Complexity-driven Risk Decision Framework for Cost Overrun using Fuzzy-Bayesian Network

Author:

Afzal Farman1ORCID,Afzal Fahim2,Junaid Danish3,Shah Imran Ahmed4,Yunfei Shao5

Affiliation:

1. University of Engineering and Technology

2. University of Sialkot

3. Bahria University

4. Shah Abdul Latif University

5. UESTC: University of Electronic Science and Technology of China

Abstract

Abstract This study adheres to find important complexity-risk interdependent causes of cost overrun in infrastructure transport projects rather considering an independent state of project risk. Aiming for addressing cost overrun problem to facilitate decision-makers, a hierarchical breakdown structure of complex elements and complexity-driven risk factors at different levels of severity is conceptualized along with their interdependency network of key relationships. In this work, an integrated approach of fuzzy logic with the Bayesian belief network is employed for cost-risk assessment while assuming linguistic scales of likelihood and consequences parameters. The simulated results of cost-risk decision framework imply that poor design issues, increase in material prices and delay in relocating facilities show higher complexity-risk dependency and increase the risk of cost overrun in complex projects. This study contributes to the body of knowledge by providing a practical hybrid risk decision framework to identify and evaluate the key complexity-risk interdependencies in underline relations to the cost overrun problem in construction.

Publisher

Research Square Platform LLC

Reference86 articles.

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3. Afzal F, Yunfei S, Sajid M, Afzal F (2018) Int Trans J Eng Manage Appl Sci Technol 9(4):253–269. https://doi.org/10.14456/ITJEMAST.2018.23. Risk Assessment of First Overseas Mass Rapid Transit Project: Promulgating Interpretive Qualitative Paradigm for China Pakistan Construction Concession

4. Afzal F, Yunfei S, Sajid M, Afzal F (2020) Integrated priority decision index for risk assessment in chaos: cost overruns in transport projects. Engineering, Construction and Architectural Management, Vol. 27 No 4.. https://doi.org/10.1108/ECAM-02-2019-0079

5. Comprehensive risk management using fuzzy FMEA and MCDA techniques in highway construction projects;Ahmadi M;J Civ Eng Manag,2017

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