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Platform-empowered collaboration delivery model for express companies and rural passenger transport operators in rural areas

Weizhen Rao, Xiaohe Miao, Peng Liu and Lu Liu

Transportation Research Part E: Logistics and Transportation Review, 2025, vol. 202, issue C

Abstract: The rapid surge in e-commerce parcel volume has intensified demands for cost-effective and high-quality express delivery services in rural areas. This study proposes a platform-enabled collaborative delivery model that integrates express companies and rural passenger transport operators to improve last-mile logistics. Our goal is to facilitate efficient collaboration among stakeholders through platform-supported route planning and cost-sharing, with cost savings quickly estimated for decision-making. To assess the benefits of shared transport resources, we adopt a Shapley value-based cooperative game approach to determine cost allocation. This requires solving mixed-integer programming models for all possible alliance structures to compute characteristic functions. A mixed-integer linear programming model is formulated to address the multi-owner collaborative delivery vehicle routing problem with combined passenger and freight transport (MOCDVRP-CPFT), which quantifies delivery costs for each alliance configuration. A tailored solution framework is developed, incorporating batch processing, customer clustering, and an adaptive large neighbourhood search (ALNS) algorithm to generate high-quality solutions across all alliances. Six representative case studies in eastern, central, and western China using real-world data confirm the effectiveness of the proposed model, with the most significant savings observed in the western region. Based on the results, we offer region-specific policy suggestions to facilitate the implementation of CPFT in varying rural contexts. This study highlights the potential of digitally enabled, short-term collaborative alliances as a practical approach to improving rural logistics coordination and delivery efficiency.

Keywords: Collaborative delivery; Integration of passenger and freight; Adaptive large neighbourhood search; Cost allocation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.tre.2025.104311

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