Search Results (459)

This paper investigates the relationship between environmental information disclosure (EID) quality and green technology innovation (GTI) using panel data from Chinese A-share listed companies over 2008–2024. EID quality is measured by a 27-indicator index, and GTI by the number of granted green patents. Based on 39,075 firm-year observations with firm and year fixed effects and firm-level clustered standard errors, the results show that EID quality is significantly and positively associated with GTI, and this association remains robust to a series of checks, including the exclusion of municipalities, a one-period lagged explanatory variable, propensity score matching, and entropy balancing, among other approaches. The mechanism analysis provides evidence consistent with two channels: EID quality is positively associated with Environmental, Social and Governance (ESG) performance and analyst coverage, each of which is positively associated with GTI. The EID–GTI association is also stronger under stronger board environmental expertise, audit quality, government subsidies, and market competition, and in firms with higher managerial myopia. Heterogeneity analysis shows that the positive association is stronger in state-owned enterprises and weaker in heavy-polluting industries and in regions with higher marketization. The study offers updated micro-level evidence on the role of EID quality in corporate green transformation, with implications for regulators and practitioners. Full article

This study examines whether China’s Intelligent Manufacturing Pilot Demonstration Program is associated with changes in Huazheng-rated environmental, social, and governance (ESG) performance among listed manufacturing firms. Using a panel of 2581 firms from 2012 to 2022, we exploit the staggered admission of 91 pilot firms. The preferred doubly robust group-time difference-in-differences estimator yields an average treatment effect of 0.881 Huazheng points, positive at the 10% level. The conventional firm and year fixed-effects estimate is 1.801 points and significant at the 1% level; it is retained as a benchmark rather than the main policy estimate. The direction remains positive across alternative fixed effects, lagged controls, a pre-COVID-19 sample, reweighting, matching, stacked estimation, randomization inference, wild-cluster bootstrap inference, and leave-one-out tests. Under the benchmark specification, the environmental and governance ratings rise significantly, whereas the social estimate is imprecise. The organizational regressions are consistent with possible information verification, managerial incentive, and financing channels, and cross-fitted double machine learning provides a functional-form check. Overall, pilot designation is associated with higher Huazheng-rated ESG performance, with evidence consistent with a possible policy effect. Selective designation and the provider-specific outcome preclude stronger claims about independently verified corporate sustainability. Full article

Managing the transition risks of carbon-intensive firms is essential for reconciling climate governance with the stable operation of the real economy; nevertheless, existing scholarship has yet to fully elucidate how climate policy uncertainty contributes to the formation of these risks. In this paper, we develop a firm-specific measure of climate policy uncertainty exposure by integrating China’s aggregate climate policy uncertainty index with climate-risk-related textual data retrieved from listed companies’ annual reports. Drawing on a panel dataset of A-share listed companies in nine carbon-intensive sectors over 2010–2023, we employ a partial-linear double/debiased machine-learning methodology to investigate how climate policy uncertainty exposure influences multidimensional firm transition risk. Our baseline estimations indicate that greater climate policy uncertainty exposure is associated with a statistically significant rise in transition risk among high-carbon firms, with the preferred model producing a coefficient estimate of 0.0243. These findings remain robust to an array of sensitivity checks and endogeneity-correction procedures. Mechanism analysis provides evidence consistent with four potential channels involving weaker intra-industry competition, lower corporate risk-taking, tighter financing constraints, and higher agency costs. Heterogeneity examinations reveal that the detrimental impact is particularly evident among larger enterprises, high-technology companies, and firms characterized by comparatively lower pollution levels. Further analysis based on conditional average treatment effects and best linear predictors reveals that media supervision and the presence of long-term institutional investors substantially reduce the extent to which climate policy uncertainty translates into firm transition risk. This study provides firm-level empirical evidence elucidating how climate policy uncertainty shapes multidimensional transition risk in the low-carbon transformation of high-carbon industries. Full article

