Search Results (372)

Evidence-based prioritization is essential for effective specialization strategies (RIS3). However, there is a scarcity of evidence on whether regions are leveraging their own strengths or mimicking other policies. This study examines 236 EU regions, 178,314 publications, 116,336 projects and 470 RIS3 energy priorities (2021–2027) across 112 energy-related topics. We measure capability potential in two dimensions: proven areas of activity (inside strengths) and related areas with similar technologies (adjacent frontiers). Selective behavior is described using exploitation and exploration indicators, a stretch indicator and portfolio–priority adjustment indicators. Our findings reveal that surface rationality masks deep mimicry. Capabilities drive the direction of selection but not its scale. Regions select less than 10% of available strengths or adjacent areas. Instead, 40.3% of priorities are in ambitious areas, such as hydrogen and offshore wind energy, that exceed the potential opportunities. The portfolio–priority alignment is minimal at 0.10, and the wishful gaps are close to the maximum at 1.85 out of 2.0. Conversely, regions leave 93% of their potential untapped. RIS3 energy priorities indicate a greater desire to follow priorities than an ability to act. We suggest that policymakers should conduct capability audits to confirm absorptive capacity before setting priorities, establish benchmarks in strategy monitoring to measure the exploitation and exploration of regional assets and provide financial incentives that reward choices based on capabilities rather than historical alignment. Future research should examine whether capability-based priorities outperform choices that merely mimic others. Full article

In the global economy, traditional accounting-based ratios alone are often insufficient to fully explain firm performance, increasing the importance of complementary information sources such as sustainability and governance disclosures. In this context, environmental, social, and governance (ESG) indicators, together with corporate governance signals, have increasingly been recognized as important drivers of firm performance. However, the literature does not provide a clear and generalizable view on the impact of ESG indicators on profitability. This study aims to examine whether sustainability and corporate governance signals provide additional information value beyond traditional financial ratios in predicting ROE. To this end, two models were compared using a sample of 428 non-financial publicly traded companies operating in Turkey. The firm-level dataset was constructed using financial statements and independent audit disclosures obtained from the Turkish Public Disclosure Platform (KAP). Tree-based machine learning models were employed to capture potential nonlinear relationships and complex interactions between financial and non-financial indicators. Model performance was evaluated within a Bootstrapped Grouped Cross-Validation framework that considered firm-level dependency; the statistical reliability of performance differences was tested using bootstrap-based confidence intervals and matched tests. Among the evaluated models, Random Forest achieved the strongest overall predictive performance. In conclusion, this study demonstrates that sustainability and corporate governance disclosures provide statistically significant additional information value to ROE prediction. Due to the use of multiple algorithms, it contributes to the literature in a generalizable manner. Full article

This study investigates how ownership structure conditions the transmission of corporate governance mechanisms into dividend policy within the context of South Korea’s evolving regulatory environment. Using a balanced panel of 5022 firm-year observations from 558 non-financial KOSPI-listed firms over 2011–2019, we analyze governance quality using data from the Korea Corporate Governance Service. We employ both an aggregate score and four constituent dimensions: board effectiveness, shareholder rights protection, audit committee competency, and disclosure transparency. The empirical framework combines firm fixed effects estimation, binary logistic regressions, and a two-step dynamic System GMM approach to account for unobserved heterogeneity, payout persistence, and endogeneity. The results reveal systematic heterogeneity across ownership regimes. Among non-Chaebol firms, higher governance quality across all dimensions is associated with higher dividend payouts, consistent with the governance outcome hypothesis. In contrast, among Chaebol-affiliated firms, the effectiveness of governance mechanisms is selective rather than uniform. While the aggregate governance score and shareholder rights protection retain explanatory power for dividend outcomes, internal oversight mechanisms related to board structure, audit competency, and disclosure do not exert independent influences once ownership structure is taken into account. These findings show that concentrated ownership structures condition which governance mechanisms remain effective in shaping payout policy. Regulators seeking to mitigate valuation discounts in conglomerate-dominated economies should prioritize the substantive empowerment of minority shareholder rights, as these mechanisms retain influence over payout policy even under concentrated ownership structures. Full article

