Abstract
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.
Highlights
Accounting for approximately 90% of goods transportation between countries [1,2], maritime transportation is regarded as an important means to keep global trade flowing and ensure the stability of supply chains
This paper aims to answer the following three research questions: RQ1: What are the risk factors contributing to port congestion during the pandemic? RQ2: What risk parameters should be considered in port congestion risk assessment? RQ3: How to realize flexible and accurate congestion risk assessment?
While results from sensitivity analysis validated the robustness of the developed model, they illustrated the effectiveness of the five selected risk parameters in evaluating port congestion risk, i.e., any changes in the estimations of each risk parameter directly led to the relative variation in risk prioritization index (RPI)
Summary
Accounting for approximately 90% of goods transportation between countries [1,2], maritime transportation is regarded as an important means to keep global trade flowing and ensure the stability of supply chains. The COVID-19 pandemic hit the world and triggered an unprecedented health and economic crisis, upending the landscape for maritime transport and trade [3] Against this background, the frequency and severity of port congestion, stimulated by a variety of factors are rising, severely challenging the continuity of shipping services. The use of risk assessment as the solution to decision-making of operation management and port investment has been recognized by researchers with various backgrounds and verified effectively by real examples These studies could be classified into networkbased cascading congestion risk models [14] and traditional risk models [15,16] where risk was defined as the combination of probability and impact. There are some studies [17,18] focused on robustness and recovery planning for ports, in which both the proactive and reactive disruption management for ports were taken into account
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