Identifying Psychological Factors of E-Bike Riders’ Traffic Rule Violating Intention and Accident Proneness in China

This paper aims to understand and predict electric bike (e-bike) riders’ traffic rule violating intention and accident proneness using self-report survey data of over 2,000 e-bike riders in Shanghai. An extension of the theory of planned behavior (TPB) is proposed for this purpose which integrated seven new psychological factors (moral norm, perceived risk, conformity tendency, self-identify, descriptive norm, legal norm, and past behavior) alone with three basic variables (attitude, subjective norm, and perceived behavioral control) in the original TPB. Structural equation models were estimated to understand the impacts of different TPB variables on traffic rule violating intention and accident proneness. Model estimation results show that the proposed model framework can better explain e-bike riders’ traffic rule violating intention and accident proneness compared to the original TPB. These findings can be used by policy-makers to design traffic safety management countermeasures that target identified psychological variables for reducing e-bike riders’ traffic rule violating intention and accident proneness.