Evaluating age-friendly smart city policy design: A PMC-Index analysis of chinese provincial frameworks

The intersections of rapid demographic aging and urban digitalization present unprecedented governance challenges, yet current smart city evaluation frameworks inadequately address age-friendly policy implementation. This study addresses the critical analytical gap in evaluating age-friendly dimensions within smart city policy frameworks through development of an adapted Policy Modeling Consistency (PMC-Index) methodology. Analyzing 18 provincial-level policy documents in China (2011-2024) through integrated text mining techniques, this research examines relationships between policy text characteristics and implementation effectiveness. Statistical analysis reveals significant correlations (r = 0.83, p < 0.001) between textual features and implementation outcomes. Principal component analysis identifies three determinants of policy effectiveness: implementation mechanism sophistication (42.3% variance), resource integration capacity (28.7%), and stakeholder coordination efficiency (18.4%). The adapted framework explains 71.8% of implementation variance, substantially exceeding conventional approaches. The study links textual analysis with implementation assessment, offering empirical guidance for age-friendly smart urban governance.