Notice bibliographique
Résumé
Purpose Functional foods, also known controversially as “phoods,” are perceived by many as the food industry's response to consumers' increasing desire to make healthier eating choices. The objective of the present study is to determine the influence of the production technology used to make functional foods on the perceived health value of functional foods. Design/methodology/approach To meet the objectives of the study, the paper employs an exploratory study with six conditions. The two factors addressed were the added nutrient (lycopene and beta‐carotene) and the degree of production technology (low, medium, and high). Lycopene and beta‐carotene were both added to two functional foods with different health features, which in this study were orange juice and apple pie. The use of this latter factor supposed that the level “low” implied a product which was improved by adding a food that naturally contained a nutrient, the level “medium” implied that the nutrient was added in the laboratory, and the level “high” refers to an ingredient whose genetic code had been modified in order to introduce the gene producing the nutrient. In order to reduce the effect of the order of presentation of the technology levels, the sequence of levels was randomized. Findings The results show that perceived health benefits and intention to purchase are not so much influenced by what we pose as graduated stages of production technologies as by a perceived dichotomy between natural and artificial foods. The results also show the extensive mediating effect of perceived risks and benefits on the relationship between experimental conditions, perceived health benefits, and intent to purchase. The results also reveal that pre‐purchase intentions of functional foods are more noteworthy for orange juice, which has a usefulness valence, than for apple pie, which has a less healthy epicurean valence. Originality/value This study has various strengths, including a novel intervention that addressed a timely topic for which few data are currently available. The sale of functional foods is a complex practice. This exploratory study took a few steps toward understanding how health benefits of functional foods are perceived and how these perceptions can be better understood by food manufacturers and consumers in today's society.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,143 | 0,057 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».