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Random Utility Models with Cardinality Context Effects for Online Subscription Service Platforms

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  • Uzma Mushtaque

    (Rensselaer Polytechnic Institute)

  • Jennifer A. Pazour

    (Rensselaer Polytechnic Institute)

Abstract

A more general family of random utility models is developed to model a cognitive heuristic, known as consideration sets. These new models, denoted as Multinomial Logit Cardinality Effect models (MNL-CE), define perceived representative utility of items by assigning a penalty as a function of assortment cardinality to the representative utility of each item beyond a threshold value (except for the no-choice option). This definition of perceived representative utility of an item is context-dependent and thus a function of assortment attributes (cardinality), in addition to item and user attributes. The user’s net benefit is therefore a trade-off between the benefits and the costs of considering a certain number of items. A developed algorithm efficiently solves the subscription platform assortment optimization problem with equal profit when user selection is modeled via variants of the MNL-CE. The sensitivity of model parameters on the optimal assortment cardinality and no-choice probability is analyzed with the MovieLens dataset.

Suggested Citation

  • Uzma Mushtaque & Jennifer A. Pazour, 2020. "Random Utility Models with Cardinality Context Effects for Online Subscription Service Platforms," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(4), pages 276-290, August.
    • Handle: RePEc:pal:jorapm:v:19:y:2020:i:4:d:10.1057_s41272-019-00227-0
    DOI: 10.1057/s41272-019-00227-0
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