A Novel Framework for Identifying Major Fishing Vessel Accidents and Their Key Influencing Factors

Hongxia Zhou, Fang Wang, Weili Hu, Manel Grifoll, Jiao Liu, Weijie Du () and Pengjun Zheng ()
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Hongxia Zhou: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
Fang Wang: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
Weili Hu: Taizhou Maritime Safety Administration, Taizhou 318001, China
Manel Grifoll: Barcelona School of Nautical Studies, Universitat Politècnica de Catalunya, 08028 Barcelona, Spain
Jiao Liu: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
Weijie Du: Ningbo Pilot Station, Ningbo 315040, China
Pengjun Zheng: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China

Sustainability, 2024, vol. 16, issue 18, 1-19

Abstract: This research addresses the critical issue of major fishing vessel accidents, which traditionally suffer from a lack of focused analysis due to their rarity and the subjective nature of their classification. We propose an innovative methodology of Peaks Over Threshold to overcome subjectivity in accident classification. This approach ensures a more representative and accurate analysis of major accidents, distinguishing them from more common, less severe incidents. Employing a Bayesian network model, we further explore the most influential factors contributing to these major accidents. The key innovation lies in our novel approach to data handling and analysis, enabling us to uncover hidden patterns and causal relationships that traditional methods often overlook. The results show that the approach proposed in this study can effectively capture the key factors of major fishing vessel accidents. This study identifies accident type, vessel-related factors, and accident location as the key influential factors leading to major accidents. The findings from our research are intended to inform sustainable fisheries management practices, promoting interventions that aim to decrease the occurrence and impact of severe maritime accidents while balancing economic, safety, and sustainable development considerations.

Keywords: fishing vessel; accident analysis; influencing factors; peaks over threshold; hybrid data resampling; Bayesian network; random forest; fishing safety; sustainable fisheries (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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