Search Results (792)

China’s dual-carbon goals require firms to pursue low-carbon transformation, while digital infrastructure offers new opportunities for corporate emission reduction. Using data from Chinese A-share listed firms from 2010 to 2024, this study treats the establishment of National Big Data Comprehensive Pilot Zones (NBDCPZ) as a quasi-natural experiment and applies a multi-period difference-in-differences model. The results indicate a statistically significant negative relationship between policy and estimated corporate carbon emissions. This result remains robust to parallel-trend tests, propensity-score-matching difference-in-differences (PSM-DID) estimation, and lagging control variables by one period. Mechanism tests suggest that the policy is negatively associated with estimated corporate carbon emissions through pathways consistent with green innovation, digital transformation, and easing financing constraints. Heterogeneity analysis indicates stronger effects among firms in highly competitive industries, non-heavy-polluting sectors, and southern China. Moreover, the pilot policy enhances corporate Environmental, Social, and Governance (ESG) performance. Overall, this study provides evidence that big-data-related policies can facilitate corporate decarbonization and offers policy implications for carbon reduction through data sharing, openness, and governance. Full article

Sustainability policies introduced under the European Green Deal have strengthened climate-related disclosure requirements for agri-food companies. In particular, the Corporate Sustainability Reporting Directive requires in-scope companies to transparently disclose information on their environmental performance. However, the academic literature on decarbonisation in the olive oil sector remains fragmented. This systematic literature review synthesises findings by considering cultivation, milling and retail, and waste management as interconnected stages of the olive oil supply chain and by developing a matrix linking decarbonisation strategies to the relevant European Sustainability Reporting Standards (ESRS) environmental, social and governance (ESG) topics. Following the PRISMA protocol, 42 peer-reviewed studies from Scopus and Web of Science were included in the final synthesis, covering cultivation (RQ1), milling and retail (RQ2), and waste management (RQ3). The cultivation stage represents an important part of the emission profile of the chain while also offering potential for carbon sequestration through sustainable management practices, such as reduced tillage, cover crops, organic amendments and biochar application. In the downstream stages, the mill and its retail interface rely on a different set of measures, including two-phase extraction, rooftop photovoltaic systems, thermal recovery from pits, and lighter bottles transported in bulk. Waste management also offers opportunities to recover value from pomace, mill wastewater and pruning waste through biogas, biochar, compost or phenolic extracts. The potential for a net-negative carbon balance is context-dependent and varies with system boundaries, the balancing period, functional units, and the methods used to account for carbon sequestration. The matrix offers a clear classification of decarbonisation strategies and ESRS topics, opening valuable avenues for upcoming studies to extend its practical utility. Full article

Balancing production resilience with environmental, social and governance (ESG) performance is difficult when disruptions, policy constraints and stakeholder expectations interact over time. This paper proposes a six-node dynamic network data envelopment analysis architecture whose admissible weight intervals are adjusted by an LSTM learner using IoT-derived shock states. The application covers 96 aggregate monthly periods from 2018 to 2025 across three countries and four technology-based manufacturing groups. Figure-grounded diagnostics indicate mean resilience scores of 0.7016 for the basic IoT-DEA benchmark and 0.7134 for the complete model (paired difference = 0.0118; 12-month moving-block bootstrap 95% CI = 0.0015–0.0245; p = 0.001), while mean uncertainty falls from 0.0536 to 0.0205, a 61.8% reduction. Threshold sensitivity shows that governance-delay and skill boundaries vary by industry and carbon-constraint severity rather than constituting universal standards. In the calibrated policy simulation, the combined carbon-tax and green-subsidy path reaches approximately 0.90 by month 96, compared with 0.79 under no policy; this contrast is interpreted as a scenario result, not a firm-level causal treatment effect. NSGA-III and SHAP then connect the measured constraints to Pareto-efficient portfolios and sector-specific managerial priorities. The framework’s main supported contribution is more stable, temporally explicit ESG-resilience diagnosis with transparent limits on causal and cross-sectional inference. Full article

