간과 비용을 예측하는 건설 프로젝트에 적용 할 수 있는 것으로 나타났다. 또한, 본 연구에서 네가지 회귀모델을 개발하여 선택된 다른 국가간 BTC모델의 결과와 종합적으로 비교하였다.
이 번 연구결과는 일정초과에 대한 프로젝트의 성능을 제어하는데 있어 방글라데시 건설 산업에 상당한 기여를 할 것으로 예상된다.
핵심용어: 일정지연, 비용초과, 원인, 시간-비용 관계, 회귀모형,건설프로젝트, 방글라데시
The construction industry is the key sector that provides important elements for the development of a country’s economy. However, this sector affected with various types of problems. Among them, Delay problem in construction projects are critical issues worldwide that adversely affect project delivery and public relations, and disrupt construction projects. It has many negative effects on project’s success in terms of time, cost, quality, and safety. Therefore, identification of delay causes and estimating time and cost is an important mission in the early phase of a construction project, especially in feasibility study. It provides a foundation for making decision whether or not the project is performed on schedule and within budget. Thus, reliability of this estimate plays a key role in measuring the success of a project.
There are seven objectives that have been prepared to conduct this research including (1) to explore the schedule delay and cost overrun and their relationship in construction projects, (2) to investigate the main causes of schedule delay have strong impact on construction performance, (3) to identify the causes from points of view of the project parties, types, and sizes, (4) to investigate latent relationships between causes of schedule delay, (5) to perform a comparative study regarding five top important causes of delay with some selected countries, (6) to develop time-cost models for using as tools of feasibility study in construction, and (7) to conduct a comparative study regarding time-cost relationships with some selected countries.
Through the comprehensive literature review, about 48 causes of schedule delay were found. Among them, some causes of delay were adopted, and some were merged and deleted in this study. Finally, 35 delay causes were selected to meet the objectives of this study. These factors are classified into seven categories: (1) materials, (2) manpower and equipment, (3) owner, (4) consultant, (5) contractor, (6) construction, (7) external causes.
The populations of the survey are the professional who have much experience in construction project management in Bangladesh. Due to the certain limitations, the non-probability sampling has been applied in this study. The method used for collecting data was questionnaire survey according to the opinions from several experts. All incomplete feed backs from respondents were deleted to increase the consistency of data. The tools used for data analysis included both descriptive and inferential statistical analysis.
The main results of analysis have shown that the professionals in construction industry highly perceived the schedule delay and cost overrun. According to the ranking of causes of schedule delay based on importance level calculated through their frequency index and severity index. Based on this analysis, there were top seven delay causes extracted are, in order (1) F2 ‘price of construction materials increased very rapidly’, (2) F33 ‘political situation (revolution/ public strikes)’, (3) F4 ‘shortages of skilled workers’, (4) F21 ‘poor site management and supervision by contractor’, (5) F23 ‘incompetent/ immature subcontractors’, (6) F12 ‘delay in running bill payments to contractor and financial difficulties of owner’, and (7) F20 ‘difficulties in financing project by contractor’. The results of overall analysis have shown that among the seven most influential delay causes, three of the causes belong to the contractor; one cause belongs to owner; one cause belongs to materials; one cause belongs to manpower and equipment; and one cause belongs to external category. Based on this finding, it can be concluded that no single party is responsible for the construction delay. It means that any step to prevent or mitigate delay has to be a joint attempt and based upon teamwork. This study also conducted to identify delay causes according to project party, project type, and project size.
Based on factor analysis, there were eight components extracted from thirty five initial delay causes with 76.80% of explained variance.
Regarding comparison of delay cause with some other countries, gives the results that ‘financial difficulties’ is a common factor of delay causes for most developing countries including Ghana, Nigeria, Benin, Egypt, Kuwait, and India. ‘Political situation’ is one of the most influential construction delay cause for Bangladesh and Palestine. Therefore construction delay is much related to the economic and political stability of a country as well as management implementation of its construction industry.
