Search Results (1,886)

While Environmental, Social, and Governance (ESG) criteria are extensively utilized for corporate evaluation, empirical evidence regarding sovereign ESG efficiency remains scarce. Existing national sustainability indices often fail to account for how effectively a nation translates its economic resources into ESG outcomes. This study proposes a two-stage Data Envelopment Analysis (DEA) framework to evaluate the efficiency of 38 OECD countries in 2020. The national production process is decomposed into two sequential phases: (1) Economic Efficiency, transforming resource inputs (labor and energy) into intermediate economic outputs (GDP and trade openness), and (2) ESG Transformation Efficiency, converting those intermediate outputs into a composite ESG score. A novel quartile-based classification scheme is further applied to categorize countries into strategic groups for benchmarking. Empirical results reveal significant heterogeneity across the OECD. Estonia, Iceland, and Latvia emerge as “Win–Win” benchmarks, demonstrating high efficiency in both economic production and ESG transformation. Conversely, the United States is classified as a “Laissez-faire” member, exhibiting low performance in both stages relative to its capacity. Additionally, second-stage regression analysis indicates that while higher income is negatively associated with ESG transformation efficiency, government effectiveness acts as a significant positive driver. This research contributes a transparent, reproducible framework for sovereign ESG analytics that relates outcomes directly to economic capacity. It provides policymakers with an interpretable benchmarking tool to identify national sustainability gaps and facilitates actionable insights for enhancing public-sector effectiveness in achieving ESG goals. Full article

Sustainable Supply Chain Management (SSCM) increasingly integrates environmental, social, and governance (ESG) criteria to address sustainability risks and performance across multi-tier supply networks. However, it remains unclear whether ESG practices directly enhance supply chain outcomes or primarily operate through the development of higher-order management capabilities. This study examines how ESG practices influence supply chain resilience, operational performance, and sustainability performance in the Mexican aerospace industry, emphasizing the mediating role of Sustainable Supply Chain Management Capability (SSCM Capability). Data were collected through a structured survey administered at the Mexico Aerospace Fair (FAMEX) in April 2025, yielding 217 valid responses from Tier 1–3 aerospace firms. The research adopts a hypothesis-driven design integrating Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA) to combine sufficiency- and necessity-based perspectives. The findings show that ESG practices primarily create value by enabling SSCM Capability, which is central to improving all performance dimensions. While ESG practices directly contribute to operational and sustainability performance, resilience improvements depend mainly on capability development. NCA results further indicate that ESG practices are foundational to SSCM Capability and high performance, whereas SSCM Capability constitutes a necessary condition for resilience. These findings underscore the critical role of capability building in translating ESG commitments into robust supply chain performance within compliance-intensive aerospace ecosystems in emerging economies. Full article

(1) Background: In integrated financial markets where traditional diversification often fails, analyzing sustainability-oriented investments under non-linear dynamics is critical to averting erroneous decisions. This study investigates whether corporate sustainability provides effective downside mitigation against volatility in emerging markets, using Borsa Istanbul as a case study. (2) Methods: The analysis employs US Dollar-denominated excess returns of an equal-weighted portfolio from the longest-tenured BIST Sustainability Index constituents versus the broader BIST 100 Index (2014–2025), utilizing Markov Regime Switching (MS-AR) and Regime-Switching CAPM methodologies to model non-linear dynamics. (3) Results: Empirical results reveal two distinct regimes, where market variance surges approximately 8.5-fold during crises. The sustainable portfolio exhibits a low systematic risk sensitivity (Beta: 0.76) in normal conditions, driven by its distinct structural composition without generating statistically significant Alpha. In crisis regimes, despite increased sensitivity (Beta: 0.90), the portfolio remains resilient with a beta strictly below 1.00. While BIST 100 investors suffered a massive 40.86% USD wealth erosion over the full period, the sustainability portfolio significantly mitigated this damage, limiting the total capital loss to 20.73% due to substantial compounding accumulated during normal regimes. (4) Conclusions: Consequently, sustainability proves to be not merely an ethical preference but a rational financial strategy offering diversification benefits in tranquility and acting as an effective partial hedge during turbulence in high-volatility markets. Full article

