Search Results (357)

Environmental, Social, and Governance (ESG) management has global relevance, yet its effects differ across contexts. In Korea, with concentrated ownership, family-controlled conglomerates, and evolving governance norms, the ESG–firm performance link offers unique insights. This study examines 620 publicly listed firms in Korea over the 2020–2022 period to assess the effects of ESG performance on firm value (Tobin’s q) and financial performance (operating return on assets). Three governance-related variables that reflect the distinctive features of Korea’s corporate governance—CEO (chief executive officer) tenure, the shareholding ratio of the largest shareholder, and foreign ownership ratio—are included in the analysis as moderating variables. Results show that ESG performance positively affects both firm value and financial performance. Also, CEO tenure and foreign ownership significantly strengthen the ESG–firm value relationship, whereas the shareholding ratio of the largest shareholder enhances the ESG–financial performance link. These findings extend stakeholder, legitimacy, and institutional theories to an East Asian context and offer practical guidance for managers and policymakers aiming to enhance corporate outcomes through ESG strategies in Korea’s distinctive governance environment. Full article

Corporate transparency is vital for sustainable governance. However, detecting financial misstatements remains challenging due to their rarity and resulting class imbalance. Using financial statement data from Korean firms, this study develops an integrated AI framework that evaluates the joint effects of sampling strategy, model choice, and interpretability. Across multiple imbalance ratios, NearMiss undersampling consistently outperforms random undersampling—particularly in recall and F1-score—showing that careful data balancing can yield greater improvements than algorithmic complexity alone. To ensure interpretability rests on reliable predictions, we apply Shapley Additive Explanations (SHAP) and Permutation Feature Importance (PFI) only to high-performing models. Logistic regression emphasizes globally influential operating and financing accounts, whereas Random Forest identifies context-dependent patterns such as ownership structure and discretionary spending. Even with a reduced feature set identified by explainable AI, models maintain robust detection performance under low imbalance, highlighting the practical value of interpretability in building simpler and more transparent systems. By combining predictive accuracy with transparency, this study contributes to trustworthy misstatement detection tools that reinforce investor confidence, strengthen responsible corporate governance, and reduce information asymmetry. In doing so, it advances the United Nations Sustainable Development Goal 16 (Peace, Justice, and Strong Institutions) by supporting fair, accountable, and sustainable economic systems. Full article

The rise of common institutional ownership has a profound impact on corporate environmental policies, and the business environment in which the enterprises operate can significantly affect the decisions of institutional investors. This study evaluates the effect of common institutional ownership on corporate environmental responsibility disclosure (CERD) practices in Chinese manufacturing firms from the performance feedback perspective. Utilizing a sample period spanning from 2008 to 2021, the study indicates several key findings. Firstly, the presence of common institutional ownership is demonstrated to enhance the level of CERD in these firms, especially soft information on environmental responsibility. Secondly, this positive effect is amplified when positive performance expectation gaps exist. Mechanism tests reveal that under the dual pressures of common institutional investor exit threats and a negative expected performance gap, firms tend to lower their level of CERD. Conversely, synergistic effects effectively promote this disclosure. Furthermore, analysis of the impact pathway demonstrates that under such conditions, common institutional ownership exerts pressure to reduce both monetary and non-monetary private benefits accruing to management, thereby leading to optimized CERD. In addition, heterogeneity analysis indicates a more significant effect of common institutional ownership on CERD enhancement in private enterprises compared to their state-owned counterparts, particularly when positive performance expectation gaps are present. Full article

In this study, we provide, to our knowledge, one of the first multidimensional, data-driven evaluations of green education performance in Turkish higher education, combining the THE Education Score, THE Impact Score, and the UI GreenMetric Education & Research Score (GM-ED) with institutional characteristics, and situating the analysis within SDG 4 (Quality Education). While universities worldwide increasingly integrate sustainability into their missions, systematic evidence from middle-income systems remains scarce. To address this gap, we compile a dataset of 50 Turkish universities combining three global indicators—the Times Higher Education (THE) Education Score, THE Impact Score, and the UI GreenMetric Education & Research Score (GM-ED)—with institutional characteristics such as ownership and student enrollment. We employ descriptive statistics; correlation analysis; robust regression models; composite indices under equal, PCA, and entropy-based weighting; and exploratory k-means clustering. Results show that integration of sustainability into curricula and research is the most consistent predictor of SDG-oriented performance, while institutional size and ownership exert limited influence. In addition, we propose composite indices (GECIs). GECIs confirm stable top performers across methods, but mid-ranked universities are volatile, indicating that governance and strategic orientation matter more than structural capacity. The study contributes to international debates by framing green education as both a measurable indicator and a transformative institutional practice. For Türkiye, our findings highlight the need to move beyond symbolic initiatives toward systemic reforms that link accreditation, funding, and governance with green education outcomes. More broadly, we demonstrate how universities in middle-income contexts can institutionalize sustainability and provide a replicable framework for assessing progress toward SDG 4. Full article

