Drivers of heterogeneous artificial intelligence in corporate energy transition
企業のエネルギー転換における異種人工知能の推進要因 (AI 翻訳)
Wei Shan, Renbo Shi, Changfeng Cheng, Tailai Xu
🤖 gxceed AI 要約
日本語
本研究は、生産志向AIと研究開発志向AIの2種類のAIが企業のエネルギー転換に与える影響を、2010～2023年の中国A株上場企業4,416社のパネルデータを用いて分析。生産志向AIはエネルギー効率向上を通じて、研究開発志向AIは技術革新と効率向上を通じてクリーンエネルギー消費を促進することを実証した。
English
This study examines how production-oriented AI and R&D-oriented AI differentially impact corporate energy transition using panel data of 4,416 Chinese listed firms from 2010 to 2023. Production-oriented AI enhances energy transition via improved energy efficiency, while R&D-oriented AI promotes it through both energy technology innovation and efficiency gains.
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
中国企業のAI活用によるエネルギー転換の実証分析は、日本のGX推進策（特に省エネ・技術革新）への示唆を含む。ただし、中国固有の政策環境が反映されており、日本への直接適用には注意が必要。
In the global GX context
This empirical evidence on AI-driven energy transition in Chinese firms offers valuable insights for global policymakers and firms seeking to leverage AI for decarbonization. The distinction between production-oriented and R&D-oriented AI provides a framework applicable to other contexts, though institutional differences should be considered.
👥 読者別の含意
🔬研究者:Provides a novel taxonomy of AI types and their distinct mechanisms in corporate energy transition, useful for further empirical studies.
🏢実務担当者:Highlights how different AI investments (production vs. R&D) can drive energy efficiency and clean energy adoption, guiding corporate strategy.
🏛政策担当者:Offers evidence that AI can accelerate energy transition, suggesting policies that encourage both operational and innovation-oriented AI adoption.
📄 Abstract（原文）
As global companies pursue sustainable development goals, corporate energy transition (ET) has emerged as a critical focus. Artificial intelligence (AI) plays a pivotal role in this process through its integration capabilities. This study introduces a novel taxonomy distinguishing between production-oriented AI and R&D-oriented AI, and examines their differential impacts on ET using panel data from 4416 A-share listed Chinese firms from 2010 to 2023. The findings reveal that both types of AI facilitate the shift toward clean energy consumption, albeit via distinct mechanisms: production-oriented AI enhances ET by improving energy efficiency, while R&D-oriented AI promotes ET by driving energy technology innovation and improving energy efficiency. Heterogeneity analysis further demonstrates that AI-driven ET is more pronounced among firms with higher environmental attention, more competitive industries, and firms located in non-resource-based cities. This study provides strategic guidance for firms seeking to integrate AI into their ET processes and offers a theoretical foundation for policymakers aiming to accelerate ET initiatives and advance sustainable development goals.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.techfore.2026.124819first seen 2026-07-24 05:56:48
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。