LAUSR

Container ports are prone to delays, congestion, and logistics interruptions under the perturbation of uncertain events inside and outside the system. This not only affects the service quality of the system but also brings a serious blow to the whole transportation network. Therefore, this paper aims to develop a hybrid Bayesian network (BN) model to investigate the failure mechanism of the container port logistics system. Considering the complex coupling relationship between failure risks, the DEMATEL and ISM methods are presented to thoroughly analyze the interdependence and hierarchical structure of system failure factors. The failure evolution mechanism of the system is then analyzed using BN reasoning ability. The suggested hybrid model can identify the main failure factors, examine how factors are coupled, and produce the main propagation path resulting in system failure. The findings indicate that the risks associated with technology, facilities, and equipment are the most significant and immediate in the system; human risks affect all system components by acting on other factors; organizational management risks have a fundamental impact on the stability of the system; additionally, the uncertainty of external risks has greatly increased the variability of each logistics link. This study provides useful insights for port logistics risk management.