PACIS 2021 Proceedings

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As intelligence algorithm and machine learning gain momentum, AI is increasingly being applied in personalized diet recommendations. However, the question of how users respond to AI-based diet recommendations has yet to be resolved. In the current research, we establish an “AI-healthiness” association and investigate its downstream consequences (i.e., healthy diet choice and WTP) as well as the boundary condition (i.e., self-efficacy). We propose that AI-based diet recommendations are positively associated with perceived healthiness, and such “AI-healthiness” association has a positive effect on healthy diet preference. In addition, the effect will diminish for low self-efficacy consumers. We will conduct 3 studies to examine the proposed effects from psychological, behavioral and neural perspectives. We believe that the current research will significantly contribute to the theoretical landscape of AI-based recommendations, and provide important practical contributions for policy makers, marketers and designers.

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