As a widely recognized measure of corporate sustainability, ESG performance exerts a significant influence on corporate exports and risk-coping capabilities. Using product–destination-level panel data of Chinese listed firms from 2009 to 2016, compiled from the China Customs Database and the CSMAR Database, this paper employs the High-Dimensional Fixed Effects (HDFE) model to empirically examine the impact of ESG performance on corporate export resilience and its underlying mechanisms. The findings reveal that improved ESG performance significantly strengthens firm export resilience, a conclusion that remains robust after a series of robustness checks and addressing endogeneity concerns. ESG performance directly enhances export resilience through its environmental, social, and governance dimensions, with the social dimension exhibiting the strongest effect. Mechanism analysis indicates that ESG performance enhances export resilience by promoting diversification in both export products and export markets. Heterogeneity analysis reveals that the effect varies significantly across countries, products, and firms. Specifically, the positive effect is more pronounced for exports to developed countries, Belt and Road Initiative (BRI) participating countries, and coastal countries. Moreover, ESG performance contributes more strongly to the export resilience of final goods, high-technology products, and products with comparative advantages. At the firm level, the enhancing effect is more evident for state-owned enterprises, capital-intensive firms, and large-scale enterprises. Further analysis reveals that ESG performance and export resilience exhibit a positive joint effect in enhancing overseas market profitability and overseas revenue sustainability. These findings offer actionable implications for policymakers and exporters aiming to embed ESG principles into their export operations, which may further facilitate the sustainable and high-quality transformation of foreign trade. Full article

More than one type of policy is necessary to advance the sustainability transition and stimulate innovation. However, limited empirical evidence exists regarding the synergistic effects of environmental and innovation policies on corporate green innovation. Using data on Chinese listed companies in heavy-pollution industries from 2007 to 2022 as samples, this study employs a multi-phase difference-in-differences (DID) approach to examine the synergistic effect of China’s Innovative City Pilot Policy (ICPP) and Low-Carbon City Pilot Policy (LCPP) on corporate green innovation. The results show that the ICPP-LCPP synergy promotes green innovation among enterprises in heavily polluting industries. Further analyses reveal that this effect is concentrated among leading enterprises, with large state-owned leading enterprises (LSLEs) exhibiting a particularly pronounced response. Meanwhile, environmental, social, and governance (ESG) performance positively moderates the relationship between the ICPP–LCPP synergy and green innovation among leading enterprises. Green innovation by leading enterprises has a positive effect on follower enterprises’ green patent grants, particularly green invention patent grants. This study provides important insights into how policy synergy can foster corporate green innovation and facilitate a collaborative sustainability transition involving both leading and follower enterprises. Full article

We examine whether digital industry cluster policy is associated with corporate environmental, social, and governance (ESG) performance. We study digital industry clusters within China’s Innovative Industrial Cluster program, a spatial industrial policy combining cluster designation, fiscal support, digital infrastructure, and innovation platforms. Using Chinese A-share listed firms from 2009 to 2023, we exploit staggered cluster designation across cities and estimate difference-in-differences models with firm and year fixed effects. Cluster designation is associated with higher ESG scores, mainly through the governance dimension and, to a lesser extent, the environmental dimension. Additional analyses show that treated firms receive more government innovation subsidies, face lower financing constraints, and increase R&D intensity, consistent with resource provision channels. The results are robust to industry-by-year and province-by-year fixed effects and to wild cluster bootstrap inference. Effects are stronger for firms with greater market attention and in high-technology industries, and larger in regions with weaker digital infrastructure. The findings provide firm-level evidence on how spatially targeted digital industrial policy may support corporate sustainability practices. Full article

Environmental, Social, and Governance (ESG) ratings increasingly shape capital allocation, corporate strategy, and regulatory oversight, yet their credibility is constrained by methodological opacity, rating divergence, and greenwashing risk. Prior reviews treat machine learning (ML) in ESG as a prediction problem. We identify an emerging research trajectory in which ML is increasingly used not only to consume ESG signals but also to verify their construction and credibility. Drawing on signaling theory, we conduct a PRISMA-guided systematic review of 127 peer-reviewed studies from Scopus and Web of Science to examine how machine learning (ML), deep learning (DL), Natural Language Processing (NLP), and Explainable AI (XAI) are transforming ESG rating analysis. We develop a tripartite framework classifying studies by the functional role of the ESG score: predicted (n = 29), used (n = 57), or assessed (n = 41). Our central contribution is the first synthesis of the methodological-assessment stream, organized into four clusters: XAI reverse-engineering of proprietary scoring functions, divergence reconciliation, greenwashing detection, and unsupervised industry-materiality clustering. The evidence assembled in this stream indicates that ESG ratings weight low-cost aspirational disclosure heavily relative to costly performance evidence, suggesting that greater reliance on aspirational disclosure relative to performance evidence may increase greenwashing risk, consistent with signaling-theory concerns. A study-level validation appraisal further shows that the most extreme fit statistics often arise in target-proximal reconstruction or non-temporal validation settings, cautioning against interpreting high R² as evidence of transferable out-of-time forecasting. Full article

