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Demand Management for Attended Home Delivery – A Literature Review

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Listed:
  • Wassmuth, K.
  • Köhler, C.
  • Agatz, N.A.H.
  • Fleischmann, M.

Abstract

Given the continuing e-commerce boom, the design of efficient and effective home delivery services is increasingly relevant. From a logistics perspective, attended home delivery, which requires the customer to be present when the purchased goods are delivered, is particularly challenging. To facilitate the delivery, the service provider and the customer typically agree on a specific time window for service. In designing the service offering, service providers face complex trade-offs between customer preferences and profitable service execution. In this paper, we map these trade-offs to different planning levels and demand management levers, and structure and synthesize corresponding literature according to different demand management decisions. Finally, we highlight research gaps and future research directions and discuss the linkage of the different planning levels.

Suggested Citation

  • Wassmuth, K. & Köhler, C. & Agatz, N.A.H. & Fleischmann, M., 2022. "Demand Management for Attended Home Delivery – A Literature Review," ERIM Report Series Research in Management ERS-2022-002-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:137109
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    References listed on IDEAS

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    1. Magdalena A. K. Lang & Catherine Cleophas & Jan Fabian Ehmke, 2021. "Anticipative Dynamic Slotting for Attended Home Deliveries," SN Operations Research Forum, Springer, vol. 2(4), pages 1-39, December.
    2. Lebedev, Denis & Goulart, Paul & Margellos, Kostas, 2021. "A dynamic programming framework for optimal delivery time slot pricing," European Journal of Operational Research, Elsevier, vol. 292(2), pages 456-468.
    3. Elena Belavina & Karan Girotra & Ashish Kabra, 2017. "Online Grocery Retail: Revenue Models and Environmental Impact," Management Science, INFORMS, vol. 63(6), pages 1781-1799, June.
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    5. Remy Spliet & Said Dabia & Tom Van Woensel, 2018. "The Time Window Assignment Vehicle Routing Problem with Time-Dependent Travel Times," Transportation Science, INFORMS, vol. 52(2), pages 261-276, March.
    6. Remy Spliet & Adriana F. Gabor, 2015. "The Time Window Assignment Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 721-731, November.
    7. Strauss, Arne & Gülpınar, Nalan & Zheng, Yijun, 2021. "Dynamic pricing of flexible time slots for attended home delivery," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1022-1041.
    8. Nabila Azi & Michel Gendreau & Jean-Yves Potvin, 2012. "A dynamic vehicle routing problem with multiple delivery routes," Annals of Operations Research, Springer, vol. 199(1), pages 103-112, October.
    9. Spliet, Remy & Desaulniers, Guy, 2015. "The discrete time window assignment vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 244(2), pages 379-391.
    10. Nan Liu & Peter M. van de Ven & Bo Zhang, 2019. "Managing Appointment Booking Under Customer Choices," Management Science, INFORMS, vol. 65(9), pages 4280-4298, September.
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    Cited by:

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