Financial Intelligence and Environmental Sustainability: A Literature Review on Economic Modeling for Clean Energy Manufacturing
金融インテリジェンスと環境持続可能性：クリーンエネルギー製造のための経済モデリングに関する文献レビュー (AI 翻訳)
Tonimi Rotimi-Ojo, Juliana Kissiwah Somuah, Ndidi Ezeakunne, Blanche B. Yougang
🤖 gxceed AI 要約
日本語
本レビューは、太陽光、風力、EVバッテリー、グリーン水素分野におけるクリーンエネルギー製造への金融インテリジェンスと経済モデリングの応用を検討。LCOE、DCF、リアルオプション分析、モンテカルロシミュレーション、ESG統合予測などのツールを評価し、グリーンボンドやサステナビリティ・リンク・ローンなどのESG連動型金融商品が資本フローと開示基準を変革していることを示す。米国、EU、中国、新興国の政策枠組みを比較し、AI統合やESG指標の相互運用性に関する研究ギャップを特定。
English
This review examines the application of financial intelligence and economic modeling to clean energy manufacturing in solar, wind, EV batteries, and green hydrogen. It evaluates tools like LCOE, DCF, real options, Monte Carlo simulations, and ESG-integrated forecasting, highlighting how ESG-linked instruments (green bonds, sustainability-linked loans) and frameworks (TCFD, SASB, GRI) reshape capital flows and disclosure standards. Comparative policy analysis across the US, EU, China, and emerging economies reveals strengths and gaps in data availability, standardization, and financial innovation, identifying research needs in AI integration and ESG metric interoperability.
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、GX推進法に基づくクリーンエネルギー製造の国内立地が急務。本レビューが示す金融ツールやESG連動型商品の知見は、日本の製造業がグローバルな開示基準（SSBJ等）に対応しつつ、投資家向けに脱炭素戦略を訴求する際の参考となる。
In the global GX context
This review provides a comprehensive mapping of financial tools and ESG frameworks relevant to clean energy manufacturing, a sector critical to global decarbonization. It offers a comparative lens across major economies, which is valuable for understanding how disclosure standards (TCFD, ISSB) and transition finance mechanisms are evolving to support industrial transformation.
👥 読者別の含意
🔬研究者:Identifies research gaps in AI integration and ESG metric interoperability for clean energy manufacturing finance.
🏢実務担当者:Provides a toolkit of financial models and ESG-linked instruments for corporate sustainability teams to evaluate clean energy investments.
🏛政策担当者:Highlights comparative policy frameworks and the role of financial intelligence in aligning industrial policy with climate goals.
📄 Abstract（原文）
As the global energy transition accelerates, clean energy manufacturing has emerged as a strategic priority for achieving climate goals, industrial competitiveness, and environmental justice. This review examines how financial intelligence and economic modeling frameworks are being applied to advance sustainable investments across solar photovoltaics, wind energy, electric vehicle (EVcrip) batteries, and green hydrogen sectors. It explores a range of financial tools—including levelized cost of energy (LCOE), discounted cash flow (DCF), real options analysis, Monte Carlo simulations, and ESG-integrated forecasting—and evaluates their effectiveness in aligning profitability with decarbonization and circular economy goals. The study highlights how ESG-linked instruments such as green bonds, sustainability-linked loans, and regulatory frameworks (e.g., TCFD, SASB, GRI) are reshaping capital flows and disclosure standards globally. Comparative analysis of policy frameworks in the U.S., EU, China, and emerging economies reveals strengths and challenges in data availability, standardization, and financial innovation. Key research gaps are identified in AI integration, ESG metric interoperability, and long-term impact measurement. This review concludes that advancing clean energy manufacturing requires interdisciplinary approaches that blend finance, data science, and environmental systems thinking. Financial intelligence, when aligned with sustainability and inclusive policy design, offers a critical pathway to a climate-resilient, low-carbon industrial future.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.36348/merjem.2025.v05i03.003first seen 2026-05-05 19:07:46
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。