Do one’s moral foundations impact how they respond to information on climate change emissions? A vehicle choice experiment
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
• The influence of Climate Change Information varied significantly by moral foundations. • A new Emoji framing elicited a high willingness-to-pay for four moral foundations. • Contrasting results were found between Individualizing and Binding foundations. • Strong willingness-to-pay was found for both Individualizing and Binding foundations. Transportation is a major source of climate change emissions. Providing people with better information on those emissions is one means of helping individuals make climate-friendly choices. However, not everyone is influenced by the same type of information. Previous research has demonstrated that Goal Framing Theory could help improve the influence of climate change emissions information and that different framings have different levels of influence depending on a number of socio-demographic and attitudinal characteristics. However, apart from climate change motivation, what other underlying psychological factors might help us understand why the framings vary in their influence between individuals? Moral Foundation Theory (MFT) identifies key values that influence people’s moral decisions, providing a useful framework for understanding diverse responses to information. The objective of this study is to understand whether MFT can help explain different responses by individuals and identify which framings are associated with stronger responses for different moral foundations. This study investigates the moderating effects of moral foundations on individuals’ responsiveness to different emission information framings. Utilizing data from discrete choice experiments involving 2015 Canadian drivers, we examine how different moral foundations impact the willingness-to-pay (WTP) for reducing emissions. The results reveal that the impact of emissions information framing varies significantly according to individuals’ moral foundations. Specifically, moral values associated with Authority, Fairness, and Purity play negative moderating roles on WTP for CO 2 emissions under different framings, whereas Ingroup and Harm foundations have positive moderating effects on WTP with the framings tested. Additionally, innovative communication tools like new emojis demonstrated strong positive effects on WTP, especially among those with strong Ingroup, Fairness, and Purity values. Conversely, individuals with a strong Authority value showed the lowest WTP when presented with pressure gauge visuals. Using appropriate framing based on Moral Foundation Theory can considerably change the willingness-to-pay for climate change emissions for different parts of the population, with a notable increase in WTP observed among individuals inclined to alter their behavior. Future framings should incorporate MFT in their design.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 découle