This study was also carried out to develop the schedule delay and cost overrun as well as time-cost mathematical relationships. The computed value of R2 is 0.456 with the MAPE value is 24.24% for the schedule delay and cost overrun relationship. Therefore, it is concluded that the schedule delay and cost overrun relationship could be used in the feasibility study phase in construction phase. Moreover, the time-cost relationship is based on the basic Bromilow’s equation. The computed values of R2 and adjusted R2 showed that BTC relationships are good fit and could be applied to the different construction projects in Bangladesh. This study also performed the construction of four different regression models to compare with BTC linear regression model. The results show that the cubic regression model has been generated the maximum values of R2 in terms of type of public sector projects, while cubic regression model is for all of the remaining characteristics of projects. It means that BTC linear regression model is not the best fit regression model. The value of coefficient of determination (R2 = 45.6 to 70.2%) and comparatively small MAPE (Mean Absolute Percent Errors) value (6.6.93 to 11.57%) for cubic regression (QUA) indicated that the equations are likely to predict the project duration in terms of project cost. The results of BTC model between some selected countries were compared to gain the comprehensive view.
These findings of this study are expected to be significant contributions to Bangladesh construction industry in controlling current performance of project on time overrun.
Keywords: Schedule delay, Cost overrun, Cause, Time-cost relationship, Regression model, Construction project, Bangladesh.
- Issued Date
- 2015
- Awarded Date
- 2015. 2
- Type
- Dissertation
- Publisher
- Interdisciplinary Program of Construction Engineering and Management The Graduate School, Pukyong National University
- Alternative Author(s)
- MD. 미자누르 라흐만
- Affiliation
- Interdisciplinary Program of Construction Engineering and Management The Graduate School, Pukyong National University
- Department
- 대학원 건설관리공학협동과정
- Advisor
- Prof. Kim, Soo Yong
- Table Of Contents
- ABSTRACT i
ACKNOWLEDGEMENT viii
TABLE OF CONTENTS x
LIST OF TABLES xv
LIST OF FIGURES xvii
CHAPTER 1: GENERAL INTRODUCTION
1.1 Background of the study 1
1.2 Statement of problem 4
1.3 Research objectives 5
1.4 Scope of this study 6
1.5 Limitation of this study 7
1.6 Structure of this study 8
CHAPTER 2: LITERATURE REVIEW
2.1 Introduction 12
2.2 Schedule delay 13
2.3 Cost overrun 14
2.4 Types of delay 14
2.4.1 Excusable delay 15
2.4.2 Concurrent delay 16
2.4.3 Compensable delay 16
2.4.4 Critical and non critical delays 16
2.5 Causes for schedule delay and cost overrun 17
2.6 Development of time-cost model 23
2.6.1 Time-cost relationship 23
2.6.2 Bromilow’s model 24
2.6.3 Model validation 25
2.6.4 Level of accuracy of cost estimation 25
2.7 Chapter Conclusion 26
CHAPTER 3: RESEARCH METHODOLOGY
3.1 Introduction 27
3.2 Conceptual research framework 28
3.3 Survey population 29
3.4 Questionnaire survey 30
3.4.1 Questionnaire design 32
3.4.2 Questionnaire distribution 33
3.4.3 Questionnaire collection 34
3.4.4 Data analysis and discussion 34
3.5 Analysis tools and techniques 35
3.5.1 Descriptive analysis 35
3.5.2 Internal consistency test 37
3.5.3 Homogeneity of variance test 38
3.5.4 One way ANOVA test 39
3.5.5 Independent t-test 41
3.5.6 Statistical significance 42
3.5.7 Effect size 42
3.5.8 Practical significance 42
3.6 Ranking of delay cause 45
3.6.1 Frequency index 46
3.6.2 Severity index 46
3.6.3 Importance index 47
3.7 Pearson correlation test 47
3.8 Factor analysis 49
3.9 Development of time-cost relationship 52
3.9.1 Linear regression 53
3.9.2 Normal distribution test 55
3.10 Summary 57
CHAPTER 4: CAUSES OF TIME-COST OVERRUN IN CONSTRUCTION
4.1 Introduction 59
4.2 Results of analysis 62
