Measuring Corporate Alignment With the Circular Economy: a Text‐Based Circularity Index From Mandatory Non‐Financial Disclosures
循環経済への企業の適合性の測定：義務的な非財務情報開示に基づくテキストベースの循環性指標 (AI 翻訳)
Giuseppe Pernagallo, F. Quatraro, Eleonora Rubichi
🤖 gxceed AI 要約
日本語
本論文は、イタリアの大企業の義務的非財務開示文書を用いて、テキストマイニングにより循環経済（CE）への適合度を測る新指標を提案。FTSE MIB企業のサステナビリティ報告書（2017-2022年）からコサイン類似度でCE語彙との一致度を算出し、地域のリサイクルインフラや企業特性との関連を分析。高度なリサイクル施設のある地域の企業や、若く国際的な企業ほどCE適合度が高いことを示した。
English
This paper proposes a text-based circularity index using mandatory non-financial disclosures from large Italian companies. By computing cosine similarity between FTSE MIB sustainability reports (2017-2022) and a circular economy vocabulary from 135 documents, it measures firms' alignment with CE principles. Results show that firms in regions with advanced recycling infrastructure and younger, more international firms exhibit stronger circularity engagement.
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基準の導入により、循環経済に関する開示も注目されている。本手法は日本語報告書にも応用可能で、企業の循環性を客観的に評価するツールとして有用。ただし、イタリアの地域インフラに依存した分析結果は直接日本に当てはまらないため、日欧の開示制度比較の文脈で読むと良い。
In the global GX context
This paper contributes to global disclosure scholarship by demonstrating how text mining can extract circularity metrics from mandatory reports, a method applicable to TCFD/ISSB-aligned disclosures globally. It links corporate circularity to regional environmental infrastructure, offering insights for policymakers designing place-based circular economy policies.
👥 読者別の含意
🔬研究者:Provides a replicable text-based methodology for measuring corporate circularity that can be adapted to different regulatory contexts and languages.
🏢実務担当者:Offers a tool to benchmark circularity alignment using publicly available reports, aiding in sustainability communication and strategy refinement.
🏛政策担当者:Highlights the role of regional waste infrastructure in shaping corporate circularity, informing infrastructure investment and reporting standards.
📄 Abstract（原文）
The transition to a circular economy (CE) has become a strategic priority for firms, yet empirical assessments of corporate circularity remain fragmented and heavily dependent on structured indicators or self‐reported metrics. This paper proposes a novel, text‐based circularity index derived from mandatory non‐financial statements of large Italian companies. Using a corpus of FTSE MIB sustainability reports (2017–2022), we compute cosine similarity scores between firms' disclosures and an authoritative CE vocabulary built from 135 institutional and scholarly documents, generating a replicable and weighting‐free measure of firms' alignment with circularity principles. We link this indicator to regional environmental infrastructures and contextual characteristics, focusing on recycling performance and energy recovery systems. Our findings show that firms operating in regions with more advanced recycling infrastructures—particularly higher hazardous waste recovery—consistently exhibit stronger semantic alignment with CE concepts. Younger firms and those with greater international exposure also display higher circularity engagement, suggesting that organizational dynamism and global normative pressures shape the adoption of circular strategies. These results highlight the importance of place‐based environmental conditions in enabling corporate CE transitions and demonstrate the potential of text mining to enhance the monitoring of sustainability reporting and strategic environmental alignment.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1002/bse.70791first seen 2026-07-18 07:47:18
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