Journal article

Assortment optimization under a multinomial logit model with position bias and social influence

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

4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH | SPRINGER HEIDELBERG | Published : 2016

Abstract

Motivated by applications in retail, online advertising, and cultural markets, this paper studies the problem of finding an optimal assortment and positioning of products subject to a capacity constraint in a setting where consumers preferences can be modeled as a discrete choice under a multinomial logit model that captures the intrinsic product appeal, position biases, and social influence. For the static problem, we prove that the optimal assortment and positioning can be found in polynomial time. This is despite the fact that adding a product to the assortment may increase the probability of selecting the no-choice option, a phenomenon not observed in almost all models studied in the lit..

View full abstract

Grants

Funding Acknowledgements

We thank the reviewers for their constructive remarks and suggestions. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program.