Search Results (439)

Over the last decade, there has been a significant increase in banks’ investment in technology, alongside a substantial rise in CEO compensation. Research on executive compensation has primarily focused on traditional performance metrics, such as return on assets and return on equity, as well as governance factors. Investigating the nexus between fintech adoption and CEO compensation introduces a new perspective on the determinants of CEO pay and how technological transformation influences executive remuneration structures. This study investigated the relationship between Chief Executive remuneration and fintech adoption among banks listed on the Johannesburg Stock Exchange. There is a lack of literature on the impact of technology adoption on CEO compensation in developing and emerging economies. The quantitative longitudinal study, conducted over 15 years from 2010 to 2024, collected secondary data from the annual reports of six banks and the IRESS database. A panel data fixed effects regression analysis was employed to analyze the data. CEO compensation included both salary and total compensation. Fintech variables used for the study included automated teller machines, mobile banking, and internet banking. The findings revealed a positive relationship between CEO salary and the rollout of ATMs and mobile banking, while an inverse relationship was noted between salary and internet banking. Similarly, total compensation showed an inverse relationship with the adoption of ATMs and internet banking, whereas mobile banking had a positive effect on total compensation. Understanding how technology impacts CEO compensation can help remuneration committees ensure that CEO pay is linked to the value that infrastructure investments bring to an organization, rather than simply the number of innovations introduced. This understanding will also help solve the principal-agent problem, as it will ensure technology innovations that enhance firm performance are rewarded. In the context of emerging markets, the study’s findings suggest that organizations should recognize and formalize pay linked to digital transformation, rather than focusing solely on short-term financial metrics. This also suggests the need to develop guidelines for executive remuneration disclosure related to the technology sector. The close connection between fintech adoption and technological and regulatory risks highlights the need to balance incentive structures that reward innovation with risk-adjusted performance measures. Full article

Internal accounting control personnel constitute the operational foundation through which firms ensure the accuracy and reliability of financial reporting, yet their relevance to capital market outcomes remains insufficiently documented. This study evaluates whether investment in internal accounting control personnel is incorporated into corporate bond pricing by considering both the quantitative dimension of staffing levels and the qualitative dimension of personnel expertise. Corporate bond issuance data are merged with mandatory disclosures on internal accounting control personnel for manufacturing firms listed on the Korea Exchange between 2011 and 2021. The analysis shows a significantly negative association between internal accounting control personnel and corporate bond yield spreads, with personnel expertise further reinforcing this relationship. These patterns are consistent with the view that enhanced monitoring capacity and stronger reporting credibility reduce information asymmetry and perceived default risk among bond investors. The evidence positions internal accounting control personnel as an operational and signaling indicator of internal control effectiveness reflected in debt market pricing and suggests that investment in internal control staff extends beyond compliance to produce measurable financial benefits through lower borrowing costs. Full article

This paper develops a quantitative framework for climate–financial risk measurement that combines a spatially explicit jump–diffusion asset–loss model with prudentially aligned risk metrics. The approach connects regional physical hazards and transition variables derived from climate-consistent pathways to asset returns and credit parameters through the use of climate-adjusted volatilities and jump intensities. Fat tails and geographic heterogeneity are captured by it, which conventional diffusion-based or purely narrative stress tests fail to reflect. The framework delivers portfolio-level Spatial Climate Value-at-Risk (SCVaR) and Expected Shortfall (ES) across scenario–horizon matrices and incorporates an explicit robustness layer (block bootstrap confidence intervals, unconditional/conditional coverage backtests, and structural-stability tests). All ES measures are understood as Conditional Expected Shortfall (CES), i.e., tail expectations evaluated conditional on climate stress scenarios. Applications to bank loan books, pension portfolios, and sovereign exposures show how climate shocks reprice assets, alter default and recovery dynamics, and amplify tail losses in a region- and sector-dependent manner. The resulting, statistically validated outputs are designed to be decision-useful for Internal Capital Adequacy Assessment Process (ICAAP) and Pillar 2: climate-adjusted capital buffers, scenario-based stress calibration, and disclosure bridges that complement alignment metrics such as the Green Asset Ratio (GAR). Overall, the framework operationalises a move from exposure tallies to forward-looking, risk-sensitive, and auditable measures suitable for supervisory dialogue and internal risk appetite. Full article

