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Choice-Based Demand Management and Vehicle Routing in E-Fulfillment

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Listed:
  • Xinan Yang

    (Department of Mathematical Sciences, University of Essex, Colchester CO4 3SQ, United Kingdom)

  • Arne K. Strauss

    (Warwick Business School, University of Warwick, Coventry CV4 7AL, United Kingdom)

  • Christine S. M. Currie

    (Mathematical Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom)

  • Richard Eglese

    (Lancaster University Management School, Lancaster LA1 4YX, United Kingdom)

Abstract

Attended home delivery services face the challenge of providing narrow delivery time slots to ensure customer satisfaction, while keeping the significant delivery costs under control. To that end, a firm can try to influence customers when they are booking their delivery time slot so as to steer them toward choosing slots that are expected to result in cost-effective schedules. We estimate a multinomial logit customer choice model from historic booking data and demonstrate that this can be calibrated well on a genuine e-grocer data set. We propose dynamic pricing policies based on this choice model to determine which and how much incentive (discount or charge) to offer for each time slot at the time a customer intends to make a booking. A crucial role in these dynamic pricing problems is played by the delivery cost, which is also estimated dynamically. We show in a simulation study based on real data that anticipating the likely future delivery cost of an additional order in a given location can lead to significantly increased profit as compared with current industry practice.

Suggested Citation

  • Xinan Yang & Arne K. Strauss & Christine S. M. Currie & Richard Eglese, 2016. "Choice-Based Demand Management and Vehicle Routing in E-Fulfillment," Transportation Science, INFORMS, vol. 50(2), pages 473-488, May.
    • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:2:p:473-488
    DOI: 10.1287/trsc.2014.0549
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    References listed on IDEAS

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