Thinking AI or feeling AI? The effect of AI on consumers’ willingness to purchase healthy food from the perspective of nudge

• Published in: Humanities & social sciences communications Vol. 12; no. 1; pp. 1032 - 15
• Main Authors: Bi, Chongwu, Cui, Xinyu, Sun, Zhuo, Jin, Yan
• Format: Journal Article
• Language: English
• Published: London Palgrave Macmillan UK 07.07.2025; Palgrave Macmillan; Springer Nature
• Subjects: 4000/4001; 4014/4045; 4014/477; Anthropomorphism; Artificial intelligence; Automation; Big Data; Classification; Consumer behavior; Consumers; Customer relationship management; Decision making; Efficiency; Emotions; Food; Health care; Health literacy; Humanities and Social Sciences; Influence; Machine learning; multidisciplinary; Natural & organic foods; Natural language; Public health; Recommender systems; Science; Science (multidisciplinary); User behavior; User experience; User needs
• ISSN: 2662-9992; 2662-9992
• DOI: 10.1057/s41599-025-05391-w

The application of AI technologies in influencing consumers’ willingness to purchase healthy food is becoming increasingly prevalent. Significant differences have been observed in the service characteristics of different AI types (thinking AI vs. feeling AI) and consumers’ decision-making pathways across various consumption contexts (public vs. personal). In response to this, the present study systematically explores the interactive effects of AI type and consumption context on consumers’ willingness to purchase healthy food based on nudge theory, employing two 2 × 2 between-subject experiments. Study 1 recruited 120 valid participants, who were randomly assigned to either a public or personal consumption context. Their willingness to purchase healthy food was measured using a seven-point Likert scale to examine the interaction between AI type and consumption context. Study 2 further investigated the mediating roles of cognitive and affective responses in this interaction effect. Additionally, robustness checks were conducted by modifying AI product materials and repeating the experiment to ensure the reliability of the findings. This study unveils the interaction effect between AI type and consumption context, as well as its underlying mediating mechanism, thereby expanding the theoretical framework of research on health food consumption behavior. Furthermore, the findings provide practical insights for businesses to develop precise AI-driven health food marketing strategies.