This study examined the influence of Environmental, Social, and Governance factors on the financial performance of companies listed on the Saudi Stock Exchange (Tadawul). Employing a panel data approach, the analysis covers 450 firm observations collected annually during the period 2018–2023. Financial performance is measured using Return on Assets (ROA) and Return on Equity (ROE), while ESG disclosure scores are disaggregated into their three constituent pillars. Firm size, revenue per share, and leverage are incorporated as control variables. The fixed effects regression results reveal that social factors demonstrate statistically significant positive relationships with both ROA and ROE, supporting the stakeholder theory-based perspective that strong social practices enhance operational efficiency and investor confidence. Conversely, environmental and governance factors exhibit no significant association with either financial performance metric within the study period. Leverage shows a significant negative relationship with ROA but not with ROE, while revenue per share consistently demonstrates strong positive associations with both performance measures. These findings contribute to the limited literature on ESG–performance linkages in Gulf Cooperation Council markets and offer important implications for corporate managers, investors, and policymakers seeking to advance sustainability objectives within the framework of Saudi Vision 2030. Full article

Sustained innovation is pivotal for establishing long-term technological advantages and ensuring corporate sustainability, which holds particular significance for “specialized, refined, unique, and innovative” (SRUI) enterprises that concentrate on niche segments and are innovation-intensive. Grounded in signaling theory and principal–agent theory, and situated within the practical context of financing constraints, this paper investigates how environmental, social, and governance (ESG) performance contributes to sustaining innovation in such firms. Using panel data from Chinese SRUI enterprises between 2010 and 2023, we measure sustained innovation along two dimensions: sustained innovation input and sustained innovation output. The results demonstrate that ESG performance significantly enhances sustained innovation among SRUI enterprises. Mechanism analysis reveals that ESG operates through three pathways: optimizing talent structure, mitigating managerial myopia, and strengthening working capital management. Heterogeneity tests further indicate that the positive effect of ESG on overall innovation sustainability is stronger with a younger management team and lower government subsidies. Moreover, in firms with heightened climate risk perception, ESG strongly promotes the sustained innovation input but exhibits a weaker effect on the continuity of innovative output. In enterprises with stronger big-data technology application capabilities, ESG significantly improves the continuity of patent output yet does not significantly affect the continuity of innovative input. This study extends the literature on the economic consequences of ESG from the perspective of sustained innovation, while providing new mechanistic evidence for understanding how highly specialized small and medium-sized enterprises build long-term innovation capacity. Full article

Promoting substantive green innovation is the core pathway for enterprises to achieve sustainable development. However, its inherent characteristics of high investment and high risk often result in insufficient innovation motivation among enterprises. Rooted in the Resource-Based View (RBV) and Dynamic Capability Theory (DCT), the research investigates the influence of underlying technology digital transformation on enterprises’ substantive green innovation. Using panel data from Chinese A-share listed firms (2009–2024), this analysis reveals a significant promotional effect of underlying technology digital transformation on substantive green innovation. The robustness of this conclusion is confirmed by a battery of tests. Mechanism analysis demonstrates that this effect functions mainly through two pathways: “technology empowerment” and “governance optimization”, namely enhancing corporate R&D capability and improving ESG performance. Heterogeneity analysis further indicates that this promotional effect is more prominent in enterprises with higher environmental disclosure levels and better internal control quality. This study elucidates the internal mechanism and boundary constraints by which underlying technology digital transformation empowers substantive green innovation, thereby offering micro-level evidence for comprehending the in-depth integration of digital technologies and eco-friendly development. The findings offer important practical implications for firms in formulating effective “digitalization–greenization” synergy strategies. Full article

