TY - JOUR PY - 2021// TI - Understanding electric bike riders' intention to violate traffic rules and accident proneness in China JO - Travel behaviour and society A1 - Tang, Tianpei A1 - Guo, Yuntao A1 - Zhou, Xizhao A1 - Labi, Samuel A1 - Zhu, Senlai SP - 25 EP - 38 VL - 23 IS - N2 - As electric bicycles (e-bikes) have emerged as an important transportation mode in China in the past decade, e-bike-related accidents have increased drastically. Research suggests that the main cause of most of these accidents is traffic rule violations by e-bike riders and that some e-bike riders have a higher propensity to experience accidents (i.e., higher accident proneness) than otherwise similar individuals. To facilitate the design of safety policies, it is important to understand the factors that influence both e-bike riders' intention to violate traffic rules and accident proneness. For this purpose, an extension of the theory of planned behavior framework (E-TPB) was developed by incorporating seven new latent psychological factors (descriptive norm, moral norm, perceived risk, self-identity, legal norm, conformity tendency, and past behavior) into the original TPB framework (O-TPB). Using self-reported survey data from over 2000 e-bike riders collected in Shanghai, China, structural equation models for the E-TPB and the O-TPB were estimated. The model estimation results show that the E-TPB provides a more intuitive explanation of e-bike riders' intention to violate traffic rules and accident proneness and has superior predictive power compared to the O-TPB. The model estimation results also show that descriptive norm, conformity tendency, and past behavior are important factors that affect both e-bike riders' intention to violate traffic rules and accident proneness. These findings can be used by policymakers to design safety policies such as reward programs for safe riding behavior, e-bike rider education initiatives, and behavior modification interventions to improve road safety.
Language: en
LA - en SN - 2214-367X UR - http://dx.doi.org/10.1016/j.tbs.2020.10.010 ID - ref1 ER -