Moving Beyond Optimism Bias and Strategic Misrepresentation: An Explanation for Social Infrastructure Project Cost Overruns

2012 ◽  
Vol 59 (4) ◽  
pp. 560-571 ◽  
Author(s):  
Peter E.D. Love ◽  
David J. Edwards ◽  
Zahir Irani
Keyword(s):  
Social Infrastructure ◽  
Project Cost ◽  
Cost Overruns ◽  
Optimism Bias ◽  
Infrastructure Project

scholarly journals A BESPOKE APPROACH FOR RELATING MATERIAL WASTE TO COST OVERRUN IN THE CONSTRUCTION INDUSTRY

2017 ◽  
Vol 1 (1) ◽  
pp. 39-52
Author(s):  
Ibrahim Saidu ◽  
W Shakantu ◽  
A Adamu ◽  
I Anugwo
Keyword(s):  
Construction Industry ◽  
Construction Material ◽  
Methodological Approach ◽  
Construction Project ◽  
Project Managers ◽  
Cost Overrun ◽  
Project Cost ◽  
Cost Overruns ◽  
Project Completion ◽  
Final Project

The problems of material waste and cost overruns are common in the construction industry. These problems occur at different stages of a construction project, from planning, design to project completion. The argument on how to eliminate cost overrun has been on-going for the past 70 years as on-site wastage of materials leads to increase in the final project cost. This paper examines the relationship between the causes of material waste and those of cost overrun at the pre-contract and post-contract stages of a project. The desktop methodological approach was firstly adopted in comparing the causes of material waste and those of cost overruns from the literature, in order to determine the possible relationship. Subsequently, interviews were purposively conducted with construction professionals within Abuja, Nigeria, in order to verify the literature based information. The result reveals that all the causes of material waste also cause cost overrun at the pre-contract and the post-contract stages of a project. 96.88% and 81.81% of the causes of cost overrun also cause material waste at the pre-contract and post-contract stages respectively. Other causes which are not related are mostly, the micro-economic and macro-economic factors. These results are not different from those of the interviews conducted with professionals and summarised in the tick box. It was also found that to achieve Effective Construction Material Waste Management (ECMWM) for any construction project, material waste must be controlled at its sources and causes, and at different stages of a project. Based on these findings, it can be concluded that effective management of material waste would translate into a reduction in the level of project cost overrun. The study recommends that construction-project managers, as well as the construction practitioners should encourage the management of material-waste causes, as it has the potential to minimise cost overrun for projects. 

Regression Modelling for Prediction of Construction Cost and Duration

2016 ◽  
Vol 857 ◽  
pp. 195-199 ◽  
Author(s):  
Nivea Thomas ◽  
Anu V. Thomas
Keyword(s):  
Regression Models ◽  
Critical Path ◽  
Real Data ◽  
Project Managers ◽  
Statistical Regression ◽  
Statistical Process ◽  
Project Cost ◽  
Cost Overruns ◽  
Building Projects ◽  
The Relationship

Construction investments are sensitive to time and cost overruns. Delay and cost escalation are considered two threats to project success. The project objective is to develop a model to predict project cost and duration based on historical data of similar projects. Statistical regression models are developed using real data of building projects. The methodology is adopted in 3 steps: a) Data collection b) Statistical analysis using Statistical Package for Social Sciences (SPSS) software c) Interpretation of results. The real data of cost and duration of 51 building projects have been collected. In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modelling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. The analysis is done using SPSS developed by IBM Corporation. The Regression models have been developed using the data collected from Noel Builders, Kakkanad, Ernakulam to predict the project cost and duration. The developed models are validated using split sample approach. The model outputs can be used by project managers in the planning phase to validate the scheduled critical path time and project budget.

scholarly journals Structural Equation Model for Investigating the Causal Relationships Between Project Complexities and Project Cost: An Empirical Study from New Zealand

2019 ◽  
Author(s):  
Linlin Zhao ◽  
Huirong Zhang
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Empirical Studies ◽  
Poor Performance ◽  
Equation Model ◽  
Evidence Based ◽  
Direct Effects ◽  
Project Cost ◽  
Cost Overruns ◽  
Project Complexity

Project complexity is usually considered as one of main causes of cost overruns, resulting in poor performance and thus project failure. However, empirical studies focused on evaluating its effects on project cost remain lacking. Given this circumstance, this study attempts to develop the relationships between project cost and the multidimensional project complexity elements. We establish complexity as a multidimensional factor including the task, organization, market, legal, and environment complexities. This study uses an empirical evidence-based structural model to account for the relationships between project cost and project complexity. By doing so, a quantitative assessment of multi-dimensional project complexity has been developed. The findings suggest that task and organization complexities have direct effects on project cost, while market, legal and external environment complexities have indirect effects on project cost. The practical contribution is that the findings can improve the understanding of which dimension of complexity significantly influence project cost, and the need to focus efforts on strategically addressing that complexities.

scholarly journals Effects of Project Cost Overruns and Schedule Delays in Sub-Saharan Africa

2017 ◽  
Vol 3 (2) ◽  
pp. 46 ◽  
Author(s):  
Paul Terna Gbahabo ◽  
Oluseye Samuel Ajuwon
Keyword(s):  
Economic Effect ◽  
Sub Saharan Africa ◽  
Control Mechanisms ◽  
Cost Overrun ◽  
Project Cost ◽  
Cost Overruns ◽  
Schedule Delay ◽  
Wide Range ◽  
Sub Saharan ◽  
Secondary Information

This paper provides conceptual insights on the economic impact of project cost overrun and schedule delays on infrastructure procurement in developing countries with huge infrastructure deficit in Sub-Saharan Africa. Projects cost overruns and schedule delay are a major and widespread problem in infrastructure procurement the world over. It has received a lot of attention in the recent past. However, the literature reveals that extant studies on project overruns are heavily skewed towards causative factors, with little or no attention to the effects it has on the economy as a whole. The paucity of studies on the effects of project cost overrun and schedule delay will further reinforce the imperative to reacquaint policymakers and infrastructure developers, as well as project financiers with the gravity and import of the problem for infrastructural development in particular and the wider economy in general. The study undertakes an exploratory approach drawing from a wide range of secondary information and materials obtained from policy documents, study reports and peer-reviewed articles. The findings show that cost overrun and schedule delay in infrastructure procurement can have a damaging economic effect ranging from allocative inefficiency of scarce resources, further delays, contractual disputes, claims and litigation to project failure and total abandonment. The study recommends project management capacity-building for infrastructure developers, project managers as well as a number of innovative control mechanisms such as reference class forecasting, public-private partnership and computer-aided cost estimating tools including artificial neural networks, data mining, building information modelling as well as fuzzy neural inference model, genetic algorithms, and stochastic simulation to curb the menace of the problem.

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