This study investigates the relationship between corporate governance mechanisms and tax avoidance in Greek service-sector firms over the period 2014–2023. Using panel data, the analysis evaluates the influence of board characteristics, audit committees, auditor quality, and ownership structures on firms’ tax behavior. The results reveal that traditional governance mechanisms—such as board size, independence, audit committee composition, and gender diversity—do not significantly constrain tax avoidance, reflecting the formalistic rather than substantive adoption of governance practices in Greece. In contrast, external audit quality and ownership structure emerge as critical determinants. Engagement with high-quality auditors, particularly Big 4 firms, is associated with reduced tax aggressiveness, while state ownership similarly curbs avoidance, consistent with reputational and political accountability incentives. Conversely, managerial and foreign ownership are positively related to aggressive tax planning. The findings underscore the contextual nature of governance effectiveness: in weak enforcement environments, formal mechanisms serve largely symbolic roles, whereas external oversight and ownership incentives carry greater weight. This study contributes to agency and institutional theory by highlighting the limits of formal governance reforms absent substantive independence and enforcement. Full article

Corporate boards play a pivotal role in shaping firms’ environmental strategies, yet the influence of board demographics, particularly director age, on sustainability outcomes remains insufficiently understood. This study investigates how the age profile of board members affects corporate environmental performance, including greenhouse gas emissions. Analyzing a comprehensive panel of 1843US publicly listed firms (17,218 firm-year observations) from 1996 to 2018, primarily through panel regressions with firm and year fixed effects, we find consistent evidence that firms with older boards tend to exhibit poorer environmental performance and higher direct, indirect and value chain greenhouse gas emissions. We argue that this relationship is driven by age-related differences in risk tolerance, time horizons, and sensitivity to environmental concerns. Additionally, the study explores moderating factors such as poor governance oversight (board co-option), pressure for profitability from institutional ownership, CEO social and environmental consciousness (CEO gender), and managerial ability, revealing that these governance dynamics significantly influence the strength of the director age–environmental performance link. The results, robust to endogeneity concerns, underscore the importance of considering age diversity and board refreshment in corporate governance to foster more effective environmental stewardship. These insights offer valuable implications for board members, corporate leaders, and policymakers aiming to advance sustainable business practices, but also open up opportunities for further exploration in alternative institutional contexts. Full article

With the rapid expansion of digital knowledge platforms and intelligent information systems, organizations and communities are producing a vast number of unstructured knowledge data, including annotated corpora, technical diagrams, collaborative whiteboard content, and domain-specific multimedia archives. However, knowledge sharing across institutions is hindered by privacy risks, high communication overhead, and fragmented ownership of data. Federated learning promises to overcome these barriers by enabling collaborative model training without exchanging raw knowledge artifacts, but its success depends on motivating data holders to undertake the additional computational and communication costs. Most existing incentive schemes, which are based on non-cooperative game formulations, neglect unstructured interactions and communication efficiency, thereby limiting their applicability in knowledge-driven scenarios. To address these challenges, we introduce SC-NBTI, a smart contract and Nash bargaining-based incentive framework for federated learning in knowledge collaboration environments. We cast the reward allocation problem as a cooperative game, devise a heuristic algorithm to approximate the NP-hard Nash bargaining solution, and integrate a probabilistic gradient sparsification method to trim communication costs while safeguarding privacy. Experiments on the FMNIST image classification task show that SC-NBTI requires fewer training rounds while achieving 5.89% higher accuracy than the DRL-Incentive baseline. Full article

