Risk induced contingency cost modeling for power plant projects

Muhammad Saiful Islam*, Madhav Prasad Nepal, Martin Skitmore, Robin Drogemuller

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The current practice of expert judgment-based contingency cost allocation by owners lacks a holistic understanding of project risks, their causal relationships, and impact on project costs. This study presents an integrated fuzzy set theory and fuzzy Bayesian belief network model for a rational, realistic determination of contingency costs for infrastructure projects. The application of the model is demonstrated for real-world power plant projects in Bangladesh. The model has promising results for its ability to establish the amount of contingency costs with a maximum error of 20% between the contingency cost predicted with the model and the actual contingency cost. It has the potential to assist both the owner and contractor to set aside a realistic amount of contingency cost in the preliminary phase of a project. The approach is also equally useful for monitoring and controlling project risks, and dynamically updates the contingency cost amount during project execution.

Original languageEnglish
Article number103519
JournalAutomation in Construction
Volume123
Early online date30 Dec 2020
DOIs
Publication statusPublished - Mar 2021
Externally publishedYes

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