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

Uzma Mushtaque () and Jennifer A. Pazour ()
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Uzma Mushtaque: Rensselaer Polytechnic Institute
Jennifer A. Pazour: Rensselaer Polytechnic Institute

Journal of Revenue and Pricing Management, 2020, vol. 19, issue 4, No 8, 276-290

Abstract: 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.

Keywords: Recommender systems; Consideration sets; Random utility models; Assortment optimization; Subscription platforms (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1057/s41272-019-00227-0

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