Background: Accurate estimation of mortality is essential for effective public health planning, policymaking, and monitoring of health interventions. In Ghana, multiple data sources are used to estimate mortality, including civil registration systems, household surveys, census data, and health and demographic surveillance systems. This scoping review explores the existing sources of mortality data in Ghana, examining their challenges and opportunities. Methods: Using Arksey and O’Malley’s framework, we identified peer-reviewed and grey literature from Ghana Health Service, Ministry of Health, Ghana Statistical Service, WHO, and the United Nations. We selected studies published between 2000 and 2024 that focused on mortality estimation in Ghana. Data was extracted and synthesized into key themes: data sources, challenges, and opportunities. Results: Six major data sources on mortality were identified: Civil Registration and Vital Statistics (CRVS), census data, Demographic and Health Surveys (DHS), Health and Demographic Surveillance Systems (HDSS), Facility-Based Health Information Systems (HMIS), modeled estimates from the Global Burden of Disease (GBD) and from the United Nations Department of Economic and Social Affairs (UN DESA). Key challenges include under-registration of deaths (CRVS and HMIS), recall bias (DHS, census), limited geographic coverage (HDSS), inconsistencies in cause-of-death classification (HMIS, HDSS), and lack of local geographic coverage (GBD, UN DESA, DHS). Nonetheless, benefits include longitudinal follow-up (HDSS), local coverage and ownership (CRVS, HMIS) and international comparability (GBD, UN DESA, DHS). Conclusions: Mortality estimation in Ghana is supported by diverse but fragmented data sources. Strengthening the CRVS and HMIS systems, integrating multiple data streams, standardizing methodologies, and enhancing institutional partnership are essential steps toward improving data quality and coverage. This review provides recommendations for improvement towards better quality estimations of mortality in Ghana. Full article

Inspired by the limited research regarding the influence of CEO succession origin on corporate misconduct, this study draws on organizational identification theory and agency theory to examine this issue. Empirical analysis indicates that insider CEOs significantly constrain corporate misconduct in China. Furthermore, the moderating results indicate that internal control strengthens the negative association between insider CEOs and corporate misconduct, whereas institutional ownership weakens this governance effect. Further analysis confirms that the restraining effect of insider CEOs on corporate misconduct remains robust across different types of misconduct. Overall, our study emphasizes the positive role of insider CEOs from the perspective of CEO succession origins and provides valuable practical implications for controlling corporate misconduct. Full article

The objective of this article is to propose a novel model for evaluating retention solutions in urban areas. This model is designed to serve as a tool to support integrated urban planning in the context of reurbanization and climate change adaptation processes. The model is both diagnostic and decision-support in nature, integrating spatial, environmental, and functional data. It analyzes these data based on a spatial dependency matrix. A comprehensive consideration of both physiographic factors (e.g., geomorphological typology and land ownership) and social and institutional factors (e.g., institutional readiness and stakeholder engagement) was undertaken. The modelling employs methodologies that are characteristic of urban and landscape design, including multi-criteria analysis, case studies, expert assessment, and Geographic Information System (GIS) tools. The assessment of the retention potential was conducted with consideration for the typology of buildings, infiltration capacity, soil permeability, and existing infrastructure. The findings of the present study demonstrate that local spatial and social conditions exert a substantial influence on the efficacy of retention implementation. The model enables the prioritization of actions and the selection of suitable solutions (context-sensitive retention strategies), thus making it a valuable instrument for designers, urban planners, and decision-makers. The proposed approach can be used in urban planning as a practical tool to support decisions on resilient city development and urban water management. Full article

The end of the conflict in Sierra Leone between 1991 and 2002 provided an important context for exploring the role of peace education in restoring governance, rebuilding institutions, and promoting socio-economic development. Following the civil war, a variety of externally designed peace education programmes were introduced across the country. These included formal programmes integrated into the school curriculum and non-formal initiatives led by stakeholders. This study evaluated these programmes by examining their goals, implementation approaches, and effectiveness in fostering sustainable peace alongside development. The evaluation employed a social constructionist framework, recognising that understandings of peace and education are shaped by historical, social, and cultural factors. Data were gathered through the analysis of documentary sources and semi-structured online interviews with 12 key informants involved in peace education. The findings reveal important insights regarding both the potential of peace education as a developmental tool and its limitations in achieving lasting peace. Key lessons emphasise the critical role of local ownership, cultural relevance, and ongoing support for post-conflict educational interventions. These insights offer valuable guidance for enhancing future peacebuilding and reconstruction efforts in Sierra Leone and other similar post-conflict settings. Full article

