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Strategic Network Design for Parcel Delivery with Drones Under Competition

Author

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  • Gohram Baloch

    (Department of Management Sciences, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada)

  • Fatma Gzara

    (Department of Management Sciences, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada)

Abstract

This paper studies the economic desirability of unmanned aerial vehicle (UAV) parcel delivery and its effect on e-retailer distribution networks while taking into account technological limitations, government regulations, and customer behavior. We consider an e-retailer offering multiple same-day delivery services including a fast UAV service and develop a distribution network design formulation under service-based competition where the services offered by the e-retailer not only compete with the stores (convenience, grocery, etc.) but also with each other. Competition is incorporated using the multinomial logit market share model. To solve the resulting nonlinear mathematical formulation, we develop a novel logic-based Benders decomposition approach. We build a case based on New York City, carry out extensive numerical testing, and perform sensitivity analyses over delivery charge, delivery time, government regulations, technological limitations, customer behavior, and market size. The results show that government regulations, technological limitations, and service charge decisions each play a vital role in the future of UAV delivery.

Suggested Citation

  • Gohram Baloch & Fatma Gzara, 2020. "Strategic Network Design for Parcel Delivery with Drones Under Competition," Transportation Science, INFORMS, vol. 54(1), pages 204-228, January.
    • Handle: RePEc:inm:ortrsc:v:54:y:2020:i:1:p:204-228
    DOI: 10.1287/trsc.2019.0928
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    2. Osakwe, Christian Nedu & Hudik, Marek & Říha, David & Stros, Michael & Ramayah, T., 2022. "Critical factors characterizing consumers’ intentions to use drones for last-mile delivery: Does delivery risk matter?," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    3. Lin, Yun Hui & Wang, Yuan & Lee, Loo Hay & Chew, Ek Peng, 2022. "Omnichannel facility location and fulfillment optimization," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 187-209.
    4. Long He & Sheng Liu & Zuo‐Jun Max Shen, 2022. "Smart urban transport and logistics: A business analytics perspective," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3771-3787, October.
    5. Sun, Xuting & Fang, Minghao & Guo, Shu & Hu, Yue, 2024. "UAV-rider coordinated dispatching for the on-demand delivery service provider," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    6. 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.
    7. Yun Hui Lin & Qingyun Tian & Yanlu Zhao, 2022. "Locating facilities under competition and market expansion: Formulation, optimization, and implications," Production and Operations Management, Production and Operations Management Society, vol. 31(7), pages 3021-3042, July.
    8. Jianxun Li & Hao Liu & Kin Keung Lai & Bhagwat Ram, 2022. "Vehicle and UAV Collaborative Delivery Path Optimization Model," Mathematics, MDPI, vol. 10(20), pages 1-22, October.
    9. Meng, Zhu & Zhu, Ning & Zhang, Guowei & Yang, Yuance & Liu, Zhaocai & Ke, Ginger Y., 2024. "Data-driven drone pre-positioning for traffic accident rapid assessment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    10. Dukkanci, Okan & Campbell, James F. & Kara, Bahar Y., 2024. "Facility location decisions for drone delivery: A literature review," European Journal of Operational Research, Elsevier, vol. 316(2), pages 397-418.
    11. Guo, Penghui & Zhu, Jianjun, 2023. "Capacity reservation for humanitarian relief: A logic-based Benders decomposition method with subgradient cut," European Journal of Operational Research, Elsevier, vol. 311(3), pages 942-970.
    12. Yantong Li & Jean-François Côté & Leandro Callegari-Coelho & Peng Wu, 2022. "Novel Formulations and Logic-Based Benders Decomposition for the Integrated Parallel Machine Scheduling and Location Problem," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1048-1069, March.
    13. Schmidt, Sebastian & Saraceni, Adriana, 2024. "Consumer acceptance of drone-based technology for last mile delivery," Research in Transportation Economics, Elsevier, vol. 103(C).
    14. 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.
    15. Li, Yantong & Côté, Jean-François & Coelho, Leandro C. & Zhang, Chuang & Zhang, Shuai, 2023. "Order assignment and scheduling under processing and distribution time uncertainty," European Journal of Operational Research, Elsevier, vol. 305(1), pages 148-163.
    16. Hou, Wenjuan & Fang, Tao & Pei, Zhi & He, Qiao-Chu, 2021. "Integrated design of unmanned aerial mobility network: A data-driven risk-averse approach," International Journal of Production Economics, Elsevier, vol. 236(C).

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