This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright © 2023 The Author(s). Published by Vilnius Gediminas Technical University ISSN 2669-2481 / eISSN 2669-249X BUSINESS, MANAGEMENT AND ECONOMICS ENGINEERING 2023 Volume 21 Issue 1 Pages 124–139 https://doi.org/10.3846/bmee.2023.18958 MACRO-ECONOMIC DEVELOPMENT OF THE EU COUNTRIES IN THE CONTEXT OF PERFORMANCE AND COMPETITIVENESS OF SMES Katarina VALASKOVA , MAREK NAGY Department of Economics, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia Article History: Abstract. Purpose – The paper focuses on the identification of disparities in the development of the macroeconomic environment across the member states of the European Union and problematic factors impacting the business environment’s level. Research methodology – To find the disparities in the development of the EU countries, the TOPSIS method was used. Based on this analysis, the crucial factors influencing the develop- ment of the macroeconomic environment were determined. The discriminant analysis was then used to form a model, which could help assess and examine the relationship between the business environment and significant determinants of development. Findings – Based on the methods applied, the determinants influencing the development of the macroeconomic environment and key factors and aspects affecting the rate of devel- opment of the economic and business environment were identified and the analysis of the economic and business environment was performed through selected statistical techniques. Practical implications – The analysis confirmed that some countries have certain gaps in its assessment of the dynamics of economic development in EU countries in terms of the sus- tainability and competitiveness of small and medium-sized businesses, and that the business climate is not entirely conducive to these businesses. Originality/Value – The additional value of the paper is the formation of the model, which helps identify the countries with appropriate business environment and those where the eco- nomic development is not sufficiently developed which may be useful for enterprises, inves- tors, and creditors. ■ received 12 April 2023 ■ accepted 09 May 2023 Keywords: competitiveness, small and medium-sized enterprises, TOPSIS analysis, discriminant analysis, business environment. JEL Classification: L25, F63, O11.      Corresponding author. E-mail: katarina.valaskova@fpedas.uniza.sk Introduction Competitiveness has become a much-discussed term in the past period. This term is often found in government program statements and other important documents. However, this concept is often understood differently and occurs in different dimensions (Valaskova et al., 2021a). The absence of a uniform definition of the term makes it impossible to understand the term well. The historical context of the concept of competitiveness differs considerably from period to period (Rajnoha & Lesnikova, 2022). In the past, this term was associated with an active balance of payments, productivity growth, or the use of basic production factors (la- bor, capital, and land). Currently, there are already several ways to evaluate the competitive- ness of a country by different indicators – some measure competitiveness, some innovations, http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ https://doi.org/10.3846/bmee.2023.18958 https://orcid.org/0000-0003-4223-7519 mailto:karahan.kara@artvin.edu.tr mailto:katarina.valaskova@fpedas.uniza.sk https://orcid.org/0000-0003-0740-6268 Business, Management and Economics Engineering, 2023, 21(1): 124–139 125 others map the state of the business environment, and some contain entire complex factors that provide a comprehensive view on the country’s competitiveness (Kiselakova et al., 2018). According to Safar et al. (2018), small and medium-sized businesses have a significant global and regional economic influence, not only in Central Europe. These are the main pillars of a successful labor policy. The European Union offers a number of initiatives that might benefit businesses and works to make the environment in which they operate as favorable as possible. One of the key benefits of the European Union is the openness of its borders, which allows for the potential of expanding into new markets and the harmonization of the eco- nomic, social, and legal frameworks for businesses. Consequently, it may be claimed that this combination of social, economic, cultural, and political components produces an ecosystem that either supports or impedes entrance into undertaking commercial operations following first company failure (Guerrero & Espinoza-Benavides, 2021. Stam and van de Ven (2021) dis- covered a considerable correlation between the incidence of high-growth businesses and the strength of the entrepreneurial environment. Business units have the chance to expand and thrive in new areas and find their essential success elements thanks to the open community (Moktadir et al., 2020). The nations of Central Europe take advantage of this chance and set up shop wherever it is practical and profitable. It should be stressed, nonetheless, that the macroeconomic climate and business-friendly conditions do have an impact and must be accurately analyzed and assessed (Roszko-Wójtowicz & Grzelak, 2020). Thus, the article fo- cuses on identifying differences in the macroeconomic environment among European Union member states as well as problematic elements that have an influence on the level of the business environment. Based on the calculations it would be possible to identify the most significant factors affecting the quality of the business climate and overall competitiveness of the countries. The paper focuses on the identification of disparities in the development of the macro- economic environment across the member states of the European Union and problematic factors impacting the level of the business environment. The paper is divided into the Liter- ature review which summarizes the most important and up-to-date references to show the importance of the issue in the international context. The Research methodology describes the database od inputs used in the research as well as the methodological steps which were followed. The section focused of the Research results highlight the outputs of the calculations which are then discussed in the context of other relevant studies. 