This study investigates whether the determinants of dividend policy differ across distinct dimensions of distribution. Whereas most empirical studies rely on a single measure, generally the payout ratio, we adopt a multidimensional approach that distinguishes the decision to pay a dividend, payout intensity, and dividend yield. The analysis is based on a balanced panel of 33 firms listed on the Casablanca Stock Exchange over 2003–2025, yielding 759 firm-year observations. Each dimension is estimated using an econometric strategy tailored to its statistical properties: a random-effects logit model with firm-clustered robust standard errors for the payment decision, a random-effects model with firm-clustered robust standard errors for the payout ratio, and a fixed-effects model with Driscoll–Kraay standard errors for dividend yield, following a sequential model-selection and diagnostic procedure. The findings reveal substantial heterogeneity across the three dimensions of dividend policy. Profitability primarily affects the decision to pay and dividend yield, while firm size emerges as the most pervasive determinant. Financial leverage significantly reduces both the probability of paying a dividend and the payout ratio. The most distinctive result concerns the Price-to-Book ratio: its effect is positive for the payment decision and payout ratio, but negative for dividend yield. A battery of robustness checks confirms the stability of the main findings. Overall, the results show that the determinants of dividend policy depend on the dimension examined and underscore the value of a multidimensional framework for understanding payout decisions in emerging markets. Full article

We exploit the staggered rollout of the Standard Land Reform across Chinese cities as a quasi-natural experiment to examine its impact on enterprise innovation efficiency. Using a sample of A-share listed companies from 2013 to 2020, we find that the reform significantly increases enterprise-level innovation efficiency by approximately 4.86%. This result remains robust across a series of robustness checks. Mechanism analyses reveal that the reform promotes innovation through reducing transaction costs, increasing fiscal subsidies, and strengthening regional intellectual property protection. Heterogeneity analyses show that the effect is more pronounced for enterprises with higher financing constraints, higher human capital, and greater media attention, as well as in more competitive industries and regions with stronger intellectual property protection. Our findings provide enterprise-level causal evidence that improving land allocation efficiency can foster enterprise innovation, offering policy implications for leveraging institutional reforms in land allocation to promote innovation-driven development. Full article

Background: Research in behavioral genetics has demonstrated that genetic factors significantly contribute to individual differences in behavior, while environmental exposures shape gene expression through epigenetic mechanisms. This interaction is also relevant to the development of antisocial behavior and psychopathic traits. One of the first evidence of gene–environment interaction was the association between low-activity variants of the MAOA gene, childhood maltreatment, and increased risk of antisocial behavior [¹]. Similarly, our research in incarcerated populations showed that adverse paternal parenting is associated with higher levels of psychopathy and the HTR1B rs13212041 TT genotype appears to modulate the individual susceptibility to negative experiences [²]. Single genetic variants, however, exert only modest effects and current evidence supports a polygenic model in which multiple genetic factors interact with environmental adversity to influence neurodevelopment and behavioral outcomes. Using a genome-wide/endophenotype informed analysis, for example, we identified novel gene–environment interactions as risk factors for psychopathy, involving three independent genetic loci in interaction with paternal maltreatment, which were previously associated with disruptive behavior, temperament, and neuroticism [³]. More recently, we also evaluated whether machine-learning models, integrating behavioral, environmental, and genetic variables, could be helpful to predict psychopathic traits. Methods: We compared logistic regression, random forest, support vector machine, XGBoost, and multilayer perceptron. Results: Support vector machine showed the highest accuracy for predicting Psychopathy Check List-Revised (PCL-R) Factor 2 (antisocial lifestyle). Feature-importance analyses identified impulsivity (BIS-11), empathy (IRI), childhood maltreatment (MOPS), and 12 SNPs as the most informative predictors. Notably, removing genetic variables or MOPS scores substantially reduced the model accuracy, indicating that both genetic and environmental information meaningfully contributed to prediction of antisocial behavior. Conclusions: These findings confirm that genetic influences are neither deterministic nor sufficient to explain criminal behavior but may contribute to interindividual differences in vulnerability, particularly through their interaction with environmental and psychosocial factors. In forensic psychiatry, the integration of genetic and environmental information into behavioral assessment may provide additional objective correlates that complement, rather than replace, traditional clinical and psychosocial evaluations. Such an integrated approach could potentially contribute to a more comprehensive understanding of individual vulnerability and behavioral trajectories. However, the use of genetic information in assessments of criminal responsibility should be approached with caution and proven expertise, given the complex, multifactorial nature of antisocial and criminal behavior. Full article

