China's Railway Transportation Safety Regulation System Based on Evolutionary Game Theory and System Dynamics. Issue 10 (3rd June 2020)

• Record Type: Journal Article
• Authors: Feng, Fenling; Liu, Chengguang; Zhang, Jiaqi
• Is Part Of: Risk analysis. Volume 40:Issue 10(2020)
• Page Start: 1944
• Page End: 1966
• Publication Date: 2020-06-03
• Subjects: Dynamic reward and penalty strategy -- evolutionary game theory -- railway transportation safety regulation -- system dynamics -- the public supervision; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.13528
• Languages: English
• ISSNs: 0272-4332

Abstract

Abstract: China's railways were restructured in 2013. The number of regulatory practitioners has decreased significantly, making real‐time regulation more difficult. Regulatory transfers from inside to outside the railway industry increases information risks. A more reasonable regulation mechanism is needed. The article considers introducing a public supervision mechanism into the railway transportation safety regulation system, which includes two regulators and one regulatee. As the government regulator, the State Railway Administration (SRA) regulates the safety of China Railway Corporation (CR) and encourages the public to act as supervisors to expose the CR's unsafe production information. To analyze the risks and effectiveness of the system, a multiplayer evolutionary game and system dynamics‐based model for railway transportation safety regulation is established. The decision processes of players under different conditions are simulated. The results show that improving the public supervision ratio is conducive to improve the CR's safe production ratio. However, there is no evolutionarily stable strategy (ESS) in the system. Strategies and evolutionary processes have large fluctuations, which represent high risk. Excessive penalty and reward coefficients can aggravate the amplitude and frequency of fluctuations, causing uncertainty in regulation and making it more difficult to control the actual problems. A dynamic reward and punishment mechanism is proposed to control these fluctuations. The system finally achieves an ESS that results in the lowest regulation investment for the SRA, a safe production ratio for the CR of 95%, and a public supervision ratio of 95.2%. Introducing public supervision and dynamic reward and punishment mechanisms help to stabilize and improve the CR's safe production ratio and to decrease the SRA's regulatory investment.