Exploring the mediating role of gastronomic experience in tourist satisfaction: A multigroup analysis
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https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.3.48Keywords:
Local food, Famous, Tourists' segmentation, Gastronomic experience, Tourist satisfactionDimensions Badge
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Gastronomic experience encountered by tourists in a famous local food outlet plays a crucial role in delivering overall satisfaction with the destination. Previous studies widely acknowledge the importance of region’s cuisine in enhancing gastronomic tourism, and have identified various types of tourists depending upon their interest in local food preparations. This empirical analysis presents a novel approach in investigating the mediating role of gastronomic experience in the relation between gastronomic motivation, and overall satisfaction of the tourists who are segmented according to the relevance of local gastronomy in their destination selection, in context of famous local food outlets which offer delectable traditional Punjabi cuisine in the holy city of Amritsar, proclaimed as the food capital of Punjab. Data was gathered through a well-structured, and self-administered survey questionnaire circulated amongst the tourists after their gastronomic encounter. The constructs of the study were specified as reflective or formative as per the nature of their measurement indicators. Hierarchical and K-means cluster analysis was used for segmentation, and PLS-SEM was further utilized to conduct Multigroup analysis, after ascertaining the common method bias, and measurement invariance using the MICOM process. The results reveal full mediation exhibited by gastronomic experience, and an insignificant difference between the tourist segments on the strength of proposed relationships amongst the study’s constructs. Implications and suggestions are provided for the owners, and managers of local food outlets, the government and all other stakeholders linked to the enhancement of tourist experience at the destination. Future studies may replicate the current model in other tourist destinations, to further validate the findings.Abstract
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