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Mitigating Spillover in Online Retailing via Replenishment

Author(s)
Acimovic, Jason; Graves, Stephen C
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Abstract
Online purchases constitute about one-tenth of U.S. retail sales. The supply chains that support online retailing are fundamentally different from those that support traditional brick-and-mortar stores. Traditional solutions are not always appropriate to solve online retailing’s operations problems; thus, there is an opportunity to understand and improve these novel supply chains. One key characteristic of the inventory systems for online retailing is demand spillover, whereby a stockout at a fulfillment center (FC) results in demand spilling over to another FC. For this context we examine how to allocate inventory to the FCs under a periodic-review joint-replenishment policy, with an objective to minimize outbound shipping costs for a fixed amount of inventory. We first show how traditional decentralized allocation policies may perform suboptimally and induce dynamics (whiplash) that result in costly spillover. We find that this phenomenon increases with the prevalence of local stockouts and with the level of inventory imbalance. We then describe that inventory imbalance occurs in online retailing because of operational realities and provide evidence based on real data. Finally, we propose a heuristic to allocate inventory accounting for possible spillover during the lead time. We test the heuristic by a simulation and show that it performs better than the status quo policy, is robust to operational realities, and captures over 90% of the possible improvement as compared to a pseudo-optimal policy.
Date issued
2017-06
URI
http://hdl.handle.net/1721.1/111138
Department
Sloan School of Management
Journal
Manufacturing & Service Operations Management
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Citation
Acimovic, Jason, and Graves, Stephen C. “Mitigating Spillover in Online Retailing via Replenishment.” Manufacturing & Service Operations Management 19, 3 (July 2017): 419–436 © 2017 Institute for Operations Research and the Management Sciences (INFORMS)
Version: Author's final manuscript
ISSN
1523-4614
1526-5498

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