A Social Risk‐Based Approach Supporting Corporate Sustainability Reporting Directive Framework
社会的リスクに基づくアプローチによる企業サステナビリティ報告指令(CSRD)枠組みの支援 (AI 翻訳)
Monica Serreli, Manuela D’Eusanio, Luigia Petti
🤖 gxceed AI 要約
日本語
本論文は、欧州の企業サステナビリティ報告指令(CSRD)に対応するため、社会組織ライフサイクルアセスメント(SO-LCA)とリスクマッピングツールを統合した社会的リスクベースの意思決定アプローチを提案する。多国籍包装企業のケーススタディを通じて、労働権と公正な労働条件の影響カテゴリーを評価し、地域ごとの社会的リスクの差異を特定した。結果はCSRDの開示要件との強い整合性を示し、企業が社会的データを構造化し、ホットスポットを特定する実践的経路を提供する。
English
This paper proposes a social risk-based decision-making approach integrating Social Organisational Life Cycle Assessment (SO-LCA) and risk mapping to support the European Corporate Sustainability Reporting Directive (CSRD). A case study on a multinational packaging company across 16 countries assessed labour rights and decent work conditions, identifying significant geographic variations in social risks. The results show strong alignment with CSRD disclosure requirements, providing a practical pathway for companies to structure social data collection and identify hotspots.
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
日本企業もEU市場に進出する場合、CSRD対応が求められる。本論文のSO-LCAとリスクマッピングの統合アプローチは、日本企業が社会的側面の開示を強化する際の参考になる。ただし、日本のSSBJはまだ環境中心であり、社会的側面の詳細な開示基準は整備途上である。
In the global GX context
The CSRD is a landmark regulation in global sustainability reporting. This paper offers a concrete methodology integrating SO-LCA and risk mapping to address social sustainability disclosure, which has been less developed than environmental reporting. It provides a replicable framework for companies worldwide to enhance social data governance and transparency.
👥 読者別の含意
🔬研究者:Researchers in sustainability accounting and life cycle assessment can leverage the integrated SO-LCA and risk mapping methodology for further refinement and application.
🏢実務担当者:Corporate sustainability teams can use the proposed approach to structure social data collection, identify high-risk geographies, and align with CSRD disclosure datapoints.
🏛政策担当者:Policymakers can consider the demonstrated alignment between risk mapping and mandatory disclosure points to refine regulatory requirements and support social risk governance.
📄 Abstract(原文)
Social sustainability is difficult to measure due to its qualitative and context‐specific nature. However, regulatory pressure and stakeholder expectations increasingly require organisations to disclose robust and verifiable information. In this context, the European Corporate Sustainability Reporting Directive (CSRD) sets new sustainability reporting standards. This paper proposes a social risk‐based decision‐making approach that integrates Social Organisational Life Cycle Assessment (SO‐LCA) and risk assessment tools to enhance reporting accuracy and transparency. A methodological framework was developed to combine SO‐LCA principles with a social risk mapping tool (RMT), aligned with CSRD requirements. A case study was conducted on a multinational packaging company operating in 16 countries. This study assessed the impact category ‘Labour Rights and Decent Work Conditions’ using the Social Hotspot Database (SHDB) RMT. Indicators were mapped against the CSRD's ‘Own Workforce’ reporting datapoints (EFRAG IG3 2024). The risk mapping identified significant variations in social risks across geographies. India, Thailand and China emerged with the highest frequencies of very high‐risk indicators, whereas Germany and France showed the best performance. The results provide prioritisation insights for monitoring and mitigation actions. Cross‐analysis confirmed strong alignment between RMT indicators and mandatory CSRD disclosure points. SO‐LCA and CSRD are complementary tools for social risk governance. Integrating social life cycle thinking into reporting improves decision‐making, enhances transparency and supports compliance. The proposed approach provides a practical pathway for companies to structure social data collection, identify social hotspots and align with evolving EU sustainability requirements.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1002/csr.70459first seen 2026-05-15 18:35:54 · last seen 2026-06-15 05:27:34
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