An Empirical Study on Consumer Behavior in the Interaction with Knowledge-based Recommender Applications

Authors:
A. Felfernig;B. Gula
Affiliations:
University Klagenfurt, Austria;University Klagenfurt, Austria
Venue:
CEC-EEE '06 Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services
Year:
2006

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Abstract

Knowledge-based recommender technologies provide a couple of mechanisms for improving the accessibility of product assortments for customers, e.g., in situations where no solution can be found for a given set of customer requirements, the recommender application calculates a set of repair actions which can guarantee the identification of a solution. Further examples for such mechanisms are explanations or product comparisons. All these mechanisms have a certain effect on the behavior of customers interacting with a recommender application. In this paper we present results from a user study, which focused on the analysis of effects of different recommendation mechanisms on the overall customer acceptance of recommender technologies.