Lending to small and medium-sized enterprises (SMEs) on the basis of their environmental, social, and governance (ESG) performance is difficult for commercial banks. The data needed for a proper assessment are rarely at hand, and existing tools cannot capture experts’ fuzziness, complex hesitation, and preference characteristics at the same time. This paper introduces the probabilistic picture hesitant fuzzy set (PPHFS) into SME ESG evaluation and develops a multi-attribute group decision-making (MAGDM) method that rests on the correlation coefficient of PPHFSs. The method has three components. It first defines the information energy of PPHFSs, builds a correlation measure on that foundation, and then derives several correlation coefficients together with their weighted forms. A separate procedure converts the multi-dimensional voting information that evaluators provide through questionnaires and balloting into probabilistic picture hesitant fuzzy information, which keeps the approach close to practice. These components are assembled into a complete MAGDM framework for banks and illustrated on a numerical case of five SME loan applicants. Sensitivity analysis and comparative experiments corroborate the feasibility and effectiveness of the method. By aligning bank credit decisions with ESG screening, the framework supports the extension of green credit to SMEs and contributes to sustainable finance and the Sustainable Development Goals (SDGs). Full article

This study examines the joint and interactive effects of environmental, social, and governance (ESG) performance and digital transformation on firm value by using a sample of 64 non-financial firms listed on the Saudi Exchange over 2020–2024. The empirical analysis employs panel data techniques, feasible generalized least squares (FGLS), Driscoll–Kraay standard errors, and two-stage least squares (2SLS) estimation. The results show that ESG performance is positively associated with firm value, which suggests that capital markets reward firms for sustainability activities. Digital transformation also shows a positive association with firm value and is consistent with its role as a driver of firm valuation. The positive interaction between ESG and digital transformation suggests that digitalization reinforces the association between ESG practices and firm value. The findings remain robust across alternative model specifications and firm value measures. Digital transformation is measured with a text-based disclosure index built from digital-related keywords in annual reports. The index captures disclosed digital orientation rather than realized digital capability, so a high disclosure frequency may partly reflect signalling or impression management rather than fully deployed digital infrastructure. The findings show the importance of adding digital strategies to sustainability practices and provide useful implications for managers, investors, and policymakers under Saudi Vision 2030. Full article

Small and medium-sized enterprises (SMEs) play a pivotal role in advancing sustainability, yet many struggle to translate voluntary sustainability practices into structured, strategic business models. This study examines how this gap can be bridged between voluntary certification frameworks and emerging regulatory requirements, with a specific focus on workforce-related sustainability reporting under the European Sustainability Reporting Standards (ESRS). Using a qualitative case study of a Green Globe-certified, family-owned hotel, the research conducts a comparative gap analysis between existing organisational practices and corporate disclosure requirements, applying a Policy–Action–Target–Metric (PAT&M) framework. The findings reveal strong alignment in Policies and Actions (89%) but limited alignment in Targets and Metrics (14%), indicating a gap between sustainability activities and strategic performance management. The results highlight the need to transition from compliance-oriented initiatives to integrated, data-driven management systems. The findings also suggest that voluntary certification schemes, such as Green Globe, can be a useful first step in order to achieve better corporate reporting capabilities related to environmental, social and governance (ESG) issues. As practical implications, a roadmap solution is proposed to support system-level integration, transparency, and measurable outcomes for better business resilience. Full article

This study examines whether investor attention and the market information environment transmit environmental, social, and governance (ESG) information into stock returns. The analysis employs a balanced panel of 31 mining companies listed on the Indonesia Stock Exchange from 2019 to 2023, comprising 155 firm-year observations. ESG performance is measured using an external ESG score, investor attention is proxied by the Google Search Volume Index, and the information environment is captured inversely by the relative bid–ask spread. Firm fixed-effects models with heteroskedasticity-robust standard errors clustered at the firm level are estimated for the investor-attention, spread, and stock-return equations. Indirect effects are assessed using 5000 firm-level cluster-bootstrap replications. The results show that ESG performance is not significantly associated with contemporaneous stock returns. ESG is positively but only marginally associated with investor attention and significantly associated with a narrower relative bid–ask spread, indicating a more favourable information environment. Investor attention and the relative spread are significantly associated with stock returns. However, neither the attention-mediated effect nor the spread-mediated effect is statistically significant. These findings distinguish ESG signal recognition from signal pricing, showing that ESG information can influence investor attention and the market information environment without forming a statistically significant transmission mechanism to contemporaneous stock returns. Full article

