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 (C4 Index) thus compare results derived by subjective objective assessment methods within case study Metropolitan City Naples. After data processing with Machine-Learning (ML) algorithms, two weighting indicators were compared: principal component analysis (PCA) geographically weighted linear combination (WLC) budget allocation. The highlight similar trends among higher in seaside lower levels inner areas, although some divergences between rankings. proposed was addressed fill research gap comparing obtained different aggregation methods, allowing choice consistent decision-making environment.