Human factors in yachting tourism accidents: an integrated human factors classification framework with statistical and network analysis

Yachting tourism, as part of the global marine leisure industry, presents unique operational characteristics that increase vulnerability to safety incidents. While human factors are widely recognized as a dominant cause of maritime accidents, existing analytical frameworks offer limited explanatory power for the complexity of yachting contexts. This study develops an adapted Human Factors Analysis and Classification System for yachting (HFACS-YA) and applies it to a comprehensive dataset of yachting tourism accidents. A combination of chi-square tests was used to identify statistically significant human factor categories, and complex network modeling was employed to reveal structural relationships and critical causal pathways. Results show that "unsafe acts" are the most frequent immediate contributors to accidents, but the underlying root causes largely originate from "organizational influences," including deficiencies in safety management systems, inadequate training programs, and low safety awareness. Prominent pathways involve legislative gaps, flawed organizational processes, poor supervisory oversight, and decision-making errors. By integrating statistical inference with network analysis, this research provides a replicable methodological framework for investigating accident causation in small-vessel maritime tourism. The findings offer actionable insights for regulators, maritime authorities, and industry stakeholders to enhance safety governance and reduce accident risks.