Global seaports play a pivotal role in international supply chains; however, prevailing port performance evaluation frameworks remain predominantly intraport-oriented, limiting their capacity to support sustainability transitions and the integration of Environmental, Social, and Governance (ESG) criteria. Although ports are increasingly conceptualised as multiscale systems embedded within maritime and inland networks, existing approaches remain fragmented across intraport, foreland (seaside connectivity) and hinterland dimensions. Using a systematic literature review following PRISMA 2020, combined with bibliometric mapping through VOSviewer and covering 2019–2024, this study adopts a two-stage analytical design. First, a broad corpus of 238 peer-reviewed articles is used to develop a six-category port performance framework. Second, this corpus is refined to 95 articles focused on container ports, examined by integrating six methodological approaches with three spatial scales. This layered design ensures that the broad corpus defines the categories, while the refined corpus supports the multiscale application of the matrix. The findings reveal a persistent dominance of intraport-focused and efficiency-oriented approaches, alongside limited integration across spatial scales. Sustainability and governance perspectives are increasingly present but remain weakly connected to logistics network performance and rarely operationalise ESG criteria. The study develops a Multiscale Diagnostic Matrix that synthesises the literature and diagnoses fragmentation in port performance evaluation. Full article

Environmental, social, and governance (ESG) considerations and sovereign credit risk have reshaped how bank-level risk is understood in emerging markets. This paper examines the determinants of idiosyncratic volatility (IVOL) in Halkbank, the Turkish state-owned commercial bank with the highest public float. Using quarterly data from 2009Q1 to 2024Q3, we isolate IVOL from a Fama–French five-factor model constructed for Halkbank and estimate a two-regime Markov switching regression (MSR), with a dynamic ordinary least squares (DOLS) model as a robustness check. Sovereign credit default swap (CDS) spreads are positively associated with IVOL, and the association is larger in the high-volatility regime. ESG performance is negatively associated with IVOL, and this association is also stronger in the high-volatility regime. Wald tests confirm that both the CDS and ESG coefficients differ significantly across regimes, indicating that the relationships are state-dependent rather than constant. Bank-specific fundamentals and macroeconomic indicators are not statistically significant once sovereign risk and ESG are included. A Hansen parameter-instability test supports a long-run cointegrating relationship, and the DOLS estimates are consistent with the MSR results. The findings have implications for risk management, investment, and supervision in bank settings characterised by state ownership and strong sovereign-bank linkages. Full article

In recent times, with increasing awareness of sustainable development, environmental, social, and corporate governance (ESG) performance has emerged as an important factor in achieving sustainable development. In the current literature, the determinants of ESG performance are mostly considered at the macro level, while the impact of firm-specific factors remains limited. To fill the gap in the literature, this study uses panel data from 2014 to 2023, focusing on 89 global firms, and applies the GMM approach to examine the impact of firm-specific factors on firms’ ESG performance. The findings reveal that ESG performance demonstrates strong continuity. Furthermore, the effects of financial indicators on ESG performance differ. While return on assets and capital expenditures negatively impact environmental performance, return on equity positively affects liquidity, firm size, and market capitalization for some ESG dimensions. Conversely, the total debt to total equity has a negative impact on social performance. The findings of this study regarding the impact of financial indicators on ESG performance have important implications for firms. This paper contributes to the ESG literature by providing empirical evidence that highlights the dynamic impact of firm-specific factors on ESG performance. Full article

This paper investigates the relationship between European GDP and firm-level characteristics of European banks, with a particular emphasis on environmental, social, and governance (ESG) performance. Using Ordinary Least Squares (OLS) regression, the analysis incorporates the ESG score, board size, average number of employees, executive members’ gender diversity, and management score grade as predictors of GDP. The results show that the ESG score and executive members’ gender diversity have a positive and statistically significant effect on GDP, while board size, average number of employees, and management score grade are negatively associated with GDP. To further examine the components of ESG, a stepwise regression was conducted including the environmental, social, and governance scores. The findings reveal that only the environmental score significantly contributes to explaining GDP, suggesting that environmental performance is the most economically impactful ESG pillar among European banks. These results underscore the importance of environmental initiatives in driving macroeconomic outcomes. Full article