Serhii Lehenchuk

Intellectual capital is the total value of all entity’s intangible resources (organizational, human, and customer). Effective management of intellectual capital in high-tech industries needs determination of its role in ensuring profitability and clarifying the direction of managerial and investment policy in intangible resources. The aim of this study is to investigate the impact of intellectual capital on the profitability of Slovak software development companies. Panel data regression analysis was used as the main research method to analyze the data of 16 Slovak software development companies for 2015–2019. The study designed and analyzed four panel data regression models with different dependent variables (Return on Assets, Net Profit Margin, Gross Profit Margin, Earnings Before Interest and Taxes Margin) and similar independent variables (Capitalized Development Costs, Software, Acquired Intangible Fixed Assets, Personnel Costs, Social Security Costs, Social Costs, and Total Costs of Economic Activity). The analysis of these models was carried out based on the fixed effects method. It was found that intellectual capital reflected in the financial statements of software development companies does not meet the information needs of stakeholders and does not have a significant direct impact on profitability. Only Acquired Intangible Fixed Assets had a direct positive impact on the profitability of software development companies in all four analyzed models, and some independent variables had a negative impact. It is proposed to expand the structure of financial reporting items that characterize the intellectual capital and improve the method of recognizing costs of various types as intangibles.

The purpose of the study is to examine the impact of corporate governance mechanisms on the financial performance of listed industrial companies in Oman. As the main research method, panel data regression analysis was used to analyze data from 36 Omani industrial companies, listed on the Muscat Stock Exchange for the period 2017–2021. Three regression models were developed using three dependent variables (Return on Assets, Return on Equity, Return on Sales), seven independent variables (Board Size, Independent and Non-executive Board Members, Board Meeting, Chief Executive Officer, Dummy variable for Board Change, Dummy variable for the Secretary on the Board, Dummy variable for Internal Auditor), and two control variables (Leverage, Size of the company). According to the research results, a negative influence of the Board Size and Dummy variable for the presence of the Secretary on the Board on the Return on Assets indicator at 10% and 5% significance level was found; moreover, there is a positive influence of Leverage and Size of the company at the 1% and 5% significance level on Return of Assets. Although, none of the independent variables used has a significant impact on the Return on Equity indicator. Return on Sales is significantly affected only by two control variables, i.e., a negative impact of Leverage at the 10% significance level and a positive impact of the Size of the company at the 10% significance level. The results obtained in the study indicate the imperfection of the corporate governance mechanisms implemented by Omani industrial companies in the field of ensuring financial efficiency.

The purpose of the study is to conduct a comparative analysis of the determinants affecting the financial performance of agricultural enterprises in Poland, Slovakia and Ukraine. As the main research method, panel data regression analysis was used to analyze data from 34 Polish, 123 Slovak, and 305 Ukrainian agricultural companies for the period 2017–2020. To analyze the links between financial performance measures and its determinants, nine models were developed based on three selected dependent variables (Return on Assets, Return on Equity, Return on Sales) in each of the countries studied. Seven independent variables were used, such as Leverage, Long-Term Debt to Assets, Short-Term Debt to Assets, Debt to Equity, Current Ratio, Asset Tangibility, Capital Intensity, and two control variables such as Size and Dummy variable for legal form. The most significant impact on the financial performance of agricultural enterprises has: for Polish enterprises – Return on Assets – Leverage and Asset Tangibility, Return on Equity – Debt to Equity and Dummy variable for legal form, Return on Sales – Current Ratio, Capital Intensity, and Size; for Slovak enterprises – Return on Assets – Current Ratio, Return on Equity – Debt to Equity, Return on Sales – Current Ratio, and Capital Intensity; for Ukrainian enterprises – Return on Assets – Leverage and Size, Return on Equity – Debt to Equity, and Current Ratio, Return on Sales – Capital Intensity.

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 purpose of the paper is to study the impact of corporate sustainability practices on the financial performance of companies included in the BIST Sustainability 25 Index. To assess the efficiency and quality of corporate sustainability, general (ESG Disclosure Index) and partial (Environmental Disclosure Index, Social Disclosure Index, and Corporate Governance Disclosure Index) indices were used, calculated based on content analysis of sustainability reports. Based on the two given types of indices and four types of financial performance indicators (return on assets, return on equity, assets turnover ratio, and Tobin’s Q), two types of regression models (GEN models and PART models) were built, and eight analytical models were examined. Company size and leverage were included as control variables in each model. The regression analysis results were contradictory, partially confirming the conclusions of some scientists and refuting the findings of others. A study of GEN models revealed that companies implementing more effective general corporate sustainability practices have a significant positive impact only on return on equity; as for other measures (return on assets, assets turnover ratio, and Tobin’s Q), an insignificant relationship between them and ESG Disclosure Index was found. Results of the PART models analysis revealed a significant positive effect of the Social Disclosure Index on return on equity and assets turnover ratio and a negative relationship between the Corporate Governance Disclosure Index and assets turnover ratio. Using control variables for the two types of models showed a significant negative effect of company size on Tobin’s Q.

Acknowledgment
This study was supported by the Ministry of Education and Culture of Ukraine within the project “Development of a mechanism for the sustainable development of economic systems in the conditions of military operations and post-war recovery of the economy” (Registration number of the project: 0124U000463).

The study aims to examine the impact of risk factors of Ukrainian advertising and marketing companies on their financial performance (ROA and ROE). The study was conducted using ordinary least squares regression analysis based on an examination of the activities of 435 companies in 2022. The total number of risk factors (Risk Total) and the ten most common risk factors (10 fixed risk factors) associated with the activities of Ukrainian advertising and marketing companies, calculated using the YouControl database, were selected as independent variables. 10 fixed risk factors were interpreted as dummy variables, which allowed incorporating qualitative information about risk factors of Ukrainian advertising and marketing companies into regression analysis models. Control variables (company age, company size, financial leverage, population at the place of company registration, and total solvency ratio) were added to enhance the determination level of the models. Of these, the statistically significant ones were Company size, which increases ROA and ROE; Financial leverage, which increases ROE; and Company age, which decreases ROE. Of the 11 independent variables that characterized companies’ risk factors, only three were confirmed to significantly impact financial performance indicators (risk factor “Location in the housing stock” reduces ROA and ROE; risk factor “Frequent institutional changes” increases ROA; risk factor “Found match by full name with a politically exposed person” reduces ROE).

This article highlights the transformation of views on the understanding of accounting as a science in the new conditions for the functioning of enterprises operating in globalized markets in a dynamic competitive environment. The necessity of considering external factors (corporate scandals, financial crisis, etc.) in the development of accounting as a science is emphasized. The reasons for the need to confirm the scientific status of accounting are considered, the hypotheses concerning the gradual crowding out and replacement of accounting by information systems with artificial intelligence are refuted. Accordingly, the study aims to confirm the scientific significance of accounting and justify the need for its further development as a social science aimed at solving social issues and having a deeper social context. Various accounting models and identification of factors affecting their construction, as a result of which the goals of accounting are transformed, make the theoretical basis of this study. It is concluded that accounting is a social science that studies the features of the functioning of the accounting system as a social and institutional practice. Such an understanding of accounting science is considered one of the ways out of the existing crisis. The reasons for the lack of understanding among Ukrainian researchers of accounting as a social science are highlighted, and the ways to overcome them are suggested. It is proved that accounting, on the one hand, is a product of the social environment, an instrument for reflecting the economic reality of an enterprise. On the other hand, it influences the formation of social reality, being an instrument for shaping social processes and relations arising from the functioning of accounting as a separate socio-economic institute.

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.