Viktoriia Makarovych

The article aims to investigate, using the VAIC and MVAIC models, the impact of intellectual capital on the financial performance of Omani companies listed on the Muscat Stock Exchange from 2017 to 2021. Regression analysis revealed a significant positive influence of VAIC and MVAIC only on the Asset Turnover Ratio at a 10% significance level. This suggests that an increase in VAIC or MVAIC by one unit could lead to a respective increase in earnings for Omani listed industrial companies by 0.0017 and 0.0016. However, the overall impact of VAIC and MVAIC on financial performance appears limited, necessitating measures for enhanced efficacy. Moreover, company size and leverage were found to significantly influence EBITDA and Return on Assets, suggesting the positive effect of increased activity and resource utilization. Conversely, Return on Customer Equity negatively affected only Asset Turnover Ratio, implying that investments in marketing and advertising may not significantly enhance financial performance. Human Capital Efficiency showed no significant impact on financial performance measures, highlighting the necessity for Omani industrial enterprises to focus on enhancing employee skills and experience for improved value-creation processes. These findings underscore the intricate relationship between intellectual, physical, and financial capital in shaping financial performance, necessitating targeted strategies for enhancement. Further analysis of suggested models indicated the significance of company size on EBITDA, highlighting the importance of scaling activities for performance improvement. VAIC and MVAIC structural elements showed mixed results, while Capital Employed Efficiency negatively affected Return on Equity, Structural Capital Efficiency positively impacted EBITDA and Asset Turnover Ratio.

The UN Sustainable Development Goals (SDGs) have become a universal call to action over the past few years and a basis for assessing the progress of sustainable development of countries and organizations. This paper aims to identify the relationship between the sustainable development activities of universities in different regions of the world, as reflected in the Times Higher Education Impact Rankings (THE IR), and the progress towards achieving SDGs of the countries in which these universities operate. The research methods were correlation analysis and robust regression tools, and parametric and non-parametric methods of variance analysis. The information base was the results of annual reports based on the THE IR and Sustainable Development Reports for 2017–2021. The results confirm the existence of directly proportional close correlations between the variables, while the regression analysis confirmed that a one-unit increase in the overall THE IR ranking score leads to a corresponding increase in the overall progress of countries in achieving SDGs (on average by 0.2-0.3 units) and SDGs 3, 8, 11, 16 in particular. It was also found that universities play a key role in achieving different SDGs in various regions. In Latin America, the Caribbean, the Middle East, and North Africa, universities are critical for SDG 17 achieving. In OECD countries, universities contribute most to SDG 3. Examples of the best practices that can be used as a guide for university administrations that are at the beginning of developing sustainable development policies are also given.

Funding
Inna Makarenko gratefully acknowledges support from the Jean Monet module project “Transparency. Accountability. Responsibility. Governance. Europe. Trust. Sustainability” financed by the Erasmus+ program (101085395 – TARGETS – ERASMUS-JMO-2022-HEI-TCH-RSCH).

Type of the article: Research Article

Ukrainian transfer pricing legislation demonstrates a significantly higher level of regulatory complexity than international OECD standards, creating a disproportionate burden on the accounting and reporting system. The study aims to quantify the regulatory burden generated by the complexity of Ukrainian transfer pricing legislation through a computational linguistic analysis of its algorithmic characteristics in comparison with international OECD standards. The research methodology is based on Halstead metrics to calculate the algorithmic complexity of regulatory texts, considered as formal structures with the distribution of lexical units into operators and operands. The computational assessment reveals that Ukrainian transfer pricing regulations demonstrate algorithmic complexity 10 to 37 times higher than OECD standards, as the complexity index (L) for Article 39 of the Tax Code of Ukraine equals 2.742 percent versus 0.148 percent for OECD Transfer Pricing Guidelines, while Law of Ukraine No. 4536-IX (Verkhovna Rada of Ukraine, 2023) reaches 5.455 percent, exceeding international benchmarks by 37 times. This excessive complexity directly affects accounting practices, requiring additional resources for recordkeeping, increasing internal control requirements, and increasing the risk of financial reporting errors. The empirical findings demonstrate that excessive algorithmic density directly increases compliance costs for accounting departments, requiring additional resources for interpretation, documentation, and internal control. The study provides quantitative evidence supporting the necessity of systematic simplification of national transfer pricing regulations.

Type of the article: Research Article

Abstract
Between 2005 and 2024, the digital divide separating former Soviet economies outside the EU from EU member states shrank from 44.8 to 2.4 points of a composite 0–100 index, and whether banking systems converted this catch-up into better performance is an open question. The paper evaluates the intermediation efficiency and productivity of banking in 24 transition economies during 2010–2024 and quantifies their relationship with digital infrastructure, paying special attention to Armenia, Kazakhstan, and Ukraine. Efficiency is measured with input-oriented window DEA on deposit funding, operating costs, lending, and profitability; productivity with Malmquist indices; and digital infrastructure with a principal-component index of internet, mobile, and broadband penetration. The estimation relies on two-way fixed effects with Driscoll-Kraay and bootstrap inference on 356 country-year observations. Productivity is flat overall with a Malmquist mean of 0.995, yet technological change moves from below unity through 2015 to above unity in 2016–2023, a regime shift robust to the output set and the translation constant. Within countries, the index is unrelated to efficiency levels, productivity growth, cost efficiency, and stability outcomes; the baseline cost-to-income and credit-risk associations dissolve under country-specific trends and differencing. Cumulative productivity reaches 1.162 in Kazakhstan and 1.106 in Armenia by 2024, while Ukraine climbs back to 0.856. Frontier renewal after 2016, rather than a measurable dividend from connectivity, is the substantive finding, and expectations of direct efficiency or stability gains from digital infrastructure should remain modest, particularly in postwar Ukraine.