This study examines the drivers of net interest margin (NIM) in developing economies, with a particular emphasis on Ethiopian commercial banks. It adopts an explanatory research design, analyzing quantitative data from the audited financial statements of 13 banks over 13 years (2012–2024), totaling 169 observations. Both Driscoll–Kraay fixed- and random-effects standard errors were computed in RStudio (version 4.5). The primary analysis relied on Driscoll–Kraay random regression outcomes, though fixed regression results were included for robustness checks. Findings indicate that the loan-to-deposit ratio, bank size, capital adequacy, and foreign direct investment (FDI) inflows have a significant positive impact on NIM, underscoring their role in enhancing profitability and stability. Conversely, inflation significantly reduces margins, while no substantial effects were observed for operational efficiency or GDP. These insights suggest that Ethiopian banks should focus on asset growth, maintaining strong capital reserves, increasing the loan-to-deposit ratio, and attracting FDI. Policymakers are encouraged to stabilize inflation and create a conducive environment to FDI to support sectoral growth. Future research could investigate operational efficiency alongside industry-specific indexes, such as the Herfindahl–Hirschman index for loans, assets, and income, to better understand variations in NIM. Full article

Chronic pain is inherently multifactorial, with biological, psychological, and social factors contributing to neuropathic pain (NP) and central sensitization (CS) syndromes. Comorbidity between functional disorders and the lack of clinical biomarkers adds to the challenge of diagnosis and treatment, leading to frustration for healthcare professionals and patients. Available treatments are limited, increasing patient suffering with personal and financial costs. This systematic review examined multisensory processing alterations in chronic pain and reviewed current pharmacological and non-pharmacological interventions. A structured search was conducted on the PubMed database using the keywords Central Sensitization, Fibromyalgia, Complex Regional Pain Syndrome, and Neuropathic Pain, combined with the keywords Vision, Audition, Olfaction, Touch, Taste, and Proprioception. Papers were then filtered to discuss current treatment approaches. Articles within the last five years, from 2018 to 2023, have been included. Papers were excluded if they were animal studies; investigated tissue damage, disease processes, or addiction; or were conference proceedings or non-English. Results were summarized in table form to allow synthesis of evidence. As this study is a systematic review of previously published research rather than a clinical trial or experimental investigation, the risk of bias was assessed independently by at least two reviewers. 138 studies were identified and analyzed. Of these, 96 focused primarily on treatment options for chronic pain and were analyzed for this systematic review. There were a few emerging themes. No one therapy is effective, so a multidisciplinary approach to diagnosis, including pharmacological, somatic, and psychological treatment, is generally predicted to achieve the best outcomes. Cranial neurovascular compromise, especially of the trigeminal, glossopharyngeal, and potentially the vestibulocochlear nerve, is being increasingly revealed with the advancement of neuroimaging. Cortical and deep brain stimulation to evoke neuroplasticity is an emerging and promising therapy and warrants further investigation. Finally, including patients in their treatment plan allows them control and offers the ability to self-manage their pain. Risk of bias limits the ability to judge the quality of evidence. Full article