Enhancing corporate ESG performance through digital technologies has become a central issue as digital transformation and green development advance in tandem. Using data on Chinese A-share listed companies from 2010 to 2024, a total of 13,917 observations, this study develops a dual-path framework of structural and resource empowerment from a supply chain network perspective, to systematically uncover the mechanisms through which supply chain digitalisation affects corporate ESG performance. The results show that supply chain digitalisation significantly improves ESG performance (β = 4.4127, p < 0.01), a finding that remains robust across a series of robustness checks. Mechanism analysis further shows that digitalisation generates structural empowerment by increasing firms’ network centrality (β = 0.4036, p < 0.01) and structural-hole positions (β = −0.1668, p < 0.05), and also generates resource empowerment by alleviating financing constraints (β = −0.8366, p < 0.01) and promoting substantive green innovation (β = 0.6263, p < 0.05). Heterogeneity analysis reveals that the positive effect is more pronounced at the planning, production, and logistics stages, in capital- and labour-intensive industries, among upstream firms in the industrial chain, under low environmental uncertainty, and under intense market competition. From a meso-level network perspective, this study extends the literature on the mechanisms underlying corporate ESG performance and provides empirical evidence for firms seeking to align digital transformation with green development. Full article

As generative AI chatbots become a primary information channel, users increasingly accept answers without verification, and citations can raise trust even when sources are irrelevant or fabricated. How source-attribution visualization shapes the visual preconditions of verification remains unknown: users can notice, read, or compare a source without clicking. This within-subjects eye-tracking study (N = 23; 92 trials) evaluated four attribution visualizations abstracted from commercial AI chatbots and rendered as simulated screens: inline component (sentence-end chips), card list (cards above the answer), side panel (adjacent panel), and raw hyperlink (bare URLs), combining gaze metrics, surveys, and interviews. Repeated-measures ANOVAs revealed strong layout effects on source discoverability and engagement, largely robust to sensitivity checks (the panel’s discovery latency was order-sensitive): the card list was discovered almost immediately, with the raw hyperlink last. Yet no self-reported measure differed detectably. The most frequently nominated format, the inline component, attracted about half the dwell time of the stand-alone formats, whose prolonged fixations suggested citation-to-text mapping cost rather than genuine engagement. This attention–preference gap means both must be measured jointly. We contribute a four-layout gaze-based comparison, a reproducible participant-level analysis workflow, and three design principles (pre-click identifiability, sentence-level claim–source mapping, and in situ preview) within a proposed two-stage attribution architecture. Full article

Firms can invest in digitalization without necessarily producing greener inventions; resource organization and financial continuity may determine whether that potential is realized. This paper studies 24,126 firm-year observations for Chinese A-share listed firms over 2013–2024. Annual-report vocabulary is used to gauge digital transformation, whereas applications for green invention and utility-model patents indicate green innovation. The empirical design estimates changes within firms through firm and year fixed effects and firm-clustered standard errors, with additional specifications that absorb industry-year and province-year shocks. Guided by dynamic capability theory, capability-related resource configuration (CRC) is constructed as a firm-year archival proxy from knowledge investment, resource-allocation flexibility, and specialized human-capital support, corresponding to the absorptive, adaptive, and innovative dimensions used in prior Chinese A-share research. Financial resource availability (FRA) is treated as a boundary condition on the CRC–green innovation relationship. Lagged and alternative digitalization measures, propensity score matching, and an instrumental-variable specification are used as supplementary checks. The estimates link greater digital transformation to more green innovation. CRC carries a positive indirect association of 0.002152, equivalent to 9.2231% of the total association, which places it as a partial rather than predominant pathway. At low FRA, the CRC slope cannot be distinguished statistically from zero; at average and high FRA, it is positive. Although the supplementary estimates preserve the baseline direction, the evidence does not warrant definitive causal claims. Overall, the findings are consistent with a resource-configuration interpretation in which financial continuity conditions the CRC–green innovation relationship. Full article

