The impact of digital intelligence on urban ecological efficiency and its spatial spillover effects: evidence from China.

Abstract

Digital-intelligent transformation (DIT) has become an important driver of sustainable urban development, yet its impact on urban eco-efficiency (EE) remains insufficiently understood. Using panel data for 281 prefecture-level cities in China from 2010 to 2023, this study examines the effect of DIT on urban EE, incorporating mechanism analysis, heterogeneity, and spatial effects. DIT is measured using the entropy-weight method, and urban EE is calculated based on the super-efficiency slack-based measure (Super-SBM) model. A two-way fixed effects framework, combined with mediation, moderation, and spatial econometric models, is employed for empirical analysis. The results show that DIT significantly improves urban EE, and this finding remains robust after multiple robustness checks and endogeneity treatments. The effect operates mainly through innovation-driven development and industrial structure upgrading, while human capital and fiscal transparency further strengthen this relationship. Significant heterogeneity is observed across regions, industrial structures, and environmental regulation levels, with stronger effects in northeastern and western regions, in cities with lower industrial dependence, and in areas with weaker environmental regulation. In addition, DIT generates positive spatial spillover effects, while also being associated with a potential widening of regional disparities. This study integrates DIT and urban EE into a unified analytical framework, providing new empirical evidence on their mechanisms and spatial dynamics, and offering useful implications for policy design.