Author
Listed:
- Ronan de Kervenoael
- Alexandre Schwob
- Rajibul Hasan
- Sara Kemari
Abstract
Food Recommender Systems (RecSys) are innovative knowledge systems that inform consumers of food choices according to criteria, including nutritional content, health concerns, production method, carbon footprint or other social and ethical considerations. They raise important questions at the intersection of technology accuracy and today evolving consumers’ knowledge seeking behaviours, which implies to unpack the epistemic value of food RecSys. This study investigates the drivers of the perceived value of food RSs consumption by proposing a model that establishes via PLS-SEM (n = 253) a positive relationship between the Yuka company’s food RecSys’ epistemic value and its perceived value. The model demonstrates that Yuka RecSys’ epistemic value relies on the disciplinary drivers of compatibility, self-confidence, and consumer innovativeness, and the problematising drivers of memory and learning, which come from using the application. The perceived value of food RecSys is found to relate to RecSys epistemic value beyond the functional accuracy aspects of recommendation algorithms. Results highlight the importance of developing a refined understanding of epistemic value considering the consumption of RecSys. RecSys’ developers, retailers, food manufacturers and policy makers must work on better mapping and adjusting information through consumers socialised RecSys’ usage to shape the design of the next generation RecSys.
Suggested Citation
Ronan de Kervenoael & Alexandre Schwob & Rajibul Hasan & Sara Kemari, 2024.
"Food choice and the epistemic value of the consumption of recommender systems: the case of Yuka’s perceived value in France,"
Behaviour and Information Technology, Taylor & Francis Journals, vol. 43(7), pages 1381-1400, May.
Handle:
RePEc:taf:tbitxx:v:43:y:2024:i:7:p:1381-1400
DOI: 10.1080/0144929X.2023.2212088
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