- Data, Statistics and AI for Well-Being of People and Organisations
- A cura di Luigi Fabbris, Alberto Franci, Pietro Renzi
Commercial desertification in Italy and structural characteristics of municipalities
- Agata Maria Madia Carucci
- Annamaria Fiore
- Giovanni Vannella
- © 2026 Author(s) |
- CC BY 4.0
- DOI: 10.36253/979-12-215-1062-1.49
This study investigates how Italy’s commercial desertification between 2014 and 2022 differs according to geographical areas and the demographic structure, analysing the links between key dependent variables. Central to this research is the examination of the retail sector in non-specialised stores, a cornerstone of the urban economic fabric. The decline of these businesses often serves as an early indicator of wider economic and social deterioration. Their disappearance not only restricts access to essential goods, increasing reliance on large chains and online shopping, but also triggers a cascading effect on local commerce, undermining the vibrancy of urban spaces.
- Keywords:
- Italy’s commercial desertification,
- Demographic ageing,
- Urban economy,
ISTAT, Italian National Institute of Statistics, Central Directorate for Sistan and Territorial Relations (DCST), Territorial Office - Southern Area (TSU), Italy
ARTI, Agency for Technology and Innovation of Apulia, Italy - ORCID: 0000-0001-8641-1836
University of Bari Aldo Moro, Italy - ORCID: 0000-0003-4649-1346
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Informazioni sul capitolo
Titolo del capitolo
Commercial desertification in Italy and structural characteristics of municipalities
Autori
Agata Maria Madia Carucci, Annamaria Fiore, Giovanni Vannella
Lingua
Inglese
DOI
10.36253/979-12-215-1062-1.49
Opera sottoposta a peer review
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Informazioni bibliografiche
Titolo del libro
Data, Statistics and AI for Well-Being of People and Organisations
Curatori
Luigi Fabbris, Alberto Franci, Pietro Renzi
Opera sottoposta a peer review
Numero di pagine
420
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press
DOI
10.36253/979-12-215-1062-1
ISBN Print
979-12-215-1061-4
eISBN (pdf)
979-12-215-1062-1
eISBN (xml)
979-12-215-1063-8
Collana
Applied Statistics Series