Search Results (351)

We examine the association between Environmental, Social, and Governance (ESG) initiatives and corporate performance using a sample of 360 S&P 500 firms from 2010 to 2018. Employing MSCI ESG ratings and controlling for industry and time effects, we find that environmental initiatives positively associate with current profitability (ROA), while gender diversity correlates with long-term growth prospects (Tobin’s Q). This study moves beyond aggregated ESG metrics by providing a disaggregated analysis, revealing that different ESG dimensions affect performance through distinct financial mechanisms. To address common endogeneity concerns, we implement a rigorous empirical identification strategy, including propensity score matching, Heckman selection models, and instrumental variable approaches using industry-average instruments. Our results quantify the economic magnitude of these effects, demonstrating that a one-standard-deviation increase in environmental performance corresponds to a 0.92 percentage point increase in ROA, representing approximately $176 million in additional annual net income for the median firm. These findings provide theoretical advancement for the resource-based view and stakeholder theory by showing that specific ESG capabilities serve as valuable, inimitable resources. Ultimately, the study contributes standardized, high-resolution evidence on how specific ESG dimensions drive superior corporate performance. Through mechanism analysis, we show that environmental effects operate primarily via operational cost reduction and risk mitigation, while gender diversity creates value through enhanced innovation findings, which has direct implications for corporate ESG strategy. Full article

In the strategic context of China’s efforts to promote agricultural power and modernization, the key to achieving sustainable development for agricultural enterprises lies in fostering breakthrough innovations and enhancing their market competitiveness. This paper uses Chinese agricultural enterprises listed on the A-share market from 2009 to 2024 as its research sample. From the perspective of breakthrough innovation in agriculture-related enterprises, it examines the association between agricultural new quality productivity and the sustainable development of agricultural enterprises. The regression results show that, first, agricultural new quality productivity is positively associated with breakthrough innovation in agricultural enterprises. After a series of robustness tests, these findings remain valid. Second, the bootstrap mediation results indicate that this relationship operates mainly through government policy orientation and enterprise knowledge creation capacity, while the indirect effects of government resource support and independent R&D capacity are weaker and not statistically robust. Furthermore, a heterogeneity test revealed that agricultural new quality productivity has a more pronounced positive association with breakthrough innovation in regions with strong intellectual property protection and high environmental regulations, as well as in samples where corporate executives demonstrate greater environmental awareness and companies achieve higher overall ESG scores. Finally, further analysis shows that as the level of corporate green transformation increases, the enabling effect of agricultural new quality productivity on breakthrough innovation in agricultural enterprises becomes more pronounced, providing evidence on how ANQP may support the sustainable development of agricultural enterprises. Full article

In green credit markets, information asymmetry and corporate greenwashing increasingly undermine the efficiency of resource allocation, while traditional assessment models relying on static, self-reported environmental data fail to impose effective constraints. To address this limitation, this paper develops a dynamic corporate carbon credit evaluation framework by integrating multiple sources of physical (hard) signals and embeds it into commercial banks’ credit management systems. Anchored in multi-source power-carbon signals (e.g., carbon intensity and compliance records), the framework integrates verifiable physical metrics with ESG disclosures via a Bayesian AHP–CRITIC weighting scheme to construct a dual-dimensional classification scheme (“Credit Rating–Green Label”). It further embeds carbon credit scores into dynamic adjustments to credit limits and differentiated interest rate pricing, forming an integrated risk management mechanism. Empirically, a stratified validation strategy is adopted. Analysis based on a sample of 3327 firms shows that the proposed framework achieves a classification consistency of 81.3%, significantly outperforming both a financial-only baseline model (46.8%) and models based on voluntary carbon disclosure (61.4%). Ablation studies further confirm that physical (hard) signal indicators contribute substantially to ranking stability. Moreover, panel regression analysis, based on 36,185 firm-year observations from 3327 firms over the period 2000–2023, demonstrates that carbon credit scores have robust predictive power for future financial distress. Overall, the proposed framework offers a sustainable, data-driven approach to green credit risk management. Full article

The article provides a systematic and bibliometric review of the literature on the relationship between countries’ ESG scores and their sovereign ratings. The study, which follows the PRISMA 2020 guidelines, employs a bibliometric methodology using a sample of 168 peer-reviewed articles sourced from Scopus and WoS (2006–2024) to analyze the progression of research in this growing area. The analysis shows that academic output is concentrated in Europe (35% of publications) and North America (12% of publications), and that there is increasing interest in incorporating ESG factors into sovereign risk assessment, especially since 2019. The bibliometric mapping shows that themes concerning ESG integration into sovereign risk assessment, rating methodologies, and sustainability-driven financial risk pricing are predominant. Four main research streams are revealed through co-occurrence and clustering analyses, which also highlight an expanding yet disjointed body of knowledge. The results also suggest large differences in how ESG ratings are calculated, which brings into question how comparable and reliable they are for use in empirical studies. This study helps structure the field and proposes a more coherent research agenda by identifying four key research puzzles. Future research should concentrate on enhancing ESG measurement, breaking down its components, and crafting tailored approaches for emerging markets. Full article