This paper examines the connection between Environmental, Social, and Governance (ESG) factors and the risk of geopolitics, as defined by the Geopolitical Risk (GPR) index. The concept of geopolitical risk is conventionally defined as the direct result of political incidents, war, and international tensions. The current study argues that the concept should be understood in a more structural and sustainable manner, relating to the underlying forces driving geopolitical risk. The main research question is whether and how the three pillars of ESG factors contribute to explaining and understanding cross-country and over-time variations in geopolitical risk. In an effort to avoid information loss associated with the ESG index’s aggregate nature, the three factors are considered separately and the three pillars are analyzed individually. The empirical context is a balanced cross-country panel dataset including 42 countries over the 2000–2023 time period. Data for the three factors are obtained from the World Bank dataset to standardize and compare data across countries and over time. The GPR index measures the level of geopolitical risk and is defined by Dario Caldara and Matteo Iacoviello. The GPR index captures the level of geopolitical tensions by analyzing media signals. The combination of the three sources enables direct connections and correlations among the three factors and the internationally recognized GPR index. The paper uses an integrated methodological approach that combines results from three distinct methods. The first method uses panel data analysis to estimate average marginal effects while controlling for unobserved heterogeneity. The second method uses clustering to identify structural patterns and divide countries into groups based on their unique characteristics and risk profiles. The third method uses machine learning regressions and nonparametric analysis to capture the complex relationships and interactions in the data. The three-step method is used for each pillar to ensure consistency and comparability. The results suggest that the three factors contribute to the GPR index in a unique manner. The environment and energy structure contribute to the GPR index as a risk multiplier; the social factor relates to exposure to instability; and the governance factor is a central stabilizing factor. The paper makes a unique contribution to the literature by defining the three factors and their relationship to the GPR index in a clear, sustainable manner. Full article

This study focuses on the impact of the audit committee features on the quality of environmental, social, and governance (ESG) disclosure of the Saudi Stock Exchange-listed companies. Grounded in agency theory, stakeholder theory, and resource dependence theory, this research considers key audit committee characteristics, such as independence, expertise, and tenure, to determine the manner in which they contribute to the improvement of ESG disclosure through enhanced monitoring, accountability, and access to critical reporting-related resources. This study employed a regression model as a hypothesis-testing model using panel data of 78 Saudi-listed firms, which represent 234 firm-years until 2023. ESG disclosure quality is measured using the standardized ESG score obtained from the Refinitiv Eikon database. The results indicate that a positive and statistically significant relationship exists between ESG disclosure quality and audit committee independence and expertise. Conversely, the tenure of audit committees has a negative relationship with ESG disclosure quality. This research contributes to the ESG and corporate governance literature by extending audit committee research beyond traditional financial reporting oversight into ESG oversight in an emerging-market context, and by providing context-specific evidence from Saudi Arabia, where ESG reporting frameworks and enforcement mechanisms are still evolving. Practically, the implications of the findings provide useful recommendations to regulators and firms that intend to enhance their governance practices in accordance with the Saudi Vision 2030 and reforms at the Capital Market Authority. Full article

Strengthening transparency has emerged as a pivotal issue in promoting the responsible development of artificial intelligence (AI). As the prevailing framework for corporate information disclosure, Environmental, Social, and Governance (ESG) reporting shares an inherent synergy with AI governance; both are rooted in the pursuit of sustainable development and the disclosure of specific matters to investors and broader stakeholders. This study analyzes the status of artificial intelligence (AI) information disclosure in the ESG (Environmental, Social, and Governance) reports of listed companies across the United States, Europe, and China, finding that: (1) ESG reports have emerged as a primary channel for business organizations to disclose AI-related information; (2) significant disparities exist in disclosure levels across four key AI-related domains—development, application, manufacturing, and consumption; and (3) disclosure density varies considerably across E, S, and G dimensions, with the Governance (G) pillar exhibiting the most comprehensive information. Based on an empirical analysis of the ESG-AI disclosure framework, this study proposes an optimization scheme for ESG-AI reporting, clearly defining mandatory ESG-AI disclosure obligations for listed companies and employing the “comply or explain” mechanism to balance corporate transparency with operational efficiency while adhering to the “Double Materiality” principle by disclosing model training energy consumption and ecological impacts under Environmental (E) matters, addressing employment, employee training, marketing labeling, and customer privacy under Social (S) matters, and elaborating on corporate AI strategies, risk management protocols, and governance policies under Governance (G) matters. Regarding procedural safeguards, taking China as a case study, centralized disclosure could be implemented through the National Enterprise Credit Information Publicity System, complemented by an assurance system for listed company reports to enhance the accessibility and accuracy of information disclosure. Full article

