The role of demographic similarity in people's decision to interact with online anthropomorphic recommendation agents: Evidence from a functional magnetic resonance imaging (fMRI) study. Issue 133 (January 2020)

• Record Type: Journal Article
• Authors: Benbasat, Izak; Dimoka, Angelika; Pavlou, Paul A.; Qiu, Lingyun
• Is Part Of: International journal of human-computer studies. Issue 133(2020)
• Page Start: 56
• Page End: 70
• Publication Date: 2020-01
• Subjects: Online product recommendation agents -- Anthropomorphic interface -- Avatars -- Ethnicity -- Gender -- fMRI -- Similarity attraction -- Dissimilarity repulsion; Human-machine systems -- Periodicals; Systems engineering -- Periodicals; Human engineering -- Periodicals; Human engineering; Human-machine systems; Systems engineering; Periodicals; Electronic journals; 004.019
• DOI: 10.1016/j.ijhcs.2019.09.001
• Languages: English
• ISSNs: 1071-5819

Abstract

Highlights: Why similarity matters: similarity-attraction vs dissimilarity-repulsion theories. An fMRI study examined neural correlates of similarity and dissimilarity with anthropormophic recommendations agents with human-like avatars. Men prefer avatars that match their ethnicity, as per similarity-attraction theory. Women prefer avatars that match their gender, as per dissimilarity-repulsion theory. Abstract: Recommendation agents (or decision aids) are prevalent in technology-mediated environments. Evidence suggests that people prefer to interact with anthropomorphic recommendation agents with human-like interfaces (avatars) that are demographically similar to them in terms of ethnicity and gender. Several competing theories in the literature have tried to explain why demographic similarity matters, most commonly similarity-attraction theory and dissimilarity-repulsion theory. We compare and contrast these theories by examining the neural bases of why demographic (ethnicity and gender) similarity matters when subjects decided to interact with the human-like avatars of online recommendation agents using functional Magnetic Resonance Imaging (fMRI). The fMRI results showed that men prefer to interact with online anthropomorphic recommendation agents whose avatar matches their ethnicity, while women tend to avoid interacting with online anthropomorphic agents of the opposite gender. Interestingly, the activation levels in the identified brain areas predict the product recommendation of the online recommendation agent from which subjects choose to purchase. Implications for theory, managerial practice, and the design of online anthropomorphic recommendation agents are discussed.