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Travel satisfaction of delivery electric two-wheeler riders: Evidence from Nanjing, China

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  • Fan, Zhang
  • Yanjie, Ji
  • Huitao, Lv
  • Yuqian, Zhang
  • Blythe, Phil
  • Jialiang, Fan

Abstract

Sustainable transport policies aim to promote the well-being of all transport participants. Although the travel satisfaction of ordinary travelers has received extensive attention in previous studies, few have focused on the important bearer groups of the last mile urban logistics, especially with the current influx of delivery electric two-wheeler (DETW) riders on the road. This study aims to quantitatively explore the impact of riding perception, delivery attributes, built environment, and demographic variables on delivery travel satisfaction of DETW riders. Data were collected in Nanjing, China, through a questionnaire survey. The results show that the inclusion of built environment variables has provided additional variance explanation and proved their direct or indirect effect on delivery travel satisfaction. Besides, safety and accessibility, environmental comfort, delivery convenience, policy acceptance, and perceived stress positively affect delivery travel satisfaction, while delivery punishment has a negative effect. Delivery convenience is the most important variable explaining delivery travel satisfaction. Finally, policies at all levels, including individual riders, platforms, consumers, and public administration, are proposed to enhance the DETW riders’ well-being and make the food delivery industry more sustainable and appealing.

Suggested Citation

  • Fan, Zhang & Yanjie, Ji & Huitao, Lv & Yuqian, Zhang & Blythe, Phil & Jialiang, Fan, 2022. "Travel satisfaction of delivery electric two-wheeler riders: Evidence from Nanjing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 253-266.
    • Handle: RePEc:eee:transa:v:162:y:2022:i:c:p:253-266
    DOI: 10.1016/j.tra.2022.06.001
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    Cited by:

    1. Zhang, Fan & Lv, Huitao & Xing, Qiang & Ji, Yanjie, 2024. "Deployment of battery-swapping stations: Integrating travel chain simulation and multi-objective optimization for delivery electric micromobility vehicles," Energy, Elsevier, vol. 290(C).
    2. Zhang, Fan & Lv, Huitao & Liu, Yang & Yang, Ying & Wong, Melvin & Qu, Xiaobo, 2025. "Optimizing battery-swapping systems management for electric micro-mobility: A reinforcement learning approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 195(C).
    3. Ahmad, Hafsoah & Rahul, T.M. & Asija, Navdeep K., 2025. "Accelerators and hurdles, and their mediating effects on electric vehicle adoption," Transport Policy, Elsevier, vol. 162(C), pages 20-30.

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