Sustainability in Peripheral and Ultra-Peripheral Rural Areas through a Multi-Attribute Analysis: The Case of the Italian Insular Region

Abstract

Italy has adopted the strategy of inner areas, mainly based on physical distance from public services. The strategy promotes a multi-level and multi-fund governance approach and the local partnership of mayors. Our paper focuses on rural areas, identified by the national strategy of inner areas, as peripheral and ultra-peripheral, in the Italian insular region (Sicily and Sardinia). It analyzes, at the municipality level, socio-demographic, economic, and environmental sustainability using appropriate indicators. Aiming at discovering the underlying relationship portrayed by multi-attribute data in an information system, we applied rough set theory. The inductive decision rules obtained through this data mining methodology reveal the simultaneous presence or absence of important characteristics aiming at reaching different levels of sustainability. Without the requirement of statistical assumptions regarding data distribution or structures for collecting data, such as functions or equations, this method ensures the description of patterns exhibited by data. Of particular interest is the assessment of conditional attributes (i.e., the selected indicators), and the information connecting them to sustainability, as a decision attribute. The most important result is rule generation, specifically, decision rules that are able to suggest tools for policy makers at different levels.

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

“…The study presented in this article enriches the literature focused on internal areas and in particular on the identification of new methodologies based on clustering algorithms to define and analyze internal areas (Zolin et al, 2020), as well as to guide future planning processes (Leimgruber, 2010;Pateman, 2011;Scott et al, 2007). Compared to other previous studies (Ferri, 2015), this work leverages a multi-domain and multidimensional The study provides evidence about how to overcome the limits of the SNAI indicator grid (Rossitti et al, 2021), especially for what concerns the weaknesses related to data collection and data visualization that are solved by using advanced knowledge discovery algorithms and knowledge visualization techniques.…”

“…Inner areas cover more than half of the entire Italian territory and represent almost ¼ of the total population. In this direction, the legislator has developed the National Strategy for inner areas (MISE, 2012(MISE, , 2013, which aims to reverse the demographic trend and promote socio-economic well-being processes by strengthening endogenous development resources (Zolin et al, 2020).…”

A knowledge visualization approach to identify and discovery inner areas: a pilot application in the province of Lecce

“…Actually, some studies already focused on the identification of new methodologies based on the adoption of multiple criteria, clustering algorithms and knowledge discovery techniques to define and analyse inner areas (Zolin et al , 2020). For example, Leimgruber (2010), Pateman (2011) and Scott et al (2007) experienced clustering as innovative and replicable operational tool for guiding the future planning processes of inner areas.…”

“…Since 2012, in Italy, where inner areas cover almost the 60% of the whole national territory and embrace about the 23% of total population, it was developed a national strategy for inner areas, with a twofold objective: in the short term, to improve the quality of life and economic well-being of people living in relatively isolated and sparsely populated areas; in the long term, to invert the demographic trends of such areas, to reduce the social costs and strengthen the local development factors (Zolin et al , 2020).…”

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

“…Chia-Li (2019) and Zolin et al (2020) adopted a tourism composite index to evaluate the sustainable development of tourism in urban and rural towns. In particular, they proposed a method and a tool that may support local decision-makers to realize bottom-up consultation and updating through which defining sustainable territorial development strategies and plans.…”