文章基本信息

标题：Risk Assessment of Port Congestion Risk during the COVID-19 Pandemic
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作者：Gui, Dongping ; Wang, Haiyan ; Yu, Meng 等
期刊名称：Journal of Marine Science and Engineering
电子版ISSN：2077-1312
出版年度：2022
卷号：10
期号：2
页码：1-18
DOI：10.3390/jmse10020150
语种：English
出版社：MDPI AG
摘要：With the COVID-19 outbreak hitting the world, the frequency and severity of port congestion caused by various factors are increasing, challenging the stability of international supply chains. Thus, it is necessary to conduct an in-depth study on congestion risks to reduce their adverse impacts on congestion. Although traditional criticality analysis techniques may be capable of ranking port congestion risk in common scenarios, new risk analysis methods are urgently required to tackle uncertainty along with the COVID-19 pandemic. This paper develops a methodology designed for the identification and prioritization of port congestion risk during the pandemic. First, a novel congestion risk assessment model is established by extending the risk prioritization index (RPI) suggested by failure mode and effects analysis (FMEA). Next, the combination of fuzzy Bayesian reasoning, AHP and the variation coefficient method is incorporated into the model in a complementary way to facilitate the treatment of uncertainty and quantitative analysis of the congestion under the different influence of risk factors in ports. Finally, the mode introduces a set of risk utility values for calculating the RPI for prioritization. A real case study and a sensitivity analysis were carried out to illustrate and validate the proposed model. The results proved that the applied method is feasible and functional. In the illustrative example, the top three risk factors are “Interruption of railways/barges services”, “Skilled labor shortage” and “Shortage of truck-drivers/drayage truck”. The findings obtained from this paper could provide useful insights for risk prevention and mitigation.
关键词：the COVID-19 pandemic; port congestion risk; risk parameter structure-based FMEA; fuzzy belief rule-based Bayesian network (FBRB-BN); AHP; the variation coefficient method