Citation

He Y, Sun C, Chang F. Accid. Anal. Prev. 2023; 184: e107013.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.aap.2023.107013

PMID

36863170

Abstract

The delivery industry has seen dramatic growth in demand and scale in China. Due to the stock limitations and delivery time restrictions, the couriers may commit traffic violations while delivering, resulting in a pessimistic road safety situation. This study aims to reveal critical factors that influence delivery vehicle crash risks. A cross-sectional structured questionnaire survey is conducted to collect demographic attributes, workload, work emotions, risky driving behavior, and road crash involvement data among 824 couriers in three developed regions of China. The collected data is then analyzed through an established path model to identify the contributing factors of delivery road crash risks and risky behaviors. The road crash risk level (RCRL) indicator is defined by taking into consideration both frequency and severity. While the risky behaviors are defined by both their frequency and correlations to crash risks. The results indicate that 1) Beijing-Tianjin Urban Agglomeration has the highest road crash frequency and RCRL; 2) distracted driving and wrong-lane-use are among the top three risky behaviors for both Yangtze River Delta Urban Agglomeration and Pearl River Delta Urban Agglomeration. For Beijing-Tianjin Urban Agglomeration, distracted driving, aggressive driving, and lack of protection are the top three risky behaviors; 3) time demand and personal efforts are important factors contributing to the cognitive workload of couriers; 4) objective workload can affect the cognitive workload and both workloads influence drivers' emotions (anxiety and anger); 5) the objective, cognitive workload, drivers' emotions influence the RCRL through their impacts on risky behavior but in different paths for three agglomerations. The findings highlight the importance of developing targeted countermeasures to reduce the delivery workers' workload, improve their performance on roads, and mitigate severe crash risks.

Language: en

Keywords

Workload; Delivery workers; Path analysis model; Risky behavior; Road crash