The influence of AI-generated versus real food images on perceived value and negative WOM
Guinalíu, Miguel (Universidad de Zaragoza) ; Belanche, Daniel (Universidad de Zaragoza) ; Casaló, Luis V. (Universidad de Zaragoza)
Resumen: Purpose – As the use of generative AI in food marketing continues to grow, understanding how consumers evaluate AI-generated imagery has become increasingly important. In this article, a comparison is made of how AI-generated images and real images influence consumers’ perceived value and negative word-of-mouth (WOM) intentions through the mediating effects of pleasure and perceived risk. Design/methodology/approach – This study draws on decision-making theory, the cost–benefit paradigm and affect heuristic theory. Data were collected through an online survey distributed to 241 Spanish consumers, who were randomly exposed to either AI-generated (with an AI disclosure label) or real food images. Data were analysed using partial least squares structural equation modelling (PLS-SEM).
Findings – AI-generated food images, when compared to real food images, significantly reduce consumers’ perceptions of value and increase their negative WOM. Pleasure and perceived risk mediate these effects, and consumers with more experience of AI are less prone to the adverse influence of AI-generated (vs real) images on pleasure. Practical implications – AI-generated imagery may diminish pleasure and heighten perceived risk, leading to less favourable consumer responses. Therefore, food marketers should ensure that AI-generated images retain a realistic and appetising appearance to prevent negative effects on perceived value and brand evaluations. Originality/value – This research integrates emotional and cognitive processes and advances decision-making and affect heuristic frameworks by revealing how pleasure and perceived risk jointly shape consumer responses to AI-generated (vsreal)food imagery. Specifically, we confirm that emotion-based heuristics continue to play a decisive role in consumer decision-making, even in technologically mediated environments.
Idioma: Inglés
DOI: 10.1108/BFJ-05-2025-0657
Año: 2025
Publicado en: BRITISH FOOD JOURNAL (2025), 1-24
ISSN: 0007-070X
Financiación: info:eu-repo/grantAgreement/ES/DGA-FSE/S20-23R METODO Research Group
Tipo y forma: Article (PrePrint)
Área (Departamento): Área Comerci.Investig.Mercados (Dpto. Direc.Mark.Inves.Mercad.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes.
Exportado de SIDERAL (2026-01-30-14:56:14)
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Findings – AI-generated food images, when compared to real food images, significantly reduce consumers’ perceptions of value and increase their negative WOM. Pleasure and perceived risk mediate these effects, and consumers with more experience of AI are less prone to the adverse influence of AI-generated (vs real) images on pleasure. Practical implications – AI-generated imagery may diminish pleasure and heighten perceived risk, leading to less favourable consumer responses. Therefore, food marketers should ensure that AI-generated images retain a realistic and appetising appearance to prevent negative effects on perceived value and brand evaluations. Originality/value – This research integrates emotional and cognitive processes and advances decision-making and affect heuristic frameworks by revealing how pleasure and perceived risk jointly shape consumer responses to AI-generated (vsreal)food imagery. Specifically, we confirm that emotion-based heuristics continue to play a decisive role in consumer decision-making, even in technologically mediated environments.
Idioma: Inglés
DOI: 10.1108/BFJ-05-2025-0657
Año: 2025
Publicado en: BRITISH FOOD JOURNAL (2025), 1-24
ISSN: 0007-070X
Financiación: info:eu-repo/grantAgreement/ES/DGA-FSE/S20-23R METODO Research Group
Tipo y forma: Article (PrePrint)
Área (Departamento): Área Comerci.Investig.Mercados (Dpto. Direc.Mark.Inves.Mercad.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. Exportado de SIDERAL (2026-01-30-14:56:14)
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Record created 2026-01-30, last modified 2026-01-30