PACIS 2021 Proceedings
Paper Type
RIP
Paper Number
319
Abstract
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.
Recommended Citation
Yang, Yikai; Yu, Yining; Zheng, Jiehui; and Wang, Lei, "The Effect of AI-based Recommendations on Healthy Diet Promotion" (2021). PACIS 2021 Proceedings. 101.
https://aisel.aisnet.org/pacis2021/101
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.