Exploring the Psychological Mechanism of Passengers Adhering to Emergency Evacuation Signs During Subway Fire Emergencies: An Application of the Protective Action Decision Model and the Heuristic–Systematic Model
Bian Yang, Zhao Xuena, Zhao Xiaohua, Yu Zhang, Liu Zhuoran
Beijing Transportation Research Center
内容与影响
In emergency evacuation scenarios, ensuring the safe and prompt evacuation of passengers is of utmost importance. Although emergency evacuation signs hold significant meaning, passengers often hesitate to comply with them during emergencies. Therefore, it is crucial to understand the psychological decision-making process that passengers undergo in these critical situations. This study focuses on subway fire emergencies and examines the psychological decision-making mechanisms influencing passengers' evacuation sign compliance (ESC) intention. To achieve this, a psychological mechanism framework model based on the protection action decision model (PADM) and the heuristic-systematic model (HSM) is constructed. The study adopts a questionnaire survey to establish a structural equation model for passengers' ESC intention, followed by mediation and moderation analyses of the predictive factors. The research findings reveal that passengers' ESC intention is positively correlated with risk perception (RP), hazard-related attributes, information seeking (IS), and systematic information processing (SIP), while being negatively associated with resource-related attribute (RRA) perception. The mediation analysis indicates that both IS and SIP act as mediators in the relationship between RP and ESC intention. Furthermore, SIP serves as a mediator between IS and ESC intention. The moderation analysis demonstrates that the importance of RRAs intensifies the negative association between RRAs and ESC intention. This research enhances our understanding of the psychological mechanisms underlying passengers' ESC intention and provides practical suggestions for subway engineering design and emergency management.
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工程Evacuation and Crowd Dynamics
Safety Warnings and Signage · Disaster Management and Resilience
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