Abstract
Recommendation services capture and exploit personal information such as demographic attributes, preferences, and user behaviors on the internet. It is known that some users feel uneasiness regarding such information acquisition by systems and have concern over their online privacy. Investigating the structure of the uneasiness and evaluating the effect to user acceptance of the recommender systems is an important issue to develop user-accepting services. In this study, we developed an acceptance model of recommender systems based on a large-scale internet survey using 60 kinds of pseudo-services.
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Asoh, H., Ono, C., Habu, Y., Takasaki, H., Takenaka, T., Motomura, Y. (2012). An Acceptance Model of Recommender Systems Based on a Large-Scale Internet Survey. In: Ardissono, L., Kuflik, T. (eds) Advances in User Modeling. UMAP 2011. Lecture Notes in Computer Science, vol 7138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28509-7_39
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DOI: https://doi.org/10.1007/978-3-642-28509-7_39
Publisher Name: Springer, Berlin, Heidelberg
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