Determinants of Carbon Emission Disclosure Among Indonesian SOEs: Empirical Evidence from Firm Size and Leverage Dynamics (2021–2024)
インドネシア国有企業における炭素排出開示の決定要因:企業規模とレバレッジの動態からの実証的証拠(2021-2024) (AI 翻訳)
M. Satria
🤖 gxceed AI 要約
日本語
本研究は、2021~2024年のインドネシア国有企業(SOE)19社を対象に、企業規模とレバレッジが炭素排出開示に与える影響を検証した。GRI 305に基づく37項目の開示指標を用いた内容分析と回帰分析の結果、企業規模は開示と正の関係、レバレッジは負の関係にあることが示された。財務制約が規模よりも持続的な決定要因であることを示す新規性がある。
English
This study examines the influence of firm size and leverage on carbon emission disclosure among 19 Indonesian SOEs from 2021-2024. Using GRI 305-based content analysis and regression, it finds firm size positively and leverage negatively associated with disclosure, highlighting financial constraints as a more persistent determinant than size.
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開示義務化が進む中、国有企業や大企業の開示実態と財務構造の関係は、日本の上場企業や政府系企業の開示戦略を考える上で示唆に富む。特に、レバレッジが高い企業の開示意欲が低いという知見は、日本企業の財務健全性と開示の関連性を考察する際に有用。
In the global GX context
This study contributes to global disclosure scholarship by focusing on SOEs, which face unique accountability pressures. The finding that leverage negatively impacts disclosure suggests that financial constraints may hinder voluntary carbon reporting, relevant for policymakers and investors in emerging markets and beyond.
👥 読者別の含意
🔬研究者:Provides empirical evidence on determinants of carbon disclosure in SOEs, extending the literature on firm characteristics and environmental transparency.
🏢実務担当者:Highlights that financial leverage can impede voluntary carbon disclosure, informing corporate strategies to balance debt and sustainability reporting.
🏛政策担当者:Suggests that regulators may need to address financial constraints to encourage broader carbon disclosure among state-owned enterprises.
📄 Abstract(原文)
This study examines the influence of firm size and leverage on carbon emission disclosure among Indonesian State-Owned Enterprises (SOEs) during the period 2021–2024. Using secondary data obtained from sustainability and annual reports, this research adopts a quantitative associative approach with a sample of nineteen SOEs, resulting in seventy-six firm-year observations. Carbon emission disclosure is measured using a comprehensive index based on the Global Reporting Initiative (GRI) 305 Emissions standard, employing a structured content analysis of thirty-seven disclosure items. Multiple linear regression analysis is conducted after fulfilling classical assumption tests, including normality, multicollinearity, and heteroskedasticity diagnostics. The findings indicate that firm size is positively associated with carbon emission disclosure, suggesting that larger enterprises tend to disclose carbon-related information more extensively. In contrast, leverage is negatively associated with disclosure, indicating that firms with higher debt levels are less inclined to engage in voluntary carbon reporting. These results highlight the joint role of organisational scale and financial structure in shaping environmental transparency. To ensure robustness, additional analyses are performed using alternative variable proxies, winsorisation of extreme values, heteroskedasticity-consistent estimators, extended models with control variables, and panel data specifications. The results remain consistent across alternative estimations. This study addresses a gap in the literature by focusing exclusively on State-Owned Enterprises, which operate under heightened public accountability yet remain underexplored in carbon disclosure research. The key novelty lies in demonstrating that financial constraints, reflected through leverage, constitute a more persistent determinant of carbon emission disclosure than organisational size within publicly owned enterprises. This study is subject to limitations related to its SOE-specific focus and reliance on report-based disclosure data, providing avenues for future research in broader ownership and institutional contexts.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://owner.polgan.ac.id/index.php/owner/article/download/2941/1723first seen 2026-05-15 18:26:19 · last seen 2026-07-18 07:00:56
🔔 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。