This study empirically investigates how Environmental, Social, and Governance (ESG) discourses among major Korean Business-to-Business (B2B) corporations (POSCO, LG Chem, and HD Hyundai) were reconfigured in the context of former President Trump’s re-election campaign and the 2024 U.S. presidential election. The observation periods were divided into the Pre-Trump period (1 May 2023 to 30 April 2024) and the Post-Trump period (1 May 2024 to 30 April 2025). External discourses were examined using social media, news, and blog posts, while internal discourses were analyzed through the CEO’s New Year addresses from 2021 to 2025. Keyword frequency analysis and co-occurrence network analysis, conducted via the ‘Sometrend’ platform, were combined to trace structural transitions in corporate discourses. The results show that: (1) the relative share and network centrality of environmental (E) keywords declined in the Post-Trump period, with several environmental terms losing core positions and becoming peripheral or bridging nodes, while policy- and economic-related terms increased; (2) social (S) and governance (G) keywords appeared only sporadically and remained peripheral across periods; (3) temporal concentrations of policy–economic keywords coincided with significant political and market-related events, such as financial volatility in 2023 and the tariff policy announcement in February 2025, indicating temporal alignment rather than deterministic causality; (4) firm-level differences were evident: POSCO exhibited the most pronounced structural shift, LG Chem’s discourses increasingly emphasized supply chain and investment-related terms alongside environmental keywords, and HD Hyundai showed a shift toward more risk- and operation-oriented keywords in the later period; and (5) CEO New Year addresses displayed directionally consistent patterns with external discourse, supporting cross-textual alignment. These findings demonstrate that ESG discourse is not a fixed normative language but a strategically adaptive frame that varies according to political–economic contexts and industrial conditions. The relative weakening of the environmental frame in terms of discourse centrality, alongside the strengthening of the policy–economic frame, differed by industry, reflecting variations in regulatory exposure and operational characteristics. By observing ESG discourses longitudinally and comparatively, this study provides empirical evidence of how political and industrial dynamics reshape corporate discourses and CEO communication. Moreover, keyword frequency and co-occurrence network analysis are validated as effective methods for identifying discourse shifts, offering both academic contributions and practical implications for corporate communication analysis. Full article

Achieving simultaneous control over total carbon emissions and intensity is essential for China’s dual carbon goals. Using panel data from 1235 listed manufacturing firms (2015–2022), we construct a composite index to measure dual carbon control and investigate how data elements influence corporate carbon performance from an industry heterogeneity perspective. The main findings are as follows. (1) Data elements significantly enhance dual carbon control, with effects concentrated in high-pollution sectors, particularly metallurgy and mineral products, while remaining insignificant in low-pollution industries. (2) Mechanisms differ across industry types: capacity utilization drives improvements in high-pollution industries, whereas green technology innovation matters in low-pollution sectors such as agro-processing and textiles. (3) ESG disclosure and green credit subsidies amplify these effects, though with varying efficacy. Policymakers should adopt differentiated strategies including removing structural barriers to green innovation in high-pollution industries and activating capacity utilization through monitoring standards and technology markets in low-pollution sectors. A tailored policy framework is essential to realize the full potential of data elements in advancing China’s dual carbon goals. Full article

This study develops an integrated decision-support framework to advance green supply chain management (GSCM) by systematically linking Environmental, Social, and Governance (ESG) practices, environmental product innovation, corporate performance, and strategic alternatives. Employing the Analytic Network Process (ANP), the proposed model captures complex interdependencies and feedback relationships across life-cycle value chain stages, enabling a holistic evaluation of sustainability-oriented strategies. A Delphi panel comprising 15 experts from academia, industry, and government is used to validate the evaluation criteria and network structure. The empirical results indicate that eco-friendly design, energy and resource efficiency, and carbon–climate management are the most influential drivers shaping green supply chain performance. Moreover, operational and sustainability performance are found to exert greater strategic importance than short-term financial performance, highlighting GSCM as a long-term capability-building approach rather than a cost-centered initiative. To enhance analytical adaptability, this study proposes a conceptual extension integrating neural feature extraction (NFE) signals with ANP-based expert weights. The NFE module is not empirically trained or validated; rather, it illustrates a theoretically consistent mechanism for incorporating data-driven feature signals into structured multi-criteria decision frameworks. Empirical validation of the NFE component is proposed as a future research direction. Full article

