TOWARDS A BETTER COMPOSITE INDEX: A CASE STUDY OF SMART CITIES

Abstract

Urbanization has positioned cities as key actors in achieving sustainable development, necessitating robust tools to evaluate their performance. This study focuses on developing a reliable composite index for assessing urban sustainability, addressing the multifaceted nature of cities. An advanced methodological framework integrating Monte Carlo simulations for uncertainty analysis and variance-based Sobol sensitivity analysis rigorously assesses the reliability and variability of the index. Using 35 European cities as a case study, the research explores how methodological choices including selection of indicators, data imputation, normalization, weighting, and aggregation affect the robustness of the index. Sensitivity analysis highlights indicator selection and aggregation as key sources of variability, while also revealing that interaction effects among input factors have a greater influence on the final results than direct effects. City-specific analyses further validate the framework's applicability and emphasize the need for tailored strategies. The findings enhance composite index reliability, providing a robust foundation for informed policymaking and promoting sustainable urban development aligned with SDGs.