Estimating Consumers' Valuation of Sustainability Labeling Using Stated Choice Analysis: Evidence from McGill University's Residential Dining Halls
Notice bibliographique
Résumé
As the threat of human-induced climate change grows, individuals across the globe are becoming increasingly concerned with finding ways to reduce their impact on environmental degradation.Household food consumption contributes largely to global greenhouse gas emissions through the high usage of land and water materials involved in food production to meet this demand.Sustainable food consumption practices, such as adopting a plant-based diet, are encouraged to minimize the effects of agricultural production.Although a sustainable diet can be effective in reducing greenhouse gas emissions relative to the consumption of conventional food products, it is challenging to bring this shift in dietary preferences.The labeling of sustainable foods can inform consumers about the environmental benefits of selecting certain food products and may incentivize producers to invest in and increase the use of sustainable agricultural practices.Higher education institutions such as universities can serve as a meaningful out-of-home setting to implement sustainable food labeling, as dining halls and food chains on university campuses are visited by a large and diverse population of consumers.However, little is known about how labels that inform diners of food attributes influence diners' willingness to pay for meals in these settings.Using a discrete choice experiment, this study examines consumers' preferences and willingness to pay (WTP) for labeled sustainable ingredients used in McGill University's residential dining hall meals in Montreal, Quebec.A sample of 408 consumers was presented with hypothetical meal choices that differed in their sustainability attributes, including locally sourced, vegetarian, and organic ingredients.Participants were randomly placed into a control group or one of two information treatment groups, providing them with basic or enhanced information about the sustainability attributes.Using a conditional logit model, our results show that participants were willing to pay price premiums for meals containing the sustainability attributes.However, those who received detailed information were not willing to pay an additional price premium.A latent class model was used to determine the influence of individual characteristics on consumption behaviors and WTP.The model resulted in three distinct classes: the "combined preferences" group of consumers; the "loyal meat-eaters" group; and the "sustainably-conscious" group.Despite these distinct groups, however, the enhanced information did not have a significant effect on participants' WTP for the sustainability attributes.The findings from this research iii suggest that McGill University's Food and Dining Services, as well as other out-of-home dining settings and food marketers, can effectively promote the sustainability attributes of their meals without providing detailed information to diners.
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 | 0,008 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».