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Shared e-bike riders' psychology contribution to self-reported traffic accidents: a structural equation model approach with mediation analysis.

Authors :
Zhang, Xiaolong
Huang, Jianling
Bian, Yang
Zhao, Xiaohua
Han, Tangshan
Source :
Journal of Transportation Safety & Security. 2023, Vol. 15 Issue 9, p895-917. 23p.
Publication Year :
2023

Abstract

With the rise of the transportation mode of shared electric bikes (shared e-bikes) in China, shared e-bike related accidents have gradually increased. To facilitate the design of safety policies, it is important to understand the factors that influence shared e-bike riders' traffic accidents to facilitate intervention strategies. For this purpose, the structural equation model (SEM) with mediation analysis was applied by incorporating seven latent factors: traffic accidents, traffic violation behaviors, attitude toward safety responsibility, and attitude toward rule violations, risk perception, perceptive-motor skills, and safety skills. A questionnaire survey of a sample of 406 shared e-bike riders in China was conducted to obtain self-reported survey data. The results reveal that traffic violation behaviors and attitude toward safety responsibility had a statistically significant consequence on traffic accidents. Attitude toward rule violations, perceptive-motor skills, and safety skills can predict shared e-bike riders' traffic accidents when the traffic violation behaviors are used as a mediator. Moreover, risk perception could also be used to predict shared e-bike riders' traffic accidents when using attitudes toward safety responsibility or rule violations and traffic violation behaviors as a mediator. This paper lays a foundation for policymakers and traffic managers to develop effective intervention strategies and improve shared e-bike safety. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19439962
Volume :
15
Issue :
9
Database :
Academic Search Index
Journal :
Journal of Transportation Safety & Security
Publication Type :
Academic Journal
Accession number :
171842863
Full Text :
https://doi.org/10.1080/19439962.2022.2137868