Type of the article: Research Article This study proposes Agilance as a conceptual and technical framework for explainable strategic financial planning in data-intensive organizational environments. The framework is based on a custom transformer architecture that incorporates three sector-specific components: Financial Relevance Weighting, Context Shift Stabilization, and Output Compression. Because the evaluation was conducted on a confidential sector-specific dataset and through internal benchmarking procedures, the underlying source data and job-level operational records cannot be publicly released. Within these constraints, the internal evaluation yielded indicative results: 96.03% accuracy and 95.8% F1-score for priority classification on the held-out test set, 90.26% accuracy and 90.22% F1-score for implementation-duration classification, and an average 10-fold cross-validation accuracy of 91.7%. The expert explainability assessment produced mean scores of 4.67 for clarity, 4.53 for trustworthiness, and 4.48 for actionability, with inter-rater agreement ranging from 0.87 to 0.91. Internal operational benchmarks further suggested planning-cycle reductions and economic benefits, including 95.8% improvement in real-time data analysis and time-zone synchronization, 5.4% operational cost savings, and an illustrative first-year ROI of 46%. These results should be interpreted as preliminary internal evidence obtained under specific evaluation conditions, not as independently verified proof of broad organizational generalizability. The study contributes an auditable AI-supported framework and identifies the need for future validation using anonymized multi-organizational datasets, externally audited protocols, or independently reproducible benchmarks. Acknowledgments The publication fees of this manuscript have been financed by the MSc Tax and Financial Services Digital Transformation (DITAF), University of Patras.
Type of the article: Research Article A comparative assessment of how audit firms’ attributes affect financial performance using both market-based and traditional metrics remains limited in emerging markets. Hence, the study evaluated the comparative effect of audit firms’ attributes on financial performance measured by market-based and traditional metrics. Secondary data from thirty-five manufacturing companies listed at the Nigerian Exchange Group from 2012 to 2022 were analyzed. These companies are purposively selected from a population of fifty-six. Descriptive statistics and panel data regression analysis were used in the data analysis. Results indicate that audit firm resource availability has a significant positive effect on earnings per share (β = 2.1550; p ≤ 0.05), while other proxies of audit firm attributes do not have a significant effect when traditional metrics of financial performance (i.e., earnings per share and share price) were used. However, when market-based metrics of financial performance (market value added and economic value added) are used, audit firm resources availability has a positive significant effect on both market value added (β = 3.842; p ≤ 0.05) and economic value added (β = 0.1789; p ≤ 0.05). The study concluded that audit size, tenure, and industry specialization do not influence firm financial performance, but audit resource availability does. Besides, using market-based financial performance metrics yields more consistent results than traditional metrics.
Type of the article: Research Article This study examines how accounting-based financial performance and corporate governance affect firm value among Indonesian listed technology firms. The study analyzes panel data from 28 technology companies listed on the Indonesia Stock Exchange during 2021–2024. The data were obtained from annual reports, audited financial statements, corporate governance disclosures, and capital market information. Panel regression analysis was applied, and the Fixed Effects Model was selected based on model specification tests. Corporate governance and accounting-based financial performance are measured using standardized equal-weighted composite indices constructed from their respective indicators. The corporate governance index was constructed from board independence, board size, audit committee size, and ownership concentration, while the financial performance index was constructed from ROA, ROE, TATO, current ratio, and reverse-coded DER. The results show that the corporate governance composite index has a positive and significant effect on firm value, with a coefficient of 0.263 and a t-statistic of 2.791. The accounting-based financial performance composite index also has a positive and significant effect on firm value, with a coefficient of 0.415 and a t-statistic of 4.526. Furthermore, the interaction between the corporate governance index and the financial performance index is positive and significant. These findings indicate that corporate governance strengthens the value relevance of financial performance. The model has strong explanatory power, with an adjusted R2 of 0.672. The study concludes that profitability and leverage remain relevant accounting-based for firm valuation, while corporate governance enhances transparency, financial control, and investor confidence in Indonesian technology firms.
Type of the article: Research ArticleIn the dynamic landscape of emerging economies like Vietnam, digital transformation is increasingly recognized as a strategic imperative for enhancing corporate governance and transparency. This study aims to evaluate the direct impact of technological integration on internal control effectiveness and investigate the moderating mechanism of firm size in this relationship. To ensure representativeness across small, medium, and large organizational scales, a stratified random sampling technique was employed. The quantitative data were collected over a six-month period from October 2024 to March 2025. A structured questionnaire, validated by experts and utilizing a 5-point Likert scale, was distributed via email to key personnel in Vietnamese enterprises, resulting in 452 valid responses. The partial least squares structural equation modeling method was applied to analyze the data, specifically chosen for its suitability with non-normal distributions. The results demonstrate that digital transformation exerts a substantial positive influence on internal control effectiveness (β = 0.424, p-value < 0.001), confirming that digitization significantly bolsters risk management capabilities. Crucially, the analysis identifies a statistically significant negative moderating effect of firm size (β = –0.190, p-value < 0.001). These findings indicate that the positive impact of digitalization on internal control diminishes as organizational scale increases. The study concludes that while large corporations face structural inertia, small and medium-sized enterprises leverage their agility to achieve superior control outcomes, necessitating tailored strategies for different enterprise scales.
Type of the article: Research Article Although financial reporting and auditing standards are substantially harmonized across the European Union, important differences remain in national accounting regulations, audit thresholds, and the practical application of the going concern principle. These differences are particularly relevant for small and medium-sized enterprises (SMEs), which constitute the dominant segment of the Visegrad Four (V4) economies. This paper examines differences in financial reporting and auditing frameworks among the Czech Republic, Hungary, Poland, and Slovakia and develops sector-specific distress prediction models to support going-concern assessments in SME auditing. The empirical analysis is based on financial statement data for 66,988 active firms obtained from the Orbis database. After data cleaning and consistency checks, a modelling sample of approximately 41,000 SMEs was constructed. Financial distress is defined as a persistent inability to cover interest obligations, represented by two consecutive years in which earnings before interest and taxes (EBIT) are lower than interest expenses. Distress status is modelled using financial ratios, firm-size indicators, industry characteristics, and selected variables inspired by ISA 570. Separate binomial logistic regression models are estimated for country–industry groups derived from NACE classifications and evaluated using hold-out samples. The results confirm that country- and sector-specific models achieve satisfactory predictive performance and provide useful support for assessing going-concern risks. The results also show that the most informative predictors differ across countries and industries, reflecting differences in regulatory environments and economic structures. The study highlights the importance of local calibration when developing distress prediction models and demonstrates that a universal approach may lead to reduced predictive accuracy. The proposed models provide a practical screening tool for auditors, lenders, and SME managers, complementing professional judgement and broader audit procedures. Acknowledgments This study is co-financed by the governments of Czechia, Hungary, Poland, and Slovakia through Visegrad Grants from the International Visegrad Fund. Visegrad Grant No. 22420285, Title of the project: “Distress prediction models in V4 countries and their audit applicability”. The mission of the Fund is to advance ideas for sustainable regional cooperation in Central Europe. The authors gratefully acknowledge the support of their home institutions and thank the anonymous reviewers for their insightful comments and suggestions.
