Search Results (89)

Emerging markets face growing pressures to integrate sustainable English business practices while maintaining economic growth, particularly in addressing environmental challenges and achieving carbon neutrality goals. English Financial information extraction becomes crucial for supporting green finance initiatives, Environmental, Social, and Governance (ESG) compliance, and sustainable investment decisions in these markets. This paper presents FinATG, an AI-driven autoregressive framework for extracting sustainability-related English financial information from English texts, specifically designed to support emerging markets in their transition toward sustainable development. The framework addresses the complex challenges of processing ESG reports, green bond disclosures, carbon footprint assessments, and sustainable investment documentation prevalent in emerging economies. FinATG introduces a domain-adaptive span representation method fine-tuned on sustainability-focused English financial corpora, implements constrained decoding mechanisms based on green finance regulations, and integrates FinBERT with autoregressive generation for end-to-end extraction of environmental and governance information. While achieving competitive performance on standard benchmarks, FinATG’s primary contribution lies in its architecture, which prioritizes correctness and compliance for the high-stakes financial domain. Experimental validation demonstrates FinATG’s effectiveness with entity F1 scores of 88.5 and REL F1 scores of 80.2 on standard English datasets, while achieving superior performance (85.7–86.0 entity F1, 73.1–74.0 REL+ F1) on sustainability-focused financial datasets. The framework particularly excels in extracting carbon emission data, green investment relationships, and ESG compliance indicators, achieving average AUC and RGR scores of 0.93 and 0.89 respectively. By automating the extraction of sustainability metrics from complex English financial documents, FinATG supports emerging markets in meeting international ESG standards, facilitating green finance flows, and enhancing transparency in sustainable business practices, ultimately contributing to their sustainable development goals and climate action commitments. Full article

This study investigates the impact of environmental, social, and governance (ESG) disclosure on value creation in a balanced panel of 100 non-financial Sharia-compliant firms listed on the Saudi Stock Exchange over the period 2014–2023. The analysis employs a combination of econometric techniques, including fixed effects models with Driscoll–Kraay standard errors, Pooled Ordinary Least Squares (POLS) with Driscoll–Kraay standard errors and industry and year dummies, and two-step system generalized method of moments (GMM) estimation to address potential endogeneity and omitted variable bias. Value creation is measured using Tobin’s Q (TBQ), Return on Assets (ROA), and Return on Equity (ROE). The models also control for firm-specific variables such as firm size, leverage, asset tangibility, firm age, growth opportunities, and market capitalization. The findings reveal that ESG disclosure has a positive and statistically significant effect on firm value across all three performance measures. Furthermore, firm size significantly moderates this relationship, with larger Sharia-compliant firms experiencing greater value gains from ESG practices. These results align with agency, stakeholder, and signaling theories, emphasizing the role of ESG in enhancing transparency, reducing information asymmetry, and strengthening stakeholder trust. The study provides empirical evidence relevant to policymakers, investors, and firms striving to achieve Saudi Arabia’s Vision 2030 sustainability goals. Full article

This study examines the influence of ethical leadership on corporate sustainability and financial performance, highlighting the moderating effect of firms’ commitment to the United Nations Sustainable Development Goals (SDGs). Utilizing panel data from 420 automotive companies spanning 2015 to 2024, the analysis applies the System Generalized Method of Moments (GMM) to control for endogeneity and unobserved heterogeneity. All data were gathered from the Refinitiv Eikon Platform (LSEG) and annual reports. Panel GMM regression is used to estimate the relationship to deal with the endogeneity problem. The results reveal that ethical leadership significantly improves corporate sustainability performance—measured by ESG scores from Refinitiv Eikon and Bloomberg—as well as financial indicators like Return on Assets (ROA) and Tobin’s Q. Additionally, firms that demonstrate breadth (the range of SDG-related themes addressed), concentration (the distribution of non-financial disclosures across SDGs), and depth (the overall volume of SDG-related information) in their SDG disclosures gain greater advantages from ethical leadership, resulting in enhanced ESG performance and higher market valuation. This study offers valuable insights for corporate leaders, policymakers, and investors on how integrating ethical leadership with SDG alignment can drive sustainable and financial growth. Full article

