Choice-based demand management and vehicle routing in e-fulfillment
Choice-based demand management and vehicle routing in e-fulfillment
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.
473-488
Yang, Xinan
fda05284-c4ac-45e3-8d5c-de5dd45ace7a
Strauss, Arne
35a58f12-928c-430a-9b1f-c3f03cff9a9e
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Eglese, Richard
72626388-5dd1-4d37-a576-408e4f26d449
Yang, Xinan
fda05284-c4ac-45e3-8d5c-de5dd45ace7a
Strauss, Arne
35a58f12-928c-430a-9b1f-c3f03cff9a9e
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Eglese, Richard
72626388-5dd1-4d37-a576-408e4f26d449
Yang, Xinan, Strauss, Arne, Currie, Christine S.M. and Eglese, Richard
(2014)
Choice-based demand management and vehicle routing in e-fulfillment.
Transportation Science, 50 (2), .
(doi:10.1287/trsc.2014.0549).
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.
Text
Yang et al Trans Sci.pdf
- Author's Original
Text
jointdemandmanagementfinalplainr1.pdf
- Accepted Manuscript
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e-pub ahead of print date: 7 August 2014
Organisations:
Operational Research
Identifiers
Local EPrints ID: 372078
URI: http://eprints.soton.ac.uk/id/eprint/372078
ISSN: 0041-1655
PURE UUID: 8b6f9778-8b34-41b3-8858-babba7085947
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Date deposited: 27 Nov 2014 11:14
Last modified: 15 Mar 2024 03:15
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Author:
Xinan Yang
Author:
Arne Strauss
Author:
Richard Eglese
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