Optimizing Expected Utility in a Multinomial Logit Model with Position Bias and Social Influence

Andres Abeliuk; Gerardo Berbeglia; Manuel Cebrian; Pascal Van Hentenryck

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arxiv 1411.0279 v2 pith:VLKS7XGZ submitted 2014-11-02 cs.DS

Optimizing Expected Utility in a Multinomial Logit Model with Position Bias and Social Influence

Andres Abeliuk , Gerardo Berbeglia , Manuel Cebrian , Pascal Van Hentenryck This is my paper

classification cs.DS

keywords influencesocialassortmentoptimalpositioningbiaslogitmodel

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Motivated by applications in retail, online advertising, and cultural markets, this paper studies how to find the optimal assortment and positioning of products subject to a capacity constraint. We prove that the optimal assortment and positioning can be found in polynomial time for a multinomial logit model capturing utilities, position bias, and social influence. Moreover, in a dynamic market, we show that the policy that applies the optimal assortment and positioning and leverages social influence outperforms in expectation any policy not using social influence.

Optimizing Expected Utility in a Multinomial Logit Model with Position Bias and Social Influence

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