Citation

Zhou J, Shen Y, Guo Y, Dong S. J. Traffic Transp. Eng. Engl. Ed. 2023; 10(4): 633-646.

Copyright

(Copyright © 2023, Periodical Offices of Chang'an University, Publisher Elsevier Publishing)

DOI

10.1016/j.jtte.2021.12.006

PMID

unavailable

Abstract

The rapid development of the delivery industry brings convenience to modern society. However, the high rates of crashes and the survival of electric bicycle (e-bike) riders in the delivery industry raise concerns. The primary objective of this study is to explore the factors affecting delivery e-bike riders' stressful work pressure and crash involvement in China. Data were collected by a questionnaire survey administered in the city of Ningbo, China. A bivariate ordered probit (BOP) model was developed to simultaneously examine the factors associated with both the working conditions of delivery e-bike riders and their involvement in crashes. The marginal effects for the contributory factors were calculated to quantify their impacts on the outcomes. The results showed that the BOP model can account for commonly unobserved characteristics of the working conditions and crash involvement of delivery e-bike riders. The BOP model results showed that the stressful working conditions of delivery e-bike riders were affected by the number of orders and delivery time and rider age and risky riding behaviors. Delivery rider involvement in crashes was affected by the number of orders, strength of the punishment for traffic violations, and familiarity with traffic regulations. It was also found that stressful working conditions and crash involvement were strongly and positively correlated. The findings of this study can enhance our understanding of the factors that affect the working conditions and delivery rider crash involvement. Based on the results, some suggestions regarding public policy, risky riding behaviors, safety promotion, and stronger corporate governance rules were discussed to increase the targeted safety-related interventions for delivery e-bike riders in Ningbo, China.

Language: en

Keywords

Bivariate ordered probit model; Crash involvement; Delivery e-bike; Electric bicycle riders; Stressful working conditions; Traffic safety