Article ID Journal Published Year Pages File Type
400932 International Journal of Human-Computer Studies 2010 20 Pages PDF
Abstract

Product Recommendation Agents (PRAs) and other web-based decision aids are deployed extensively to provide online shoppers with virtual advising services. While the design of PRA’s functional features has received a high degree of attention in academic studies, the social aspects of human–PRA interactions are comparatively less explored.This paper investigates the potential of enhancing users’ social experiences of interacting with an anthropomorphic PRA (i.e., an agent with human-like characteristics, such as facial expressions, body gestures, or speech output) by manipulating its demographic embodiments. The two demographic variables assessed are ethnicity and gender. As suggested by similarity-attraction theory and social identity theory, the results of our laboratory experiment reveal that PRAs that match the ethnicity, though not the gender, of their users are perceived as more sociable, more enjoyable, and more useful to interact with than the mismatched ones. More interestingly, the “matching-up” effects of ethnicity are more significant among female users than males. Implications for practitioners on how to use an anthropomorphic agent’s demographic characteristics to enhance users’ interaction experience are also discussed.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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