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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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    3. 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).
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    5. 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).
    6. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    7. 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.
    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. 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.
    10. 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.
    11. 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.
    12. 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.

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