デジタル・インテリジェント統合と都市群建設用地の低炭素転換：建設用地炭素排出強度からの空間計量学的証拠

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Spatial econometric methods for assessing low-carbon transition policies, with attention to spillover effects.

🏢実務担当者:Insights for urban planners and regional developers on the limits of digital solutions for carbon reduction.

🏛政策担当者:Evidence for designing regional carbon reduction policies that account for cross-city spillovers and industrial lock-in.

Urban low-carbon transition is increasingly shaped by the interaction between digital infrastructure, intelligent applications, land-space allocation, and regional governance. Existing studies have mainly examined whether the digital economy or smart-city development can reduce emissions, but less attention has been paid to the coordination between digitalization and intelligentization, the carbon cost of digital infrastructure, and the spatial consequences of local gains. This research defines digital–intelligent integration as the coupling coordination between digitalization and intelligentization subsystems. Using panel data for 39 prefecture-level cities in the Middle Reaches of the Yellow River Urban Agglomeration from 2013 to 2022, it applies Global Moran’s I, a spatial Durbin model, partial-derivative effect decomposition, alternative spatial weight matrices, alternative dependent variable tests, and multidimensional heterogeneity analysis. The own-city coefficient of digital–intelligent integration in the carbon-efficiency model is positive (0.0282, p < 0.05), whereas the spatial-equilibrium direct effect is statistically insignificant. These quantities are not short- and long-run estimates: the former is a conditional model coefficient, while the latter incorporates spatial feedback. The indirect effect on neighboring carbon efficiency is negative and remains negative under contiguity, economic-distance, and geo-economic nested matrices. Under an otherwise identical fixed-effects specification, digital–intelligent integration lowers local construction-land carbon intensity but raises neighboring intensity. The structural estimates further show that local conversion is weaker in industrially and energy-intensive cities. Digital–intelligent integration should therefore be interpreted as a governance capacity rather than a net-carbon technology; its regional effect depends on industrial lock-in, infrastructure-energy demand, and cross-city responsibility sharing.

• openalex https://doi.org/10.3390/su18168510first seen 2026-08-22 04:53:39