Akademik Məlumat İdarəetmə Sistemi
Sustainable Cities and Society, vol.132, 2025 (SCI-Expanded, Scopus)
Significant disparities in economic structure and environmental governance between urban centers and boundary areas underscore the need to explore spatially differentiated carbon reduction (CR) mechanisms enabled by the digital economy (DE). Leveraging panel data from 279 Chinese cities (2011–2022), this study employs machine learning models, SHapley Additive exPlanations (SHAP), and econometric analysis to dissect the heterogeneous CR effects of DE subsystems across urban functional zones. Results reveal a pronounced “central effect”, where DE-driven carbon mitigation is substantially stronger in urban centers than in boundary areas. Key drivers include telecommunications development (TDI) and digital finance (DFI), contributing 0.76 and -0.19 to central effect of CR, respectively, while internet penetration (IPI) and digital talent (DTI) exhibit limited impacts. Notably, resource-based cities and regions at lower administrative tiers benefit disproportionately from DE's CR potential, whereas high-innovation cities show diminished spatial disparities due to balanced digital adoption. These findings challenge the homogeneous treatment of DE in existing literature and provide actionable insights for policymakers and corporate strategists to design spatially targeted green policies. By aligning digital infrastructure investments with regional industrial characteristics and prioritizing DFI-TDI synergies, cities can amplify DE's role in achieving climate goals while addressing core-periphery inequities.