Characteristics exploration of human and organizational factors in maritime traffic accidents

This paper introduces a reliable analytical methodology designed to delve into the characteristics of human-organizational factors (HOFs) in maritime traffic accidents along China's coastal waters and uncover the causal chains of critical accident HOFs. By collecting 811 relevant accident reports from the China Maritime Safety Administration (CMSA) database, the frequency of HOFs occurrence across different accident reports was statistically analyzed. Employing co-word clustering analysis, a co-occurrence relationship map was constructed, and cluster analysis and visualization analysis of HOFs were performed. Subsequently, the Human Factors Analysis and Classification System (HFACS) model was applied to analyze the accident causes, extracting the salient features of maritime traffic accidents and HOFs. Furthermore, complex network theory was utilized to explore the interconnected pathways within the HOFs network of maritime traffic accidents by analyzing the key nodes and edges of the network. The analysis results indicate that the primary HOFs contributing to maritime vessel traffic accidents are negligent lookout, poor safety awareness, and failure to implement safety management responsibilities. Based on the HFACS model, 235 HOFs and 3 causal pathways were identified, with "ineffective education and training - failure to implement safety management responsibilities - failure to use safe speed - poor safety awareness" being the most critical causal pathway for HOFs-related accidents. These findings can serve as a reference for relevant authorities to formulate targeted measures to prevent maritime traffic accidents along China's coastal waters and enhance maritime safety management.