Xiaolong Zhang, Jianling Huang, Yang Bian, Xiaohua Zhao, Tangshan Han
{"title":"Shared e-bike riders’ psychology contribution to self-reported traffic accidents: a structural equation model approach with mediation analysis","authors":"Xiaolong Zhang, Jianling Huang, Yang Bian, Xiaohua Zhao, Tangshan Han","doi":"10.1080/19439962.2022.2137868","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":"184 1","pages":"895 - 917"},"PeriodicalIF":2.4000,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Transportation Safety & Security","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/19439962.2022.2137868","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 1
Abstract
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.