Asymptotic optimality of myopic optimization in trial-offer markets with social influence

Andres Abeliuk, Gerardo Berbeglia, Felipe Maldonado, Pascal Van Hentenryck

    Research output: Contribution to journalConference articlepeer-review

    4 Citations (Scopus)

    Abstract

    We study dynamic trial-offer markets, in which participants first try a product and later decide whether to purchase it or not. In these markets, social influence and position biases have a greater effect on the decisions taken in the sampling stage than those in the buying stage. We consider a myopic policy that maximizes the market efficiency for each incoming participant, taking into account the inherent quality of products, position biases, and social influence. We prove that this myopic policy is optimal and predictable asymptotically.

    Original languageEnglish
    Pages (from-to)2458-2464
    Number of pages7
    JournalIJCAI International Joint Conference on Artificial Intelligence
    Volume2016-January
    Publication statusPublished - 2016
    Event25th International Joint Conference on Artificial Intelligence, IJCAI 2016 - New York, United States
    Duration: 9 Jul 201615 Jul 2016

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