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Retail Deliveries by Drones: How Will Logistics Networks Change?

Author

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  • Sandun Perera
  • Milind Dawande
  • Ganesh Janakiraman
  • Vijay Mookerjee

Abstract

Emerging technologies such as drone delivery services enable retailers to cost‐effectively offer unprecedented delivery speed and adaptable delivery lead times using dedicated aerial vehicles for individual orders. A natural and important question arises: What is the impact of a drone delivery system (DDS) on a retailer’s extant logistics parameters, for example, the number of customer‐facing delivery centers (last‐mile warehouses) it uses and delivery lead times it offers? On the one hand, the ability to reach customers faster than through traditional means argues for more centralization of delivery services. On the other hand, more decentralization can allow the retailer to offer hitherto unheard‐of delivery lead times and thereby spur demand. We show that, as drone technology matures and becomes more cost‐effective, delivery networks will become increasingly decentralized while delivering products at faster speeds. While perfect delivery customization—under which each demand location is offered a customized delivery guarantee—is theoretically feasible under a DDS, it may not be practical to implement such a finely differentiated delivery strategy. Instead, we show that retailers can recover a significant portion of the profit under this ideal scenario by offering limited delivery‐time customization, that is, partitioning the market into a few delivery “zones” and offering the best feasible delivery guarantee for each zone. In physically congested metropolitan markets, where retailers may be forced to operate with only a few delivery centers, it may be optimal to operate a DDS by offering delivery guarantees that are inferior to the best possible in order to throttle unprofitable demand. In such markets, the effectiveness of limited delivery‐time customization increases as the extent of physical congestion increases.

Suggested Citation

  • Sandun Perera & Milind Dawande & Ganesh Janakiraman & Vijay Mookerjee, 2020. "Retail Deliveries by Drones: How Will Logistics Networks Change?," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2019-2034, September.
    • Handle: RePEc:bla:popmgt:v:29:y:2020:i:9:p:2019-2034
    DOI: 10.1111/poms.13217
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    References listed on IDEAS

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    7. Sunil Mithas & Zhi‐Long Chen & Terence J.V. Saldanha & Alysson De Oliveira Silveira, 2022. "How will artificial intelligence and Industry 4.0 emerging technologies transform operations management?," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4475-4487, December.
    8. Chen, Heng & Hu, Zhangchen & Solak, Senay, 2021. "Improved delivery policies for future drone-based delivery systems," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1181-1201.
    9. Amine Masmoudi, M. & Mancini, Simona & Baldacci, Roberto & Kuo, Yong-Hong, 2022. "Vehicle routing problems with drones equipped with multi-package payload compartments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
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    12. Büyüközkan, Gülçin & Ilıcak, Öykü, 2022. "Smart urban logistics: Literature review and future directions," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    13. Zhang, Guowei & Jia, Ning & Zhu, Ning & Adulyasak, Yossiri & Ma, Shoufeng, 2023. "Robust drone selective routing in humanitarian transportation network assessment," European Journal of Operational Research, Elsevier, vol. 305(1), pages 400-428.
    14. Cao, Kaiying & Xu, Yuqiu & Hua, Ye & Choi, Tsan-Ming, 2023. "Supplier or co-optor: Optimal channel and logistics selection problems on retail platforms," European Journal of Operational Research, Elsevier, vol. 311(3), pages 971-988.

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