← 論文一覧に戻る

マレーシアにおけるAI活用ESG報告と企業の経済的成果

Artificial Intelligence-Enabled ESG Reporting and Firm Economic Outcomes in Malaysia (原題)

Chua Shang Hu, Dr Chua Chong Keow

Computer and decision making.📚 査読済 / ジャーナル2026-09-30#AI×ESG経営インパクト: 資金調達対象セクター: cross_sector
DOI: 10.1922/comdem.v3i2s.18695
原典: https://doi.org/10.1922/comdem.v3i2s.18695
📄 PDF

🤖 gxceed AI 要約

日本語

本論文は、AI支援型ESG報告が企業の収益性・企業価値・資本コストに与える影響を分析するマレーシア固有のフレームワークを提案する。AI能力を自動データ取得・分析高度化・保証支援・トレーサビリティ・ガバナンスの多次元構成として捉え、報告品質とステークホルダー信頼を媒介変数とする。ガバナンス品質がこの経路を強化し、グリーンウォッシング・モデル不透明性・データ管理の弱さを境界条件として組み込む。ブルサ・マレーシア上場企業を対象に、機械支援コンテンツ分析と媒介・交互作用検証を含む再現可能な実証設計を提示する。

English

This paper proposes a Malaysia-specific framework linking AI-enabled ESG reporting to profitability, firm value, and cost of capital. It treats AI capability as a multidimensional reporting construct (automated capture, analytics, assurance support, traceability, governance), with reporting quality and stakeholder trust as mediators and governance quality as a moderator. Greenwashing risk, model opacity, and weak data controls are modeled as boundary conditions. A reproducible archival design for Bursa Malaysia Main Market firms is specified using machine-assisted content analysis, mediation and interaction tests, and robustness checks.

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

新興国におけるAI×ESG報告の枠組みは、SSBJ基準や有報での保証・ガバナンス要件を検討する日本企業にとっても、AI導入時の情報統制や第三者保証の設計に示唆を与える。特にグリーンウォッシング抑制とモデル透明性の境界条件は、日本でのAI活用ESG開示の内部統制整備に直結する。

In the global GX context

The framework speaks directly to ISSB/CSRD-era debates on assurance readiness and AI governance in sustainability disclosure, extending the discussion to an emerging-market reform context (Bursa Malaysia). Its treatment of greenwashing risk and model opacity as boundary conditions adds a governance lens often missing from AI-ESG literature. It offers a transferable empirical protocol for jurisdictions undergoing mandatory sustainability-reporting transitions.

👥 読者別の含意

🔬研究者:Provides a testable, multidimensional AI-reporting construct with mediation/moderation hypotheses and a reproducible archival protocol for emerging-market ESG research.

🏢実務担当者:Guides sustainability teams on pairing AI-enabled reporting with credible information governance, human oversight, and external assurance to realize economic value.

🏛政策担当者:Highlights the need for assurance and AI-governance safeguards in mandatory sustainability-reporting regimes to prevent greenwashing and model-opacity risks.

📄 Abstract（原文）

AI can help with gathering, validating, analyzing, and communicating environmental, social, and governance (ESG) data, but only if the economic benefits don't simply come from speeding up corporate disclosure. The study proposes a framework specific to the case of Malaysia to connect AI-supported ESG reporting with profitability, firm value, and cost of capital. It combines stakeholder theory, signalling theory, the resource-based view, and legitimacy theory to describe value-creating and risk-amplifying paths. AI capability is viewed as a multi-dimensional reporting capability that includes automated data capture, analytical sophistication, assurance support, traceability, and governance. The framework suggests that the quality of reporting and the trust of stakeholders lie in the middle as a mediator between AI-driven reporting and economic results, and that the quality of governance enhances this pathway. The risk of greenwashing, model opacity, and weak data controls are considered as boundary conditions instead of being omitted implementation details. For Bursa Malaysia Main Market companies, a reproducible design of the archival design is specified using annual and sustainability reports, machine-assisted content analysis, ESG and accounting data, firm and year fixed effects, mediation tests, interaction models, and robustness tests on selection and endogeneity. The study provides a measurable construct, a set of testable hypotheses, and an empirical protocol appropriate for an emerging-market context that is rapidly undergoing sustainability-reporting reform. It also explains that AI is just as much an economic value if it is supported by credible information governance, human oversight, and external assurance.

🔗 Provenance — このレコードを発見したソース

🔔 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。