Proceedings of the
35th European Safety and Reliability Conference (ESREL2025) and
 the 33rd Society for Risk Analysis Europe Conference (SRA-E 2025)
 15 – 19 June 2025,  Stavanger, Norway
How to assess the resilience of the European container shipping network from a national perspective: A data-driven cascading failure model
1Liverpool Logistics, Offshore and Marine (LOOM) Research Institute, Liverpool John Moores University, United Kingdom
2Navigation College, Dalian Maritime University, PR China
ABSTRACT
The European Container Shipping Network (ECSN) is highly interconnected due to the advanced water transport systems across European countries. Such highly connected feature makes the network complicated and vulnerable to disruptions, particularly to cascading failures triggered by extreme events like the COVID-19 pandemic and regional conflicts. A fundamental step in mitigating these failures involves simulating load redistribution, yet a robust modelling approach tailored to Europe's specific needs remains undeveloped. To fill these gaps, this study aims to develop an innovative framework for resilience analysis against cascading failures, designed to rigorously assess the impact of port disruptions on the resilience of individual countries within the ECSN. The proposed framework integrates a port importance assessment model, a multi-target cascading modelling approach, and three resilience metrics, all analysed from a national perspective. The detailed analysis and case studies across 172 European ports reveal that disruptions at the Port of Rotterdam could significantly compromise the network's resilience. To enhance the ECSN's resilience, this study recommends two primary strategies: expanding interregional strategic cooperation and maintaining adequate reserve capacity at critical ports. This study provides valuable insights for port and logistics stakeholders in managing unforeseen risks and in the planning and development of port infrastructure.
Keywords: Resilience analysis, European container shipping network, Cascading failure

