Abstract: This study proposes a composite sustainable smart city (SSC) index based on 17 indicators grouped into four dimensions and applies it to nine European cities using 2018 data. It examines how weights derived using Redundancy-Penalized Entropy Weighting (RPEW), the Analytic Hierarchy Process (AHP), and the Analytic Network Process (ANP) affect the resulting city scores and rankings. RPEW is an objective method that derives weights from entropy-based variation across cities and adjusts for redundancy among correlated indicators. AHP and ANP are judgment-based, subjective methods. AHP derives indicator and dimension priorities from pairwise comparisons within a hierarchy, while ANP accounts for interdependencies among indicators through a network structure. The pairwise judgments used for AHP and ANP in this study were collected from three domain experts. To isolate the effect of the weighting approach, the same winsorization, normalization, aggregation, and scoring procedures were applied across all three methods. Stockholm ranks first under RPEW and AHP, while Amsterdam ranks first under ANP. Spearman’s rank correlations range from 0.783 to 0.933, showing that the rankings are strongly related while still differing in the positions of some cities. Overall, the results illustrate how objective data patterns, hierarchical judgments, and indicator interdependencies can lead to different assessments of city performance.

Keywords: Sustainable Smart City, Composite Index, Redundancy-Penalized Entropy Weighting, Analytic Hierarchy Process, Analytic Network Process, Indicator Interdependence, City Ranking

Pages: 1237-1248