A systematic review of value-aware recommender systems

Research on recommender systems (RSs) has traditionally focused on the design of systems capable of suggesting items of interest for users. However, often the most important expectation for RSs used in commercial applications is to improve the business performance of the organization. For this reason, alongside the growth of e-business, we have witnessed growing interest in value-aware RSs that, unlike traditional RSs, are designed to optimize the economic value of recommendations by considering the objectives of multiple stakeholders. In this paper, we provide a systematic literature review, following the PRISMA guidelines, specialized in value-aware RSs. We explore key commercial applications, main algorithms, value categories typically optimized, and the most commonly used datasets. Furthermore, we note limitations of the state-of-the-art approaches and identify future research directions.