The MENRO: Monitoring and Management System is a digital solution developed to modernize the manual operations of the Municipal Environment and Natural Resources Office (MENRO). The system provides a secure and user-friendly platform designed to streamline document handling, automate monitoring tasks, and ensure accurate environmental data management. This project specifically aims to: (1) develop a user-friendly interface that enables seamless document and record management, allowing administrators to effortlessly add, edit, update, and store essential information, and (2) design a system that is capable of automatically generating comprehensive lists of apprehension receipts, including violations and penalties issued to establishments under MENRO’s jurisdiction. These functions address long-standing inefficiencies in manual monitoring, recordkeeping, and compliance tracking. The system was evaluated using the ISO/IEC 25010:2011 software quality standards, focusing on functional suitability, performance efficiency, reliability, usability, compatibility, maintainability, portability, and security. Results show high usability and strong security features, ensuring that the platform meets operational needs while safeguarding sensitive environmental and legal records. By integrating real-time data access, automated reporting, and digitized forms used in environmental compliance checks, the system enhances MENRO’s capability to uphold environmental governance with greater transparency, accuracy, and accountability. Full article

Amid growing external uncertainty, strengthening supply chain resilience has become vital for the long-term survival and development of enterprises. Drawing on the Resource-Based View and Dynamic Capabilities Theory, this study develops a “capital–capability–resilience” research framework using panel data of China’s A-share listed firms from 2009 to 2024, and examines the influence of patient capital on corporate supply chain resilience. The results indicate that patient capital is positively correlated with enterprise supply chain resilience, and this conclusion remains stable after a series of endogeneity tests and robustness checks. Mechanism analysis demonstrates that patient capital can enhance supply chain resilience by upgrading firms’ dynamic capabilities, which specifically include absorptive capacity, innovation capacity and adaptive capacity. Heterogeneity analysis shows that the positive effect of patient capital on supply chain resilience is more significant among non-state-owned enterprises, firms facing high financing constraints, and enterprises in high-tech industries. Patient capital is identified as a distinctive strategic resource that underpins supply chain resilience; its three core attributes—long-term orientation, strong risk-bearing capacity, and strategic nature—differentiate it from traditional long-term capital forms. This study adds to the existing literature by clarifying the unique properties of patient capital and empirically verifying its function in building supply chain resilience, and further provides practicable managerial insights for cultivating patient capital and improving supply chain stability. Full article

ESG ratings are widely used in sustainable finance, yet disagreement among agencies may weaken their information role and relate to firms’ financing frictions. Using Chinese A-share non-financial listed firms from 2009 to 2024, this study examines whether ESG rating divergence is associated with an SA-based financing-constraint proxy, whether stock turnover provides a liquidity-related pathway, and whether digital transformation weakens the association. ESG rating divergence is measured by the dispersion of available rescaled ESG ratings from five agencies, and financing constraints are proxied by the absolute value of the SA index. Firm and year fixed-effects regressions show that greater ESG rating divergence is significantly associated with higher values of the SA-based proxy. The result remains positive and significant in a lagged-variable specification. Instrumental-variable estimates provide additional sensitivity evidence, although the exclusion restriction cannot be directly verified. The bootstrap results support a statistically significant but economically small partial mediation effect through stock turnover; however, lagged mediation checks do not establish a complete temporal sequence. A moderation analysis indicates that digital transformation weakens the positive association. The subsample estimates are reported as descriptive patterns. The findings suggest that inconsistent ESG signals are associated with an SA-based financing-constraint proxy, while internal information-governance capabilities may reduce this exposure. Full article

