Acceptance issues of personality-based recommender systems

Abstract

To understand users' acceptance of the emerging trend of personality-based recommenders (PBR), we evaluated an existing PBR using the technology acceptance model (TAM). We also compare it with a baseline rating-based recommender in a within-subject user study. Our results show that while the personality-based recommender is perceived to be only slightly more accurate than the rating-based one, it is much easier to use. The side-by-side comparison also reveals that users significantly favor the personality-based recommender and have a significantly higher intention to use such a system again. Therefore, we believe that if users accepted rating-based recommenders, they are most likely to accept personality-based recommenders and personality-based recommenders have a high likelihood to be widely adopted despite the fact that rating-based recommenders are now the industry norm. We further point out some preliminary guidelines on how to design personality-based recommender systems.