The loss of urban nature and declining biodiversity pose significant challenges to the sustainability of cities and the well-being of their inhabitants. Existing initiatives such as the Taskforce on Nature-related Financial Disclosures (TNFD) have begun to address ecological risks in real estate, but they still address mental health, biodiversity, and social equity only partially as non-financial values. This article adopts an integrative review and conceptual framework approach. It develops a nature-based accounting framework for urban real estate that combines principles of traditional Chinese architecture with contemporary sustainability metrics. The study reviews ecological theory, nature-related accounting, and evidence on biodiversity and mental health, and then undertakes an operational mapping from classical site planning, courtyard design, water management, and community structures to measurable indicators that remain compatible with TNFD-aligned reporting. The framework groups indicators into three main domains: nature-related conditions, ecosystem service pathways, and human well-being outcomes. It also outlines simple procedures for normalising and combining these indicators at the project scale to support assessments of biodiversity, microclimate, mental health, and basic aspects of cost-effectiveness and social accessibility in urban real estate projects. The paper provides a structured, heritage-informed basis for future applications and empirical testing, helping to incorporate biodiversity, mental health, and equity into urban real estate assessment. Full article

Green fintech merges sustainable finance with data-intensive innovation, but national translations of EU rules can create regulatory risk. This study examines how such risk manifests in Central Europe and which policy tools mitigate it. We develop a three-dimension framework—regulatory clarity and scope, supervisory consistency, and innovation facilitation—and apply a comparative qualitative design to Hungary, Slovakia, Czechia, and Poland. Using a common EU baseline, we compile coded national snapshots from primary legal texts, supervisory documents, and recent scholarship. Results show material cross-country variation in labelling practice, soft-law use, and testing infrastructure: Hungary combines central-bank green programmes with an innovation hub/sandbox; Slovakia aligns with ESMA and runs hub/sandbox, though the green-fintech pipeline is nascent; Czechia applies a principles-based safe harbour and lacks a national sandbox; and Poland relies on a virtual sandbox and binding interpretations with limited soft law. These choices shape approval timelines, retail penetration, and cross-border portability of green-labelled products. We conclude with a policy toolkit: labelling convergence or explicit safe harbours, a cross-border sandbox federation, ESRS/ESAP-ready proportionate disclosures, consolidation of recurring interpretations into soft law, investment in suptech for green-claims analytics, and inclusion metrics in sandbox selection. Full article

This study investigates how consumer brand trust is shaped by the interplay of sustainability disclosure valence (positive/negative), domain (social/environmental), and information source credibility (internet influencer/scientific report). Using a mixed-methods approach, combining a series of focus groups and a 2 × 2 × 2 between-subjects scenario experiment with a sample of 354 university students, we analyzed both the main and interactive effects of these factors on brand trust via hierarchical regression. The findings confirm that positive disclosures in both social and environmental domains significantly enhance brand trust. We observed a significant synergistic interaction, where consistent positive disclosures across both sustainability domains yield the greatest increase in trust. The study uncovers a domain-specific boundary condition for source credibility. While the source of information significantly moderates the impact of social sustainability disclosures—with influencers failing to generate the same punitive impact as scientific reports regarding social transgressions—source credibility exerts no significant influence on environmental disclosure processing. These findings suggest that consumers process environmental data as technical information (source-neutral) but social data as moral signals (source-dependent). Practically, the results suggest that brands require a holistic sustainability communication strategy and rely on highly credible sources for sensitive social messaging, especially when managing reputational risk or responding to negative disclosures. Full article

As enterprises increasingly depend on software systems, security defects such as vulnerability disclosures, exploitations, and misconfigurations have become economically relevant risk events. However, their short-term impacts on capital markets remain insufficiently understood. This study examines how different types of software security defects affect short-horizon stock market behavior. Using a multi-model event-study framework that integrates the Constant Mean Return Model (CMRM), Autoregressive Integrated Moving Average (ARIMA), and the Capital Asset Pricing Model (CAPM), we estimate abnormal returns and trading-activity responses around security-related events. The results show that vulnerability disclosures are associated with negative abnormal returns and reduced trading activity, while exploitation events lead to larger price declines accompanied by significant increases in trading activity. Misconfiguration incidents exhibit weaker price effects but persistent turnover increases, suggesting that markets interpret them primarily as governance-related issues. Further analyses reveal that market reactions vary with technical severity, exposure scope, industry context, and firm role, and that cyber shocks propagate through both price adjustment and liquidity migration channels. Overall, the findings indicate that software security defects act as short-term information shocks in financial markets, with heterogeneous effects depending on event type. This study contributes to the literature on cybersecurity economics and provides insights for firms, investors, and policymakers in managing software-related risks. Full article