Self-efficacy is relevant to sport performance, but its role in artistic gymnastics is unclear because studies vary in construct definition, timing, and outcomes. This PRISMA 2020- and PERSIST 2021-informed systematic review was prospectively registered in PROSPERO (CRD420251266838). PubMed, Scopus, Web of Science, and EBSCOhost (SPORTDiscus and APA PsycInfo) were searched from inception to 18 December 2025, supplemented by backward reference-list checking and forward citation searching. Eligible quantitative studies assessed self-efficacy or task- or apparatus-specific efficacy expectations, or used performance predictions or an adapted gymnastics-task confidence measure as efficacy-related proxies and reported a performance outcome; qualitative evidence was contextual only. Nine studies were included (eight quantitative; one qualitative). Competitive studies using direct task- or event-specific efficacy measures or efficacy-related proxies and judged outcomes generally reported positive associations, but correlations and predictive patterns varied across apparatus, samples, and measures. Educational findings and broader confidence constructs were treated as indirect evidence. Meta-analysis was inappropriate because constructs, samples, apparatus, timing, outcomes, and reporting were heterogeneous. The evidence therefore indicates a possible positive but inconsistent, low-certainty association between task- or apparatus-specific efficacy-related beliefs and performance. Contemporary longitudinal studies and standardized gymnastics-specific measures are needed. Full article

Corporate resilience has become a critical capability for firms to cope with increasing environmental uncertainties and external shocks. Against the backdrop of the rapid development of the digital economy, this study examines whether digital transformation enhances corporate resilience and further investigates whether environmental, social, and governance (ESG) performance serves as a complementary transmission mechanism in this relationship. Drawing on resource orchestration theory, this study uses panel data of Chinese A-share listed companies from 2016 to 2024 and estimates a series of firm fixed-effects models. The results indicate that digital transformation significantly enhances corporate resilience, and the findings remain robust after a series of robustness checks and endogeneity tests are conducted. Further analysis reveals that ESG performance partially mediates the relationship between digital transformation and corporate resilience, suggesting that responsible business practices complement the resilience-enhancing effect of digital transformation. The results of the heterogeneity analysis further indicate that the positive effect of digital transformation is significantly stronger for high-tech firms. In addition, firms exhibit substantial variation in the consistency between digital transformation communication and actual digital investment. Further analysis suggests that greater alignment between digital transformation communication and substantive implementation is associated with stronger resilience outcomes, providing supplementary evidence on the implementation process of digital transformation. This study contributes to the literature on digital transformation and corporate resilience by revealing the resource orchestration process through which digital transformation creates organizational value and identifying ESG performance as a complementary transmission mechanism. The findings also have practical implications for firms seeking to strengthen their resilience and achieve sustainable development in an increasingly uncertain environment. Full article

Market-based instruments for environmental governance have emerged as a central pillar of China’s climate policy architecture, though their capacity to drive corporate green innovation continues to be the subject of active scholarly debate. Drawing on a staggered difference-in-differences identification strategy and a panel of Chinese A-share listed firms covering 2008 to 2023, this study evaluates the impact of China’s carbon emission trading scheme (CETS) pilot policy on firm-level green innovation. Our estimates indicate that the CETS pilot policy significantly increases green patent applications, a finding that proves robust for an extensive set of checks: parallel trends assessment, placebo exercises, PSM-DID estimation, alternative estimation strategies, and varied sample constructions. Heterogeneity analyses show that the innovation-enhancing effect is concentrated among firms operating in non-regulated industries and located in the western region, and that enterprises and regions endowed with stronger baseline carbon performance and higher pollution control investment display amplified responses. Mechanism analysis shows that the CETS pilot policy increases both operating costs and debt financing costs, yet these two cost channels exert opposite effects on green innovation. Operating costs drive innovation through cost-induced pressure, while financing costs inhibit innovation through a crowding-out effect. The net-positive effect suggests that the innovation-inducing effect of operating costs outweighs the innovation-inhibiting effect of financing costs. This study recommends maintaining stable carbon price signals, implementing complementary green finance policies, providing differentiated support for low-capability firms and regions, and accounting for spillover effects in policy evaluation. Full article