Identification of Accident Risks and Configuration Safety in Coal Mines Based on Complex Networks and QCA

Coal mine accidents frequently arise from the complex interplay of multiple risk factors. This study aims to identify key causal factors and typical configurations underlying these accidents to provide targeted prevention strategies. First, representative coal mine accident cases were collected, and risk factors were extracted using the 24Model accident causation framework. A causal network of these factors was then constructed and analyzed to identify the nodes exerting the greatest influence within the accident chain. Subsequently, crisp-set qualitative comparative analysis was employed to determine the configurational patterns of accident causation. The results indicate that the accident network exhibits short transmission paths, with critical factors including unsafe worker behaviors, disordered safety management, insufficient safety risk identification, and improper hazard handling. The qualitative comparative analysis (QCA) results classify accident scenarios into four types: lax coal mining management, inadequate safety culture, weak safety awareness, and alienated organizational behavior. Tailored prevention strategies are proposed for each scenario. By integrating complex network analysis with QCA, this study deepens the theoretical understanding of coal mine accident causation and offers practical guidance to enhance the precision of accident prevention and optimize resource allocation efficiency.