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ESG Integration in Financial Accounting: Comparative Evidence and Policy Implications

財務会計におけるESG統合:比較証拠と政策的含意 (AI 翻訳)

Cruift Andika

Sinergi International Journal of Accounting and Taxationプレプリント2025-08-31#ESGOrigin: Global
DOI: 10.61194/ijat.v3i3.863
原典: https://doi.org/10.61194/ijat.v3i3.863

🤖 gxceed AI 要約

日本語

本レビューは、ESG報告の財務会計への統合に関する進展、課題、政策的含意を整理。IFRS S1/S2、GRI、SASB等の枠組みは比較可能性を高めるが、地域・業種間の不整合が残る。AIやブロックチェーンによるデータ完全性向上とグリーンウォッシュ抑制の可能性、包括的なESG開示と財務パフォーマンスの正の関連を示す。標準化と規制強化の必要性を強調。

English

This narrative review synthesizes trends, challenges, and policy implications of ESG integration into financial accounting. Frameworks like IFRS S1/S2, GRI, and SASB improve comparability but inconsistencies persist across regions and industries. Technological tools (AI, blockchain) can enhance data integrity and mitigate greenwashing. Empirical evidence shows a positive link between comprehensive ESG disclosure and financial performance. The study calls for standardization, regulatory enforcement, and interdisciplinary collaboration.

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基準の公表や有報でのサステナビリティ情報開示義務化が進む中、本レビューはIFRS S1/S2等の国際枠組みとの整合性やAI・ブロックチェーン活用の可能性を示しており、実務者・規制当局にとって参考となる。

In the global GX context

As ISSB standards (IFRS S1/S2) gain global traction and jurisdictions like the EU (CSRD) and US (SEC) move toward mandatory disclosure, this review provides a comparative overview of frameworks, technological enablers, and the link to financial performance, offering insights for standard-setters and practitioners worldwide.

👥 読者別の含意

🔬研究者:Provides a structured synthesis of ESG integration themes and a conceptual model for further empirical testing.

🏢実務担当者:Highlights key frameworks (IFRS S1/S2, GRI, SASB) and technological tools (AI, blockchain) to improve disclosure quality and comparability.

🏛政策担当者:Emphasizes the need for standardized reporting and regulatory enforcement to bridge regional and sectoral gaps.

📄 Abstract(原文)

The integration of Environmental, Social, and Governance (ESG) reporting into financial accounting has accelerated as stakeholders demand greater transparency and accountability. This study synthesizes evolving trends, challenges, and policy implications of ESG disclosure, emphasizing its comparative and interdisciplinary contributions. Using a narrative review approach, literature from Scopus, Web of Science, and Google Scholar was analyzed through targeted keywords such as ESG reporting, sustainability accounting, financial performance, and regulatory frameworks. Only peer-reviewed studies from the past decade with financial relevance were included. The review identifies four major themes: (1) standardization and frameworks, (2) technology and innovation, (3) sectoral and regional perspectives, and (4) financial performance and market impact. A conceptual model was developed to illustrate the relationships among these themes. Results show that while frameworks such as IFRS S1/S2, GRI, and SASB improve comparability, inconsistencies remain across regions and industries. Technological tools—particularly artificial intelligence and blockchain—offer potential to enhance data integrity and mitigate greenwashing. Sectoral variations highlight the importance of industry-specific approaches, and comparative analyses indicate that developed economies exhibit stronger ESG reporting practices than emerging markets. Empirical evidence reveals a positive association between comprehensive ESG disclosure and improved financial performance, including profitability and investor confidence. The study concludes that advancing standardized reporting, strengthening regulatory enforcement, and fostering interdisciplinary collaboration are essential to bridge current gaps. Overall, ESG integration within financial accounting is pivotal to aligning corporate strategies with sustainability objectives and ensuring long-term economic resilience.

🔗 Provenance — このレコードを発見したソース

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。