A composite tourism index for the competitiveness of marginal areas: a pilot application in a Southern Italy province

Abstract

Purpose Differently from traditional approaches that rely on the analysis of single dimensions of the tourism phenomenon, this study aims to experiment a systemic approach based on structured and unstructured data sources to elaborate a composite index to measure the tourist competitiveness of marginal areas, with the final aim to design and plan proper socio-economic development strategies. Design/methodology/approach The methodology adopted to carry out the study follows a four-step process and relies on indicators that are both relevant and accessible. The first step concerns the analysis of the literature about the existing approaches to calculate a tourism index. The second step concerns the definition of the indicators and the collection of data by using both structured and unstructured sources. The third step focuses on the population of the data set. Finally, the fourth step aims at calculating the tourism index through a composite-based methodology and using it for a pilot application in a Southern Italy province. Findings The study calculates a synthetic tourism index for each of the 97 municipalities of the Province of Lecce (a city located in the southeast of Italy). The proposed index combines administrative, institutional and open data sources to derive a single indicator for each municipality, thus supporting decision-makers in understanding the complex reality and competitiveness level of territories in the tourism industry. Originality/value The main elements of originality of the study are the breadth and typology of data sources considered to calculate the composite indicator of tourism competitiveness (both structured and unstructured); and the use of weighting and aggregation procedures in the methodological issues.

Leveraging knowledge discovery and knowledge visualization to define the “inner areas”: an application to an Italian province

“…This confirms that knowledge represents the most valuable resource for territorial development (Rim et al, 2017;Bakici et al, 2013), above all when it is created and shared amongst stakeholders (Rastegar and Ruhanen, 2021); similarly, knowledge management can be considered as the most strategic process (Laurini, 2020;Ardito et al, 2019). In this view, it is particular interesting to rethink the strategies for the development of marginal areas, by leveraging the distinctive local characteristics and resources (Moretto et al, 2021b;Battaglia et al, 2019;Piani et al, 2019;Gray, 2007;Tonn et al, 2006;Tonn et al, 2010). In this "regional foresight" perspective (Bootz et al, 2019), it is relevant the geographic concept of "inner areas" introduced by Barca (2009) and in particular its social, physical and economic dimensions (Romagnoli and Mastronardi, 2020;Pateman, 2011).…”

“…Such distance generates a progressive marginalization in the form of increasing depopulation, high rates of demographic aging and unemployment, inequalities in the provision of services and infrastructure, relevant emigration flows (Bertolini and Pagliacci, 2017; Barca et al , 2014; Lucatelli et al , 2013). This happens, although such territories are rich of natural resources and attractions, cultural heritage, artistic events, typical agriculture and others valuable assets (Mastronardi et al , 2020) that can revitalize the entire tourism industry (Moretto et al , 2021b).…”

“…Recently, Moretto et al (2021a) focused on discovering similarities existing among different municipalities by using a knowledge discovery algorithm based on association mining method. Besides, by focusing on the tourism industry, Moretto et al (2021b) elaborated a composite index to measure the tourist competitiveness of marginal areas, in the final aim to support local policy makers in the process of local territorial development.…”

“…In this view, it is particular interesting to rethink the strategies for the development of marginal areas, by leveraging the distinctive local characteristics and resources (Moretto et al , 2021b; Battaglia et al , 2019; Piani et al , 2019; Gray, 2007; Tonn et al , 2006; Tonn et al , 2010). In this “regional foresight” perspective (Bootz et al , 2019), it is relevant the geographic concept of “inner areas” introduced by Barca (2009) and in particular its social, physical and economic dimensions (Romagnoli and Mastronardi, 2020; Pateman, 2011).…”

“…A further study carried out byMastronardi et al (2020) proposed a cooperative-based approach as a factor capable of contributing to the reduction of regional gaps and increasing resilience and rebirth of inner areas by offering collective services, such as mobility and elderly care, and creating job opportunities in traditional profitable sectors, such as agriculture and land maintenance.Recently,Moretto et al (2021a) focused on discovering similarities existing among different municipalities by using a knowledge discovery algorithm based on association mining method. Besides, by focusing on the tourism industry,Moretto et al (2021b) elaborated a composite index to measure the tourist competitiveness of marginal areas, in the final aim to support local policy makers in the process of local territorial development.…”