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When Are Deliveries Profitable?

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  • Catherine Cleophas
  • Jan Ehmke

Abstract

The paper aims to optimize the final part of a firm’s value chain with regard to attended last-mile deliveries. It is assumed that to be profitable, e-commerce businesses need to maximize the overall value of fulfilled orders (rather than their number), while also limiting costs of delivery. To do so, it is essential to decide which delivery requests to accept and which time windows to offer to which consumers. This is especially relevant for attended deliveries, as delivery fees usually cannot fully compensate costs of delivery given tight delivery time windows. The literature review shows that existing order acceptance techniques often ignore either the order value or the expected costs of delivery. The paper presents an iterative solution approach: after calculating an approximate transport capacity based on forecasted expected delivery requests and a cost-minimizing routing, actual delivery requests are accepted or rejected aiming to maximize the overall value of orders given the computed transport capacity. With the final set of accepted requests, the routing solution is updated to minimize costs of delivery. The presented solution approach combines well-known methods from revenue management and time-dependent vehicle routing. In a computational study for a German metropolitan area, the potential and the limits of value-based demand fulfillment as well as its sensitivity regarding forecast accuracy and demand composition are investigated. Copyright Springer Fachmedien Wiesbaden 2014

Suggested Citation

  • 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.
    • Handle: RePEc:spr:binfse:v:6:y:2014:i:3:p:153-163
    DOI: 10.1007/s12599-014-0321-9
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Nielsen, Clara Chini & Pisinger, David, 2023. "Tactical planning for dynamic technician routing and scheduling problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    3. 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.
    4. Kunovjanek, Maximilian & Wankmüller, Christian, 2021. "Containing the COVID-19 pandemic with drones - Feasibility of a drone enabled back-up transport system," Transport Policy, Elsevier, vol. 106(C), pages 141-152.
    5. Köhler, Charlotte & Ehmke, Jan Fabian & Campbell, Ann Melissa, 2020. "Flexible time window management for attended home deliveries," Omega, Elsevier, vol. 91(C).
    6. Marlin W. Ulmer & Alan Erera & Martin Savelsbergh, 2022. "Dynamic service area sizing in urban delivery," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(3), pages 763-793, September.
    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. Avraham, Edison & Raviv, Tal, 2021. "The steady-state mobile personnel booking problem," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 266-288.
    9. Techane Bosona, 2020. "Urban Freight Last Mile Logistics—Challenges and Opportunities to Improve Sustainability: A Literature Review," Sustainability, MDPI, vol. 12(21), pages 1-20, October.
    10. Visser, T.R. & Savelsbergh, M.W.P., 2019. "Strategic Time Slot Management: A Priori Routing for Online Grocery Retailing," Econometric Institute Research Papers EI2019-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. John Olsson & Daniel Hellström & Henrik Pålsson, 2019. "Framework of Last Mile Logistics Research: A Systematic Review of the Literature," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    12. 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.
    13. Robert Klein & Michael Neugebauer & Dimitri Ratkovitch & Claudius Steinhardt, 2019. "Differentiated Time Slot Pricing Under Routing Considerations in Attended Home Delivery," Service Science, INFORMS, vol. 53(1), pages 236-255, February.
    14. Bruck, Bruno P. & Cordeau, Jean-François & Iori, Manuel, 2018. "A practical time slot management and routing problem for attended home services," Omega, Elsevier, vol. 81(C), pages 208-219.
    15. 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).
    16. Visser, T.R. & Agatz, N.A.H. & Spliet, R., 2019. "Simultaneous customer interaction in online booking systems for attended home delivery," ERIM Report Series Research in Management ERS-2019-011-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.
    17. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    18. 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.
    19. Lang, Magdalena A.K. & Cleophas, Catherine & Ehmke, Jan Fabian, 2021. "Multi-criteria decision making in dynamic slotting for attended home deliveries," Omega, Elsevier, vol. 102(C).
    20. Robert Klein & Jochen Mackert & Michael Neugebauer & Claudius Steinhardt, 2018. "A model-based approximation of opportunity cost for dynamic pricing in attended home delivery," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 969-996, October.
    21. Yang, Xinan & Strauss, Arne K., 2017. "An approximate dynamic programming approach to attended home delivery management," European Journal of Operational Research, Elsevier, vol. 263(3), pages 935-945.

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