AI-Enhanced ESG Integration Transforming Corporate Performance for a Sustainable Economy
AI強化ESG統合が持続可能な経済のための企業業績を変革 (AI 翻訳)
Hussain K. Alagele, Nagham Hussein Neama
🤖 gxceed AI 要約
日本語
本研究はOECD3カ国を対象に、経済・ESG・AI要素がエネルギー移行に与える影響をスキル向上を通じて分析。CS-ARDLモデルを用い、2022〜2026年のパネルデータを検証。経済要因は負の影響を与えるが、スキル向上により正に転じ、環境要因は正の影響。AIは負の相関を示すが、ガバナンス要因は経済成長と正の相関。短期的な経済拡大戦略は長期的な環境・社会に悪影響を及ぼすため、統合的戦略が必要と結論。
English
This study analyzes the impacts of economic, ESG, and AI factors on energy transition in three OECD countries via skills enhancement, using CS-ARDL on 2022-2026 panel data. Economic factors negatively impact transition, but skills enhancement turns it positive; environmental factors are positive. AI shows negative correlation, while governance positively correlates with growth. Short-term economic expansion may harm long-term sustainability, necessitating a holistic strategy.
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
日本ではSSBJ開示やGX推進法に基づく移行計画が求められており、本研究成果はAI活用によるESG統合が企業業績とエネルギー移行に与える影響を示唆。スキル向上が鍵となる点は、日本の人材育成政策にも示唆を与える。
In the global GX context
Globally, this paper contributes to the discourse on integrating AI and ESG in transition finance and disclosure frameworks like ISSB and CSRD. It highlights the need for holistic strategies balancing economic growth and sustainability, relevant for policymakers and investors.
👥 読者別の含意
🔬研究者:Provides empirical evidence on the interplay of AI, ESG, and energy transition, useful for further research on policy design.
🏢実務担当者:Suggests that skills enhancement can mitigate negative impacts of economic factors on sustainability, informing corporate training and ESG integration.
🏛政策担当者:Highlights the risk of short-term economic policies undermining long-term energy transition, advocating for integrated policy approaches.
📄 Abstract（原文）
This study investigates the impacts of economic factors, environmental, social, and governance (ESG) aspects, and artificial intelligence (AI) elements on the energy transition in three OECD countries through skills enhancement. The CS-ARDL model analyzes long-term relationships and short-term dynamics in panel data, considering cross-sectional dependencies from 2022 to 2026. The results show that economic factors negatively impact the energy transition, but skills enhancement leads to a more positive outcome, while environmental factors have a positive impact. However, although economic factors and AI show negative correlations with the energy transition, governance factors show positive correlations with economic growth through skills enhancement.strategies that promote immediate economic expansion may harm long-term environmental and social impacts, negatively affecting the energy transition. Therefore, adopting a holistic strategy that integrates economic, environmental, social, and AI elements is essential for achieving economic growth.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.4018/979-8-2600-0116-5.ch001first seen 2026-07-31 05:10:49
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