Balancing consumer and business value of recommender systems: A simulation-based analysis

In our latest paper, we are concerned with a challenge that recommendation providers (such as Netflix, Amazon, and Airbnb, among others) face. In particular, we focus on the challenge of designing balanced recommendation strategies that consider both the recommendation provider’s and the customers’ interests. We propose a recommendation framework that allows for the exploration of the longitudinal dynamics of selected recommendation strategies. Amongst others, we show that a hybrid recommendation strategy can significantly increase profit in the long run. The findings are reinforced if customers share their experiences with the recommendation provider on social media. The simulation framework is publicly available. The paper is available here: