Communications of the ACM
Recommender systems for evaluating computer messages
Communications of the ACM
Personalized pricing recommender system: multi-stage epsilon-greedy approach
Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Maximizing revenue from strategic recommendations under decaying trust
Proceedings of the 21st ACM international conference on Information and knowledge management
Rating Protocols in Online Communities
ACM Transactions on Economics and Computation
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We study optimal pricing in the presence of recommender systems. A recommender system affects the market in two ways: (i) it creates value by reducing product uncertainty for the customers and hence (ii) its recommendations can be offered as add-ons which generate informational externalities. The quality of the recommendation add-on is endogenously determined by sales. We investigate the impact of these factors on the optimal pricing by a seller with a recommender system against a competitive fringe without such a system. If the recommender system is sufficiently effective in reducing uncertainty, then the seller prices otherwise symmetric products differently to have some products experienced more aggressively. Moreover, the seller segments the market so that customers with more in.exible tastes pay higher prices to get better recommendation.