共享电动车使用者心理对自述交通事故的贡献:结构方程模型与中介分析

IF 2.4 3区 工程技术 Q3 TRANSPORTATION
Xiaolong Zhang, Jianling Huang, Yang Bian, Xiaohua Zhao, Tangshan Han
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引用次数: 1

摘要

随着共享电动自行车(共享电动自行车)这种交通方式在中国的兴起,与共享电动自行车相关的事故也逐渐增多。为了方便安全政策的设计,了解影响共享电动自行车使用者交通事故的因素,以便制定干预策略。为此,采用结构方程模型(SEM)进行中介分析,将交通事故、交通违规行为、安全责任态度、违规态度、风险感知、感知运动技能和安全技能这7个潜在因素纳入研究。以406名共享电动自行车骑行者为样本进行问卷调查,获得自述调查数据。结果表明,交通违法行为和安全责任态度对交通事故有显著的影响。当交通违规行为作为中介时,违规态度、感知运动技能和安全技能可以预测共享电动自行车骑行者的交通事故。此外,当以安全责任态度或违反交通规则行为和交通违规行为作为中介时,风险感知也可以用于预测共享电动自行车骑行者的交通事故。本文为政策制定者和交通管理者制定有效的干预策略,提高共享电动自行车的安全性奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shared e-bike riders’ psychology contribution to self-reported traffic accidents: a structural equation model approach with mediation analysis
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.
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来源期刊
CiteScore
6.00
自引率
15.40%
发文量
38
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