4.2.1 Respondents and projects’ information 62
4.2.2 Comparative analysis of time-cost overrun in project 67
4.2.3 Internal consistency results 69
4.2.4 Establishment of time-cost overrun model 69
4.2.5 Validation of time-cost overrun model 70
4.2.6 One way ANOVA test results 70
4.3 Ranking 74
4.3.1 Ranking according to overall case 74
4.3.2 Ranking according to project party 78
4.3.3 Ranking according to project type 85
4.3.4 Ranking according to project size 91
4.4 Factor analysis 97
4.4.1 Application of factor analysis 97
4.4.2 Interpretation of factor 107
4.5 Comparison with others country 114
4.6 Chapter recommendation 116
4.7 Chapter conclusion 119
CHAPTER 5: DEVELOPMENT OF TIME-COST RELATIONSHIP
5.1 Introduction 123
5.2 Results of analysis 126
5.2.1 Internal consistency test 126
5.2.2 Levene’s and ANOVA test results 126
5.2.3 Development of time-cost regression model 127
5.2.4 Comparison with others regression model 137
5.2.5 Validation of time-cost model 138
5.3 Comparison between some selected countries 139
5.4 Chapter conclusion 142
CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS
6.1 General conclusions 143
6.2 Causes of schedule delay and cost overrun 144
6.3 Development time-cost relationship 146
6.4 Limitations 147
6.5 Future studies 148
6.6 General recommendations 149
REFERENCES 152
APPENDIX: Questionnaire 165
CURRICULUM VITAE 171
LIST OF TABLES
Table 1.1 Contribution of construction sector in Bangladesh 3
Table 2.1 Source of delay causes selection for schedule delay 20~21
Table 3.1 Description of 5-point scale for frequency 33
Table 3.2 Description of 5-point Likert scale for severity 33
Table 3.3 Cronbach’s alpha’s values in internal consistency test 37
Table 3.4 Calculation process of Independent t-test 41
Table 3.5 Interpretation of strength of correlation coefficient 49
Table 4.1 Time overrun and under run in construction project 66
Table 4.2 Cost overrun and under run in construction project 67
Table 4.3 Coefficient of internal consistency test result 69
Table 4.4 Validation of time-cost overrun model 70
Table 4.5 Statistical significance test results for frequency 72
Table 4.6 Statistical significance test results for severity 73
Table 4.7 Frequency index, severity index, importance index and ranking by overall case 75
Table 4.8 Frequency index, severity index, importance index and ranking by project party 81
Table 4.9 Seven most important factors of delay by overall and project party 84
Table 4.10 Pearson’s correlation coefficient between parties 85
Table 4.11 Frequency index, severity index, importance index and ranking by project type 88
Table 4.12 Seven top important factors of delay by project type 89
Table 4.13 Frequency index, severity index, importance index and ranking by project size 94
Table 4.14 Top seven important causes by project size 95
Table 4.15 KMO and Bartlett's test results 97
Table 4.16 Correlation matrix in factor analysis 98
Table 4.17 Communalities of Factor analysis 99
Table 4.18 Total variance explained 100
Table 4.19 Factor analysis loading result 102
Table 4.20 Component structure of Factor analysis 103~104
Table 4.21 Revised component structure by Affinity diagram 106
Table 4.22 Comparison of five most influential causes of delay among some selected countries 115
Table 5.1 Coefficient of internal consistency test results 126
Table 5.2 Results of Levene’s test and ANOVA test 127
Table 5.3 Development of time-cost relationships 127
Table 5.4 Summary of time-cost relationship’s linear regression results in SPSS 131
Table 5.5 Different forms of time-cost model 137
Table 5.6 R2 values of regression models 138
Table 5.7 Validation of time-cost model 138
Table 5.8 Comparative analysis between some selected countries 140~141
LIST OF FIGURES
Figure 1.1 Bangladeshi GDP per capita in (BD TK.) 2
Figure 1.2 Bangladeshi GDP per capita in (USD) 2
Figure 1.3 Structure of the research process 11
