| Titre : | Emerging technologies for investigating food consumer behavior: a systematic review (2025) |
| Auteurs : | K. Kechri ; C. Kleisiari ; L.S. Kyrgiakos ; M. Vasileiou ; D.D. Tosiliani ; V. Angelopoulos ; G. Kleftodimos ; G. Vlontzos |
| Type de document : | Article |
| Dans : | Comprehensive Reviews in Food Science and Food Safety (vol. 24, n. 6, November 2025) |
| Article en page(s) : | p. e70340 |
| Langues : | Anglais |
| Langues du résumé : | Anglais |
| Catégories : |
Catégories principales 08 - ALIMENTATION ; 8.1 - Consommation Alimentaire. ComportementThésaurus IAMM COMPORTEMENT ALIMENTAIRE ; PREFERENCE ALIMENTAIRE ; MEGADONNEES ; SECTEUR AGROINDUSTRIEL ; INNOVATION ; METHODE ; ANALYSE DE DONNEES |
| Mots-clés: | RÉALITÉ VIRTUELLE |
| Résumé : | The evolving nature of food preferences and consumption patterns highlights the need for ongoing research in food consumer behavior. Most existing research relies on traditional methods, like questionnaires, which are often costly, time-consuming, and prone to bias. The increasing integration of emerging technologies, including Artificial Intelligence (AI), Virtual Reality (VR), Social Media Analytics (SMA), and Big Data, into the food sector presents novel opportunities to overcome these limitations. This systematic review, conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, identified 628 records, out of which 159 eligible articles were included. These examine how technological innovations contribute to understanding food trends and consumption preferences, as well as consumer attitude towards these technologies. The findings reveal the considerable potential of big data, SMA, and transactional analytics to provide large-scale, diverse, and real-time data into consumer behavior. Machine Learning (ML) techniques improve the analysis and interpretation of such complex datasets, enabling high predictive capability and a more precise market segmentation to provide consumers with personalized marketing content. Immersive technologies like VR offer realistic simulations of food purchasing behaviors and adapt to multiple research scenarios, overcoming limitations of traditional research methods. However, most technology-based studies remain primarily quantitative, limiting depth of understanding. Challenges in automated data interpretation, reduced sensory immersion in VR environments, users' unfamiliarity and data privacy concerns need also to be addressed. Thus, future research should focus on technological advancement, improving usability and establishing ethical frameworks to foster consumer trust, while also integrating qualitative methods too beyond only relying on technology-based outcomes. |
| Note de contenu : | FOODMISSION (Grant Agreement No 101181774) |
| Cote : | Online |
| URL / DOI : | https://doi.org/10.1111/1541-4337.70340 |
Documents numériques (1)
 PRO54038.pdf Adobe Acrobat PDF |
