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Flexible time window management for attended home deliveries

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  • Köhler, Charlotte
  • Ehmke, Jan Fabian
  • Campbell, Ann Melissa

Abstract

In the competitive world of online retail, customers can choose from a selection of delivery time windows on a retailer’s website. Creating a set of suitable and cost-efficient delivery time windows is challenging, since customers want short time windows, but short time windows can increase delivery costs significantly. Furthermore, the acceptance of a request in a short time window can greatly restrict the ability to accommodate future requests. In this paper, we present customer acceptance mechanisms that enable flexible time window management in the booking of time-window based attended home deliveries. We build tentative delivery routes and check which time windows are feasible for each new customer request. We offer the feasible long delivery time windows and let our approaches decide when to offer short time windows. Our approaches differ in the information they consider with regard to customer characteristics as well as detailed characteristics of the evolving route plan. We perform a computational study to investigate the approaches’ ability to offer short time windows and still allow for a large number of customers to be served. We consider various demand scenarios, partially derived from real order data provided by a German online supermarket.

Suggested Citation

  • Köhler, Charlotte & Ehmke, Jan Fabian & Campbell, Ann Melissa, 2020. "Flexible time window management for attended home deliveries," Omega, Elsevier, vol. 91(C).
    • Handle: RePEc:eee:jomega:v:91:y:2020:i:c:s030504831830803x
    DOI: 10.1016/j.omega.2019.01.001
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    References listed on IDEAS

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    1. Catherine Cleophas & Jan Ehmke, 2014. "When Are Deliveries Profitable?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(3), pages 153-163, June.
    2. Bard, Jonathan F. & Jarrah, Ahmad I., 2013. "Integrating commercial and residential pickup and delivery networks: A case study," Omega, Elsevier, vol. 41(4), pages 706-720.
    3. Ann Melissa Campbell & Martin W. P. Savelsbergh, 2005. "Decision Support for Consumer Direct Grocery Initiatives," Transportation Science, INFORMS, vol. 39(3), pages 313-327, August.
    4. Niels Agatz & Ann Campbell & Moritz Fleischmann & Martin Savelsbergh, 2011. "Time Slot Management in Attended Home Delivery," Transportation Science, INFORMS, vol. 45(3), pages 435-449, August.
    5. Ann Melissa Campbell & Martin Savelsbergh, 2006. "Incentive Schemes for Attended Home Delivery Services," Transportation Science, INFORMS, vol. 40(3), pages 327-341, August.
    6. Asdemir, Kursad & Jacob, Varghese S. & Krishnan, Ramayya, 2009. "Dynamic pricing of multiple home delivery options," European Journal of Operational Research, Elsevier, vol. 196(1), pages 246-257, July.
    7. Lu, Quan & Dessouky, Maged M., 2006. "A new insertion-based construction heuristic for solving the pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 175(2), pages 672-687, December.
    8. Ehmke, Jan Fabian & Campbell, Ann Melissa, 2014. "Customer acceptance mechanisms for home deliveries in metropolitan areas," European Journal of Operational Research, Elsevier, vol. 233(1), pages 193-207.
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    Cited by:

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    2. Jasper Grashuis & Theodoros Skevas & Michelle S. Segovia, 2020. "Grocery Shopping Preferences during the COVID-19 Pandemic," Sustainability, MDPI, vol. 12(13), pages 1-10, July.
    3. Haider, Zulqarnain & Hu, Yujie & Charkhgard, Hadi & Himmelgreen, David & Kwon, Changhyun, 2022. "Creating grocery delivery hubs for food deserts at local convenience stores via spatial and temporal consolidation," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    4. Waßmuth, Katrin & Köhler, Charlotte & Agatz, Niels & Fleischmann, Moritz, 2023. "Demand management for attended home delivery—A literature review," European Journal of Operational Research, Elsevier, vol. 311(3), pages 801-815.
    5. Mancini, Simona & Gansterer, Margaretha & Triki, Chefi, 2023. "Locker box location planning under uncertainty in demand and capacity availability," Omega, Elsevier, vol. 120(C).
    6. Zhou, Yizi & Mandania, Rupal & Liu, Jiyin, 2022. "Green vehicle routing and dynamic pricing for scheduling on-site services," International Journal of Production Economics, Elsevier, vol. 254(C).
    7. Koch, Sebastian & Klein, Robert, 2020. "Route-based approximate dynamic programming for dynamic pricing in attended home delivery," European Journal of Operational Research, Elsevier, vol. 287(2), pages 633-652.
    8. Agatz, N.A.H. & Fleischmann, M., 2023. "Demand Management for Sustainable Supply Chain Operations," ERIM Report Series Research in Management ERS-2023-001-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.
    9. Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
    10. Abdollahi, Mohammad & Yang, Xinan & Nasri, Moncef Ilies & Fairbank, Michael, 2023. "Demand management in time-slotted last-mile delivery via dynamic routing with forecast orders," European Journal of Operational Research, Elsevier, vol. 309(2), pages 704-718.
    11. van der Hagen, L. & Agatz, N.A.H. & Spliet, R. & Visser, T.R. & Kok, A.L., 2022. "Machine Learning-Based Feasibility Checks for Dynamic Time Slot Management," ERIM Report Series Research in Management ERS-2022-001-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.
    12. Avraham, Edison & Raviv, Tal, 2021. "The steady-state mobile personnel booking problem," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 266-288.
    13. Sharif Azadeh, Sh. & Atasoy, Bilge & Ben-Akiva, Moshe E. & Bierlaire, M. & Maknoon, M.Y., 2022. "Choice-driven dial-a-ride problem for demand responsive mobility service," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 128-149.

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