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人工知能、企業の社会的責任、サステナビリティ報告コンプライアンス:企業パフォーマンスの統合モデル

Artificial Intelligence, Corporate Social Responsibility, and Sustainability Reporting Compliance: An Integrated Model of Firm Performance (原題)

Khurram Ashfaq, Kainat, Nasir Abbas*, Arooj Naz

International Journal of Business and Management Sciences📚 査読済 / ジャーナル2026-10-13#AI×ESG対象セクター: cross_sector
DOI: 10.63468/ijbms.7.8.11
原典: https://doi.org/10.63468/ijbms.7.8.11

🤖 gxceed AI 要約

日本語

サステナビリティ報告コンプライアンスとAIの知的活用能力が企業業績に与える影響を、CSRパフォーマンスの媒介とAI統合型リーダーシップの調整効果を通じて検証した研究。PLS-SEMによる356件の分析から、報告コンプライアンスとAI能力はいずれもCSRパフォーマンスを高め、CSRパフォーマンスが企業業績を押し上げることが示された。さらにAI支援型リーダーシップがこれらの関係を強める調整効果を持つことを明らかにし、報告プロセス・AIツール・AI主導のリーダーシップを統合することの重要性を強調している。

English

This study examines how sustainability reporting compliance and AI intellectual capability affect firm performance, mediated by CSR performance and moderated by AI-integrated leadership. Using PLS-SEM on 356 observations, it finds that both reporting compliance and AI capability improve CSR performance, which in turn boosts firm performance. AI-supported leadership significantly strengthens these relationships, highlighting the value of embedding reporting processes, AI tools, and AI-driven leadership together.

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

SSBJ基準・有価証券報告書でのサステナ開示義務化が進む日本企業にとって、報告コンプライアンスを業績向上につなげるAI活用とリーダーシップの役割は実務的示唆が大きい。統合報告書や投資家対応の高度化を検討する企業の内部体制設計に資する。

In the global GX context

As ISSB/CSRD-aligned disclosure becomes mandatory worldwide, this paper links reporting compliance to firm performance through CSR and AI capability, offering evidence that disclosure infrastructure and AI adoption jointly create value. It adds to the global debate on whether sustainability reporting is a compliance cost or a performance driver.

👥 読者別の含意

🔬研究者:AI能力と報告コンプライアンスがCSRを介して業績に至る調整媒介モデルを提示し、AI×ESG研究の実証的枠組みを提供する。

🏢実務担当者:サステナ報告体制の整備とAIツール導入をリーダーシップの下で統合することがCSR成果と業績向上に寄与することを示唆する。

🏛政策担当者:開示義務化が企業のCSRパフォーマンスを高める可能性を示し、AI活用支援策と開示制度設計の連動を検討する材料となる。

📄 Abstract(原文)

This study investigates how the compliance to sustainability reporting and the intellectual capability of artificial intelligence (AI) affect the corporate performance of the companies, with the mediation of corporate social responsibility (CSR) performance and the moderation of AI-integrated leadership. The approach of this study was quantitative research with partial least squares structural equation modeling (PLS-SEM) and the number of observations used was 356. The results suggest that both sustainability reporting compliance and the intellectual capacity of AI have a positive impact on CSR performance and that CSR performance positively affects firm performance. In addition, CSR performance plays an important role in the relationships between the compliance of sustainability reporting and firm performance, and between the intellectual ability of AI and firm performance. The results also show that the relationships between sustainability reporting compliance and CSR performance and between the intellectual capability of AI and CSR performance are significantly moderated by the AI-supported leadership. The results underscore the significance of embedding sustainability reporting processes, AI tools, and AI-driven leadership to boost CSR performance and improve organizational results. The study builds upon the literature by introducing a combined moderated mediation model that elucidates the double mediated effect of sustainability practices and AI-related capabilities on firm performance. The study is important because it introduces a combined and moderated mediated model that contributes to the existing literature by explaining the double moderated mediated effect of sustainability practices and AI-related capabilities on firm performance. The results have implications for managers and policy makers looking to enhance corporate sustainability, responsible business practices and organizational performance.

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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。