EconPapers    
Economics at your fingertips  
 

Spatial Analysis to Investigate the Relationship Between Tourism and Wellbeing in Italy

Najada Firza (najada.firza@uniba.it), Laura Antonucci, Corrado Crocetta, Francesco Domenico d’Ovidio and Alfonso Monaco
Additional contact information
Najada Firza: University of Bari “Aldo Moro”
Laura Antonucci: University of Foggia
Corrado Crocetta: University of Bari “Aldo Moro”
Francesco Domenico d’Ovidio: University of Bari “Aldo Moro”
Alfonso Monaco: Università degli Studi di Bari Aldo Moro

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2024, vol. 175, issue 3, No 14, 1027-1043

Abstract: Abstract The level and variety of services offered by tourist destinations are intricately linked to the overall health and condition of its area. We would like to investigate the existence of a possible connection between tourism and the social, economic, and environmental well-being of a territory. The tourism industry can improve the general well-being of a specific area by promoting consumption, reducing the income gap, and improving infrastructures. However, the well-being of the territory through enhancing the specific features of the local context and its factors of excellence can also influence tourism. In this context, we applied Machine Learning methods to investigate the relationship between tourism and well-being in Italy. The analysis used Italian BES indicators at the provincial level, referred to a time window of 17 years (2004–2020). We developed a Machine Learning algorithm based on a hybrid (unsupervised and supervised) approach to study 51 well-being indexes and 9 tourism indicators. We found a close connection (80% of accuracy) between tourism and well-being. We also selected a group of tourism indicators that have a strong effect on this connection. Using eXplainable Artificial Intelligence (XAI) methods, we detected that tourism in low season periods ranks first for importance followed by the spread of farms business and urban green areas density. Our research suggests that improved social, economic, environmental, and health well-being can positively spill over the effect on tourism arrivals and revenues in the long period.

Keywords: Well-being; Tourism; Machine learning; eXplainable Artificial Intelligence (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11205-023-03234-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:soinre:v:175:y:2024:i:3:d:10.1007_s11205-023-03234-2

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11135

DOI: 10.1007/s11205-023-03234-2

Access Statistics for this article

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement is currently edited by Filomena Maggino

More articles in Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement from Springer
Bibliographic data for series maintained by Sonal Shukla (sonal.shukla@springer.com) and Springer Nature Abstracting and Indexing (indexing@springernature.com).

 
Page updated 2025-01-12
Handle: RePEc:spr:soinre:v:175:y:2024:i:3:d:10.1007_s11205-023-03234-2