As global markets navigate the dual transition of digitalization and sustainability, the risk of “digital greenwashing” has emerged as a critical corporate governance challenge. Utilizing a comprehensive dataset of Chinese A-share listed firms from 2018 to 2024—an ideal laboratory characterized by rapid regulatory shifts and unique state-market dynamics that provide highly generalizable insights for other emerging economies—this study empirically investigates whether corporate digital transformation acts as a genuine driver for Environmental, Social, and Governance (ESG) enhancement or merely serves as a symbolic disclosure tool. Fortified by rigorous identification strategies, including Propensity Score Matching and Lewbel heteroskedasticity-based instrumental variable estimations, the results confirm that digitalization serves as an incremental yet statistically significant driver for corporate sustainability. Crucially, mechanism analyses reveal a “full moderation” effect: the positive impact of digitalization on ESG performance is completely activated only in the presence of premium external assurance (e.g., Big 4 audits). Without high-quality IT auditing to act as a credibility enforcer and verify the substance of digital signals, technological adoption alone fails to yield significant ESG improvements. Furthermore, a nuanced structural asymmetry is identified: foundational data infrastructures (Cloud Computing and Big Data) directly enhance quantifiable Environmental and Governance metrics, whereas premium audits are strictly required to activate the “soft,” qualitative Social dimension. Finally, the synergy exhibits distinct boundary conditions. It is heavily concentrated within high-pollution industries where digital transition acts as a regulatory survival imperative rather than mere market expansion, and its reliance on external assurance is fundamentally driven by the market-signaling needs of non-State-Owned Enterprises (non-SOEs) rather than the policy-distorted mandates of SOEs. These findings offer critical theoretical extensions and policy implications for standardizing digital-audit infrastructures globally. Full article

This study assesses how a country’s digitalization impacts sustainability indicators as measured by unmonitored environmental, social and governance (ESG) risks, which serve as a proxy for the development of financial technology (FinTech). The study employs a cross-country approach using data for up to 163 countries, going beyond the firm-level focus of previous studies. The DiGiX Digitalization Index and the ICT Development Index are used to measure digital maturity, while pillar-level indicators and Sustainalytics ESG country risk scores are used to assess ESG indicators. With evidence of nonlinear, threshold-type effects at higher levels of digital maturity, the regression results suggest a strong negative correlation between digital maturity and ESG risk. Different country typologies are further identified using unsupervised cluster analysis, which reveals a continuous digital and ESG gradient in environmental, social and governance aspects. The analysis proves digital maturity serves as a systemic enabler of ESG risk management by strengthening data availability, governance capacity and policy enforcement. These findings provide policy-related guidance for coordinating digitalization strategies in line with the Sustainable Development Goals. Full article

Expanding ESG disclosure mandates under the Corporate Sustainability Reporting Directive (CSRD) and the International Sustainability Standards Board (ISSB) have driven rising demand for artificial intelligence (AI) and data analytics capable of supporting sustainability reporting and verification at scale. Nevertheless, the scholarly literature remains dispersed across discrete disciplinary fields—natural language processing, machine learning, auditing, and regulatory compliance—with limited integrative synthesis. To address this gap, the present study conducts a PRISMA 2020-compliant systematic review of 45 peer-reviewed articles indexed in Scopus and published between 2020 and 2025. The methodology combines bibliometric mapping through VOSviewer with qualitative thematic content analysis. Findings document a rapidly expanding field exhibiting a compound annual growth rate of 91.9%. Four principal thematic dimensions emerge: (i) NLP and text mining for ESG disclosure analysis; (ii) machine learning for ESG scoring and corporate performance; (iii) AI-enabled ESG assurance, auditing, and governance; and (iv) regulatory frameworks and the digital transformation of sustainability reporting. The evidence indicates that AI is progressively reshaping ESG disclosure from a largely narrative and self-reported practice into a data-driven, independently verifiable transparency system. These developments carry substantive implications for regulators, corporate practitioners, assurance providers, and investors seeking to strengthen the reliability and comparability of sustainability disclosures. Full article

