Consumers’ Valuation of Functional Properties of Foods: Results from a Canada‐wide Survey
Bibliographic record
Abstract
Very few economic analyses have been done about functional foods and nutraceuticals. The current paper seeks to characterize Canadian consumers' attitudes, beliefs, knowledge and willingness‐to‐pay for functional foods. In the spring of 2001, a telephone survey of 1008 Canadian household food shoppers was conducted. The questionnaire included stated‐choice experiments to derive distributions of price‐functional property trade‐offs. The majority of respondents appeared willing to purchase and to pay a price premium for functional foods, particularly if the functional property were added to foods derived from plants. Consumers were less receptive to a functional property incorporated in a meat product. A large proportion of respondents negatively perceived genetically modified (GM) and organic foods relative to conventional foods, after controlling for price and the health property. This suggests that there could be a niche market for organic functional foods and that GM functional foods would have to be discounted to attract a wide range of consumers. Peu d'études ont été réalisées sur les aliments fonctionnels et les nutraceutiques. Notre papier a pour but de caractériser les attitudes, les croyances, les connaissances et la volonté des consommateurs canadiens de payer plus cher pour des aliments fonctionnels. Un sondage téléphonique fut administré auprès de 1008 répondants à trovers le Canada. Des expériences amenant les répondants àénoncer leur préférences en faisant des choix de produits ont été réalisées pour générer les distributions des compromis entre les prix et les propriétés fonctionnelles. La majorité des répondants sontprêt á payer des suppléments pour des propriétés fonctionnelles, surtout si celles‐ci sont ajoutées a des produits dérivés des plantes. Les répondants semblent mains réceptifs aux propriétés ajoutées à de la viande. Une proportion élevée de répondants entretiennent des perceptions négatives des aliments GM et organiques, relativement aux produits conventionnels après avoir contrôlé pour les prix et les propriétés fonctionnelles. Ceci suggère qu'il y aurait un marché niche pour les aliments fonctionnels organiques et que les aliments fonctionnels GM devraient être réduits en prix pour attirer une vaste clientele.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".