1. Literature review The notion of competitiveness has moved from the business level to the international level because of globalisation. However, many scholars see the idea of competition differently. Yumei et al. (2021) and Abdul-Rashid et al. (2017), for example, argue that competitiveness is a multifaceted term that allows for several interpretations. In the same breath, they say that technical competitiveness is the most important part of firm competitiveness. Belas et al. (2021) acknowledge that competitiveness is a complex concept and add that it must be viewed holistically; therefore, its evaluation should reflect the extent to which the country fosters a business environment in which businesses can grow at a sustainable rate, thereby 126 K. Valaskova, M. Nagy. Macro-economic development of the EU countries in the context of performance... creating jobs and enhancing the well-being of its citizens. It follows from the preceding that company competitiveness is crucial. Since wealth is produced at the micro level, Brieger et al. (2020) and Buyukozkan et al. (2018) explore the idea of competition at this level. Based on the social and behavioural sciences, Teece (2007) and Zhang and Browne (2012) specify in greater detail the nature and particularly the micro foundations of capabilities that are re- quired to maintain excellent business performance in an open economy, primarily through rapid innovation, globally dispersed sources of invention, and production capabilities. Thus, those are the dynamic skills that enable firms to generate, deploy, and safeguard intangi- ble assets, hence supporting long-term business performance excellence. Evangelista et al. (2014) and Valaskova et al. (2021b) assert that the degree of profit achieved has a significant impact on the financial health and competitiveness of businesses. According to the research findings by Kiselakova et al. (2019), in the countries of the European Union, the micro level (business sector) is dominated by small and medium-sized enterprises (SMEs), which play a crucial role in the process of sustainable, competitive economic development. Further- more, human resources are a significant factor in the internationalisation of European SMEs. Du et al. (2017) and Gajanova et al. (2020) claim, that small and medium-sized enterprises are the actual lifeblood of economies throughout the world, since they contribute to the creation of employment and the competitiveness of economies, particularly during times of economic crisis. A portion of the scientific-research basis supports the study of the notion of innovation-based competitiveness. In terms of Elkington (1994) and Grewal et al. (2021), the primary objective of creative acts by businesses is to increase their assortment, quality, and market share or competitiveness. Cheng et al. (2022) stated that there is a substantial correlation between a state’s degree of competitiveness and its investment in research and development, human capital devel- opment, innovation potential, and scientific research base strengthening. Jayarathna et al. (2022) and Kliestik et al. (2020) conducted research on the competitiveness of regions and reached the conclusion that uneven development of natural, human, financial, infrastructur- al, and security aspects can lead to regional differences in the country, resulting in uneven development of regions and a decrease in competitiveness regions, which can result in a lower standard of living for residents in less developed regions. Several authors have studied the interrelationships and interdependencies between competitiveness and quality of life. Valaskova et al. (2021b), who examined the multidimensional evaluation of competitiveness, well-being, and innovation, determined that there is a significant and direct relationship between competitiveness, innovation, and well-being. Governments and corporations that engage more in innovation-focused research to boost the competitiveness of their goods and services have a higher GDP and a more prosperous populace. Cieslik and Michalek (2018) identified the following as factors that increase well-being, prosperity, and economic growth: population growth, working time, technology, specialisation, capital, labour, and productivity, in addition to numerous institutional factors, such as political system, economic freedom, and development (Cantele & Cassia, 2020). Climate change and global warming have compelled economists and scientists to incorporate an environmental dimension into the idea of com- petitiveness. Porter (1998) presented the research in which he determined that environmental regulations raise expenses needlessly, hence retarding environmental progress. The industry’s Business, Management and Economics Engineering, 2023, 21(1): 124–139 127 competitiveness has suffered because of the disregard of innovation’s advantages, which has led to a rise in compliance-related expenses and a decline in innovation’s benefits. In the past, the term “eco-innovation” was also used. This phrase is associated with organisational innovations, creative goods or processes designed to decrease environmental costs, boost societal acceptability, and eventually achieve sustainable development (Isensee et al., 2020; Vatamanescu et al., 2021). The rise of the global economy, however, sparked a desire for indices that give a gen- erally recognised assessment of competitiveness and construct a worldwide