Weather Action: A Study on the Industry Peer Effects of Corporate Climate Risk Information Disclosure
気候行動：企業の気候リスク情報開示における業界ピア効果に関する研究 (AI 翻訳)
Huer Shuang, Shenghua Lou, Renjie Luo, Jiajia Luo
🤖 gxceed AI 要約
日本語
本研究は、中国上場企業の2008-2022年のパネルデータを用いて、企業の気候リスク開示における業界ピア効果を実証的に分析した。社会的学習理論に基づき、「観察-模倣-強化」の枠組みを提案し、業界リーダーの観察学習、規範的压力や資金制約・経営者評判による模倣、排出削減成功による強化の動的フィードバックループを明らかにした。ハイテク部門では効果が弱く、中央国有企業・高排出産業で強い。また、ピア駆動の開示は排出削減に寄与する。
English
This study empirically tests industry peer effects on corporate climate risk disclosure using panel data of Chinese listed firms from 2008-2022. It proposes an 'observation-imitation-reinforcement' framework, finding a robust positive peer effect driven by observational learning from industry leaders, imitation due to normative pressure, financing constraints, and managerial reputational concerns, and reinforcement through successful emission reductions. The effect is weaker in high-tech sectors but stronger in central SOEs and high-carbon industries. Peer-driven disclosure significantly reduces carbon emissions.
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
中国企業の分析だが、日本企業の気候リスク開示にも類似したピア効果が存在する可能性を示唆。SSBJ対応において、競合他社の開示動向を意識することが実務上のヒントとなる。
In the global GX context
This paper contributes to the global disclosure literature by empirically documenting peer effects in climate risk disclosure, a phenomenon relevant to TCFD/ISSB adoption worldwide. It highlights how social learning shapes disclosure decisions, offering insights for regulators and firms in the transition to mandatory disclosure regimes.
👥 読者別の含意
🔬研究者:Provides empirical evidence on the role of peer effects in corporate climate disclosure, extending social learning theory to the sustainability context.
🏢実務担当者:Firms can anticipate that competitors' climate disclosure will influence their own, and early movers may create peer pressure for disclosure.
🏛政策担当者:Regulators designing mandatory disclosure rules should consider that peer effects can accelerate adoption, but also that certain sectors may lag.
📄 Abstract（原文）
ABSTRACT Global climate change has elevated the strategic importance of corporate climate risk disclosure, yet the role of industry peer effects in shaping such disclosure remains underexplored. Grounded in social learning theory, this study proposes an “observation–imitation–reinforcement” framework and empirically tests it using panel data on Chinese listed firms from 2008 to 2022. The results document a robust positive peer effect in corporate climate risk disclosure. Specifically, firms first engage in active observational learning by following industry leaders. They then imitate peers driven by normative pressure, financing constraints, and managerial reputational concerns. Subsequently, successful emission reductions reinforce subsequent imitation, forming a dynamic feedback loop. Additional analyses indicate that this peer effect is weaker in high‐tech sectors but stronger among central state‐owned enterprises, heavy‐polluting firms, and high‐carbon industries. Moreover, peer‐driven climate risk disclosure significantly reduces corporate carbon emissions, while prior emission reductions enhance firms' sensitivity to peer disclosure.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.1002/bse.71243first seen 2026-07-23 06:33:39
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