Francesco Chiaradia

Mr. Francesco Chiaradia

Business Studies, Roma Tre University, Rome, Lazio, Italy
orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 October 2024 in Sustainability
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Journal Article
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Francesco ChiaradiaFrancesco Chiaradia
Francesco Chiaradia
Keti LeloKeti Lelo
Keti Lelo
Salvatore MonniSalvatore Monni
Salvatore Monni
Federico TomassiFederico Tomassi
Federico Tomassi
This paper aims to assess the proximity of urban services through the lens of the 15 min city concept, using the Municipality of Rome as a case study. The question of whether Rome qualifies as a 15 min city is explored by examining proximity in terms of the “intensity” of urban services accessible within a 15 min walking or cycling distance. A simple model, based on GIS techniques, is implemented to measure proximity to urban services at the neighbourhood level. Furthermore, the proximity levels in urban areas characterised by similar socioeconomic conditions, referred to as the “seven cities” of Rome, are analysed to identify potential inequalities. Our analysis shows that the dense and walkable Rome known by tourists is not the place most Romans live in.

16 September 2024 in Preprints.org
Verified
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Keti LeloKeti Lelo
Keti Lelo
Francesco ChiaradiaFrancesco Chiaradia
Francesco Chiaradia
Salvatore MonniSalvatore Monni
Salvatore Monni
Federico TomassiFederico Tomassi
Federico Tomassi
This paper aims to assess the proximity of urban services through the lens of the 15-minute city concept, using the Municipality of Rome as a case study. The question of whether Rome qualifies as a 15-minute city is explored by examining proximity in terms of the "intensity" of urban services accessible within a 15-minute walking or cycling distance. A simple model, based on GIS techniques, is implemented to measure proximity to urban services at the neighborhood level. Furthermore, proximity levels in urban areas characterized by similar socioeconomic conditions, referred to as the "seven cities," are analyzed to identify potential inequalities.

21 October 2026 in Preprints.org
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Preprint
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Francesco ChiaradiaFrancesco Chiaradia
Francesco Chiaradia
LMLuigia Marchesani
Luigia Marchesani
Katarzyna Chudy-LaskowskaKatarzyna Chudy-Laskowska
Katarzyna Chudy-Laskowska
TPTeresa Piecuch
Teresa Piecuch
NANAJIBA EL IDRISSI EL AMRANI
NAJIBA EL IDRISSI EL AMRANI
MTManuela Tvaronaviciene
Manuela Tvaronaviciene
Renewable energy sources are central to decarbonization, and social support for their expansion is linked to how citizens understand and evaluate the energy transition. This study examines attitudes towards Renewable Energy Sources (RES) among 408 Generation Z respondents in Italy, Lithuania, Morocco and Poland, providing the possibility to compare different energy contexts, while using a common questionnaire on the same attitudinal dimensions across samples. Country-specific OLS regressions with forward variable selection were used to analyse associations between attitudes towards RES and a set of cognitive, evaluative and behavioural measures. Climate-change importance is the only correlate appearing in all four final models, while the other selected correlates differ across countries. The results therefore point to a common climate-related association within otherwise country-specific patterns in Generation Z attitudes towards renewable energy. By applying a common questionnaire and the same modelling strategy to four Generation Z samples, the study provides a structured comparison of RES attitudes across contrasting national energy contexts. This design makes it possible to examine which associations recur across the four samples and which appear only in particular specifications.

31 October 2026 in Sustainability
Verified
Journal Article
Open access
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Keti LeloKeti Lelo
Keti Lelo
Francesco ChiaradiaFrancesco Chiaradia
Francesco Chiaradia
Youth exclusion from employment, education and training is a challenge to social sustainability because it limits participation and may reinforce territorial inequalities. This study examines the spatial structure of young people not in employment, education or training (NEET) across 208 Nomenclature of Territorial Units for Statistics level 2 (NUTS 2) regions in 21 European Union (EU) Member States, combining spatial clustering, cluster profiling and spatial regression analysis. Queen contiguity defines the main spatial structure, while a four-nearest-neighbours matrix tests robustness, and false discovery rate (FDR) correction addresses multiple local testing. NEET rates display strong positive spatial autocorrelation, with high-NEET clusters concentrated mainly in Southern and South-Eastern Europe and low-NEET clusters predominantly in Northern and Central Europe. Hot spots are characterised by greater poverty risk, lower disposable income, weaker adult educational attainment, lower service establishment intensity and lower population density. Spatial regression prefers a spatial error model (SEM): poverty risk and low educational attainment are positively associated with NEET, while disposable income is negatively associated, and these associations remain stable under the alternative weights matrix. The findings show that youth disengagement has a clear territorial structure, linking inequalities in participation to persistent regional disparities, placing the geography of youth exclusion within the social sustainability debate.

1 October 2026 in Preprints.org
Verified
Preprint
Open access
PDF file
Francesco ChiaradiaFrancesco Chiaradia
Francesco Chiaradia
Keti LeloKeti Lelo
Keti Lelo
Youth exclusion from employment, education and training is a challenge to social sustainability because it limits participation and may reinforce territorial inequalities. This study examines the spatial structure of young people not in employment, education or training (NEET) across 208 Nomenclature of Territorial Units for Statistics level 2 (NUTS 2) regions in 21 EU Member States, combining spatial clustering, cluster profiling and spatial regression analysis. Queen contiguity defines the main spatial structure, while a four-nearest-neighbors matrix tests robustness and false discovery rate (FDR) correction addresses multiple local testing. NEET rates display strong positive spatial autocorrelation, with high-NEET clusters concentrated mainly in Southern and South-Eastern Europe and low-NEET clusters predominantly in Northern and Central Europe. Hotspots are characterized by greater poverty risk, lower disposable income, weaker adult educational attainment, lower service-establishment intensity and lower population density. Spatial regression prefers a spatial error model (SEM): poverty risk and low educational attainment are positively associated with NEET, while disposable income is negatively associated and these associations remain stable under the alternative weights matrix. The findings show that youth disengagement has a clear territorial structure, linking inequalities in participation to persistent regional disparities, placing the geography of youth exclusion within the social-sustainability debate.