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  • March 2021
  • Article
  • Management Science

Assortment Rotation and the Value of Concealment

By: Kris J. Ferreira and Joel Goh
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Abstract

Assortment rotation—the retailing practice of changing the assortment of products offered to customers—has recently been used as a competitive advantage for both brick-and-mortar and online retailers. We focus on product categories where consumers may purchase multiple products during a season and investigate a new reason why frequent assortment rotations can be valuable to a retailer. Namely, by distributing its seasonal catalog of products over multiple assortments rotated throughout the season—as opposed to selling all products in a single, fixed assortment—the retailer effectively conceals a portion of its full product catalog from consumers, injecting uncertainty into the consumer's relative product valuations. Rationally acting consumers may respond to this structural difference by purchasing more products, thereby generating additional sales for the retailer. We refer to this phenomenon as the value of concealment and show that the retailer enjoys a positive and significant value of concealment under quite general conditions. However, we show that when consumers are forward looking, the value of concealment is context dependent; we present insights and discuss intuition regarding which product categories likely lead to a positive vs. negative value of concealment.

Keywords

Assortment Optimization; Retailing; Imperfect Information; Sales; Strategy; Consumer Behavior

Citation

Ferreira, Kris J., and Joel Goh. "Assortment Rotation and the Value of Concealment." Management Science 67, no. 3 (March 2021): 1489–1507.
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About The Author

Kris Johnson Ferreira

Technology and Operations Management
→More Publications

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    Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift

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    ReUp Education: Can AI Help Learners Return to College?

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    Demand Learning and Pricing for Varying Assortments

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More from the Authors
  • Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift By: Matthew DosSantos DiSorbo and Kris Ferreira
  • ReUp Education: Can AI Help Learners Return to College? By: Kris Ferreira, Christopher Thomas Ryan and Sarah Mehta
  • Demand Learning and Pricing for Varying Assortments By: Kris Ferreira and Emily Mower
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