Using the Theory of Planned Behavior to Understand Traffic Violation Behaviors in E-Bike Couriers in China
Author(s) -
Cheng Qian,
Wei Deng,
Qizhou Hu
Publication year - 2021
Publication title -
journal of advanced transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 46
eISSN - 2042-3195
pISSN - 0197-6729
DOI - 10.1155/2021/2427614
Subject(s) - theory of planned behavior , psychology , structural equation modeling , variance (accounting) , descriptive statistics , psychological intervention , salient , survey data collection , social norms approach , human factors and ergonomics , control (management) , social psychology , applied psychology , poison control , computer science , statistics , mathematics , business , environmental health , artificial intelligence , perception , accounting , psychiatry , neuroscience , medicine
This paper identifies salient beliefs that influence e-bike couriers’ traffic violation behavior based on the theory of planned behavior (TPB). Two surveys were conducted in Nanjing, China, in 2018. The first survey extracted the key psychological beliefs, which were used to design a questionnaire. The second survey assessed TPB components and reported e-bike couriers’ traffic violation behavior. A structural equation model was adopted to analyze the data. The results revealed that attitudes, descriptive norms, and perceived behavioral control explained 55.7% of the variance in intention to perform traffic violation behavior, and intentions together with perceived behavior control accounted for 28.5% of the variance in self-reported violation riding behavior. All of the belief composites had strong direct impacts on their respective TPB constructs. Salient beliefs were applied to develop effective intervention strategies. Age, education level, whether one possessed a driver’s license, and past traffic violation behaviors had significant effects on belief composites and behavior. The quantitative analysis results obtained in the study can provide theoretical support for designing more effective interventions for reducing the traffic violation rate of e-bike couriers.
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