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Offsetting omnichannel grocery fulfillment cost through advance ordering of perishables

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  • Siawsolit, Chokdee
  • Gaukler, Gary M.

Abstract

With the rise of online grocery adoption, customers are now placing more delivery and pickup orders. This mode of interaction allows the grocer to collect advance demand information, which has been shown to reduce inventory costs in non-perishables. For perishable items where spoilage is a major cost driver, the effects of advance ordering on a grocer's daily operation is not yet clear. To investigate this, we develop an MDP-based model that reflects a modern grocer's inventory decision system. Key model characteristics are stochastic demand and random product shelf lives. The model solves for the optimal replenishment policy, and facilitates quantifying how next-day or two-day orders influence profitability. A numerical study is presented for various short-life products, and the results indicate that two-day orders can increase profit, reduce inventory and spoilage, while maintaining the overall availability level. These benefits increase as the replenishment product's shelf life decreases. We show that the average cart value, proportion of short life items, handling time, and order pick rate are strong determinants of the extent that two-day orders can offset omnichannel fulfillment cost. In some cases, there exists an attainable breakeven pick rate, such that the grocer's expected profit is higher with curbside advance orders than with traditional in-store purchases.

Suggested Citation

  • Siawsolit, Chokdee & Gaukler, Gary M., 2021. "Offsetting omnichannel grocery fulfillment cost through advance ordering of perishables," International Journal of Production Economics, Elsevier, vol. 239(C).
  • Handle: RePEc:eee:proeco:v:239:y:2021:i:c:s0925527321001687
    DOI: 10.1016/j.ijpe.2021.108192
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    References listed on IDEAS

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    2. Yang, Lu & Li, Xiangyong & Zhong, Ning, 2022. "Omnichannel retail operations with mixed fulfillment strategies," International Journal of Production Economics, Elsevier, vol. 254(C).
    3. Qiu, Ruozhen & Ma, Lin & Sun, Minghe, 2023. "A robust omnichannel pricing and ordering optimization approach with return policies based on data-driven support vector clustering," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1337-1354.
    4. Li, Zonghuo & Guan, Xu & Mei, Wanxia, 2023. "Coupon promotion and its cross-channel effect in omnichannel retailing industry: A time-sensitive strategy," International Journal of Production Economics, Elsevier, vol. 258(C).
    5. Dong, Shuang & Qin, Zhongfeng & Yan, Yingchen, 2022. "Effects of online-to-offline spillovers on pricing and quality strategies of competing firms," International Journal of Production Economics, Elsevier, vol. 244(C).
    6. Vyt, Dany & Jara, Magali & Mevel, Olivier & Morvan, Thierry & Morvan, Nélida, 2022. "The impact of convenience in a click and collect retail setting: A consumer-based approach," International Journal of Production Economics, Elsevier, vol. 248(C).
    7. Calzavara, Martina & Finco, Serena & Persona, Alessandro & Zennaro, Ilenia, 2023. "A cost-based tool for the comparison of different e-grocery supply chain strategies," International Journal of Production Economics, Elsevier, vol. 262(C).
    8. Gaukler, Gary M. & Zuidwijk, Rob A. & Ketzenberg, Michael E., 2023. "The value of time and temperature history information for the distribution of perishables," European Journal of Operational Research, Elsevier, vol. 310(2), pages 627-639.

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