Baseline regression results (Gamma GLM).

This study investigates the role of human error factors in shaping the severity of railway accidents. Using a structured coding scheme to transform qualitative accident investigation reports into quantitative variables, the analysis reveals that deficiencies in managerial oversight, shortcomings in maintenance practices, and failures in equipment and system reliability are consistently associated with higher accident costs. These findings underscore the organizational and technical dimensions of human error as critical factors linked to accident severity, rather than merely front line worker mistakes. At the modeling level, the explanatory variables collectively account for a meaningful portion of the variation in accident costs, indicating that such outcomes are not purely random but systematically related to underlying human and organizational conditions. By identifying the relative importance of managerial, maintenance, and equipment-related deficiencies, this study provides empirical evidence for prioritizing these factors in railway safety management. The results highlight the need to strengthen organizational accountability, improve maintenance regimes, and ensure the reliability of technical systems as essential strategies for mitigating high-consequence accidents. These insights contribute to a deeper understanding of the organizational and systemic correlates of accident severity and can inform targeted interventions aimed at enhancing overall railway safety.