Journal article
Flexible time window management for attended home deliveries
Omega (Oxford), Vol.91, p.102023
03/2020
DOI: 10.1016/j.omega.2019.01.001
Abstract
•We consider routing flexibility when offering short or long time windows.•We present four flexibility approaches to decide when to offer short time windows.•The flexibility approaches are based on route utilization and/or location of a request.•We evaluate the approaches for different demand patterns and customer behaviors.
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.
Details
- Title: Subtitle
- Flexible time window management for attended home deliveries
- Creators
- Charlotte Köhler - Management Science Group, Otto von Guericke University, Magdeburg, GermanyJan Fabian Ehmke - Management Science Group, Otto von Guericke University, Magdeburg, GermanyAnn Melissa Campbell - Department of Management Sciences, University of Iowa, Iowa City, United States
- Resource Type
- Journal article
- Publication Details
- Omega (Oxford), Vol.91, p.102023
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.omega.2019.01.001
- ISSN
- 0305-0483
- eISSN
- 1873-5274
- Grant note
- EH449/1-1 / German Research Foundation (https://doi.org/10.13039/501100001659)
- Language
- English
- Date published
- 03/2020
- Academic Unit
- Business Analytics
- Record Identifier
- 9984083862102771
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