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    Public policy and financial regulation in preventing and combating financial fraud: a bibliometric analysis
    (LLC CPC Business Perspectives, 2023-06-30) Filatova, Hanna; Tumpach, Miloš; Reshetniak, Yaroslav; Lyeonov, Serhiy; Vynnychenko, Nataliia
    This study aims to conduct a bibliometric analysis on the topic of public policy and financial regulation in preventing and combating financial fraud using a variety of bibliometric methods and tools, including the in-built tools of Scopus by Elsevier (SciVal) and Web of Science by Clarivate Analytics, as well as VOSviewer software. The most relevant publications related to the search terms were identified. Based on the results, a map illustrating the interrelationships of concepts such as “financial fraud, ” “public policy, ” and “financial regulation” with other categories was created, allowing for the identification of five clusters, each of which was characterized in detail. The results of the evolutionary and temporal analysis of scientific research showed that before 2000, scholars focused on the legislative aspects of combating financial fraud; from 2000 to 2015, on risk management and the impact of financial fraud on economic growth; from 2016 to the present, on the search for methods and tools to detect and combat financial fraud. The spatial analysis confirmed a predominantly intercontinental connection between researchers. The comparison of subject areas demonstrated the interdisciplinary nature of the study, with a predominant focus on the fields of “computer science” and “economics, econometrics, and finance, ” which is logical considering the economic nature and the ongoing technological transformation of financial fraud. The results can be utilized to develop new strategies, policies, and legislative initiatives to ensure financial integrity and increase confidence in financial systems.
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    Effect of Education on Ease of Doing Business in Conditions of Innovation Development: Factor Analysis and Multiple Regression
    (SUMY STATE UNIVERSITY, 2023-06-30) Samoilova, Anastasiia; Herasymenko, Valeriia; Kuznyetsova, Anzhela; Tumpach, Miloš; Ballová, Martina; Savga, Larisa
    Education accelerates changes and transformations in social life, as well as one of the main factors of progress and development in general and business. The article substantiates and formalises the relationships between indicators of the level of education (taking into account its innovative development) and the ease of doing business based on evidence from 28 world countries and the data from the World Bank, the United Nations, Tufts University and Standard & Poor's Ratings Services. The article aims to find indicators of innovative education that most significantly contribute to the ease of doing business. For this, cognitive analysis of statistical data is carried out, and with the help of descriptive analysis tools, a statistically significant characteristic space of indicators is formed. Checking the density and direction of the relationship is carried out by calculating the values of the Pearson correlation coefficients. The multidimensionality of input feature space is reduced to the four most significant indicators from nine investigated ones (digital development indicator; human development index; digital trust, financial literacy index) using the procedure of principal component analysis and orthogonal transformation using the Varimax method in the Statgraphics Centurion 19 software. The quality of the factorisation is confirmed by Kaiser-Meier-Olkin testing and Bartlett's sphericity testing. As a result of the developed multiple econometric models, which describe the dependence of ease of doing business and the above indicators, and the Backward Stepwise Selection hard screening procedure in Statgraphics 19, a statistically significant model of the effect of digital development on ease of doing business is built. It shows that with the value increase of digital development by 1%, ease of doing business will also increase by 0.79%. The obtained results can be useful to scientists for further research, as well as to change-makers in education and business and all stakeholders in the direction of & DLANGBRAC;business-education & drangbrac; competition.
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    Banking system stability in crisis periods: The impact of the banking regulator independence
    (LLC CPC Business Perspectives, 2023-09-29) Kerimov, Atik; Babayev, Azer; Dudchenko, Viktoria; Samusevych, Iaryna; Tumpach, Miloš
    This study aims to conduct a bibliometric analysis on the topic of public policy and financial regulation in preventing and combating financial fraud using a variety of bibliometric methods and tools, including the in-built tools of Scopus by Elsevier (SciVal) and Web of Science by Clarivate Analytics, as well as VOSviewer software. The most relevant publications related to the search terms were identified. Based on the results, a map illustrating the interrelationships of concepts such as “financial fraud, ” “public policy, ” and “financial regulation” with other categories was created, allowing for the identification of five clusters, each of which was characterized in detail. The results of the evolutionary and temporal analysis of scientific research showed that before 2000, scholars focused on the legislative aspects of combating financial fraud; from 2000 to 2015, on risk management and the impact of financial fraud on economic growth; from 2016 to the present, on the search for methods and tools to detect and combat financial fraud. The spatial analysis confirmed a predominantly intercontinental connection between researchers. The comparison of subject areas demonstrated the interdisciplinary nature of the study, with a predominant focus on the fields of “computer science” and “economics, econometrics, and finance, ” which is logical considering the economic nature and the ongoing technological transformation of financial fraud. The results can be utilized to develop new strategies, policies, and legislative initiatives to ensure financial integrity and increase confidence in financial systems.
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    A novel approach to estimating the debt capacity of European SMEs
    (Institute of Economic Research, 2023-06-30) Karas, Michal; Režňáková, Mária
    Research background: The concept of debt capacity assumes that a maximum value of debt ratio exists that when exceeded triggers unfavourable consequences, such as drop in market value, default or a change in the business' creditworthiness. With the current state of the art there is a priori no theoretical assurance that such a specific value exists, or rather it is repre-sented by an interval of values. Beyond that, our understanding of debt capacity is often limited to a theoretical approximation by firm-specific factors, while the context of macroeco-nomic factors, especially those critical for SMEs, is neglected.Purpose of the article: The aim of this paper is to present a novel approach to estimating SMEs' debt capacity. Further, the aim is to answer the question of what firm-level and macro -economy conditions lead to exhausting the SMEs' debt capacity and under what conditions a specific value of maximum debt capacity could be estimated.Methods: To estimate the debt capacity, we suggest a use of an information entropy minimis-ing heuristic and the Minimal Description Length Principle. In this approach, the observed feature space is categorised into several regions. In this case, such a region represents a set of firm-and macroeconomy-specific conditions forming the debt capacity of the SMEs. To the best of our knowledge, such an approach has not yet been used in debt capacity applications.Findings & value added: We found out that the debt ratio itself provides little explanation of exhausted debt capacity, suggesting that high debt levels are compensated for by other fac-tors. By using the suggested approach, a set of more than 100 different regions was analysed. It was found that in case of five regions (sets of conditions) the debt capacity is exhausted, as the high level of debt has significant distress consequences.
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    Predicting Bankruptcy of Agriculture Companies: Validating Selected Models
    (Faculty of Management, Czestochowa University of Technology, 2017-07-05) Karas, Michal; Režňáková, Mária; Pokorný, Petr
    Many bankruptcy prediction models have been published so far, most of them were especially designated for the manufacturing companies. According to several studies, these models are inappropriate for other industries, as such application would be connected with a significantly lower accuracy than could be expected. The aim of this paper is to analyse the current accuracy of four traditional bankruptcy prediction models in the field of agriculture. The results showed that these models are less accurate in this field in comparison with the original results. This motivates the effort of deriving new models that would be specially developed for agriculture business.