Energy import resilience evaluation considering maritime transport disruptions: A case of China

Major trading nations rely on maritime transport to meet their energy, commodity, and other vital goods requirements. However, maritime transport systems are facing increasingly significant challenges as global trade expands rapidly. This study developed a four-step research framework to evaluate energy import resilience under maritime transport disruptions. The main events and factors related to maritime transport disruptions are also discussed. Time windows for different emergencies are identified based on the Google Search Index. System resilience is then measured from absorptive, adaptive, and restorative capabilities, and sub-factors are considered based on the complex network theory and entropy weight method. A data-driven Bayesian network (BN) is proposed to qualify the oil import system resilience, where the expectation-maximization algorithm is applied to estimate the parameters of conditional probability tables of the BN. The results of the sensitivity analysis, forward inference, and backward inference are presented. Finally, conclusions and recommendations for resilience improvements are summarized.