Impact of Sustainability on Firm Performance Under the Moderation of Competition: Considering Financial and Operational Performance Metrics
競争の調整下におけるサステナビリティが企業業績に与える影響:財務・業績指標を考慮して (AI 翻訳)
Bhakti Agarwal, Shailesh Rastogi
🤖 gxceed AI 要約
日本語
本研究は、インドの非金融上場企業316社の12年間のデータを用いて、ESGスコアと社会スコアが企業業績(在庫回転率、売上高、粗利益率)に与える影響を、競争を調整変数として分析した。分位点回帰により線形・非線形の関係を検討し、ESGスコアと業績の関係が分位によって異なること、競争がその関係を有意に調整することを発見した。
English
This study examines the linear and non-linear relationship between ESG/social scores and firm performance (inventory turnover, sales, gross profit margin) using panel data from 316 Indian non-financial firms (2011-2022), with competition as a moderator. Quantile regression reveals that ESG effects vary across performance quantiles and competition significantly moderates these associations, providing insights for managers and policymakers.
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開示基準の導入が進む中、ESGスコアと業績の関連性を競争環境の観点から示す本研究成果は、日本企業が競争優位性を考慮したESG経営を推進する上で参考となる。特に、非線形効果の存在は、日本の実務家にとって重要な示唆を与える。
In the global GX context
This paper adds to the global ESG-financial performance literature by using quantile regression to uncover non-linear effects and the moderating role of competition in an emerging market context. It offers empirical evidence that can inform corporate sustainability strategy and disclosure practices worldwide, particularly in competitive industries.
👥 読者別の含意
🔬研究者:Highlights the value of quantile regression and moderation analysis in ESG-performance studies.
🏢実務担当者:Managers can use competitive advantage as a lever to optimize ESG integration for better performance.
🏛政策担当者:Provides evidence that ESG disclosure may have differential impacts depending on market competition, useful for disclosure regulation design.
📄 Abstract(原文)
This research proposes to probe the mutual association between environmental, social and governance (ESG) and social scores on the operational (inventory turnover ratio and sales) and financial (gross profit margin) performance of Indian firms. Moreover, the competition is used as a moderator to study the association between ESG and social scores on the Indian firm performance. This study measures linear and non-linear associations between the variables. Employing quantile regression for the 25th, 50th and 75th quantiles, it examines the association between a firm’s performance and its social and ESG score. For the study, data from 316 listed non-financial enterprises in India during 12 years (2011–2022) are combined. The study found that ESG and social score significantly affect inventory turnover, gross profit margin ratio and sales differently on different levels. Competition also significantly moderates the association of ESG, social score and a firm’s financial and operational performance in different quantiles. These research findings help managers consider competitive advantage as a factor in enhancing firm performance. According to the study’s findings, it guides managers, practitioners and authorities who are curious about firm performance, competitive advantage and ESG scores find interesting insights into the information. Managers can find the right amount of competitive advantage that enhances firm performance. The results also provide information on potential future growth for corporations to the board of directors and other authorities. We do not observe any paper reporting the non-linear and linear association where the connection of ESG and performance is assessed under the moderation of competition in Indian firms. The research’s conclusions can guide Indian businesses, outlining a workable structure for highlighting the value of ESG disclosure in performance evaluations. Therefore, the current article contributes substantially to the existing body of knowledge on sustainability and finance.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.1177/09731741251400966first seen 2026-05-14 22:30:10
🔔 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。