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Discrete Choice via Sequential Search

Author

Listed:
  • Natalia Kosilova

    (Oracle Labs, Burlington, Massachusetts 01803)

  • Aydın Alptekinoğlu

    (The Pennsylvania State University, University Park, Pennsylvania 16802)

Abstract

Essentially every choice involves an information collection or search phase prior to a decision-making phase that culminates in a choice . To study the information collection phase within an important class of search problems and understand how it influences the final choice, we embed an analytically tractable discrete choice model in a classical model of sequential search with perfect recall. Although significant progress has been made in the theory literature in analyzing consumers’ discrete choice behavior using random utility models, discrete choice through a sequential search process has not received enough attention at least in part because of analytical intractability issues. We build on the seminal Pandora’s Problem as a model of sequential search with perfect recall and on Exponomial Choice as a model of discrete choice (with each choice specified by a deterministic or observable utility component minus a random or unobservable utility component following an exponential distribution). We derive the search path and final choice probabilities in closed form, develop all the analytical tools to optimize prices for a given assortment of products, and show that the optimal assortment must contain some number of highest-value products at optimal prices. These results enable joint optimization of assortment and prices efficiently. The structure of the solution features a distinct group of products that are priced just so they remain on the search path with higher probability. Through simulation studies, allowing us to control the ground truth, we also show that our model is competitive against the state of the art in empirical modeling of sequential search and that ignoring sequential search distorts both optimal variety and pricing decisions in an upward direction.

Suggested Citation

  • Natalia Kosilova & Aydın Alptekinoğlu, 2026. "Discrete Choice via Sequential Search," Management Science, INFORMS, vol. 72(2), pages 1236-1252, February.
    • Handle: RePEc:inm:ormnsc:v:72:y:2026:i:2:p:1236-1252
    DOI: 10.1287/mnsc.2023.01552
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    References listed on IDEAS

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    1. Weitzman, Martin L, 1979. "Optimal Search for the Best Alternative," Econometrica, Econometric Society, vol. 47(3), pages 641-654, May.
    2. Yicheng Bai & Jacob Feldman & Huseyin Topaloglu & Laura Wagner, 2024. "Assortment Optimization Under the Multinomial Logit Model with Utility-Based Rank Cutoffs," Operations Research, INFORMS, vol. 72(4), pages 1453-1474, July.
    3. Gérard P. Cachon & Christian Terwiesch & Yi Xu, 2008. "On the Effects of Consumer Search and Firm Entry in a Multiproduct Competitive Market," Marketing Science, INFORMS, vol. 27(3), pages 461-473, 05-06.
    4. Garrett van Ryzin & Siddharth Mahajan, 1999. "On the Relationship Between Inventory Costs and Variety Benefits in Retail Assortments," Management Science, INFORMS, vol. 45(11), pages 1496-1509, November.
    5. Gerardo Berbeglia & Agustín Garassino & Gustavo Vulcano, 2022. "A Comparative Empirical Study of Discrete Choice Models in Retail Operations," Management Science, INFORMS, vol. 68(6), pages 4005-4023, June.
    6. T. Tony Ke & Zuo-Jun Max Shen & J. Miguel Villas-Boas, 2016. "Search for Information on Multiple Products," Management Science, INFORMS, vol. 62(12), pages 3576-3603, December.
    7. Ali Aouad & Danny Segev, 2021. "Display Optimization for Vertically Differentiated Locations Under Multinomial Logit Preferences," Management Science, INFORMS, vol. 67(6), pages 3519-3550, June.
    8. Michele Samorani & Aydın Alptekinoğlu & Paul R. Messinger, 2019. "Product Return Episodes in Retailing," Service Science, INFORMS, vol. 11(4), pages 263-278, December.
    9. Anthony Dukes & Lin Liu, 2016. "Online Shopping Intermediaries: The Strategic Design of Search Environments," Management Science, INFORMS, vol. 62(4), pages 1064-1077, April.
    10. Aydın Alptekinoğlu & John H. Semple, 2021. "Heteroscedastic Exponomial Choice," Operations Research, INFORMS, vol. 69(3), pages 841-858, May.
    11. Raluca Ursu & Stephan Seiler & Elisabeth Honka, 2025. "The sequential search model: A framework for empirical research," Quantitative Marketing and Economics (QME), Springer, vol. 23(1), pages 165-213, March.
    12. Rafael P. Greminger, 2022. "Optimal Search and Discovery," Management Science, INFORMS, vol. 68(5), pages 3904-3924, May.
    13. Ali Aouad & Jacob Feldman & Danny Segev, 2023. "The Exponomial Choice Model for Assortment Optimization: An Alternative to the MNL Model?," Management Science, INFORMS, vol. 69(5), pages 2814-2832, May.
    14. Mahsa Derakhshan & Negin Golrezaei & Vahideh Manshadi & Vahab Mirrokni, 2022. "Product Ranking on Online Platforms," Management Science, INFORMS, vol. 68(6), pages 4024-4041, June.
    15. Jun B. Kim & Paulo Albuquerque & Bart J. Bronnenberg, 2017. "The Probit Choice Model Under Sequential Search with an Application to Online Retailing," Management Science, INFORMS, vol. 63(11), pages 3911-3929, November.
    16. Fernando Branco & Monic Sun & J. Miguel Villas-Boas, 2016. "Too Much Information? Information Provision and Search Costs," Marketing Science, INFORMS, vol. 35(4), pages 605-618, July.
    17. Ruxian Wang & Ozge Sahin, 2018. "The Impact of Consumer Search Cost on Assortment Planning and Pricing," Management Science, INFORMS, vol. 64(8), pages 3649-3666, August.
    18. Aydın Alptekinoğlu & John H. Semple, 2016. "The Exponomial Choice Model: A New Alternative for Assortment and Price Optimization," Operations Research, INFORMS, vol. 64(1), pages 79-93, February.
    19. Rafael P. Greminger, 2019. "Optimal Search and Discovery," Papers 1911.07773, arXiv.org, revised Feb 2022.
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