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Digital empowerment for green governance: digital economy, public environmental concern, and urban industrial pollution control

IMPACT SIGNAL83/100
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Information from the abstract

The digital economy (DE) is a nascent economic model with the potential to mitigate urban industrial pollution (UIP) while encouraging high-quality economic expansion. This paper utilized panel data from 258 Chinese cities and employed the fixed-effects model, the mechanism test model, panel threshold model, and the spatial Durbin model to undertake an empirical investigation into the DE on UIP emissions. The research outcomes suggest that developing the DE has a positive influence on UIP reduction and that the effect of the DE on UIP reduction varies significantly across regions with different levels of industrial development, digital infrastructure, and environmental regulatory intensity. Further examination shows that the DE can reduce UIP by promoting public environmental concern and green technology innovation. Additionally, when the DE is used as a threshold variable, the DE’s impact on UIP emissions exhibits a nonlinear double-threshold effect, with two key turning points of 0.0921 and 0.5515, which constitute a three-stage model of “weak effect—strong effect—weak effect”. When human resource leve is used as a threshold variable, the impact of the digital economy on reducing urban industrial pollution is gradually increasing and exhibits a nonlinear single threshold effect. Under different geographical and economic distance spatial weight matrices, the DE’s development has a substantial negative spatial spillover effect on UIP emissions. That is, developing the local DE can directly reduce local UIP and significantly suppress UIP in neighboring areas indirectly through information sharing and technology diffusion. The findings of this study provide important management insights for government managers to advance environmental governance and promote green development.

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Why this record is monitored

This record has an Impact Signal of 83/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.

Related topics: Energy, Environment, Economic Growth · Recycling and Waste Management Techniques · Environmental Sustainability in Business

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Thai researcher and institutional participation

Yize Li · Dhurakij Pundit University

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Data limitations

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