Smartness and sustainability are undoubtedly closely intertwined issues gaining growing attention from both practitioners and policy makers. Sustainability assessment is a major challenge due to the many multidisciplinary aspects involved, of course this makes the evaluation process complex thus hindering the effectiveness of available monitoring tools. We introduce a new methodological approach to account for the inherent uncertainty and vagueness of the involved variables by modelling a fuzzy-logic-based framework. Our approach has been tested on Italy at a provincial scale and compared with two others sustainability indexes. A correlation analysis has also been performed to assess the relationship between our ranking results and the attained quality of life scores. Our approach, differently from the traditional ones, ensures a high level of versatility that makes its use possible jointly with (or alternatively to) other existing methodologies promoted by international institutions.

“Smartness” and “sustainability” are gaining growing attention from both practitioners and policy makers. “Smartness” and “sustainability” assessments are of crucial importance for directing, in a systemic perspective, the decision-making process toward sustainability and smart growth objectives. Sustainability assessment is a major challenge due to the multidisciplinary aspects involved that make the evaluation process complex and hinder the effectiveness of available monitoring tools. To achieve the assessment objective, we introduce an enhanced fuzzy logic-based framework for handling the inherent uncertainty and vagueness of the involved variables: we apply our approach to Italy, and we compare it with two other sustainability methodologies. We also perform a correlation analysis to assess the relationship between our ranking results and the attained quality of life scores. Our approach ensures a high level of versatility that makes its use possible jointly with (or alternatively to) other existing methodologies such as the Global Sustainable Tourism Council Criteria and the United Nations World Tourism Organization destination-level indicators.

A heuristic fuzzy algorithm for assessing and managing tourism sustainability

Giacomo Di Tollo;Raffaele Pesenti
2020-01-01

Abstract

“Smartness” and “sustainability” are gaining growing attention from both practitioners and policy makers. “Smartness” and “sustainability” assessments are of crucial importance for directing, in a systemic perspective, the decision-making process toward sustainability and smart growth objectives. Sustainability assessment is a major challenge due to the multidisciplinary aspects involved that make the evaluation process complex and hinder the effectiveness of available monitoring tools. To achieve the assessment objective, we introduce an enhanced fuzzy logic-based framework for handling the inherent uncertainty and vagueness of the involved variables: we apply our approach to Italy, and we compare it with two other sustainability methodologies. We also perform a correlation analysis to assess the relationship between our ranking results and the attained quality of life scores. Our approach ensures a high level of versatility that makes its use possible jointly with (or alternatively to) other existing methodologies such as the Global Sustainable Tourism Council Criteria and the United Nations World Tourism Organization destination-level indicators.
2020
20
File in questo prodotto:
File Dimensione Formato  
AndriaetAl PrePrint.pdf

non disponibili

Descrizione: Preprint
Tipologia: Documento in Pre-print
Licenza: Accesso chiuso-personale
Dimensione 495.74 kB
Formato Adobe PDF
495.74 kB Adobe PDF   Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3714770
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 23
  • ???jsp.display-item.citation.isi??? 20
social impact