Price and Profit Awareness in Recommender Systems

Academic research in the €eld of recommender systems mainly focuses on the problem of maximizing the users’ utility by trying to identify the most relevant items for each user. However, such items are not necessarily the ones that maximize the utility of the service provider (e.g., an online retailer) in terms of the business value, such as pro€t. One approach to increasing the providers’ utility is to incorporate purchase-oriented information, e.g., the price, sales probabilities, and the resulting pro€t, into the recommendation algorithms. In this paper we speci€cally focus on priceand pro€taware recommender systems. We provide a brief overview of the relevant literature and use numerical simulations to illustrate the potential business bene€t of such approaches.