gxceed
← 論文一覧に戻る

A CHRONOLOGICAL REVIEW OF THE IMPACT OF GREENWASHING ON ESG PERFORMANCE

グリーンウォッシングがESGパフォーマンスに与える影響に関する時系列レビュー (AI 翻訳)

Bushra Mohd Zaki, Siti Nur Aqilah Ab-Wahab, Hock-Ann Lee, Nik Rozila Nik Mohd Masdek, Fauziana Fauzi, Nor Harlina Abd Hamid, Heizal Hezry Omar

Advanced International Journal of Business Entrepreneurship and SMEs📚 査読済 / ジャーナル2026-06-04#ESG経営インパクト: 資金調達
DOI: 10.35631/aijbes.828001
原典: https://gaexcellence.com/aijbes/article/download/7581/6701
📄 PDF

🤖 gxceed AI 要約

日本語

本レビューは、グリーンウォッシングがESG研究と実践に与える影響を、2020年から2026年までの3つのフェーズに分けて分析した。各フェーズで焦点が開示の信頼性からAIやデジタルガバナンスへと移行していることを示し、グリーンウォッシングが報告問題だけでなく、ガバナンス、財務、規制上の課題であると結論づけている。

English

This chronological review examines greenwashing's impact on ESG research and practice across three phases from 2020 to 2026. It shows a shift from disclosure credibility to AI and digital governance, concluding that greenwashing is a governance, financial, and regulatory challenge beyond reporting.

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や有報でのESG開示が進む中、グリーンウォッシング問題は投資家の信頼を損なうリスクがあり、本レビューの知見は開示の質向上に役立つ。

In the global GX context

Globally, greenwashing undermines ESG credibility and aligns with regulatory efforts like SEC climate rules and CSRD. This review tracks evolving strategies to detect symbolic conduct, relevant for policymakers and standard-setters.

👥 読者別の含意

🔬研究者:Provides a structured timeline of greenwashing research, highlighting gaps for future work on AI-based detection and governance mechanisms.

🏢実務担当者:Offers insights into how greenwashing risks have evolved, helping corporate teams strengthen authentic ESG disclosure.

🏛政策担当者:Emphasizes the need for stronger regulatory frameworks to distinguish substantive ESG performance from symbolic claims.

📄 Abstract(原文)

This chronological literature review examines the impact of greenwashing on Environmental, Social, and Governance (ESG) research and practice, with emphasis on how scholarly understanding has evolved across recent years. The study is motivated by the growing concern that ESG disclosure, although increasingly important for investors, regulators, and other stakeholders, may be undermined by symbolic sustainability claims that do not reflect actual environmental or social performance. Such a condition weakens the credibility of ESG reporting, creates information asymmetry, and may distort sustainable investment decisions. To address this issue, the review applies a systematic advanced search strategy using the Scopus database, guided by the main keywords greenwashing, ESG, and sustainability. After screening and selection, the final primary dataset comprised 104 documents (n = 104). The selected studies were analysed using a chronological approach and grouped into three temporal phases: Foundational Emergence (2020–2021), Early Development and Consolidation (2022–2023), and Rapid Expansion and Intensification (2024–2026). The results indicate a clear growth in publication activity and conceptual maturity over time. In the first phase, the literature mainly focused on disclosure credibility, governance mechanisms, and the early identification of greenwashing behaviour. In the second phase, the discussion expanded toward financial constraints, regulatory pressures, green finance, assurance, and methodological refinement in detecting symbolic ESG conduct. In the third phase, the literature showed substantial intensification, with stronger attention to artificial intelligence, digital governance, investor reactions, policy intervention, and more advanced measurement frameworks for distinguishing substantive ESG performance from reputational signalling. Overall, the review concludes that greenwashing has become a central challenge in ESG literature, not only as a reporting issue but also as a governance, financial, and regulatory concern. The chronological structure provides a clearer understanding of how the field has progressed and where future research should be directed.

🔗 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。