The study of tourists’ profiles regarding gastronomy as a tourist attraction has been widely addressed in the academic literature. However, little research has focused on segmentation, despite its importance for destination positioning. In this context, the main objective of this research is to segment Spanish tourists according to their culinary interests and preferences. Based on a sample of 603 Spanish tourists, this study applies regression analysis to identify the factors that position gastronomy as a motivation for travelling. In addition, latent class regression models are employed to identify and explain different segments of gastronomic tourists. Regression analyses revealed the factors influencing the importance placed on gastronomy for travel; they include seeking gastronomic experiences, valuing culinary culture and heritage, the availability of famous dishes, and tradition. A latent class regression model further uncovered segment-specific drivers of gastronomic travel motivations: identifying five clusters of tourists with different profiles. The findings provide valuable insights for tourism stakeholders to develop targeted marketing strategies, design authentic food-related experiences, support sustainable practices, and optimize revenue management based on the diverse profiles of Spanish gastronomic tourists.

Gastronomy, as a driving force of tourism in Spain: a study using segmentation and latent classes

Bassi, Francesca;
2026

Abstract

The study of tourists’ profiles regarding gastronomy as a tourist attraction has been widely addressed in the academic literature. However, little research has focused on segmentation, despite its importance for destination positioning. In this context, the main objective of this research is to segment Spanish tourists according to their culinary interests and preferences. Based on a sample of 603 Spanish tourists, this study applies regression analysis to identify the factors that position gastronomy as a motivation for travelling. In addition, latent class regression models are employed to identify and explain different segments of gastronomic tourists. Regression analyses revealed the factors influencing the importance placed on gastronomy for travel; they include seeking gastronomic experiences, valuing culinary culture and heritage, the availability of famous dishes, and tradition. A latent class regression model further uncovered segment-specific drivers of gastronomic travel motivations: identifying five clusters of tourists with different profiles. The findings provide valuable insights for tourism stakeholders to develop targeted marketing strategies, design authentic food-related experiences, support sustainable practices, and optimize revenue management based on the diverse profiles of Spanish gastronomic tourists.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3579238
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