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Optimal inventory management for a retail chain with diverse store demands

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  • Agrawal, Narendra
  • Smith, Stephen A.

Abstract

Item demands at individual retail stores in a chain often differ significantly, due to local economic conditions, cultural and demographic differences and variations in store format. Accounting for these variations appropriately in inventory management can significantly improve retailers’ profits. For example, it is shown that having greater differences across the mean store demands leads to a higher expected profit, for a given inventory and total mean demand. If more than one inventory shipment per season is possible, the analysis becomes dynamic by including updated demand forecasts for each store and re-optimizing store inventory policies in midseason. In this paper, we formulate a dynamic stochastic optimization model that determines the total order size and the optimal inventory allocation across nonidentical stores in each period. A generalized Bayesian inference model is used for demands that are partially correlated across the stores and time periods. We also derive a normal approximation for the excess inventory from the previous period, which allows the dynamic programming formulation to be easily solved. We analyze the tradeoffs between obtaining information and profitability, e.g., stocking more stores in period 1 provides more demand information for period 2, but does not necessarily lead to higher total profit. Numerical analyses compare the expected profits of alternative supply chain strategies, as well as the sensitivity to different distributions of demand across the stores. This leads to novel strategic insights that arise from adopting inventory policies that vary by store type.

Suggested Citation

  • Agrawal, Narendra & Smith, Stephen A., 2013. "Optimal inventory management for a retail chain with diverse store demands," European Journal of Operational Research, Elsevier, vol. 225(3), pages 393-403.
  • Handle: RePEc:eee:ejores:v:225:y:2013:i:3:p:393-403
    DOI: 10.1016/j.ejor.2012.10.006
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    References listed on IDEAS

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    6. A. Gürhan Kök & Kevin H. Shang, 2007. "Inspection and Replenishment Policies for Systems with Inventory Record Inaccuracy," Manufacturing & Service Operations Management, INFORMS, vol. 9(2), pages 185-205, February.
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    Cited by:

    1. Talebian, Masoud & Boland, Natashia & Savelsbergh, Martin, 2014. "Pricing to accelerate demand learning in dynamic assortment planning for perishable products," European Journal of Operational Research, Elsevier, vol. 237(2), pages 555-565.
    2. Ma, Shaohui & Fildes, Robert, 2017. "A retail store SKU promotions optimization model for category multi-period profit maximization," European Journal of Operational Research, Elsevier, vol. 260(2), pages 680-692.

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    Keywords

    Inventory; Supply chain management; Retailing;

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