E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact1
Authors: Xiao, Bo; Benbasat, Izak
Journal: MIS Quarterly (2007)
DOI: 10.2307/25148784
Recommendation agents (RAs) are software agents that elicit the interests or preferences of individual consumers for products, either explicitly or implicitly, and make recommendations accordingly. RAs have the potential to support and improve the quality of the decisions consumers make when searching for and selecting products online. They can reduce the information overload facing consumers, as well as the complexity of online searches. Prior research on RAs has focused mostly on developing and evaluating different underlying algorithms that generate recommendations. This paper instead identifies other important aspects of RAs, namely RA use, RA characteristics, provider credibility, and factors related to product, user, and user–RA interaction, which influence users’ decision-making processes and outcomes, as well as their evaluation of RAs. It goes beyond generalized models, such as TAM, and identifies the RA-specific features, such as RA input, process, and output design characteristics, that affect users’ evaluations, including their assessments of the usefulness and ease-of-use of RA applications. Based on a review of existing literature on e-commerce RAs, this paper develo…