Adaptive decision support system (ADSS) for B2C e-commerce
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Prior efforts in personalization have focused primarily on modeling individual consumer'spreferences so that products for which they have a higher likelihood of purchasing are presented. In this study we explore the potential of an approach to personalization focusing on customizing shopping tools based on a consumer's Product Category Knowledge. The low Product Category Knowledge user may not be able to use the shopping tools as well as the high Product Category Knowledge user, because lower Product Category Knowledge usersallocate cognitive power to learning the product attribute space at the expense of using the tool effectively. Alternatively, shopping tools may effectively guide the decision making of low Product Category Knowledge users, but be perceived as too restrictive by high Product Category Knowledge users, thus diminishing their Decision Confidence. To determine which of these scenarios holds true we had sixty-six subjects interact with different decision toolsof varying effort-accuracy tradeoffs in our purposebuilt web store for purchasing a computer. We examine the impact of Product Category Knowledge on perceptions of ease of use and usefulness of the decision tools, and ultimately Decision Confidence, a key predictor of purchase likelihood. The results evidence the potential value of adapting tools to the degree of user Product Category Knowledge. High Product Category Knowledge users may require less restrictive decision tools to promote Decision Confidence, whereas low Product CategoryKnowledge users may require simpler tools and more decisional guidance [1].