The rapid advancement and broad adoption of digital technologies have infused ESG practices with new dimensions and significance. Drawing on panel data from Chinese A-share listed companies spanning from 2012 to 2023, this paper aims to explain the impact of digital transformation on corporate ESG performance, explore its mechanisms and external regulatory effects, and provide systematic ideas and methods for improving corporate ESG performance from the perspective of digital transformation. The key findings of this study are summarized as follows: (1) Digital transformation (DT) has a significant positive effect on corporate ESG performance, and this association remains statistically robust following multiple robustness tests and a correction for potential endogeneity. (2) An analysis of the entire operational process reveals that DT improves ESG performance through enhancing environmental information disclosure quality, strengthening the integration of digital and physical industry technologies, and bolstering supply chain resilience. (3) The implementation of the “Broadband China” strategy exerts a positive moderating effect on the linkage between DT and ESG performance. (4) A heterogeneity analysis shows that the positive impact of DT on ESG performance is more significant and stable in non-state-owned enterprises, eastern regions, less-polluted areas, and growth stage enterprises. These findings offer theoretical and empirical insights for understanding ESG performance drivers. However, the focus on Chinese A-share firms and the use of Sino-Securities ratings may limit generalizability, warranting further improvement. Full article

This study investigates voluntary compliance with the Task Force on Climate-Related Financial Disclosures (TCFD) framework in 64 financial, Environmental, Social, and Governance (ESG) reports from six Spanish IBEX-35 energy firms (2020–2023) and explores the implications for intangible assets and corporate reputation, employing empirical quantitative text mining and Natural Language Processing (NLP) in Python. A validated scale-based taxonomy within the TCFD framework applies query-driven rules to extract relevant text. This enables an evaluation of aspects of the reports, facilitating the development of a compliance index measuring each company’s adherence to TCFD recommendations. All companies showed year-on-year improvements (2023 was the most comprehensive), yet none fully adhered due to information gaps. Disparities in the disclosures of Scope 1,2 and 3, persisted, suggesting reputational risks. A replicable methodological model generating a compliance index that assesses the ‘being’ (‘true performance’) versus ‘seeming’ (‘external perception’) dichotomy within sustainability reports and acts as a potential reputational barometer for stakeholders. By providing unprecedented evidence of TCFD reporting in the Spanish energy sector, this study closes a significant academic gap. Future research may analyze ESG reports using AI agents, study the impact of ESG on energy-intensive companies from AI data centers, supporting services like Copilot, ChatGPT, Claude, Gemini, and extend this methodology to other industrial sectors. Full article

In 2020, the Chinese government announced the “Dual Carbon” goals, making carbon responsibility the most prominent focus within the Environmental, Social, and Governance (ESG) practices of Chinese firms. This shift creates a new type of ESG-washing, a practice involving the selective disclosure of information that portrays the firm in a favorable light, thereby leading stakeholders to overestimate its ESG performance. In this study, we define a novel type of ESG-washing behavior called “ESG carbonwashing”, in which firms disproportionately highlight their carbon responsibility initiatives while overlooking other dimensions of ESG. By adopting a strategy of excessively emphasizing their carbon-related efforts in ESG activities, these firms mislead stakeholders about their overall ESG performance. Using a sample of 59 high-carbon-emitting firms listed on the Shanghai and Shenzhen A-share markets from 2018 to 2022, we construct a systematic framework to measure the extent of ESG carbonwashing and further analyze its temporal and industry-level variations. Our key findings indicate that: (1) ESG carbonwashing has significantly increased alongside the rollout of the “Dual Carbon” policy; (2) there are significant inter-industry differences, with the steel and aviation sectors exhibiting the highest levels of ESG carbonwashing, while the building materials industry shows the lowest. This study offers valuable guidance for ESG information users in detecting and mitigating carbonwashing practices, while also providing robust empirical support for refining relevant regulatory frameworks. Full article

Based on sample data from A-share listed heavy polluters from 2012 to 2021, this paper adopts the double-difference method to explore the influence of the construction of national pilot zone for ecological conservation on the ESG performance of heavily polluting enterprises. Following several robustness tests, this study argues that the ESG performance of heavy-polluting companies is significantly enhanced by the construction of the national pilot zone for ecological conservation. Specifically, the construction of the pilot zone enhances the ESG performance of heavy polluters by easing financing constraints. The enhancing effect of the construction of the pilot zone on the ESG performance of heavy polluters is more prominent in terms of strengthening social responsibility and optimizing governance structure. Additionally, improving heavily polluting enterprises’ ESG performance is demonstrated to effectively enhance their financial performance. The facilitating effect of the construction of the pilot zone on ESG performance is more obvious among state-owned enterprises, enterprises with high media attention, enterprises established at a late stage, and enterprises with high-quality environmental information disclosure. This study offers an empirical foundation for the government to develop policies regarding the establishment of pilot zones and for heavily polluting enterprises to enhance their ESG performance. Full article

