Artificial Intelligence and Low-Carbon Energy Transition: From the Perspectives of Green Innovation Resilience and Green Finance
人工知能と低炭素エネルギー転換：グリーンイノベーションのレジリエンスとグリーンファイナンスの視点から (AI 翻訳)
Le Yan, Shizheng Tan, Wei Li, Mengxin Wang
🤖 gxceed AI 要約
日本語
本研究は、中国の省別パネルデータ（2013-2022年）を用いて、AIがエネルギー消費構造の低炭素転換に与える影響を実証分析。グリーンイノベーションのレジリエンスが媒介効果を持ち、グリーンファイナンスがその効果を増幅することを示した。AIと環境政策の連携強化の重要性を提言。
English
Using Chinese provincial panel data from 2013–2022, this study empirically demonstrates that AI significantly promotes the low-carbon transformation of energy consumption structures. Green innovation resilience serves as a mediating mechanism, and green finance positively moderates this relationship. The findings highlight the importance of coordinating AI development with green innovation and finance for carbon neutrality.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国におけるAIと低炭素転換の実証研究だが、日本のGX政策（AI活用とグリーンファイナンスの連携）にも示唆を与える。SSBJや企業のエネルギー戦略立案の参考となり得る。
In the global GX context
This empirical study from China offers valuable insights for the global energy transition discourse, particularly on how AI can act as a driver for structural change in energy consumption. It aligns with international initiatives like the IPCC and IEA pathways, emphasizing the role of innovation resilience and green finance.
👥 読者別の含意
🔬研究者:Provides empirical evidence on the mechanisms linking AI to energy transition, opening avenues for comparative studies across countries.
🏢実務担当者:Highlights the need to integrate AI capabilities with green innovation and finance strategies to accelerate corporate decarbonization.
🏛政策担当者:Indicates that policies promoting AI in energy sectors should be coupled with support for green innovation and financial instruments.
📄 Abstract（原文）
Achieving the low-carbon transformation of energy consumption structure is central to carbon-neutral development, yet how artificial intelligence (AI) contributes to sustained structural change remains insufficiently understood. Addressing this gap, this study examines not only whether AI facilitates the green and low-carbon transformation of energy consumption structure in China, but also through which mechanisms and under what conditions this effect is sustained. Using provincial panel data for 2013–2022, we estimate the direct effect of AI and test the mediating role of green innovation resilience and the moderating role of green finance. The results show that AI significantly promotes the low-carbon transformation of energy consumption structure. Green innovation resilience serves as an important transmission mechanism, while green finance strengthens this relationship. These findings deepen understanding of the AI-energy transition nexus and provide policy implications for effectively coordinating digital technology, green innovation, and green finance.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1177/10704965261457599first seen 2026-06-20 05:26:18
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