Optimizing Retail Assortments for Diverse Customer Preferences

  • Stephen A. Smith
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 122)


Assortment selection is one of the most important and difficult decisions that retailers face. Assortment are typically chosen subjectively, often before any sales have been observed for some candidate products. Compared to price or advertising decisions, assortment decisions are more difficult to adjust later on. For multi-featured items such as consumer electronics and durable goods, the large number of product options, together with limited display space and financial constraints all contribute to the complexity of this decision. Consumer preferences for the various product attributes may also be heterogeneous, which requires assessing tradeoffs between the products that appeal to diverse customer segments. Because of these complexities, intuitively chosen retail assortments seem likely to be suboptimal.

This paper develops an operational methodology for selecting optimal retail assortments based on an underlying multinomial logit (MNL) choice model for each customer’s...


Conjoint Analysis Expected Profit Customer Preference Product Choice Base Stock Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The author is grateful to Dale Achabal, Kirthi Kalyanam, Shelby McIntyre and Chris Miller for many valuable discussions and to Active Decisions, Inc. for providing the data base that was used for testing the optimization model. This research was partially supported by the Retail Workbench Research and Education Center at Santa Clara University.


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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Stephen A. Smith
    • 1
  1. 1.Department of Operations and MIS, Leavey School of BusinessSanta Clara UniversitySanta ClaraUSA

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