Integrated Reporting (IR) has gained prominence as a comprehensive approach to corporate disclosure, yet theoretical clarity is still developing regarding how governance mechanisms shape IR quality and its relation to ESG risk ratings. Addressing this gap, this study explores the influence of board and audit committee characteristics on IR quality and whether an improved IR quality is associated with a lower ESG risk. Drawing on different theories, this research examines how governance structures enhance transparency and accountability in line with societal expectations. Based on panel data from 158 firms across four years (2019–2022), a random effects Panel EGLS regression model is employed along with an endogeneity check. Findings show that board independence and the presence of women members significantly enhance the IR quality, while board size is not a determining factor. Similarly, audit committee independence and meeting frequency positively influence the IR quality, whereas committee size does not. Furthermore, firms with a higher IR quality demonstrate significantly lower ESG risk scores. These results underscore the theoretical proposition that effective governance improves disclosure credibility and reduces information asymmetry. This study suggests that reinforcing board independence and diversity can enhance reporting quality and stakeholder trust, offering a strategic path toward more sustainable and transparent corporate behavior. Full article

In recent years, corporate ESG performance has been widely incorporated into investment decisions and capital allocation considerations, becoming a focal point and hot topic for research by governments and organizations worldwide. However, due to various reasons, significant discrepancies have emerged in ESG ratings for the same company across different institutions, and this growing divergence in ESG ratings has increasingly drawn the attention of scholars. Studying the differences in ESG (environmental, social, and corporate governance) ratings is of great significance. This not only helps to understand the root causes of differences, improve the objectivity, consistency, and comparability of ratings, but also helps users better understand the meaning and limitations of rating results. It is beneficial for investors to understand the focus of different ratings and develop more effective investment strategies. It can promote rated companies to improve the quality and transparency of ESG-related information disclosure. It can also provide a reference for regulatory agencies and policymakers, identify market failures and potential risks, and promote the development of more unified standards and frameworks. At the same time, this study can also promote the in-depth development of relevant academic research and theories. Based on this, this study systematically reviews the relevant literature on ESG rating divergence, focusing on its existence, causes, influencing factors, and impacts. The study finds that, in addition to the widespread existence of rating divergence in corporate ESG performance, scholars also disagree on the measurement and methods of this divergence. The reasons for rating divergence are mainly that ESG is a qualitative indicator; top-level design, intermediate calculations, and bottom-level data collection across multiple stages exacerbate divergence; and controversies in practice further deepen divergence, among others. The influencing factors and impact effects of ESG rating divergence are diverse. Given the existence of ESG rating divergence, all parties should treat ESG ratings with caution. This paper offers corresponding recommendations and looks forward to the future, providing a foundation for subsequent research. Full article

Amid growing global concerns regarding sustainable governance, understanding the drivers of ESG disclosure is vital for promoting transparency and responsible corporate behavior. This study examines the peer effects of ESG disclosure among 32,187 observations from Chinese A-share listed firms between 2010 and 2021. This research employs an instrumental variable approach based on stock-specific idiosyncratic returns estimated via the Carhart four-factor model to address endogeneity concerns. The results confirm significant peer effects, suggesting that firms adjust ESG practices in response to their industry counterparts. These effects are significantly moderated by firm-level characteristics, including information asymmetry, corporate reputation, and market competition, as well as by external conditions such as economic policy uncertainty, business environment volatility, and institutional quality. This research defines peer groups by industry affiliation and conducts robustness tests using ESG risk clustering to address classification bias. This study contributes to the literature by strengthening causal inference and refining the understanding of peer-driven ESG behavior by integrating institutional theory, signaling theory, and information economics. The findings offer practical implications for policymakers, investors, and corporate managers seeking to promote ESG convergence through peer-driven incentives in diverse regulatory contexts. Full article

