How Explanations For Recommender Systems Impact Consumer Acceptance

A series of experiments explore how different explanations for recommender systems affect consumer acceptance of recommendations. While both collaborative explanations (e.g., “People who like this also like”) and content-based explanations (e.g., “More comedy shows”) suggest product-matching, only collaborative explanations signals taste-matching. Behavioral consequences are demonstrated.



Citation:

Phyliss J. Gai and Anne-Kathrin Klesse (2019) ,"How Explanations For Recommender Systems Impact Consumer Acceptance", in NA - Advances in Consumer Research Volume 47, eds. Rajesh Bagchi, Lauren Block, and Leonard Lee, Duluth, MN : Association for Consumer Research, Pages: 190-195.

Authors

Phyliss J. Gai, Erasmus University Rotterdam, The Netherlands
Anne-Kathrin Klesse, Erasmus University Rotterdam, The Netherlands



Volume

NA - Advances in Consumer Research Volume 47 | 2019



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