An advanced fuzzy Bayesian-based FMEA approach for assessing maritime supply chain risks

Wan, Chengpeng, Yan, Xinping, Zhang, Di, Qu, Zhuohua and Yang, Zaili (2019) An advanced fuzzy Bayesian-based FMEA approach for assessing maritime supply chain risks. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 125. pp. 222-240.

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Official URL: http://dx.doi.org/10.1016/j.tre.2019.03.011

Abstract

This paper aims to develop a novel model to assess the risk factors of maritime supply chains by incorporating a fuzzy belief rule approach with Bayesian networks. The new model, compared to traditional risk analysis methods, has the capability of improving result accuracy under a high uncertainty in risk data. A real case of a world leading container shipping company is investigated, and the research results reveal that among the most significant risk factors are transportation of dangerous goods, fluctuation of fuel price, fierce competition, unattractive markets, and change of exchange rates in sequence. Such findings will provide useful insights for accident prevention.

Item Type:	Article
Uncontrolled Keywords:	Maritime supply chain, Maritime transport, Bayesian network, Fuzzy logic, FMEA, Maritime risk
Depositing User:	Symplectic Admin
Date Deposited:	12 Feb 2020 11:09
Last Modified:	22 Jul 2023 06:23
DOI:	10.1016/j.tre.2019.03.011
Open Access URL:	http://researchonline.ljmu.ac.uk/id/eprint/10373/
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3074664