Optimal in-store fulfillment policies for online orders in an omni-channel retail environment

Journal Article (2021)
Author(s)

Rita Maria Difrancesco (EADA Business School Barcelona)

Isabelle M. Van Schilt (TU Delft - Policy Analysis)

Matthias Winkenbach (Massachusetts Institute of Technology)

Research Group
Policy Analysis
Copyright
© 2021 Rita Maria Difrancesco, Isabelle M. van Schilt, Matthias Winkenbach
DOI related publication
https://doi.org/10.1016/j.ejor.2021.01.007
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Rita Maria Difrancesco, Isabelle M. van Schilt, Matthias Winkenbach
Research Group
Policy Analysis
Issue number
3
Volume number
293
Pages (from-to)
1058-1076
Reuse Rights

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Abstract

The explosive growth of e-commerce creates a need for increasingly responsive omni-channel fulfillment capabilities, which raises new challenges in inventory management and order fulfillment for retailers. In response to these challenges, many retailers attempt to establish so-called ship-from-store concepts, which leverage their physical store networks to fulfill online orders. In this study, we analyze the optimal setup of these in-store fulfillment processes of online orders for an omni-channel retailer. We use a simulation-based approach combined with exploratory modeling to prescribe optimal fulfillment policies under a variety of sources of uncertainty. We apply our proposed model to a case study informed by real data from a leading sports fashion retailer in New York City in order to illustrate the practical applicability and value of our approach. Our results determine (i) the optimal amount of time to allow for batching of online orders prior to starting the in-store picking process; (ii) the optimal amount of time to allow for readily picked orders prior to starting the delivery process; (iii) the optimal number of pickers; and (iv) the optimal number of packers, and the related performance measures. Finally, we build on our analysis results to derive a set of managerial implications applicable to many omni-channel problems.

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- Embargo expired in 24-01-2023