(1) Background: The convergence of Big Data and the Internet of Things (IoT) is transforming digital accounting from retrospective documentation into real-time operational intelligence. This systematic review examines how Industry 4.0 technologies—artificial intelligence (AI), blockchain, edge computing, and digital twins—transform accounting practices through intelligent automation, continuous compliance, and predictive decision support. (2) Methods: The study synthesizes 176 peer-reviewed sources (2015–2025) selected using explicit inclusion criteria emphasizing empirical evidence. Thematic analysis across seven domains—conceptual foundations, system evolution, financial reporting, fraud detection, audit transformation, implementation challenges, and emerging technologies—employs systematic bias-reduction mechanisms to develop evidence-based theoretical propositions. (3) Results: Key findings document fraud detection accuracy improvements from 65–75% (rule-based) to 85–92% (machine learning), audit cycle reductions of 40–60% with coverage expansion from 5–10% sampling to 100% population analysis, and reconciliation effort decreases of 70–80% through triple-entry blockchain systems. Edge computing reduces processing latency by 40–75%, enabling compliance response within hours versus 24–72 h. Four propositions are established with empirical support: IoT-enabled reporting superiority (15–25% error reduction), AI-blockchain fraud detection advantage (60–70% loss reduction), edge computing compliance responsiveness (55–75% improvement), and GDPR-blockchain adoption barriers (67% of European institutions affected). Persistent challenges include cybersecurity threats (300% incident increase, $5.9 million average breach cost), workforce deficits (70–80% insufficient training), and implementation costs ($100,000–$1,000,000). (4) Conclusions: The research contributes a four-layer technology architecture and challenge-mitigation framework bridging technical capabilities with regulatory requirements. Future research must address quantum computing applications (5–10 years), decentralized finance accounting standards (2–5 years), digital twins with 30–40% forecast improvement potential (3–7 years), and ESG analytics frameworks (1–3 years). The findings demonstrate accounting’s fundamental transformation from historical record-keeping to predictive decision support. Full article

This study tests the connectionbetween corporate governance structures and firm value, incorporating financial distress as a mediating mechanism among construction companies listed in ASEAN markets. Utilizing a sample of 58 firms drawn from an initial population of 169 companies over the 2018–2021 period, this study measures governance mechanisms through managerial ownership, institutional ownership, independent commissioners, audit committees, and litigation risk. Firm value is proxied by Tobin’s Q, while financial distress is assessed utilizing the Altman Z-Score. Panel data regression is employed to test the direct connections, and the Sobel test is used to evaluate the mediating role of financial distress. The outcome describes that managerial ownership and audit committees have a favorable effect on firm value, whereas independent commissioners and litigation risk exert a negative influence. Institutional ownership shows no significant association with firm value. Moreover, institutional ownership significantly affects financial distress, whereas the other governance mechanisms show no significant association with financial distress, although financial distress itself has a detrimental impact on firm value. The mediation analysis describes that financial distress mediates only the connection between institutional ownership and firm value. These outcomes help clarify prior inconsistencies in the literature and underscore the importance of strengthening managerial ownership and audit committees, optimizing the role of independent commissioners, and mitigating litigation risk to sustain firm value. Full article

Forest certification in developing countries faces significant challenges due to weak institutions, limited market incentives, and complex trade conditions. This study investigates the status and key constraints of the Myanmar forest certification sector through a survey of 180 stakeholders from government organizations, NGOs, INGOs, third-party certification bodies, and private plantation owners, complemented by quantitative analysis and qualitative interviews. The results indicate a moderate level of familiarity with the Myanmar forest certification standard and high awareness of the Myanmar Forest Certification Committee; however, progress remains slow due to limited transparency, poor institutional coordination, financial and technical constraints, and insufficient stakeholder involvement. Non-compliances issues identified during pilot audits were primarily related to incomplete documentation, unclear land tenure, and weaknesses in environmental assessment. Geopolitical factors continue to limit Myanmar’s participation in certified timber markets and weaken efforts to improve traceability. Experiences from Indonesia, Malaysia, and Vietnam highlight that developing credible national certification systems requires time, clear legal frameworks, and strong cooperation among stakeholders. Strengthening institutional capacity, improving transparency, and aligning national standards with international forest governance frameworks are essential for Myanmar to build trust, achieve sustainable forest management, and regain market access. Full article

The rise in Blockchain-based digital assets has transformed the financial ecosystems, which has also created complex governance and taxation challenges. The pseudonymous and cross-border nature of crypto transactions undermines traditional tax enforcement, leaving regulators such as the South African Revenue Service (SARS) reliant on voluntary disclosures with limited verification mechanisms, while existing Blockchain forensic tools and regulatory technologies (RegTechs) have advanced in anti-money laundering and institutional compliance, their integration into issues related to taxpayer compliance and locally adapted solutions remains underdeveloped. Therefore, this study conducts a state-of-the-art review of Blockchain forensics, RegTech innovations, and crypto tax frameworks to identify gaps in the crypto tax compliance space. Then, this study builds on these insights and proposes a conceptual model that integrates digital forensics, cost basis automation aligned with SARS rules, wallet interaction mapping, and non-fungible tokens (NFTs) as verifiable audit anchors. The contributions of this study are threefold: theoretically, which reconceptualise the adoption of Blockchain forensics as a proactive compliance mechanism; practically, it conceptualises a locally adapted proof-of-concept for diverse transaction types, including DeFi and NFTs; and lastly, innovatively, which introduces NFTs to enhance auditability, trust, and transparency in digital tax compliance. Full article

