ArticleHeliyon2024
Corporate driver management perspectives: A PLS-SEM-based analysis of the mechanism of bus crash injury severity factor effects.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- From Prediction to Prevention: Using Text Mining and Explainable Machine Learning for Urban Bus Accident Analytics.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In view of the suddenness, complexity and high-risk potential of bus crashes, the injury severity and its influencing factors have increasingly became the research focus in urban transportation safety management. The purpose of this study is to analyze the core elements of bus crash injury severity and its interaction mechanism, in order to provide a scientific basis for improving the bus operation safety. In this study, 283 crashes occurred in a Chongqing bus company from January to June 2022 were taken as samples around the dimensions of drivers' educational background, driving characteristics, weather, and corporate management strategies. PLS-SEM, CoMe index, MICOM, and permutation-based MGA are comprehensively applied to deeply analyze the direct and indirect effects among variables and reveal the conditional mediation effect. The study found crash injury severity effects ranked in order of crash liability, work intensity, weather conditions, violation tendency, education, and driving experience. Bus driver's crash liability plays a fully mediating role between several factors and injury severity, while improving education and increasing rest gap time are effective in reducing bus driver's crash liability. Notably, bad weather flat peaks and good weather peak periods are prone to more severe bus crashes. In addition, the mediating effect of driving experience on liability level through violation tendency was significant only in bus driver groups with moderate to high sense of work responsibility. This study deepens our understanding of bus crash injury severity and its interaction mechanism, guiding targeted safety measures for bus corporation and boosting overall public transportation safety.
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Registered trials
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