The Effects of Personal Sentiments and Contexts on the Acceptance of Music Recommender Systems

A recommender system is a personalized decision support tool to suggest suitable products in proper manners for the benefits of both suppliers and consumers with the assumption of full understanding of consumers\´ needs and preferences. However, a substantial number of studies have focused on making recommender systems more accurate and efficient from the perspective of suppliers. Whereas, there have been a few studies on consumers\´ needs and preferences under their own contexts to accept recommender systems. To this end, this study attempted to find out the effects of personal sentiments and contexts on the willingness to accept music recommender systems based on the "Technology Acceptance Model". For the study, we developed a conceptual model to test the effects.