Artificial intelligence (AI) use has become a major emerging trend in corporate finance and governance. AI is used for a variety of business tasks, such as assessing credit risk, document analysis, corporate default forecasting, and detecting fraud. This study first provides an overview of the development of AI applications related to financial reporting and corporate governance and then examines the financial performance of firms rated highly for their use of AI. AI applications can improve risk management, auditing processes, financial distress, fraud detection, and board performance. The findings can help directors, managers, financial personnel, and others interested in AI. Full article

A robust audit services market is essential for ensuring financial transparency, regulatory compliance, and investor confidence. As a dimension of organizational sustainability, the capacity of audit firms to remain competitive and resilient under market pressures is increasingly relevant. However, existing research has paid insufficient attention to the stability of audit firms and the survival dynamics of mid-sized players. The present study addresses this gap by examining the volatility of the U.S. audit services market and the sustained dominance of the Big Four firms over the 2019–2023 period. Based on data from Accounting Today’s annual rankings, the study employs Kaplan–Meier survival analysis to assess the probability of audit firms remaining in the Top 100 over time. Furthermore, K-means clustering is used to identify structural factors contributing to firm exit, including revenue, number of employees, branches, and partners. The results indicate that, while the Big Four retained stable leadership, 19 firms exited the rankings, with revenue and number of specialists being the most influential exit factors. These findings provide insights for enhancing risk assessment, strategic planning, and regulatory design. Moreover, the study contributes to broader discussions on organizational sustainability and long-term competitiveness within the context of the U.S. audit sector, while offering insights that may be informative for understanding similar dynamics in other markets rather than aiming for direct global generalization. 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

Financial statement fraud is a significant threat to corporate governance, investor confidence, and global capital markets. Traditional fraud detection models, including DF-Score and PF-Score, often rely on linear approaches that may fail to capture complex fraudulent behaviors. This study applies machine learning techniques using eXtreme Gradient Boosting across 34 countries (2016–2024). Results show that enhanced DF-Score and PF-Score effectively capture fraud risk, which is significantly associated with auditors’ opinions. The study integrates machine learning with traditional models to address data complexity and nonlinearity. Practically, the findings provide auditors, regulators, and financial analysts with a tool for improved fraud detection and risk-based auditing. Full article

The Asia Pacific, led by the resource-dependent ASEAN-5, is the largest carbon contributor, yet its firms exhibit critically low transparency. This study examines the relationship between voluntary Sustainability Assurance (SA) and carbon disclosure transparency using 875 firm-year observations (2018–2022). Applying panel regression and several robustness tests, we find that SA adoption has a positive relationship with the magnitude of disclosed carbon emissions, indicating enhanced transparency. This positive relationship is significantly more pronounced in firms with high environmental performance and greater property, plant, and equipment (PPE) efficiency, suggesting SA aligns with genuine sustainability efforts rather than symbolic reporting. Furthermore, SA increases the likelihood of disclosing the complex Scope 3 emissions. However, the effectiveness of SA is conditional: its transparency benefit is statistically significant only within mandatory sustainability reporting (SR) regimes and in non-environmentally sensitive industries, highlighting crucial variations across regulatory and industrial contexts within ASEAN-5. This research provides evidence on the role of SA in emerging markets, extending Agency Theory by demonstrating its function as a credibility signal that reduces information asymmetry. We offer practical guidance for managers seeking market differentiation, and for regulators aiming to align voluntary SA with IFRS S1/S2 to enhance disclosure quality. Full article