Systematic review analysis through an overview applying methodologies text mining and coding: big data analytics for sustainability accounting
テキストマイニングとコーディングを応用した方法論による系統的レビュー分析：持続可能性会計のためのビッグデータ分析 (AI 翻訳)
Wahid Winarto, Syaiful Ali
🤖 gxceed AI 要約
日本語
2017～2024年の70編の査読論文を系統的にレビューし、ビッグデータ分析（BDA）を持続可能性会計に統合する5つの主要テーマクラスタ（サプライチェーン・循環経済、AI、気候変動・基準、株式リターン・変革、ESG相互作用）を特定。報告基準の断片化や技術的障壁に対処する必要性を強調し、データ駆動型ESG政策の重要性を示唆。
English
A systematic review of 70 peer-reviewed articles (2017-2024) identifies five thematic clusters in integrating big data analytics into sustainability accounting: supply chain & circular economy, AI-enabled practices, climate change & standards, stock returns & corporate transformation, and ESG interactions. Highlights fragmented reporting standards and technological barriers, advocating for aligned data-driven ESG policies and robust assurance.
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基準策定が進む中、持続可能性会計へのBDA統合は、報告の効率性・信頼性向上に寄与する可能性がある。本レビューは基準間の断片化を指摘し、日本企業の統合報告書作成や投資家対応への示唆を与える。
In the global GX context
Globally, this review underscores the need for harmonized sustainability reporting standards in the age of big data, aligning with ISSB's efforts to consolidate frameworks. It offers a methodological blueprint for researchers and practitioners seeking to leverage BDA for more accurate and timely ESG disclosures.
👥 読者別の含意
🔬研究者:Provides a structured overview of thematic clusters and gaps for future research on BDA in sustainability accounting.
🏢実務担当者:Highlights how BDA can streamline sustainability reporting and assurance, offering insights for technology adoption in disclosure processes.
🏛政策担当者:Emphasizes the urgency of addressing fragmented standards and technological barriers to foster coherent ESG policies and data-driven regulation.
📄 Abstract（原文）
This study aims to critically examine the integration of big data analytics (BDA) into sustainability accounting, identifying thematic developments, methodological patterns and gaps that shape future research and practice. A systematic literature review was conducted on 70 peer-reviewed articles published between 2017 and 2024. The study uses a structured analytical framework, text mining techniques and thematic coding to synthesize findings and identify research gaps. The review reveals five key thematic clusters: supply chain and circular economy, artificial intelligence-enabled sustainability practices, climate change and sustainability accounting standards, stock returns and corporate transformation and environmental, social and governance (ESG) interactions. Significant research gaps are identified, with implications for academic inquiry, professional practice and regulatory policy. The study highlights the need to address fragmented reporting standards and technological barriers, emphasizing the urgency of aligned and data-driven ESG policies, robust assurance mechanisms and adaptive regulation. This research seeks to provide methodological insights for interdisciplinary studies in sustainability accounting, integrating BDA. It explores the transformative potential of BDA to reshape sustainability reporting, assurance and policy development.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1108/jm2-09-2025-0458first seen 2026-05-15 18:46:11
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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。