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

• Published in: Transportation research. Part E, Logistics and transportation review Logistics and transportation review, 2019-05, Vol.125, p.222-240
• Main Authors: Wan, Chengpeng, Yan, Xinping, Zhang, Di, Qu, Zhuohua, Yang, Zaili
• Format: Article
• Language: English
• Subjects: Bayesian network; FMEA; Fuzzy logic; Maritime risk; Maritime supply chain; Maritime transport
• ISSN: 1366-5545; 1878-5794
• DOI: 10.1016/j.tre.2019.03.011

•Analyse the risks of maritime supply chains from different perspectives.•Develop an advanced risk analysis method to tackle the uncertainty in risk data.•Compare risk analysis results by using different methods to demonstrate the advantages of the newly proposed one.•Conduct an empirical study to provide useful insights for the identification and control of high risks. 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.