A data-driven AcciMap-BN model for risk factor analysis of collisions between merchant ships and fishing vessels

Hong Wang, Ning Chen, Jinhui Jiang, C. Guedes Soares and Bing Wu

Maritime Policy & Management, 2026, vol. 53, issue 5, 989-1019

Abstract: This paper proposes a novel quantitative and qualitative analytical methodology that integrates AcciMap and Bayesian networks, which analyses key risk factors for the occurrence likelihood and consequences of collisions between merchant ships and fishing vessels. Specifically, 195 collision accident investigation reports are collected from 2012 to 2023 from the China Maritime Safety Administration. The graphical structure of the Bayesian network model is derived from the modified AcciMap model, and the parameters of the Bayesian network model are obtained through parameter learning with the Expectation-Maximization algorithm. Key risk factors for collision occurrence, consequences, and severity are identified through sensitivity analysis, effective safety barriers are identified through the strength of influence analysis, and targeted countermeasures are proposed for relevant stakeholders to mitigate identified risks. Sensitivity analysis indicates that ‘failure to take collision avoidance measures in a timely or effective manner’ is a significant factor influencing the occurrence of such collisions, ‘inappropriate emergency response’ is a significant factor influencing their consequences, ‘failure to provide self-rescue and mutual aid in a timely manner’ is a significant factor contributing to catastrophic outcomes. The strength of influence analysis indicates that strengthening fishermen’s licensing supervision is critical to mitigating risks of insufficient crew allocation.

Date: 2026
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DOI: 10.1080/03088839.2025.2524533

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