Tools for measuring the intention for adapting to climate change by winter tourists: some thoughts on consumer behavior research and an empirical example
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Notice bibliographique
Résumé
Purpose Climate change will lead to new environmental conditions in winter sport destinations. Even if the motivations of the visitors remain the same, climate change will inevitably influence their behavior. At the same time, tourism destinations try to influence visitor behavior by implementing adaptation strategies and offering new products. The purpose of this paper is to discuss the advantages and disadvantages of possible consumer research approaches from a destination's perspective. Design/methodology/approach In order to study the influence of climate change on winter destinations in Austria, the authors adapted an existing behavioral framework to the model for proactive tourist adaptation to climate change, which is helpful to understand the influencing factors and the individual decision‐making process towards adaptation intention. Thereafter they used the results of a choice experiment (=intended behavior) to calibrate a decision support tool (DST) for a cross‐country skiing destination in Austria. Findings The paper presents a DST based on the choice experiment. The DST shows the changing market shares for three segments as a destination and its entrepreneurs attempt to identify the best opportunities for the various adaption strategies they can possibly consider. The authors suggest this as a suitable market research tool for proactive destination management. Research limitations/implications Compared to the theory of planned behavior (TPB), Choice experiments (CE) are less suitable to contribute to the understanding of behavior; at the same time, CEs are well suited to model intended behavior, and to predict the demand for currently non‐existing alternatives when past behavior might be a poor predictor. Practical implications The authors propose a conceptual framework that explicitly combines the modeling of behavior and behavioral intention with relevant concepts of the individual customer's cognitive process. The authors want to ensure that destination managers are able to understand, and eventually direct and influence travel behavior as it relates to their local conditions, which in the context of climate change implies that the destination must lay the foundation for tomorrow's success while competing today. Originality/value The paper focuses on two main challenges related to destination choice in the context of climate change: tourists encounter a rather unique decision context, as their decision to visit is completely voluntary, and predicting visitor reactions to climate change enters uncharted waters as clients have not encountered these situations before.
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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 | 0,007 | 0,002 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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