Does Digital-Intelligence Contribute to Carbon Emission Reduction? New Insights from China

Digital-intelligence plays an important role in transforming the energy consumption structure and promoting the emission reduction process. To explore the relationship between digital-intelligence and regional carbon emissions, we assume that there is a differential impact in carbon emission reduction effects, given the obvious differences in regional green technology innovation during the development of digital-intelligence in China. Thus, we systematically construct a new digital-intelligence system definition and include the heterogeneous threshold of green technology innovation in the relationship of the impact of digital-intelligence on carbon emissions by using a nonlinear dynamic threshold model. The results show that the development of regional digital-intelligence in China exhibits a relatively stable upward trend, and there is heterogeneity among regions. Interestingly, there is a significant heterogeneous threshold effect from green technology innovation between digital-intelligence and carbon emissions. A lower level of green technology innovation will increase the carbon emission effect of digital-intelligence to a certain extent, but when green technology innovation increases and exceeds a threshold, digital-intelligence is able to dramatically inhibit regional carbon emissions. Our research answers the question of how to achieve digital-intelligence transformation through green technology innovation and reduce total regional carbon emissions and provides new insights for developing countries to curb carbon emissions.

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Publication Details

Journal
SAGE Open
Published
2024-10-01
DOI
https://doi.org/10.1177/21582440241304462
Citations
8
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
9.03
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article

Does Digital-Intelligence Contribute to Carbon Emission Reduction? New Insights from China

Shuming Liang, Shuaishuai Geng, Jian Hou, Yao Li et al.
8 citations
SAGE Open
Energy, Environment, Economic Growth
9.03
article

Does Digital-Intelligence Contribute to Carbon Emission Reduction? New Insights from China

Shuming Liang, Shuaishuai Geng, Jian Hou, Yao Li, Wei Kang
article en
8 citations

Abstract

Digital-intelligence plays an important role in transforming the energy consumption structure and promoting the emission reduction process. To explore the relationship between digital-intelligence and regional carbon emissions, we assume that there is a differential impact in carbon emission reduction effects, given the obvious differences in regional green technology innovation during the development of digital-intelligence in China. Thus, we systematically construct a new digital-intelligence system definition and include the heterogeneous threshold of green technology innovation in the relationship of the impact of digital-intelligence on carbon emissions by using a nonlinear dynamic threshold model. The results show that the development of regional digital-intelligence in China exhibits a relatively stable upward trend, and there is heterogeneity among regions. Interestingly, there is a significant heterogeneous threshold effect from green technology innovation between digital-intelligence and carbon emissions. A lower level of green technology innovation will increase the carbon emission effect of digital-intelligence to a certain extent, but when green technology innovation increases and exceeds a threshold, digital-intelligence is able to dramatically inhibit regional carbon emissions. Our research answers the question of how to achieve digital-intelligence transformation through green technology innovation and reduce total regional carbon emissions and provides new insights for developing countries to curb carbon emissions.

SAGE OpenVol. 14(4)
Xiamen University (CN), Henan Agricultural University (CN)
Openalex Percentile: Top 3%
Energy, Environment, Economic Growth
9.03
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Does Digital-Intelligence Contribute to Carbon Emission Reduction? New Insights from China — Shuming Liang, Shuaishuai Geng, et al. · SAGE Open (2024) | TGRS Research Map | TGRS