Against the backdrop of global sustainable development and the fast-growing digital economy, aligning corporate ESG practices with digital transformation is key for enterprises’ high-quality development, yet existing studies have not fully explored ESG’s directional impact on digital transformation. This study examines how corporate ESG performance drives digital transformation and the moderating roles of firm characteristics, industry types, and ownership structures, using 11,109 valid observations from Chinese A-share listed companies (2009–2022); it adopts the causal forest algorithm and supplements with OLS, quantile, and Poisson regressions for robustness tests. The results show that ESG significantly promotes digital transformation—with obvious positive effects from E and S dimensions, while G has no statistical impact—and further analysis reveals nonlinear moderation by firm characteristics and contextual differences: the positive effect is stronger in high-tech and private enterprises but weaker in traditional and state-owned enterprises (due to institutional constraints). These findings offer theoretical insights into ESG–digital synergies and practical guidance for targeted sustainability and digital strategies. Full article

The green transformation of agricultural systems is crucial for environmental protection and food security, yet smallholder-dominated systems face immense structural barriers. This study investigates whether agricultural socialized services (ASSs)—an emerging institutional innovation—can serve as a catalyst for this transition. Using household survey data from the China Land Economy Survey (CLES), this study examines the direct impact and mediating pathways of ASSs on farmers’ adoption of green production behaviors. We also reveal the heterogeneity effects of household operating scale. The results show the following: (1) Agricultural socialized services positively impact farmers’ adoption of green production behaviors, which can contribute to advancing sustainable agricultural development. (2) ASSs do not simply increase the quantity of machines. Instead, they facilitate a shift from costly asset ownership to efficient mechanization-as-a-service. (3) Furthermore, a heterogeneity analysis reveals that the positive impacts of ASSs are heterogenous at different levels. ASSs more significantly influence farmers’ adoption of green practices for small-scale farms (operating at a size less than 4.8 mu). It provides robust empirical evidence that ASSs can effectively “decouple” green modernization from large-scale farmers to overcome structural barriers. These findings help to provide policy implications for promoting ASSs and sustainable agriculture production. Full article

Many companies engage in earnings manipulation that obscures their actual financial condition and sustainability efforts, undermining the credibility of financial reports and eroding stakeholder trust. To address these concerns, the United Kingdom has strictly adhered to International Financial Reporting Standards (IFRS), enhancing financial transparency and reducing the risk of manipulation. This study applies agency theory to examine the effects of earnings management and IFRS adoption on corporate sustainability performance, while also assessing the moderating roles of institutional ownership and board independence. Data were drawn from 248 companies listed on the London Stock Exchange between 2002 and 2024, using purposive sampling and sourced from Thomson Reuters Eikon DataStream. Advanced estimation techniques, specifically the Augmented Mean Group (AMG) and fixed effects models with Driscoll-Kraay standard errors, were employed to address cross-sectional dependence and slope heterogeneity. The results indicate that earnings management, as measured by discretionary accruals, has a significant negative impact on sustainability performance. In contrast, the adoption of IFRS has a positive and significant influence on sustainability outcomes. Additionally, institutional ownership and board independence significantly moderate the adverse effects of earnings management, leading to improved sustainability performance. The findings suggest that managers should enhance the clarity and accountability of financial reporting by implementing robust internal systems aligned with IFRS, conducting regular compliance audits, and training finance staff on current disclosure standards. Full article

This paper presents ModuLab, a modular, low-cost sensor platform designed to simplify real-time environmental monitoring for laboratory research and educational settings. Centered on the APP-All MCU 2023 development board with an AVR128DA48 microcontroller (Microchip Technology Inc., Taiwan) ModuLab supports plug-and-play integration of multiple sensor types—including temperature, pH, light, and humidity—using a robust I²C communication protocol. The system features configurable sampling rates, built-in signal conditioning, and a Python-based interface for real-time data visualization. As a proof-of-concept, ModuLab was operated continuously for 48 h to evaluate system stability and filtering capabilities. However, due to institutional data ownership and confidentiality policies, the underlying datasets cannot be disclosed in this submission. The architecture and implementation details described herein are intended to guide future users and research groups seeking accessible alternatives to conventional data acquisition solutions. Comprehensive performance validation and open-access data sharing are planned as the next steps in this ongoing project. Full article