Financial statement fraud remains a substantial risk in environments marked by weak regulatory oversight and information asymmetry. This study develops a decision-centric framework that integrates machine learning, explainable artificial intelligence, and decision curve analysis to improve fraud detection under severe class imbalance. Using 969 firm-year observations from 132 Mongolian firms (2013–2024), we evaluate 21 financial ratios with models including Random Forest, XGBoost, LightGBM, MLP, TabNet, and a Stacking Ensemble trained with SMOTE and class-weighted learning. Performance was assessed using PR-AUC, F1-score, Recall, and DeLong-based significance testing. The Stacking Ensemble achieved the strongest results (PR-AUC = 0.93; F1 = 0.83), outperforming both classical and modern baseline models. Interpretability analyses (SHAP, LIME, and counterfactual explanations) consistently identified leverage, profitability, and liquidity indicators as dominant drivers of fraud risk, supported by a SHAP Stability Index of 0.87. Decision curve analysis showed that calibrated thresholds improved decision efficiency by 7–9% and reduced over-audit costs by 3–4%, while an audit cost simulation estimated annual savings of 80–100 million MNT. Overall, the proposed ML–XAI–DCA framework offers a transparent, interpretable, and cost-efficient approach for enhancing fraud detection in emerging-market contexts with limited textual disclosures. Full article

This research evaluates the extent to which firms’ “green” bond disclosures create and convey a meaningful representation of their Environmental, Social, and Governance (“ESG”) commitments. Additionally, this research explores how investors distinguish between disclosures that represent genuine commitment to sustainability and those that may be indicative of “greenwashing,” and how such distinctions impact their assessment of an issuer’s credibility as well as the issuer’s performance subsequent to the issuance of a “green” bond. The methodology employed in this research employs a convergent mixed-methods approach that combines quantitative methods (Natural Language Processing (“NLP”), financial modeling, etc.) with qualitative methodologies (case studies, interviews). The NLP methodology employed in this research includes sentiment analysis, topic modeling, and ambiguity measurement in order to determine the tone, thematic content, and linguistic clarity of the disclosure texts. Subsequently, the results of the NLP methodologies are correlated with firm level outcomes using cross validated partial least squares regression (“PLS-R”), event study methodologies, and one way ANOVA to test for temporal and industrial variability. Finally, the results of the computational and financial methodologies are supplemented by qualitative case studies and interviews to provide context for the patterns identified in the computational and financial methodologies. In summary, the results of this research demonstrate that firms that communicate in a clear, balanced, and verifiable manner experience better market reaction and more favorable accounting results subsequent to the issuance of a “green” bond than do firms whose communications are vague, overly optimistic, or lacking in consistency. Conversely, the findings suggest that investors have become increasingly sensitive to potential “greenwashing” and therefore are less likely to respond favorably to communications characterized by the aforementioned characteristics. Full article

Background: Informed consent and assent are fundamental ethical and legal requirements in paediatric healthcare, yet their application in paediatric dentistry is complex and underexplored in clinical practice. Objective: This study aimed to analyse the implementation of informed consent and assent processes in paediatric dental care within a Spanish population, identifying key characteristics and factors that influence communication, understanding, and decision-making. Methods: An observational, descriptive, cross-sectional study was conducted in Spanish Paediatric Dentistry Clinics (January–June 2023). Participants included 520 child-caregiver pairs and 52 dental students. Data were collected via a semi-structured observational protocol and interviews, assessing information provided, decision-making conditions, and influencing factors. Statistical analysis was performed using SPSS v23.0, employing Chi-square, Cochran’s Q, and Kendall’s W tests. Results: The information most frequently provided was the nature of the dental problem (92%), treatment details (88%), and benefits (85%). Information on risks (64%), alternatives (37%), and the right to withdraw consent (41%) was less consistently communicated. After multivariable adjustment, child schooling remained independently associated with the disclosure of risks and alternatives (p < 0.01), whereas caregiver education showed no independent effect. Kendall’s concordance coefficient showed moderate agreement (W = 0.62, 95% CI: 0.54–0.69, p < 0.01) among operators, caregivers, and patients, which decreased in adolescents aged 16–18 years (W = 0.41, 95% CI: 0.28–0.55, p = 0.07). Conclusions: The processes of informed consent and assent in paediatric dentistry are more strongly linked to the child’s cognitive maturity and schooling than to parental education. While communication of treatment benefits is adequate, critical aspects like risks and alternatives are often overlooked. The findings underscore the need for standardized protocols and enhanced bioethical training to ensure consistent, ethical, and participatory practices that respect the progressive autonomy of minors. Full article

This study examines how physical and transition climate risks affect the greenium, assuming that implied volatility serves as a proxy for investor sentiment generated by these risks. Applying a Gated Recurrent Unit (GRU) deep learning model to daily data from January 2020 to June 2025 with a rigorous train–test split to get around the drawbacks of full-sample estimations and guarantee strong out-of-sample generalizability is a significant empirical contribution. Our findings show that adding the interaction between these climate risks and the sentiment proxy slightly increases predictive power. The GRU model outperforms random forest and linear regression benchmarks in terms of generalizability, but it remains sensitive to different data splits and hyperparameter tuning. This highlights the use of complex, non-linear models for risk forecasting and portfolio allocation for investors and risk managers, as well as the need for regular climate disclosure for policymakers to reduce information asymmetry. The GRU’s stringent validation framework directly enables more reliable pricing and exposure management. Full article