In the context of a deep structural adjustment of China’s real estate sector and heightened macroeconomic uncertainty, quantitatively assessing the resilience of listed real estate enterprises is crucial for preventing systemic risk and promoting sustainable development. This paper proposes a multidimensional resilience evaluation framework for 37 Chinese A-share listed real estate firms using panel data from 2017–2024. An index system covering four dimensions—solvency and liquidity, profitability and cash flow, operational efficiency and asset structure, and growth and value—is constructed on the basis of financial ratios. The entropy-weighted TOPSIS method is employed to derive a composite resilience index, while principal component analysis (PCA) provides a complementary robustness check of the rankings. The empirical results indicate that (1) operational efficiency and asset structure receive the highest objective weight, followed by solvency and liquidity, whereas the weights of profitability, cash flow, and growth–value dimensions are relatively lower; at the indicator level, accounts receivable turnover, inventory turnover and the cash-to-short-term-debt ratio play a leading role, underscoring the central importance of liquidity safety and asset turnover under the “three red lines” regulatory regime. (2) Firms such as Shahe Co., Shenzhen, China, Huafa Co., Zhuhai, China and Wantong Development, Beijing, China exhibit persistently higher resilience scores, characterized by lower leverage, stronger cash buffers and faster operating turnover, whereas firms such as Yunnan Metropolitan Investment, Kunming, China, Greenland Holdings, Shanghai, China, Bright Real Estate, Shanghai, China and Rongsheng Development, Langfang, China remain at the lower tail of the resilience distribution with high leverage, tight liquidity and volatile profitability. (3) The resilience rankings obtained from entropy-weighted TOPSIS and PCA are positively and significantly correlated at the 1% level, suggesting a moderate level of consistency between distance-based and variance-based evaluation schemes. Building on these findings, this paper proposes resilience-oriented policy recommendations for regulators and managers in terms of differentiated prudential regulation, capital-structure and debt-maturity optimization, operational efficiency enhancement, and the integration of digital transformation and ESG governance. Full article

Generative AI has surfaced as a key driving force for corporate sustainable development and strategic transformation, offering new perspectives for effectively enhancing corporate ESG performance practices. Utilizing panel data sourced from Chinese A-share listed firms spanning the years 2012 to 2024, this research establishes and substantiates a model elucidating the mechanism by which generative AI impacts corporate ESG performance. The findings reveal the subsequent points: First, generative AI can effectively drive improvements in corporate ESG performance. Second, the caliber of information disclosure acts, in part, as an intermediary factor influencing the correlation between generative AI and corporate ESG performance enhancement. Third, sustainable innovation partially mediates the relationship between generative AI and corporate ESG performance enhancement. Fourth, environmental regulations weaken the beneficial influence exerted by generative AI on a company’s ESG achievements. Fifth, compared to non-manufacturing firms, companies situated in the central and western parts of China, and non-technology-intensive firms, the application of generative AI exerts a more pronounced enhancing impact on ESG achievements in manufacturing firms, firms in eastern regions, and technology-intensive firms. The research findings provide new insights for improving corporate ESG performance and provide strategic guidance for businesses aiming to attain long-term sustainable growth through reliance on generative AI. Full article

Small and medium-sized enterprises (SMEs) play a central role in economic development but face distinctive challenges in adopting environmental, social, and governance (ESG) practices. While existing research identifies key drivers and barriers, there remains limited understanding of how SMEs navigate competing pressures and implement ESG in practice across different institutional contexts. This study addresses this gap by examining ESG adoption in SMEs across Ireland, Germany, Poland, and Türkiye through the lens of Activity Theory (AT). Using a qualitative multiple-case design, we draw on semi-structured interviews with SME owner–managers, ESG experts, and vocational education and training (VET) stakeholders (N = 44). Findings show that ESG engagement in SMEs is shaped by leadership framing, resource constraints, and increasing external pressures from customers, regulators, and financial institutions. ESG practices are uneven across pillars, with environmental initiatives the most developed, social practices emerging, and governance largely limited to compliance. AT highlights how persistent contradictions, such as tensions between short-term survival and long-term sustainability, or between complex regulatory demands and limited organisational capacity, shape SME responses. When supported by appropriate mediating artefacts, including training, simplified frameworks, financial incentives, and networks, these contradictions can enable learning and more strategic ESG integration. Cross-country differences reflect variations in ecosystem maturity, which condition whether ESG engagement stabilises at compliance or develops toward operational and strategic integration. The study contributes a theory-driven, practice-based explanation of SME ESG adoption, including a typology of compliance-oriented, operational, and strategic engagement modes, and offers insights for policymakers, educators, and support organisations seeking to promote more effective and context-sensitive sustainable SME transformation. Full article