Corporate social capital disclosure in integrated reports: a structural topic modelling approach
統合報告書における企業の社会的資本開示：構造的トピックモデリングアプローチ (AI 翻訳)
Arun Podayan, B Charumathi
🤖 gxceed AI 要約
日本語
本研究は、インド企業の統合報告書における社会的資本開示のパターンを、構造的トピックモデリング（STM）を用いて分析。2018〜2022年のNifty100企業のデータから9つの主要トピックを特定し、危機管理、女性リーダーシップ、人権、サプライヤー関係、コミュニティエンゲージメントが最も顕著である一方、教育プログラムやデジタル包摂は過少報告されていることを明らかにした。
English
This study analyzes social capital disclosure patterns in integrated reports of Indian firms using Structural Topic Modelling (STM). Based on Nifty 100 companies from 2018 to 2022, nine key topics were identified. Crisis management, women's leadership, human rights, supplier relationships, and community engagement are most prominent, while educational programs and digital inclusion are underreported. The findings align with legitimacy and stakeholder theories, highlighting areas for strengthening CSR practices.
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
日本においても統合報告書が普及しつつあり、SSBJや有価証券報告書での非財務情報開示の重要性が高まっている。本研究のトピックモデリング手法は、日本の企業開示分析にも応用可能であり、社会的資本開示の過不足を評価する枠組みとして参考になる。
In the global GX context
This paper contributes to global disclosure scholarship by applying advanced machine learning (STM) to integrated reports, a method increasingly relevant as ISSB and CSRD demand more structured sustainability data. While focused on India, the framework for analyzing social capital topics can be adapted to other jurisdictions, including those adopting integrated reporting under the IIRC framework.
👥 読者別の含意
🔬研究者:Researchers can adopt the STM methodology for analyzing disclosure patterns in other contexts or for other ESG topics.
🏢実務担当者:Corporate sustainability teams can use the identified topic clusters to benchmark their own social capital disclosures against peer trends.
📄 Abstract（原文）
Abstract Corporate social capital disclosure is essential for communicating a company’s societal contributions to various stakeholders. Adopting integrated reporting has enhanced non-financial reporting practices, improving the transparency and quality of sustainability-related information for investors. This study investigates patterns of social capital disclosure in the integrated reports of Indian firms by applying Structural Topic Modelling (STM) to uncover latent themes. Using data from Nifty 100 companies between 2018 and 2022, nine key disclosure topics were identified. Among these, crisis management, women’s leadership, human rights, supplier relationships, and community engagement were most prominent, while educational programs and digital inclusion were significantly underreported. Topic correlations revealed that educational and digital initiatives are linked with community support and crisis management, whereas women’s leadership and human rights align with skill development and safety. These findings suggest that firms prioritise community-oriented themes to enhance social legitimacy and stakeholder trust, aligning with legitimacy and stakeholder theories. The underrepresentation of certain themes highlights areas for strengthening corporate social responsibility practices. This study offers a novel framework for analysing corporate disclosures using advanced machine learning techniques, with implications for promoting transparency, accountability, and future ESG research.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.1186/s43093-025-00627-2first seen 2026-05-05 19:08:44
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