Data-driven resilience analysis of the global container shipping network against two cascading failures

Abstract

Being a fundamental link in the global supply chain and logistics system, the global container shipping network (GCSN) is highly interconnected, which causes the network resilience challenges by the cascading failures triggered by extreme events (e.g., COVID-19 and regional conflicts). Within this dynamic process, the load redistribution behaviour is the core countermeasure for the propagation of cascading failures, however the diversified mechanism has not been systematically studied. To fill in these gaps, this study aims to develop a pioneering resilience analysis framework against cascading failures, to comprehensively explore the impact of port disruptions on the shipping network resilience. By pioneering the influence analysis of port betweenness, weight, and connectivity on load determination and target selection, a port importance assessment method is applied as the foundation for load redistribution decisions. Based on the global service routes data from 2020 to 2023, the GCSN resilience against the sequential cascading failures of 686 ports worldwide is quantified by three metrics. A scenario analysis is conducted to simulate the effects of cascading failures triggered by 5 historical port disruption events (e.g., the COVID-19 port lockdowns and the 2024 bridge collision at Baltimore port) on resilience of the network. Determining the identified critical capacity threshold is pivotal for effectively enhancing the system’s resilience and preventing the likelihood of cascading failures. Additionally, this study offers cutting-edge perspectives to the global shipping industry stakeholders. It presents distinct strategies and preferences, offering actionable advice for port authorities in their risk response decisions. Moreover, this study delivers an economic rationale and critical evaluations, instrumental for the strategic maintenance, planning and augmentation of port infrastructures to prevent unforeseen risks.