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Estimating negative binomial demand for retail inventory management with unobservable lost sales

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  • Narendra Agrawal
  • Stephen A. Smith

Abstract

The importance of effective inventory management has greatly increased for many major retailers because of more intense competition. Retail inventory management methods often use assumptions and demand distributions that were developed for application areas other than retailing. For example, it is often assumed that unmet demand is backordered and that demand is Poisson or normally distributed. In retailing, unmet demand is often lost and unobserved. Using sales data from a major retailing chain, our analysis found that the negative binomial fit significantly better than the Poisson or the normal distribution. A parameter estimation methodology that compensates for unobserved lost sales is developed for the negative binomial distribution. The method's effectiveness is demonstrated by comparing parameter estimates from the complete data set to estimates obtained by artificially truncating the data to simulate lost sales. © 1996 John Wiley & Sons, Inc.

Suggested Citation

  • Narendra Agrawal & Stephen A. Smith, 1996. "Estimating negative binomial demand for retail inventory management with unobservable lost sales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(6), pages 839-861, September.
    • Handle: RePEc:wly:navres:v:43:y:1996:i:6:p:839-861
    DOI: 10.1002/(SICI)1520-6750(199609)43:63.0.CO;2-5
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    References listed on IDEAS

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    1. William E. Wecker, 1978. "Predicting Demand from Sales Data in the Presence of Stockouts," Management Science, INFORMS, vol. 24(10), pages 1043-1054, June.
    2. Steven Nahmias, 1994. "Demand estimation in lost sales inventory systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(6), pages 739-757, October.
    3. Steven Nahmias & Stephen A. Smith, 1994. "Optimizing Inventory Levels in a Two-Echelon Retailer System with Partial Lost Sales," Management Science, INFORMS, vol. 40(5), pages 582-596, May.
    4. Hill, Roger M., 1992. "Parameter estimation and performance measurement in lost sales inventory systems," International Journal of Production Economics, Elsevier, vol. 28(2), pages 211-215, November.
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