IDEAS home Printed from https://ideas.repec.org/a/spr/binfse/v6y2014i3p153-163.html
   My bibliography  Save this article

When Are Deliveries Profitable?

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s12599-014-0321-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s12599-014-0321-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Quante, R. & Meyr, H. & Fleischmann, M., 2007. "Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software," ERIM Report Series Research in Management ERS-2007-050-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.
    2. 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.
    3. Rainer Quante & Herbert Meyr & Moritz Fleischmann, 2009. "Revenue management and demand fulfillment: matching applications, models and software," Springer Books, in: Herbert Meyr & Hans-Otto Günther (ed.), Supply Chain Planning, pages 57-88, Springer.
    4. Potvin, Jean-Yves & Rousseau, Jean-Marc, 1993. "A parallel route building algorithm for the vehicle routing and scheduling problem with time windows," European Journal of Operational Research, Elsevier, vol. 66(3), pages 331-340, May.
    5. Bernhard Fleischmann & Martin Gietz & Stefan Gnutzmann, 2004. "Time-Varying Travel Times in Vehicle Routing," Transportation Science, INFORMS, vol. 38(2), pages 160-173, May.
    6. Stadtler, Hartmut, 2005. "Supply chain management and advanced planning--basics, overview and challenges," European Journal of Operational Research, Elsevier, vol. 163(3), pages 575-588, June.
    7. Donati, Alberto V. & Montemanni, Roberto & Casagrande, Norman & Rizzoli, Andrea E. & Gambardella, Luca M., 2008. "Time dependent vehicle routing problem with a multi ant colony system," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1174-1191, March.
    8. Ichoua, Soumia & Gendreau, Michel & Potvin, Jean-Yves, 2003. "Vehicle dispatching with time-dependent travel times," European Journal of Operational Research, Elsevier, vol. 144(2), pages 379-396, January.
    9. 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.
    10. W Maden & R Eglese & D Black, 2010. "Vehicle routing and scheduling with time-varying data: A case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 515-522, March.
    11. 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.
    12. Catherine Cleophas & Michael Frank & Natalia Kliewer, 2009. "Recent developments in demand forecasting for airline revenue management," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 3(3), pages 252-269.
    13. Baldacci, Roberto & Mingozzi, Aristide & Roberti, Roberto, 2012. "Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints," European Journal of Operational Research, Elsevier, vol. 218(1), pages 1-6.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    3. Said Dabia & Stefan Ropke & Tom van Woensel & Ton De Kok, 2013. "Branch and Price for the Time-Dependent Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 47(3), pages 380-396, August.
    4. Verbeeck, C. & Vansteenwegen, P. & Aghezzaf, E.-H., 2016. "Solving the stochastic time-dependent orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 255(3), pages 699-718.
    5. 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).
    6. Côté, Jean-François & Mansini, Renata & Raffaele, Alice, 2024. "Multi-period time window assignment for attended home delivery," European Journal of Operational Research, Elsevier, vol. 316(1), pages 295-309.
    7. Gmira, Maha & Gendreau, Michel & Lodi, Andrea & Potvin, Jean-Yves, 2021. "Tabu search for the time-dependent vehicle routing problem with time windows on a road network," European Journal of Operational Research, Elsevier, vol. 288(1), pages 129-140.
    8. Ehmke, Jan Fabian & Campbell, Ann Melissa & Urban, Timothy L., 2015. "Ensuring service levels in routing problems with time windows and stochastic travel times," European Journal of Operational Research, Elsevier, vol. 240(2), pages 539-550.
    9. Diego Cattaruzza & Nabil Absi & Dominique Feillet & Jesús González-Feliu, 2017. "Vehicle routing problems for city logistics," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 51-79, March.
    10. 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.
    11. Thomas R. Visser & Remy Spliet, 2020. "Efficient Move Evaluations for Time-Dependent Vehicle Routing Problems," Transportation Science, INFORMS, vol. 54(4), pages 1091-1112, July.
    12. Rifki, Omar & Chiabaut, Nicolas & Solnon, Christine, 2020. "On the impact of spatio-temporal granularity of traffic conditions on the quality of pickup and delivery optimal tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    13. Lu, Jiawei & Nie, Qinghui & Mahmoudi, Monirehalsadat & Ou, Jishun & Li, Chongnan & Zhou, Xuesong Simon, 2022. "Rich arc routing problem in city logistics: Models and solution algorithms using a fluid queue-based time-dependent travel time representation," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 143-182.
    14. 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.
    15. 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.
    16. Marlin W. Ulmer & Barrett W. Thomas, 2019. "Enough Waiting for the Cable Guy—Estimating Arrival Times for Service Vehicle Routing," Transportation Science, INFORMS, vol. 53(3), pages 897-916, May.
    17. Andres Figliozzi, Miguel, 2012. "The time dependent vehicle routing problem with time windows: Benchmark problems, an efficient solution algorithm, and solution characteristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 616-636.
    18. 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.
    19. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:binfse:v:6:y:2014:i:3:p:153-163. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.