Impact of Helmet-Wearing Policy on E-Bike Safety Riding Behavior: A Bivariate Ordered Probit Analysis in Ningbo, China

Jibiao Zhou, Tao Zheng, Sheng Dong, Xinhua Mao and Changxi Ma
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Jibiao Zhou: College of Transportation Engineering, Tongji University, Shanghai 200082, China
Tao Zheng: School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, China
Sheng Dong: College of Transportation Engineering, Tongji University, Shanghai 200082, China
Xinhua Mao: College of Transportation Engineering, Chang’an University, Xi’an 710064, China
Changxi Ma: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China

IJERPH, 2022, vol. 19, issue 5, 1-21

Abstract: At present, Chinese authorities are launching a campaign to convince riders of electric bicycles (e-bikes) and scooters to wear helmets. To explore the effectiveness of this new helmet policy on e-bike cycling behavior and improve existing e-bike management, this study investigates the related statistical distribution characteristics, such as demographic information, travel information, cycling behavior information and riders’ subjective attitude information. The behavioral data of 1048 e-bike riders related to helmet policy were collected by a questionnaire survey in Ningbo, China. A bivariate ordered probit (BOP) model was employed to account for the unobserved heterogeneity. The marginal effects of contributory factors were calculated to quantify their impacts, and the results show that the BOP model can explain the common unobserved features in the helmet policy and cycling behavior of e-bike riders, and that good safety habits stem from long-term safety education and training. The BOP model results show that whether wearing a helmet, using an e-bike after 19:00, and sunny days are factors that affect the helmet wearing rate. Helmet wearing, evenings during rush hour, and picking up children are some of the factors that affect e-bike accident rates. Furthermore, there is a remarkable negative correlation between the helmet wearing rate and e-bike accident rate. Based on these results, some interventions are discussed to increase the helmet usage of e-bike riders in Ningbo, China.

Keywords: electric bicycle; BOP model; helmet policy; cycling behavior; interventions (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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