Abstract
Retail inventory management is an important and challenging research area. Based on performance measures such as turns per year, the efficiency with which retailers manage their inventory lags well behind other sectors, such as manufacturing. However, retail inventory management must deal with unique problems and complexities. By the nature of their business, major retailers hold stock at many geographically dispersed locations at anywhere from several hundred to thousands of stores for the typical retailing chain. Retailers are also faced with the problem of managing an extremely large number of line items; several hundred thousand SKUs (stock keeping units) is not uncommon. Until recently, demand rates at the store level have been reported only in aggregate form, and often with considerable delay and inaccuracy. This made it nearly impossible for retailers to accurately determine the inventory position of an SKU at a store, let alone estimate the probability distribution of weekly demand or the service level experienced by customers on individual items.
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Nahmias, S., Smith, S.A. (1993). Mathematical Models of Retailer Inventory Systems: A Review. In: Sarin, R.K. (eds) Perspectives in Operations Management. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3166-1_14
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DOI: https://doi.org/10.1007/978-1-4615-3166-1_14
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