This paper explores how green digital technologies (GDTs)—ERP systems, cloud software, IoT, artificial intelligence, and big data analytics—can be used to improve the quality of ESG disclosures of industrial listed companies in the Amman Stock Exchange (ASE). Based on the institutional isomorphism theory, we examine how the relationship between coercive, mimetic, and normative institutional pressures and adopting green technology interacts to effect sustainability reporting practices. Using panel data pertaining to 30 ASE-listed industrial companies during the 2020–2024 period (N = 146 firm-year observations), we applied pooled OLS and random effects frameworks characterized by a strong clustering of standard errors. The findings show that the Green Digital Technology Index is positively and significantly associated with ESG disclosure scores (Pooled OLS: β = 5.448, t = 2.367, p = 0.019; Random Effects: β = 5.941, t = 2.507, p = 0.024), with adopting firms having an average score that is 1.73 points higher. Its largest effect is on the environmental dimension (β = 3.460, p = 0.074). Institutional pressures do not moderate the GDT–disclosure relationship; however, mediation analysis indicated that institutional pressure significantly predicts GDT adoption (β = 0.098, p < 0.001), suggesting that institutional forces are linked to disclosure quality through their association with technology adoption rather than through direct effects, indicating that institutional forces exert their influence through technology adoption. Disclosure quality is negatively associated with CEO duality (β = −4.863, p < 0.001). These results are consistent with the interpretation that green digital technologies serve as a transmission channel through which institutional pressures are associated with enhanced sustainability disclosure in emerging markets. Full article

This study examines the relationship between Environmental, Social, and Governance (ESG) and financial performance in the United Kingdom context, an area of increasing importance in both academic and practical domains. ESG is measured using the London Stock Exchange Group (LSEG) disclosure score. Using a dataset of firms in the FTSE 350 index over a 5-year period from 2020 to 2024, a panel regression model is employed to analyse the relationship between ESG and financial performance. The results of this study are mixed. When using ROA as a proxy for financial performance, the results suggest a statistically significant and positive relationship between ESG and financial performance, although the ESG coefficient indicates a relatively modest effect. However, when ROE is used as a proxy, the results are insignificant, suggesting that the impact of ESG may vary depending on the financial performance measure used. These findings contribute to the literature by providing evidence from the UK during a period of economic disruption, highlighting ESG’s role in operational performance rather than shareholder returns. However, the results should be interpreted with caution due to the use of disclosure-based ESG measures and a limited set of control variables. Full article

This study examines the causal impact of environmental, social, and governance (ESG) ratings on corporate green technology innovation using a panel of Saudi listed firms over the period 2015–2024. Adopting a multi-period difference-in-differences (DID) framework, the analysis evaluates three dimensions of innovation outcomes—quantity, quality, and efficiency (CGTI1–CGTI3). The results show that ESG ratings significantly enhance green technology innovation. Dynamic evidence indicates that these effects strengthen over time, reflecting gradual adjustment in firms’ innovation strategies. Mechanism analysis reveals that ESG ratings promote innovation primarily by alleviating financial constraints and mitigating agency problems. These effects are driven by improvements in the information environment, as ESG ratings reduce information asymmetry and enhance monitoring. From a theoretical perspective, ESG ratings are conceptualized as a digital information infrastructure that reduces informational entropy and provides algorithmic evaluation signals, thereby guiding managerial decision-making in R&D investment and project selection. Robustness tests, including propensity score matching difference-in-differences (PSM-DID), confirm that the results are not driven by selection bias. Focusing on Saudi Arabia under Vision 2030, the findings highlight the role of ESG information systems in shaping green innovation in an emerging market context. Full article

This study examines how internal board governance influences carbon emission disclosure (CED), conceptualized as both a key dimension of ESG transparency and a mechanism for managing disclosure-related risks. Using panel data from 175 listed firms across six ASEAN countries during 2014–2021, we develop a composite Board Effectiveness Score (BES) that integrates five governance attributes: gender diversity, board size, board independence, meeting frequency, and the presence of an environmental committee. Unlike prior single-attribute studies, the BES captures governance complementarities and the interactive effects of board structures. Applying a multi-method empirical framework—including fixed-effects estimation, quantile regression, two-step system GMM, Heckman selection correction, Propensity Score Matching (PSM), and Two-Stage Least Squares (2SLS)—we find that gender-diverse boards, environmental committees, and higher BES values significantly enhance carbon emission disclosure. The results remain robust across alternative disclosure measures and additional econometric specifications, with the strongest effects observed among low- and mid-level disclosing firms. These findings highlight the role of internal board governance as a potential substitute for weak institutional oversight in emerging markets. The study offers practical implications for regulators and investors seeking to strengthen climate transparency, ESG accountability, and governance-based risk management in ASEAN economies. Full article

