Exploring and Examining an Investor-Oriented ESG Intelligence Transformation Model: Insights from Chinese Analyst Reports

Environmental, social, and governance (ESG) information is increasingly vital in driving capital markets to promote sustainable development. However, significant barriers remain in effectively transforming ESG information into intelligence that supports investor decision-making. Drawing upon information chain theory and intelligence transformation theory, this study constructs an ESG intelligence transformation model tailored for investor decision-making, aiming to address relevant challenges within China’s unique capital market environment. Through a mixed deductive-inductive content analysis of analyst reports issued by Chinese securities firms, this study identifies underlying issues in current ESG information utilization: excessive focus on social dimensions at the expense of integrated consideration of environmental and governance issues; inadequate conversion of environmental and governance data into decision-relevant information; and incomplete pathways for transforming ESG knowledge into intelligence supporting investment decisions. These constraints significantly undermine the potential of ESG information to guide sustainable investment strategies and support green economic transformation. To bridge these gaps, this study proposes an integrated multi-stakeholder optimization strategy encompassing: enhanced disclosure standards by regulators; greater corporate emphasis on environmental and governance disclosures; more sophisticated assessment techniques by rating agencies; and optimized information channels between corporations and investors by financial institutions. This study provides a theoretical foundation and practical pathways for enhancing the quality and utility of ESG information, contributing to sustainable finance research.

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Publication Details

Journal
Sustainability
Published
2026-03-20
DOI
https://doi.org/10.3390/su18063076
Primary Topic
Corporate Social Responsibility Reporting
Type
article
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article

Exploring and Examining an Investor-Oriented ESG Intelligence Transformation Model: Insights from Chinese Analyst Reports

Jiayao Hong, Hua Guo
Sustainability
Corporate Social Responsibility Reporting
article

Exploring and Examining an Investor-Oriented ESG Intelligence Transformation Model: Insights from Chinese Analyst Reports

Jiayao Hong, Hua Guo
article en

Abstract

Environmental, social, and governance (ESG) information is increasingly vital in driving capital markets to promote sustainable development. However, significant barriers remain in effectively transforming ESG information into intelligence that supports investor decision-making. Drawing upon information chain theory and intelligence transformation theory, this study constructs an ESG intelligence transformation model tailored for investor decision-making, aiming to address relevant challenges within China’s unique capital market environment. Through a mixed deductive-inductive content analysis of analyst reports issued by Chinese securities firms, this study identifies underlying issues in current ESG information utilization: excessive focus on social dimensions at the expense of integrated consideration of environmental and governance issues; inadequate conversion of environmental and governance data into decision-relevant information; and incomplete pathways for transforming ESG knowledge into intelligence supporting investment decisions. These constraints significantly undermine the potential of ESG information to guide sustainable investment strategies and support green economic transformation. To bridge these gaps, this study proposes an integrated multi-stakeholder optimization strategy encompassing: enhanced disclosure standards by regulators; greater corporate emphasis on environmental and governance disclosures; more sophisticated assessment techniques by rating agencies; and optimized information channels between corporations and investors by financial institutions. This study provides a theoretical foundation and practical pathways for enhancing the quality and utility of ESG information, contributing to sustainable finance research.

SustainabilityVol. 18(6)
Hohai University (CN)
Openalex Percentile: Top 13%
Corporate Social Responsibility Reporting
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