A data-driven framework for risk and resilience analysis in maritime transportation systems : A case study of domino effect accidents in arctic waters

Resilience is a complex concept that extends beyond risk, including the ability to absorb risks from external disturbances to maintain an acceptable level of safety. In the context of maritime transportation systems (MTS), resilience can be understood as a ship's ability to withstand disasters and ensure safe navigation in the face of unexpected incidents. This study proposes a data-driven framework for the quantitative analysis of risk and resilience in MTS, considering the temporal trends and domino effects of maritime accidents. The first step involves data preparation, which includes the collection, processing, and storage of global maritime accident data from the Lloyd's List Intelligence database spanning from 2014 to 2023. Next, an analysis of evolution trends is conducted to explore temporal trends and domino effects, focusing on the severity and pollution of maritime accidents. Arctic waters, known for their typical domino effects in maritime accidents, are chosen as a case study to illustrate the proposed risk and resilience analysis approach by considering the absorptive capacity in the evolution of maritime accidents. Furthermore, proactive and reactive risk control options are suggested for critical domino accident scenarios in Arctic waters to provide targeted recommendations for managing risks in Arctic shipping.