Abstract
Sustainable development has been growingly recognized as important in the scope of tourism and hospitality industry practices. Gastronomic tourism associated with regional food-and wine pairing helps the emerging of higher quality services and contributes to the sustainability of tourist destinations. This study presents a pairing model based on three Real-Time Delphi (RTD) questionnaires to allow experts to select and pair regional wines with regional foods. In the first questionnaire, the experts were asked to choose, by category, the most representative regional dishes from the Algarve region (Portugal). In the second questionnaire, for each dish, experts voted on the best regional wines for the dish. In the third questionnaire, experts made quantitative and qualitative analyses for each of the three most voted wines for each dish. The resulting pairing model of regional food and wines will be communicated to tourism professionals and the general public. By promoting the consumption of these pairings, we promote an efficient, socially fair, and ecologically sustainable local economy. At the same time, we stimulate the circular economy in tourism.
Highlights
Tourism has an important role in sustainable development in many countries and regions worldwide [1,2,3]
Food and wine pairing should be developed, as it potentiates the emerging of higher quality services and contributes to the sustainability of these destinations [14]
This paper presents within the following section a literature review related to gastronomic tourism, the importance of consumption of local products in regional sustainability, sustainability tourism, and food and wine pairing
Summary
Tourism has an important role in sustainable development in many countries and regions worldwide [1,2,3]. Food and wine pairing should be developed, as it potentiates the emerging of higher quality services and contributes to the sustainability of these destinations [14]. In this context, this study aimed to present a model for pairing Algarve wines with. The study included sensory tasting by a group of six experts, two chefs, one maître, one sommelier, one wine expert, and one restaurant/hotel expert. The responses to the sensory tasting were registered in real-time through the third Delphi questionnaire application and were analyzed using data science techniques such as data characterization, data visualization, and text mining
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