The growing emphasis on environmental sustainability and green finance has intensified the need for effective corporate disclosures, particularly regarding biodiversity. Despite the increasing relevance of biodiversity in global investment strategies, there remains a significant research gap in understanding how corporate biodiversity information disclosure influences retail investors, particularly in emerging markets such as China. Based on this, in order to fill this research gap, this study conducts an empirical analysis using valid sample data from 464 retail investors in China and the structural equation modeling method. The results indicate that: (1) Corporate biodiversity information disclosure (CD) has a positive impact on investors’ investment confidence (IC) and investment willingness (IW). (2) Investors’ IC positively influences their IW. (3) Risk aversion (QA) weakens (negatively moderates) the effect of CD on enhancing investors’ IC. (4) QA also weakens (negatively moderates) the effect of CD on promoting investors’ IW. (5) Climate risk awareness (CA) positively moderates the effect of CD on enhancing investors’ IC. (6) CA also positively moderates the effect of CD on promoting investors’ IW. This study enriches relevant theories by emphasizing how psychological factors influence investment behavior and provides important insights for companies, policymakers, and financial intermediaries to promote sustainable investment practices. Full article

Environmental, social, and governance (ESG) disclosure has gained global prominence, yet its implementation in emerging markets particularly in environmentally intensive sectors remains fragmented. In Indonesia’s energy industry, ESG transparency still struggles to meet rising global expectations, especially amid increased foreign investment flows and sustainability demands following the country’s G20 presidency. While prior research has separately examined financial performance and ownership structure, fewer studies have explored their combined impact on ESG disclosure within this institutional context. This study investigates how financial risk indicators and ownership composition influence ESG disclosure levels among publicly listed energy firms in Indonesia during the 2020–2024 period. Drawing on 98 firm-year observations, ESG performance is measured using the Nasdaq ESG Reporting Guide, and multiple linear regression is used to assess the influence of return on assets, liquidity, and various ownership types (managerial, institutional, and foreign), controlling for firm age and COVID-19 impact. The findings reveal that institutional ownership significantly enhances ESG disclosure, while other predictors such as return on assets, liquidity, managerial, and foreign ownership show no meaningful effect. The results underscore the role of institutional investors as key drivers of ESG adoption, offering insights into how ownership structures shape sustainability reporting in a high-impact sector of an emerging economy. Full article

Child sexual abuse (CSA) has consequences beyond the direct victim, affecting non-offending mothers, who may experience psychological, physical, and social symptoms after disclosure. This systematic review examined the impact of CSA on these mothers and the variables that influence coping and recovery. Searches were run in EBSCOhost (MEDLINE, PsycInfo, CINAHL) following PRISMA 2020 and a PEO framework. Three reviewers screened 128 records in Rayyan (Cohen’s κ = 0.73), and 17 empirical studies met the inclusion criteria. Risk of bias was appraised with ROBINS-E. Distress, anxiety, depression, and secondary traumatic stress were the most frequently reported symptoms. These consequences were associated with factors such as maternal history of abuse, perceived social support, coping style, and cultural or religious beliefs, highlighting potentially modifiable cognitive and contextual targets for support. A key contribution of this review is the identification of modifiable cognitive variables that are clinically relevant. Methodological limitations of the evidence base warrant cautious interpretation–comprising seven qualitative, nine quantitative cross-sectional, and one mixed-methods study, with heterogeneity that precluded meta-analysis and limited causal inference. Overall, the findings highlight the need for comprehensive, trauma-informed interventions that address not only the child’s recovery but also the well-being and resilience of their mothers. Full article

In volatile economic environments, corporate resilience is a prerequisite for sustainable development. This study explores the non-linear impact of controversial events on corporate resilience using a sample of 4430 listed Chinese firms from 2018 to 2023. By applying the Double Machine Learning (DML) framework and Generalized Additive Models (GAMs), we uncover a distinct non-linear effect: mild controversies act as “stress tests” enhancing resilience, while severe events diminish it. Furthermore, we validate a novel “Controversial Events→ESG→VaR→Resilience” chain-mediating mechanism, where ESG improvements translate into reduced financial tail risk (VaR). Theoretically, this research bridges the gap between non-financial performance and financial risk management, while methodologically overcoming linear model limitations by pinpointing crisis “tipping points”. Practically, the findings imply that managers should prioritize ESG disclosure as a strategic “risk buffer” to stabilize market expectations. For policymakers and investors, the study suggests that regulatory frameworks and capital allocation strategies must account for the non-linear dynamics of controversies to foster long-term sustainability. Full article