Towards Integrated Solutions: A Comparative Study of Urban–Rural Last-Mile Delivery Disparities and Optimization Paths

Authors

  • Qinan Hu

DOI:

https://doi.org/10.61173/p7xkyq08

Keywords:

Last-Mile Logistics, Urban-Rural Disparity, Logistics Optimization, Cross-Sector Collaboration, Comparative Case Study

Abstract

The “last-mile delivery” problem, the most costly and challenging segment of the logistics chain, exhibits significant disparities between urban and rural areas, hindering balanced development and elevating social logistics costs. This study employs bibliometrics, comparative research, and case analysis methods to conduct a systematic comparative analysis of urban and rural last-mile delivery systems, integrating multi-source data from both domestic and international contexts. The results highlight a fundamental urban-rural dichotomy: urban pain points stem from resource imbalance and terminal congestion, whereas rural challenges are rooted in infrastructural deficits and the ‘difficult and costly delivery’ dilemma. Furthermore, common constraints across both contexts are identified, including inadequate technology adaptability and a deficiency in cross-subject collaboration. To address these differentiated and common challenges, this paper proposes a dual-path solution: ‘differentiated optimization’ for urban and rural specificities, coupled with ‘global collaboration’ to tackle systemic bottlenecks. This helps both rural renewal and city living. In theory, the research builds a new “problem-technology-model-policy” analysis framework. It fills a gap in current studies by bringing these parts together in a systematic way.

References

[1] Bai, Yong, et al. A Hierarchical Hub Location Model for Urban-Rural Logistics Networks. European Journal of Dean&Francis ISSN 2959-6130 Operational Research, 2023, 312(2): 589-602.

[2] Smith, John, et al. Tactical Routing and Fleet Planning in Drone-Assisted Last-Mile Delivery. Journal of Operations Management, 2022, 74(1): 102-120.

[3] Chen, Li, et al. Hybrid Last Mile Delivery Fleets with Crowdsourcing. Journal of Business Logistics, 2023, 44(3): 289- 308.

[4] Wang, Hong, et al. The Value of Autonomous Vehicles for Last-Mile Deliveries. Management Science, 2024, 70(5): 2103- 2121.

[5] Li, Xiao, et al. Comparative Study on Urban Logistics in Germany and China. International Journal of Production Economics, 2024, 271: 108892.

[6] Müller, Thomas, et al. Sustainable Urban Last-Mile Delivery: A Case Study of Berlin. Journal of Cleaner Production, 2023, 380: 135120.

[7] Zhang, San, et al. Rural Logistics Service Network Construction in China: A Case Study of Faku County. Chinese Journal of Logistics Management, 2023, 5(2): 45-62.

[8] Johnson, Andrew, et al. Dynamic Pricing for Rural Crowdsourced Delivery. Transportation Research Part E, 2023, 172: 103156.

[9] Liu, Hua, et al. Address Standardization in Rural China: Challenges and Solutions. Journal of Rural Studies, 2023, 102: 287-298.

[10] Brown, Kevin, et al. Public-Private Partnerships in Last- Mile Logistics: Global Experiences. International Journal of Logistics Management, 2024, 35(1): 78-99.

Downloads

Published

2025-12-19