CSR among Canadian mass tour operators: good awareness but little action
Notice bibliographique
Résumé
Purpose The purpose of this paper is to provide an exploratory case study of mass mainstream tour operators in the Canadian market and evaluate their awareness level of corporate social responsibility (CSR) activities. The research aims to address the structure and ownership of mass Canadian tour operators, how it may influence the adoption of CSR practices, key issues and concerns and awareness level and participation of CSR practices. Although the Canadian outbound leisure mass market is relatively small compared with that of the UK, Canadian travelers are a significant source of tourism to Mexico and the Caribbean islands such as Cuba and the Dominican Republic. Design/methodology/approach Canadian mass tour operators were contacted through interviews and questionnaires to assess the structure and ownership of mass Canadian tour operators, how it may influence the adoption of CSR practices, key issues and concerns and awareness level and participation of CSR practices. Existing responsible tourism practices in the destinations they operate were also gauged. Findings CSR is gaining momentum worldwide as companies begin to realize that their stakeholders are demanding accountability that goes beyond shareholders' interests. Subsequently, reporting levels are increasingly being regulated and corporate strategic initiatives focusing on improving their social and environmental responsibility are on the rise. In the case of tour operators, however, initiatives of this nature are preliminary and there is little implementation of CSR practices. Research limitations/implications The study examines Canadian mass tourism package tour operators and further research is needed to assess all tour operators (inbound and outbound) to determine whether the level of participation in responsible travel is higher or whether size is an implicating factor. As issues such as climate change and responsible tourism have only started to influence consumer demand in the past few years, the study's findings may be changing. Therefore a further follow‐up study would be beneficial in order to determine any barriers to action. Originality/value To date, little research has been done on the tourism industry, and that mainly on hotels. There is a need to understand the structure and contribution of tour operators to the industry and their level of CSR practices and movement towards more responsible tourism.
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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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,004 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».