Study on Influencing Factors of Emergency Equipment and Materials Allocation for Mountain Highway Freezing Disasters

To enhance the efficiency of emergency equipment and material allocation for freezing disasters on mountain highways in Guizhou Province, this study identifies key influencing factors, clarifies their mechanisms, and constructs an integrated analytical model by combining the Delphi method, Decision‐Making Trial and Evaluation Laboratory (DEMATEL), and interpretative structural modeling (ISM), coupled with the analytic hierarchy process (AHP) and entropy weight method for combined weighting. Through two rounds of Delphi expert consultation, 24 key influencing factors were selected and classified into four dimensions: disaster characteristics, environmental and traffic conditions, resource management status, and emergency response capabilities. DEMATEL–ISM analysis reveals a six‐level hierarchical structure of the influencing factor system, in which freezing disaster warning accuracy, terrain complexity, and completeness of emergency plans are identified as the fundamental driving factors; multi‐department collaborative decision‐making efficiency, road network reliability, and rationality of emergency material reserve layout serve as core transmission factors. The combined weights indicate that emergency response capabilities (weight 0.321) and resource management status (weight 0.285) exert the most significant influence, and multi‐department collaborative decision‐making efficiency (weight 0.092) is the most sensitive factor. Simulation verification based on historical freezing disaster cases in 2018 and 2022 demonstrates that the model‐recommended plan can improve response efficiency by more than 25%. The study suggests that emergency allocation capability should be systematically enhanced by optimizing resource layout, building cross‐departmental collaboration platforms, improving warning accuracy, and strengthening personnel training. Limitations of this study include the incomplete coverage of extreme rare scenarios in the factor system and the model’s constrained capacity to handle dynamic emergent events. Future research should integrate field validation studies and dynamic routing models. The proposed model and methodology provide quantitative decision support for emergency management on mountain highways and offer practical reference value for the construction of highway emergency support systems under similar geographic and climatic conditions.