Data‐driven research in retail operations—A review

Meng Qi, Ho‐Yin Mak and Zuo‐Jun Max Shen

Naval Research Logistics (NRL), 2020, vol. 67, issue 8, 595-616

Abstract: We review the operations research/management science literature on data‐driven methods in retail operations. This line of work has grown rapidly in recent years, thanks to the availability of high‐quality data, improvements in computing hardware, and parallel developments in machine learning methodologies. We survey state‐of‐the‐art studies in three core aspects of retail operations—assortment optimization, order fulfillment, and inventory management. We then conclude the paper by pointing out some interesting future research possibilities for our community.

Date: 2020
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Citations: View citations in EconPapers (4)

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https://doi.org/10.1002/nav.21949

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Persistent link: https://EconPapers.repec.org/RePEc:wly:navres:v:67:y:2020:i:8:p:595-616

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