Annamaria Porreca1, Salvador Cruz Rambaud2, Francesca Scozzari1, Marta Di Nicola3. 1. Department of Economics, G. d'Annunzio University of Chieti-Pescara, Pescara, Italy. 2. Department of Economics and Business, Universidad de Almería, La Cañada de San Urbano, s/n, 04120, Almería, Spain. scruz@ual.es. 3. Department of Medical Oral Science and Biotechnology, G. d'Annunzio University of Chieti-Pescara Chieti, Chieti, Italy.
Abstract
OBJECTIVES: Recently, the Italian Institute of Statistics (ISTAT) and the National Council for Economy and Labor (CNEL) have proposed a measure for the equitable and sustainable well-being called the BES ("Benessere Equo e Sostenibile"). This paper aims to propose an original application of the fuzzy k-means approach to providing an analysis of the Italian regions according to their BES. METHODS: The fuzzy k-means algorithm was used for clustering the Italian regions according to BES data 2015. Afterwards, a principal component analysis was conducted to show and interpret the results. RESULTS: There is a clear difference between the regions of the North and the South. The only exceptions are represented by Lazio and Abruzzo, which belong to both groups with almost equal degrees of truth. Moreover, Trentino-Alto Adige and Valle d'Aosta exhibit the best condition, whilst Molise is the worst region. CONCLUSIONS: This study reveals that some Italian regions are in a state of backwardness regarding health, environment, minimum economic conditions, subjective well-being, education, employment conditions, social relationships, and working conditions. Therefore, institutions should consider local policies to address these issues.
OBJECTIVES: Recently, the Italian Institute of Statistics (ISTAT) and the National Council for Economy and Labor (CNEL) have proposed a measure for the equitable and sustainable well-being called the BES ("Benessere Equo e Sostenibile"). This paper aims to propose an original application of the fuzzy k-means approach to providing an analysis of the Italian regions according to their BES. METHODS: The fuzzy k-means algorithm was used for clustering the Italian regions according to BES data 2015. Afterwards, a principal component analysis was conducted to show and interpret the results. RESULTS: There is a clear difference between the regions of the North and the South. The only exceptions are represented by Lazio and Abruzzo, which belong to both groups with almost equal degrees of truth. Moreover, Trentino-Alto Adige and Valle d'Aosta exhibit the best condition, whilst Molise is the worst region. CONCLUSIONS: This study reveals that some Italian regions are in a state of backwardness regarding health, environment, minimum economic conditions, subjective well-being, education, employment conditions, social relationships, and working conditions. Therefore, institutions should consider local policies to address these issues.
Keywords:
BES; Fuzzy k-means; Inequalities; Italian regions; Well-being