Configuration of last-mile distribution networks for an encroaching manufacturer

Tahirov, Nail; Akhundov, Najmaddin; Emde, Simon; Glock, Christoph H.

Abstract

The surge of e-commerce has revolutionized distribution channels, escalating from simple single-channel frameworks to complex multi-channel and omni-channel networks. In particular developments in information technology and rising customer expectations have popularized the transition from multi- to omni-channel distribution, where the classic brick-and-mortar stores can also be part of the omni-channel distribution strategy. This evolution poses intricate challenges for manufacturers, especially in the integration and optimization of these channels. Thus, there is a strong need for an in-depth analysis of how manufacturers navigate the transition across diverse distribution channels to meet the varying needs of different customer segments. To this end, we investigate single-, multi-, and omni-channel distribution strategies for the case of a manufacturer selling both standard and customized products to different customer segments with varying preferences. A central contribution of this research is the creation of an integrated optimization model that resolves a location-routing problem, designing a complex and realistic supply chain configuration suitable for an omni-channel distribution system. This model strategically serves to fragmented customer demands through multiple shopping and delivery options. The outcomes of our study indicate that an omni-channel distribution system is a viable approach, capable of serving more customer segments while simultaneously minimizing logistics costs. In addition, we offer a detailed analysis of the cost implications of in-store pickup versus home-delivery options, providing a comprehensive evaluation of their respective impacts on total logistics costs and customer responsiveness.

Citation

Tahirov, N., Akhundov, N., Emde, S., & Glock, C. H. (2025). Configuration of last-mile distribution networks for an encroaching manufacturer. Annals of Operations Research, 344, 679-720. https://doi.org/10.1007/s10479-024-06031-3

• Journal Article Type: Article
• Acceptance Date: Apr 24, 2024
• Online Publication Date: May 21, 2024
• Publication Date: 2025
• Deposit Date: Nov 27, 2024
• Publicly Available Date: Jun 16, 2025
• Journal: Annals of Operations Research
• Print ISSN: 0254-5330
• Electronic ISSN: 1572-9338
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 344
• Pages: 679-720
• DOI: https://doi.org/10.1007/s10479-024-06031-3
• Public URL: https://durham-repository.worktribe.com/output/3108370