Technical Papers
Sep 30, 2019

Fuzzy Logic–Based Method for Risk Assessment of Belt and Road Infrastructure Projects

Publication: Journal of Construction Engineering and Management
Volume 145, Issue 12

Abstract

The Belt and Road Initiative (BRI) is an ambitious economic project proposed by the Chinese government that focuses on establishing connectivity, strengthening cooperation, and creating closer economic ties among countries. The idea of BRI is based on the revival of the ancient Silk Road, a trade route that was once connecting China with Central Asia, India, Middle East, Western Asia, and Europe. More than 1,700 infrastructure projects are planned to be implemented under BRI. Such a huge infrastructure investment brings a lot of opportunities as well as risks for nations along the Silk Road, their governments, contractors, and investors. Compared to traditional international construction projects, BRI projects are exposed to additional risks since they are geographically distributed and complex in nature and include more stakeholders. Hence, risk assessment of BRI projects is a complex task that requires an efficient tool capable of providing detailed information about critical risks. To bridge this gap, a novel method is developed and applied to the risk assessment of complex, geographically distributed, and large-scale infrastructure projects, such as BRI projects. The proposed risk assessment method integrates fuzzy matrices, fuzzy logic, and probabilistic theory into a single approach that is applied to assess risks in BRI projects for different regions, as well as regional risk and total risk. In addition, sensitivity analysis is used to optimize the proposed fuzzy logic–based risk assessment method. The key findings are as follows: (1) the main risks in BRI projects are delay in supplying materials, increases in material prices, poor quality of materials, delays in equipment delivery, increases in the costs of equipment use, and economic risk; (2) the highest risk-ranked regions in BRI projects are Central Asia and Eastern Europe, while the lowest risk-ranked region is East Asia; and (3) a weighted-average method is the optimal defuzzification method for the proposed fuzzy logic–based method. The theoretical contribution of this research is a novel risk assessment method that integrates expert judgment, fuzzy sets, fuzzy logic, fuzzy matrices, and probabilistic theory into a single approach supported by sensitivity analysis. In practical terms, this study provides significant information about risks in various regions, regional risk, and overall risk of BRI projects to contractors, investors, and other stakeholders.

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Data Availability Statement

Data generated or analyzed during the study are available from the corresponding author by request. Information about the Journal’s data-sharing policy can be found at the following link: https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0001263.

Acknowledgments

This research was supported by the National Natural Science Foundation of China (Project ID 71272088) and China Postdoctoral Science Foundation (Grant No. 2017M622743). The authors are very grateful to Dr. Pei Tang for his support in data collection.

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Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 145Issue 12December 2019

History

Received: May 20, 2018
Accepted: Apr 9, 2019
Published online: Sep 30, 2019
Published in print: Dec 1, 2019
Discussion open until: Feb 29, 2020

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Jelena M. Andrić [email protected]
Postdoctoral Research Fellow, College of Civil Engineering, Shenzhen Univ., Shenzhen 518060, China. Email: [email protected]
Jiayuan Wang [email protected]
Professor and Dean, College of Civil Engineering, Shenzhen Univ., Shenzhen 518060, China (corresponding author). Email: [email protected]
Patrick X. W. Zou [email protected]
Professor, Dept. of Civil and Construction Engineering and Center for Sustainable Infrastructure, Swinburne Univ. of Technology, P.O. Box 218, Hawthorn, Melbourne, VIC 3122, Australia. Email: [email protected]
Jingrong Zhang [email protected]
Master Student, College of Civil Engineering, Shenzhen Univ., Shenzhen 518060, China. Email: [email protected]
Ruoyu Zhong [email protected]
Professor, China Center for Special Economic Zone Research, Shenzhen Univ., Shenzhen 518060, China. Email: [email protected]

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