Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning Approach
Culture, creativity and circularity are driving forces for the transition of cities towards sustainable development models. This contribution proposes a data-driven quantitative methodology to compute cultural performance indices of cities (C4 Index) and thus compare results derived by subjective an...
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| Format: | Article |
| Language: | English |
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Firenze University Press
2023-02-01
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| Series: | Aestimum |
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| Online Access: | https://oaj.fupress.net/index.php/ceset/article/view/13880 |
| _version_ | 1811154957385072640 |
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| author | Giuliano Poli Eugenio Muccio Maria Cerreta |
| author_facet | Giuliano Poli Eugenio Muccio Maria Cerreta |
| author_sort | Giuliano Poli |
| collection | DOAJ |
| description | Culture, creativity and circularity are driving forces for the transition of cities towards sustainable development models. This contribution proposes a data-driven quantitative methodology to compute cultural performance indices of cities (C4 Index) and thus compare results derived by subjective and objective assessment methods within the case study of the Metropolitan City of Naples. After data processing with Machine-Learning (ML) algorithms, two methods for weighting the indicators were compared: principal component analysis (PCA) and geographically weighted linear combination (WLC) with budget allocation. The results highlight similar trends among higher performance in seaside cities and lower levels in the inner areas, although some divergences between rankings. The proposed methodology was addressed to fill the research gap in comparing results obtained with different aggregation methods, allowing a choice consistent with the decision-making environment.
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| first_indexed | 2024-04-10T04:25:52Z |
| format | Article |
| id | doaj.art-30b22736878447d69cbc34be52982588 |
| institution | Directory Open Access Journal |
| issn | 1592-6117 1724-2118 |
| language | English |
| last_indexed | 2024-04-10T04:25:52Z |
| publishDate | 2023-02-01 |
| publisher | Firenze University Press |
| record_format | Article |
| series | Aestimum |
| spelling | doaj.art-30b22736878447d69cbc34be529825882023-03-10T13:41:44ZengFirenze University PressAestimum1592-61171724-21182023-02-018110.36253/aestim-13880Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning ApproachGiuliano Poli0Eugenio Muccio1Maria Cerreta2Department of Architecture, University of Naples Federico IIDepartment of Architecture, University of Naples Federico IIDepartment of Architecture, University of Naples Federico IICulture, creativity and circularity are driving forces for the transition of cities towards sustainable development models. This contribution proposes a data-driven quantitative methodology to compute cultural performance indices of cities (C4 Index) and thus compare results derived by subjective and objective assessment methods within the case study of the Metropolitan City of Naples. After data processing with Machine-Learning (ML) algorithms, two methods for weighting the indicators were compared: principal component analysis (PCA) and geographically weighted linear combination (WLC) with budget allocation. The results highlight similar trends among higher performance in seaside cities and lower levels in the inner areas, although some divergences between rankings. The proposed methodology was addressed to fill the research gap in comparing results obtained with different aggregation methods, allowing a choice consistent with the decision-making environment. https://oaj.fupress.net/index.php/ceset/article/view/13880Benchmarking cultural citiesComposite indicator(s)Machine learningUrban monitoring |
| spellingShingle | Giuliano Poli Eugenio Muccio Maria Cerreta Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning Approach Aestimum Benchmarking cultural cities Composite indicator(s) Machine learning Urban monitoring |
| title | Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning Approach |
| title_full | Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning Approach |
| title_fullStr | Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning Approach |
| title_full_unstemmed | Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning Approach |
| title_short | Circular, Cultural and Creative City Index: a Comparison of Indicators-based Methods with a Machine-Learning Approach |
| title_sort | circular cultural and creative city index a comparison of indicators based methods with a machine learning approach |
| topic | Benchmarking cultural cities Composite indicator(s) Machine learning Urban monitoring |
| url | https://oaj.fupress.net/index.php/ceset/article/view/13880 |
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