Abstract
Safety management is a key issue in the railroad industry that needs to be continuously focused on. And it is essential to study causes of accidents for preventing accidents. However, there is a limited academic discussion on the systematic study of organizations and accidents, as well as their safety-related interactions and accidents, as opposed to human-caused disasters. Thus, the model of China’s railway safety supervision and management system by sorting out the existing organizations involved in management in China is established in this paper. Firstly, social forces and auxiliary enterprises are specifically added to the model. And then, the relationship between organizations and accidents, as well as the relationship between safety interactions among organizations and accidents are explored by analyzing 224 accident reports, which led to 4 principles for accident prevention. Finally, based on these principles, measures to secure organizational nodes, as well as measures to promote safe interactions among organizations are proposed. The results showed that: (1) China Railway node is not only the most critical node in the safety supervision and management system but also the most vulnerable to the influence of other nodes. (2) The accident occurred due to the simultaneous occurrence of an accident at the China Railway node and the social force node. (3) When there are often safety risks in auxiliary enterprises and social forces simultaneously, the government’s management is likely to be defective. The findings in this study can provide helpful references not only for improvement of safety management system structure and supervision and management mechanism but also for the formulation of safety supervision and management policies in China and other countries.
Funder
National Natural Science Foundation of China
Science and technology innovation project of colleges and universities in Shanxi Province
Publisher
Public Library of Science (PLoS)
Reference50 articles.
1. A statistical study of railway safety in China and Japan 1990–2020;Y Cao;Accident Analysis & Prevention,2022
2. Measuring regional transport sustainability using super-efficiency SBM-DEA with weighting preference;N Tian;Journal of Cleaner Production,2020
3. Hazards correlation analysis of railway accidents: A real-world case study based on the decade-long UK railway accident data;N Wang;Safety Science,2023
4. Investigation and prioritization of risk factors in the collision of two passenger trains based on fuzzy COPRAS and fuzzy DEMATEL methods;A Hasheminezhad;Soft Comput,2021
5. The influence of organizational factors on safety in Taiwanese high-risk industries;SH Hsu;Journal of Loss Prevention in the Process Industries,2010