Will we let computers determine what music we listen? Exploring user acceptance of music recommenders

Music recommendation systems are becoming increasingly popular, but little is known as to how users come to accept and use such systems. In this research, a framework to explain user acceptance of music recommender systems is proposed, by means of a theoretical and empirical study. The results show that the accuracy of a recommender system alone cannot explain acceptance. In particular, it was found that we should also acknowledge the importance of Compatibility, Trust, Perceived Usefulness and Perceived Ease of Use in order to innovate music recommendation systems.