Clustering Local Tourism Systems by Threshold Acceptance

Abstract

Abstract. Despite the importance of tourism as a leading industry in the development of a country's economy, there is a lack of criteria and methodologies for the detection, promotion and governance of local tourism systems. We propose a quantitative approach for the detection of local tourism systems that are optimal with respect to geographical, economic, and demographical criteria. To this end, we formulate the issue as an optimization problem, and we solve it by means of Threshold Acceptance, a meta-heuristic algorithm which does not require us to predefine the number of clusters and also does not require all geographic areas to belong to a cluster.

Fuzzy multi-criteria decision-making: An entropy-based approach to assess tourism sustainability

“…The increased attention to sustainability led to the need to establish definitions and principles (World Travel & Tourism Council, 1998) for sustainable tourism , to quantify the degree of sustainability of a touristic destination, to assess of the state of the destination (Budeanu, 2015), and to identify the policies to be fostered in that given territory (Blancas et al, 2010; Landford, 2009). To this goal, one may identify a set of indicators to assess the degree of sustainability with respect to different criteria as, for example, in Bosh (2002) and Hezri (2004) and to combine them into a unique aggregate indicator (Andria et al, 2015; Andria and di Tollo, 2015; Andria et al, 2019a, 2019b; Blancas et al, 2011). As for the criteria, many contributions focus on economic aspects, but also social and environmental issues are taken into account, especially with respect to legal compliance, political maneuvering, marketing, and public relations (Bramwell et al, 2017; Buckley, 2009; Hall, 2010).…”