Supply chain conditions can influence firm risk by shaping operational stability and dependence within customer and supplier relationships. This study examines whether ESG performance mitigates corporate risk in such settings. Using panel data on publicly listed firms, the paper shows that higher ESG scores are associated with lower total volatility, lower idiosyncratic volatility, and lower stock price crash risk. The paper further shows that this risk-reducing effect is more pronounced when firms face greater supply chain dependence or operational instability, as captured by trade credit dependence measures and inventory-based measures. Decomposing ESG into its environmental, social, and governance dimensions, the results show that the stronger risk-mitigating effect of ESG is driven primarily by the governance dimension, with some additional support for the social dimension and relatively weak evidence for the environmental dimension. These findings suggest that ESG is especially valuable in supply chain environments where dependence, instability, and operational frictions are greater. Overall, the results indicate that ESG performance and supply chain conditions jointly shape corporate risk and resilience. Full article

Market-based environmental regulations are increasingly vital for driving green transitions. As a major construction economy and the world’s leading carbon emitter, China launched its Carbon Emission Trading System (CETS) to advance dual-carbon goals and pilot decarbonization in high-emission sectors. Using 2009–2021 data on A-share listed construction enterprises, this study employs a propensity score matching difference-in-differences (PSM-DID) approach to assess CETS’ impact on corporate Environmental, Social, and Governance (ESG) performance. Results show that CETS significantly improves construction enterprises’ ESG performance. Mechanism analysis identifies green technology innovation as a key transmission channel, with government subsidies positively moderating this effect. Heterogeneity analyses reveal stronger policy effects among state-owned enterprises and firms in eastern regions. These findings remain robust under alternative specifications, matching methods, and higher-order fixed effects. This study offers micro-level evidence on how market-based carbon regulations shape corporate sustainability through ESG, informing China’s carbon market refinement and global market-driven decarbonization efforts. Full article

Startup investment decisions are always accompanied by high uncertainty, limited historical data, and the need to simultaneously consider financial performance, sustainability, and innovation. With the rapid expansion of financial technologies, the use of digital decision-support tools to manage this complex environment has become increasingly important. This study presents a multi-objective optimization framework for startup portfolio selection that simultaneously maximizes expected returns, minimizes downside risk using the Conditional Value-at-Risk (CVaR) measure, improves sustainability performance based on ESG indicators, and considers liquidity constraints. The main innovation of this study is the simultaneous integration of financial and non-financial criteria alongside a set of realistic structural constraints, including budget constraints, the number of options available, the concentration ceiling, and the minimum required levels for ESG, innovation, and liquidity. The results show that the proposed model is able to create a transparent balance between return, risk, sustainability, and investment horizon, and by changing the parameters related to risk and sustainability, it can target capital flows towards more innovative startups with higher ESG scores. This framework can be used as a practical tool for investors, digital investment platforms, and policymakers in responsible and data-driven capital allocation. Full article

Despite the rapid institutionalization of ESG reporting mandates worldwide, the empirical question of whether ESG disclosure constitutes a structural, long-run determinant of corporate financial performance—rather than a cyclical or spurious co-trending artifact—remains unresolved. The prior literature predominantly employs short-panel estimators that assume stationarity and conflate long-run equilibrium effects with transitory associations. This study addresses that gap by applying a five-step non-stationary panel econometric framework to a sample of 479 S&P 500 firms across eleven GICS sectors over 2010–2022 (5084 firm-year observations), a period chosen to capture the full institutionalization of Bloomberg ESG reporting standards and to encompass two major macroeconomic stress episodes (the 2015–2016 commodity downturn and the COVID-19 shock). Im–Pesaran–Shin panel unit root tests confirm that ESG disclosure scores and financial performance measures are both integrated of order one. Pedroni residual-based panel cointegration tests decisively reject the null of no long-run relationship (Z = −62.38 for the ROA equation), establishing a stable cointegrating equilibrium. Fully Modified OLS and Dynamic OLS group-mean estimators yield bias-corrected long-run coefficients, and a panel error correction model quantifies short-run adjustment dynamics. The key finding is that a ten-point improvement in ESG disclosure is associated with a permanent nine-to-ten percentage-point gain in return on equity (FMOLS β = +1.023, p < 0.01; DOLS β = +0.914, p < 0.01), while the effect on return on assets is positive but more modest and sensitive to estimator choice. Complementary fixed-effects regressions reveal an asymmetric moderating role of macroeconomic uncertainty: equity market volatility (VIX) amplifies the ESG performance premium, whereas acute credit market stress (TED spread) attenuates it. Board governance variables are statistically insignificant across all five specifications, indicating that H3 (board governance) is not supported; this outcome is attributed to limited within-firm governance variation in the large-cap S&P 500 universe rather than a genuine absence of governance effects. The results are robust to lagged ESG measurement, winsorization, and alternative interaction specifications. The findings provide strong econometric evidence for the structural, permanent nature of the ESG–financial performance link in large-cap U.S. equities, with direct implications for mandatory disclosure policy and ESG-integrated investment strategies. Full article