000168259 001__ 168259
000168259 005__ 20260130145834.0
000168259 0247_ $$2doi$$a10.1108/BFJ-05-2025-0657
000168259 0248_ $$2sideral$$a147759
000168259 037__ $$aART-2025-147759
000168259 041__ $$aeng
000168259 100__ $$0(orcid)0000-0002-1456-4726$$aGuinalíu, Miguel$$uUniversidad de Zaragoza
000168259 245__ $$aThe influence of AI-generated versus real food images on perceived value and negative WOM
000168259 260__ $$c2025
000168259 5060_ $$aAccess copy available to the general public$$fUnrestricted
000168259 5203_ $$aPurpose – 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.
000168259 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FSE/S20-23R METODO Research Group
000168259 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc$$uhttps://creativecommons.org/licenses/by-nc/4.0/deed.es
000168259 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/submittedVersion
000168259 700__ $$0(orcid)0000-0002-2291-1409$$aBelanche, Daniel$$uUniversidad de Zaragoza
000168259 700__ $$0(orcid)0000-0002-9643-2814$$aCasaló, Luis V.$$uUniversidad de Zaragoza
000168259 7102_ $$14011$$2095$$aUniversidad de Zaragoza$$bDpto. Direc.Mark.Inves.Mercad.$$cÁrea Comerci.Investig.Mercados
000168259 773__ $$g(2025), 1-24$$pBr. food j.$$tBRITISH FOOD JOURNAL$$x0007-070X
000168259 8564_ $$s507069$$uhttps://zaguan.unizar.es/record/168259/files/texto_completo.pdf$$yPreprint
000168259 8564_ $$s1415599$$uhttps://zaguan.unizar.es/record/168259/files/texto_completo.jpg?subformat=icon$$xicon$$yPreprint
000168259 909CO $$ooai:zaguan.unizar.es:168259$$particulos$$pdriver
000168259 951__ $$a2026-01-30-14:56:14
000168259 980__ $$aARTICLE