Analysis of Factors Influencing Carbon Emissions Disclosure
炭素排出開示に影響を与える要因の分析 (AI 翻訳)
Mavira Fitri Muliani, Siti Nur Hadiyati
🤖 gxceed AI 要約
日本語
本研究は、インドネシア証券取引所に上場する化学・原材料セクターの企業を対象に、炭素排出開示に影響を与える要因を定量的に分析した。GRI 305基準に基づき開示を測定し、重回帰分析を実施した結果、業種、企業規模、環境パフォーマンス（PROPER格付け）、取締役会の独立性、監査委員会が有意な影響を与える一方、レバレッジは影響しないことが示された。
English
This study quantitatively examines factors influencing carbon emissions disclosure for Indonesian chemical and raw materials firms listed on IDX from 2022-2024. Using GRI 305-based content analysis and multiple regression, it finds that industry type, company size, environmental performance (PROPER), board independence, and audit committee significantly affect disclosure, while leverage does not.
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
インドネシアの化学・原材料セクターにおける炭素開示の実証分析。PROPER格付けのような独自の環境評価制度が開示促進に寄与する点は、日本のSSBJ普及策にも示唆を与える。
In the global GX context
This empirical evidence from an emerging market (Indonesia) supports the role of corporate governance and environmental performance ratings in driving carbon disclosure, relevant to ISSB implementation in developing economies.
👥 読者別の含意
🔬研究者:Provides empirical evidence on determinants of carbon disclosure in an emerging market context, useful for comparative studies.
🏢実務担当者:Highlights that improving environmental performance (e.g., PROPER ratings) and board governance can enhance carbon disclosure, which is relevant for companies seeking compliance with global standards.
🏛政策担当者:Suggests that environmental performance rating systems (like PROPER) can effectively encourage transparency, offering a model for other countries.
📄 Abstract（原文）
The main objective of this study is to examine the elements that influence carbon emission disclosure using a quantitative approach. This study covers companies in the chemical and raw materials sector listed on the Indonesia Stock Exchange (IDX) during the period 2022-2024. The sample was taken using a specific sampling technique, resulting in 33 companies consisting of a total of 99 observation units. Data analysis was performed by applying multiple linear regression with independent variables such as industry sector, company size, leverage, environmental performance (PROPER ratings), board independence and audit committee. Carbon emissions disclosure was measured based on the GRI 305 standard using content analysis with a dummy approach. The findings demonstrated that while leverage had no discernible impact on carbon emission disclosure, type of industry,size, environmental performance, board independence, and audit committee did.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.46336/ijbesd.v7i3.1216first seen 2026-06-19 05:01:55
🔔 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。