Figure 2.1 Schedule delay or time overrun in construction project 13
Figure 2.2 Sequential relationships of various categories of delays 15
Figure 2.3 Tree charts of causes of schedule delay and cost overrun 22
Figure 2.4 Define the level and extent of the corporation's cost calculation 26
Figure 3.1 Conceptual frameworks for research problems 29
Figure 3.2 Flowchart of questionnaire survey process 31
Figure 3.3 Homogeneity of variance and post hoc test process 39
Figure 3.4 ANOVA test process 40
Figure 3.5 ANOVA significance test process 40
Figure 3.6 Practical significance test process for mean difference 44
Figure 3.7 Scree plot graph of factors 51
Figure 3.8 Flowchart for the process of factor analysis 52
Figure 3.9 The process of global regression model test 55
Figure 3.10 Histogram of normal distribution 56
Figure 3.11 Data analysis according to research’s objectives 58
Figure 4.1 Flowchart of chapter research process 61
Figure 4.2 Project party in survey 62
Figure 4.3 Project type in survey 63
Figure 4.4 Respondents’ working experience in survey 64
Figure 4.5 Respondents’ involvement in project 64
Figure 4.6 Type of client in survey 65
Figure 4.7 Project size by cost. 65
Figure 4.8 Time overruns in project 68
Figure 4.9 Cost overruns in project 68
Figure 4.10 Importance indices of delay causes 74
Figure 4.11 Top seven delay causes in spider mapping chart indicates important index for overall case 76
Figure 4.12 Level of influence for frequency and severity 77
Figure 4.13 Top seven delay causes in spider mapping chart indicates important index for owner 78
Figure 4.14 Top seven delay causes in spider mapping chart indicates important index for consultant 79
Figure 4.15 Top seven delay causes in spider mapping chart indicates important index for contractor 80
Figure 4.16 Top seven delay causes in spider mapping chart indicates important index for others party 80
Figure 4.17 Top seven delay causes in spider mapping chart indicates important index for building and residential project 86
Figure 4.18 Top seven delay causes in spider mapping chart indicates important index for civil projects 86
Figure 4.19 Top seven delay causes in spider mapping chart indicates important index for industrial project 87
Figure 4.20 Top seven delay causes in spider mapping chart indicates important index for others project 89
Figure 4.21 Top seven delay causes in spider mapping chart indicates important index for small size project 92
Figure 4.22 Top seven delay causes in spider mapping chart indicates important index for medium size project 92
Figure 4.23 Top seven delay causes in spider mapping chart indicates important index for large size project 93
Figure 4.24 Scree plot of delay causes 101
Figure 4.25 Fishbone diagrams of causes of schedule delay in construction 121
Figure 5.1 Flowchart of chapter’s research process 125
Figure 5.2 Double natural logarithmic relationship between time-cost (all cases) 129
Figure 5.3 Double natural logarithmic relationship between time-cost (public) 130
Figure 5.4 Double natural logarithmic relationship between time-cost (private) 130
Figure 5.5 Scatter plots of residuals against predicted values (all cases) 131
Figure 5.6 Scatter plots of residuals against predicted values (public) 132
Figure 5.7 Scatter plots of residuals against predicted values (private) 132
Figure 5.8 Histogram of linear regression analysis (all cases) 134
Figure 5.9 Histogram of linear regression analysis (public sector) 134
Figure 5.10 Histogram of linear regression analysis (private sector) 135
Figure 5.11 Normal p-p plot of linear regression standardized residual (all cases) 135
Figure 5.12 Normal p-p plot of linear regression standardized residual (public) 136
Figure 5.13 Normal p-p plot of linear regression standardized residual (private) 136
Figure 6.1 Fishbone diagrams of top seven delay causes by project party 145
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