Risk Hazards, Quantitative Measurement, and Influencing Mechanism of Industrial Special Railway Lines in China: Empirical Analysis Based on Regional Panel Operation Data

Industrial special railway lines constitute the freight “last mile” of China’s railway network, while scattered property rights and aging safety facilities trigger frequent safety accidents. Existing railway literature lacks systematic quantitative research on the hidden dangers of special lines. Based on official supervision and accident panel data of 32 industrial special railway lines from 2022 to 2025 released by the State Railway Administration of China, this paper constructs an input-output risk evaluation system containing undesirable accident outputs covering human, capital, and equipment safety inputs. The Super-SBM model with reciprocal transformed accident indicators is adopted to measure static safety risk efficiency, the Malmquist index decomposes dynamic risk evolution characteristics, and a Tobit truncated regression model is built to identify core risk influencing factors. The empirical results show that the overall safety risk of industrial special railway lines presents a continuous upward trend year by year; coal mine dedicated railways in North China bear the highest risk level, and manufacturing railway sidings in Central China maintain better safety control performance. Human error operation, unattended level crossing density, and dangerous goods transport proportion significantly aggravate operational risks, whereas intelligent monitoring coverage effectively restricts hidden danger outbreaks. This study distinguishes heterogeneous risk characteristics of different types of special lines and puts forward differentiated hierarchical risk prevention and control strategies, which can provide quantitative decision support for railway supervision departments and industrial enterprises to implement refined safety management.