This study examines the impact of green finance policies on corporate biodiversity disclosures, focusing on China’s Green Finance Reform and Innovation Pilot Zones (GFPZs). Utilizing a comprehensive dataset of Chinese-listed firms from 2010 to 2022, we apply textual analysis to annual reports to quantify biodiversity-related disclosures. Our findings reveal that GFPZ policies significantly reduce biodiversity disclosures, suggesting a trade-off between carbon-focused financial incentives and broader environmental transparency. Cross-sectional analysis indicates that firms with higher R&D intensity and those in regions with stricter environmental enforcement exhibit fewer negative effects. Mechanism analysis highlights that carbon production intensity and green information disclosure quality mediate this relationship. Robustness checks, including propensity score matching, confirm these results. Our study underscores the need for policymakers to integrate biodiversity considerations into green finance frameworks to ensure balanced ESG priorities. Full article

Digital technology has transformed sustainability reporting practices, creating both opportunities and homogenization risks. This study analyzes 9903 sustainability reports from Chinese listed companies (2009–2021) through cosine similarity analysis. It reveals high intercorporate similarity (mean = 0.776). Fixed-effects modeling demonstrates that digital adoption increases report similarity, while analyst scrutiny and innovation capacity significantly mitigate this convergence effect. The findings suggest that digital tools promote isomorphic disclosure patterns through template-driven reporting. However, market monitoring (analyst attention) and R&D investment counterbalance this trend by incentivizing unique environmental, social, and governance (ESG) disclosures. This study offers novel insights into information asymmetry theory and social learning theory. The increased similarity in reporting will lead to standardization among Chinese companies, thereby enhancing their comparability in the international market. This will not only help Chinese companies improve their performance assessments for global investors but also facilitate cross-border investments. Full article

Solid waste governance actions are important to achieve sustainable urban development. This study uses the “zero-waste city” pilot policy as a natural experiment to evaluate the impact of solid waste governance actions on corporate environmental, social, and governance (ESG) performance. The research shows that solid waste governance actions improve corporate ESG performance by enhancing government environmental concerns, public environmental concerns, and corporate green innovation. The analysis of spillover effects indicates that solid waste governance exerts positive spatial spillover effects. Heterogeneity tests reveal that the positive effect of solid waste governance actions on corporate ESG performance is more pronounced in enterprises characterized by higher-quality information disclosure and stronger internal governance, industries with greater solid waste output and more advanced technology, regions with a closer government–market relationship, and in central–eastern regions. These findings contribute to understanding the micro-level effects of solid waste governance actions and the determinants of corporate ESG performance, providing valuable insights for other developing countries to govern solid waste and improve corporate ESG performance. Full article

Corporate social responsibility (CSR) and environmental, social, and governance (ESG) disclosures are critical for sustainable value creation. However, traditional evaluation methods struggle to quantify authentic performance and detect disclosure biases. In response, this study proposes an automated CSR polarity dictionary construction method that innovatively combines natural-language-processing technology and the multinomial inverse regression (MNIR) method. This method analyzes the correlations between corporate CSR reports and CSR ratings and constructs a dictionary that best reflects the CSR level of listed companies. We also used the CSR dictionary to construct a CSR disclosure level index for listed companies’ annual reports. This study reveals that CSR disclosure levels in annual reports expose manipulative disclosure practices and image management. However, this behavior has been proven to fail in generating excess returns for the company in the stock market. This phenomenon provides novel insights into corporate stock market performance management. In addition, the CSR disclosure level index is shown to effectively reflect the CSR level of enterprises in different industries and provides a theoretical reference for the social responsibility management of companies with different pollution levels. These findings facilitate efficient information release and strengthen ESG assessment frameworks through data-driven standardization. Full article

Greenwashing undermines the trustworthiness and integrity of environmental, social, and governance (ESG) reporting. It undermines disclosure quality, confuses decision making, destabilizes financial markets, and reduces the probability that people will trust the supplied information. This research utilizes a comprehensive literature review and bibliometric analysis to investigate the scholarly dialogue around ESG disclosure and strategies to counteract corporate “greenwashing”. This study’s objectives were achieved by bibliometric analysis, using the statistical programming tools R Studio R 3.6.0+, Biblioshiny 4.2.0, and VOSviewer 1.6.20. We acquired bibliometric data from the Scopus database for the period 2012–2024. We established the optimal sample size via the PRISMA methodology, including both inclusion and exclusion criteria. Greenwashing is a multifaceted issue that manifests in many forms, shapes, and intensities, as seen by the data. This obstructs the advancement of apparatus for prevention, quantification, and detection. Moreover, the results indicate that sustainable finance is adversely affected by greenwashing, particularly for green loans and green bonds. Moreover, the findings indicate that corporate greenwashing is a distinct kind of greenwashing. Full article