User Acceptance of Recommender Systems: Influence of the Preference Elicitation Algorithm

We conducted a user study evaluating two preference elicitation approaches for collaborative filtering recommender systems: a basic KNN algorithm and a context aware algorithm. Using the technology acceptance model (TAM) as theoretical model, we considered different factors affecting the perceived usefulness, perceived ease of use and attitude towards using the recommender system. We found that the underlying algorithm can affect in different ways the user perception of the system as a whole. Although the system interface was the same for all users, users found the context aware system easier to use, with more attractive recommendations that were better adapted to their mood and tastes. Users using the context aware system also showed a better acceptance of the fact that the system was able to learn about their preferences and expressed a stronger intention to use the system again.