指標属性を用いたサステナビリティ報告のマッピング
Mapping sustainability reporting using indicator attributes (原題)
Ramona Zharfpeykan, Paul Rouse
🤖 gxceed AI 要約
日本語
米国上場364社のGRI報告書2,184件（2018–2023年）を対象に、報告指標の属性（頻度、ステークホルダー焦点、情報の方向性・感度）をコード化し、企業の報告戦略を推定する枠組みを提示。開示量の増加は必ずしも開示範囲の拡大や包摂的な報告戦略を意味せず、同程度の開示量でも指標・ステークホルダーへの配分は大きく異なることを示す。制度・ステークホルダー・正当性理論の複数視点で評価することの重要性を強調する。
English
Using a GRI-based coding framework applied to 2,184 sustainability reports from 364 US-listed Forbes Global 2000 firms (2018–2023), the authors infer reporting strategies from indicator attributes such as frequency, stakeholder focus, and information direction/sensitivity. Disclosure volume increases do not necessarily mean broader coverage or more inclusive strategies; firms with similar volumes can allocate attention very differently. Multiple theoretical lenses are needed to assess disclosure strategy.
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・有報でのサステナビリティ開示が進む日本企業にとって、開示「量」ではなく指標属性から戦略を読み解く視点は、統合報告書の質的評価や投資家との対話設計に示唆を与える。GRIベースの枠組みはSSBJ/ISSBとの接続を考える際の比較材料になる。
In the global GX context
As ISSB/SSBJ and CSRD push toward structured, indicator-level disclosure, this paper offers a method to assess disclosure strategy beyond volume counts—useful for regulators and investors evaluating whether expanded reporting reflects genuine strategic breadth or selective attention. It also informs greenwashing and disclosure-quality debates in global scholarship.
👥 読者別の含意
🔬研究者:開示量と開示戦略の乖離を指標属性で捉える実証枠組みとして、サステナビリティ開示研究の質的評価手法に貢献する。
🏢実務担当者:自社のGRI報告書が指標・ステークホルダー間でどのように注意を配分しているかを点検し、開示戦略の偏りを可視化する際に活用できる。
🏛政策担当者:開示量の増加が必ずしも包摂的な報告を意味しない点は、開示規制の質的評価や指標設計を検討する際の参考になる。
📄 Abstract（原文）
Purpose This study aims to examine how the attributes of reported sustainability indicators can be used to infer the reporting strategies organisations adopt. Design/methodology/approach Drawing on institutional, stakeholder and legitimacy theories, we reviewed the sustainability reporting literature to identify key reporting strategies and related indicator attributes, including reporting frequency, stakeholder focus and the direction and sensitivity of information. These attributes informed a global reporting initiative (GRI)-based coding framework, which we applied to 2,184 GRI-based sustainability reports from 364 US-listed firms in the Forbes Global 2000 between 2018 and 2023. Frequency data were analysed quantitatively, while the remaining attributes were independently coded and mapped to GRI performance indicators. Descriptive trend analysis, comparative distribution analysis and regression models were then used to examine how disclosure profiles differed across reporting groups and evolved over time. The framework was subsequently applied across the sample to identify and compare firms’ reporting strategies. Findings Indicator attributes reveal strategic differences not visible from disclosure counts alone. Firms with similar disclosure volumes may allocate reporting attention very differently across indicators, stakeholders and disclosure types, while firms with differing disclosure volumes may exhibit similar reporting profiles. The findings show that increases in disclosure volume do not necessarily correspond to broader disclosure coverage or more inclusive reporting strategies. Although reporting levels generally increased over time, disclosure profiles changed only modestly, with firms largely maintaining similar reporting orientations across the study period. A firm’s reporting approach may also appear broader under one theoretical lens but selective or concentrated under another, highlighting the importance of using multiple perspectives when assessing sustainability disclosure strategies. Originality/value The study shows the value of examining sustainability reports through multiple theoretical perspectives and introduces a structured, theory-informed approach for analysing reporting content.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1108/jaoc-12-2025-0565first seen 2026-10-31 05:08:21 · last seen 2026-11-06 05:01:30
🔔 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。