Do Consumers Consider Environmental Considerations When Making Food Choices? Insights from Indonesia, Bangladesh, and Kenya
Notice bibliographique
Résumé
The world is facing multiple interconnected crises, including climate change and escalating conflicts, which pose significant challenges to food systems.These issues highlight the need for systemic transformation to improve food security, nutrition, and environmental sustainability.In response, GAIN's Nourishing Food Pathways (NFP) programme aims to strengthen and support the implementation of food system pathways in 11 countries.One focus of NFP is exploring the intersection between food and environment, including climate change, to identify consumer actions that promote both nutrition and environmental sustainability in low-and middle-income countries (LMICs).Specifically, GAIN is interested in understanding if our Emotivate™ approach, which leverages emotions to motivate consumers to want better diets, can be extended to include emotions or values associated with environmental sustainability.Our initial hypothesis was that consumers felt emotional tensions related to environmental sustainability as a driver of food choices, which could be leveraged to develop an emotionally resonant campaign.GAIN thus conducted a formative study in Bangladesh, Indonesia, and Kenya to explore this further.The study revealed varying levels of environmental awareness across the three countries.Consumers were generally aware of environmental issues, but these concerns had limited impact on their daily lives and food choices.Food choices were driven by other factors, such as convenience and cost.Consumers often viewed environmental issues as a responsibility of governments and corporations, and they did not feel personally empowered or compelled to make significant changes.While consumers acknowledged the environmental impacts of packaging and food waste, these concerns had limited influence on food choices.These findings, counter to our original hypothesis, suggest that consumers are unlikely to respond to interventions that explicitly link food choices to environmental considerations as a key motivation for change.The programmatic implication is that it is important to frame messages to resonate with KEY MESSAGES• There is limited evidence of consumer-driven actions that simultaneously promote nutrition and environmental sustainability, especially in LIMCs.• A successful demand-generation approach for healthy diets often leverages consumers' emotions to inspire change.We aimed to explore whether emotions and values linked to environmental concerns could drive such demand.• Our findings suggest that consumers in Indonesia, Bangladesh, and Kenya are unlikely to respond to interventions that explicitly link food choices to environmental considerations as key motivation for change.• Programmatic implications include framing messages that resonate with consumers' values, while ensuring that promoted choices are both nutritious and environmentally sustainable.
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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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
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 ».