Predicting e-bike users' intention to run the red light: An application and extension of the theory of planned behavior

被引:57
|
作者
Yang, Hongtai [1 ]
Liu, Xiaohan [1 ]
Su, Fan [1 ]
Cherry, Christopher [2 ]
Liu, Yugang [1 ]
Li, Yanlai [1 ]
机构
[1] Southwest Jiaotong Univ, Sch Transportat & Logist, Natl United Engn Lab Integrated & Intelligent Tra, Chengdu, Sichuan, Peoples R China
[2] Univ Tennessee Knoxville, Dept Civil & Environm Engn, Knoxville, TN USA
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Electric two-wheeler; Traffic violation; Social psychological model; Non-motorized vehicle; Riding behavior; CROSSING BEHAVIOR; RUNNING BEHAVIOR; EXTENDED THEORY; ELECTRIC BIKES; ROAD; RIDERS; CYCLISTS; DETERMINANTS; SPEED; MODEL;
D O I
10.1016/j.trf.2018.05.027
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
Electric bike (e-bike) users in China have a high red light running (RLR) rate, contributing to a large number of accidents. This paper aims to examine the psychological motivation of e-bike users' RLR intentions. A survey questionnaire was designed employing the construct of theory of planned behavior (TPB). The survey was performed in Chengdu, China in November 2016. We found that users older than 40 identify themselves as more cautious riders. Younger riders have higher intention to run the red light. E-bike users with car drivers' licenses regard running the red light as a more difficult task to perform, and regard this behavior as more morally wrong. Hierarchical regression was used to analyze the data. The results showed that demographic variables (age, marriage status, and college degree), TPB variables (attitude and perceived behavioral control) and extended variables (moral norm and self-identity) are significant predictors for the intention of RLR behavior. The results could provide reference for designing more effective interventions and safety education programs for reducing e-bike users' RLR rate. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:282 / 291
页数:10
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