comparison of the competitiveness of national economies. The Global Competitiveness Index and the World Competitiveness Index are two indices that society considers to be the most significant and most acceptable. Several authors have done research on these indices, which may be inter- preted separately or in line with other factors to produce a multidimensional model that can better characterise the business environments of nations (see Nogueira & Madaleno, 2021; Olczyk et al., 2022; Benítez-Márquez et al., 2022; Khazei et al., 2021; etc.). Lu et al. (2022) conducted a one-dimensional comparison of indices and mapping of the business envi- ronment, in which they identified the primary obstacles that prevent Slovak entrepreneurs from conducting business. Kiselakova et al. (2019) and Nagypal (2014) attempted to identify important interrelationships between the evaluation of global competitiveness, the business environment, and the human development index in EU nations by conducting a panel analysis and non-linear regression analyses with the ANOVA test. Their conclusion was that there is a correlation between the business environment and the calibre of human resources, which are regarded as a worldwide competitive advantage. Hajduova et al. (2021) and Virglerova et al. (2017) conducted a similar multivariate analysis using the TOPSIS method, which allowed them to categorise individual countries of the European Union and thus reveal individual disparities between EU countries, concluding that the least effective business environment is in Cyprus, the Czech Republic, Estonia, Hungary, Poland, Latvia, Lithuania, Slovakia, and Slo- venia because they ranked below the EU average. Estonia, Malta, and Slovenia had the most improvement in their business climates among EU nations. This awareness of the reordering of indicators is also supported by the World Economic Forum, which in 2018 introduced a revised World Competitiveness Index that began to account for Industry 4.0. As a result of this small adjustment, Slovakia improved by up to 18 positions compared to the previous year. Despite these arguments and facts, there is a scientific basis for competitiveness indexes. 2. Research methodology The study analyses the business climate of EU nations using appropriate mathematical and statistical techniques. In the context of global competition, the building of a foundation for successful appraisal of the economic environment becomes essential. To compare the business environment in the EU countries, the TOPSIS methods was used. Several important macroeconomic factors were considered, which adequately represent the business and mac- roeconomic climate of EU member states. These factors were determined as input factors of the TOPSIS method: f1 – gross domestic product (in billions of U.S. dollars), f2 – average annual unemployment rate (in percent), f3 – average annual inflation rate (in percent), f4 – 128 K. Valaskova, M. Nagy. Macro-economic development of the EU countries in the context of performance... foreign direct investment (in billions of U.S. dollars), f5 – tax rate (in percent), f6 – openness of the economy (in percent), f7 – freedom of business (score), f8 – infrastructure (score), f9 – innovation level (score) and f10 – corruption rate (score). After establishing the criteria, it was required to locate information for each European country (however, one country, Malta, was omitted from the analysis, as appropriate data were not available for the selected period). After collecting data for all 26 European countries for the period 2017–2021 and dividing it into two sections, the time before the COVID-19 pandemic till 2019 and the period after the pandemic, the average values were determined. Due to turbulent changes on the national markets and distorted development of all mac- roeconomic indicators caused by the COVID-19 pandemic, it was necessary to consider two periods when assessing the performance and competitiveness of enterprises. After gathering the data, the computations begin; initially, the preferences between the criteria are deter- mined. The quantitative comparison was conducted using the Saaty’s matrix, in which a pair of criteria is always compared, followed by the determination of the preference’s magnitude. This matrix arranges the elements into a hierarchy using subjective judgments in order to assign numerical values based on the relative importance of these elements to the overall goals (Saaty, 1987). To eliminate the subjectivism in the calculation, the consistency ratio should be calculated, which is the ratio of a consistency index to the mean consistency index from a large sample of randomly generated matrices. If the consistency ratio is above 0.1, it is needed to reconsider the decision matrix for any inconsistent rating of factors (Pourghase- mi et al., 2012). The recommended point scale for this method is as follows: 1 – The criteria are of equal importance, 3 – The criterion in the row is less significant than the criterion in the column, 5 – The criterion in the row is more significant than the criterion in the column, 7 – The criterion in the row is extremely more significant than the criterion in the column, 9 – The criterion in the row is absolutely more significant than the criterion in the column (Table 1). The calculated value of the consistency ratio was below the limit value of 0 indicat- ing a reasonable level of consistency. Table 1. Saaty matrix (source: authors’ compilation) f1 f2 f3 f4 f5 f6 f7 f8 f9 f10 f1 1 1/3 1/4 5 1/4 5 2 1/5 1/5 1/5 f2 3 1 1/5 5 1/4 4 2 1/5 1/5 1/5 f3 4 5 1 5 1 4 3 1/5 1/5 1/5 f4 1/5 1/5 1/5 1 1/5 1/3 1/2 1/5 1/5 1/5 f5 4 4 1 5 1 5 5 1/4 1/4 1/4 f6 1/5 1/4 1/4 3 1/5 1 1 1/5 1/5 1/5 f7 1/2 1/2 1/3 2 1/5 1 1 1/5 1/5 1/5 f8 5 5 5 5 4 5 5 1 1 1 f9 5 5 5 5 4 5 5 1 1 1 f10 5 5 5 5 4 5 5 1 1 1 Business, Management and Economics Engineering, 2023, 21(1): 124–139 129 Subsequently, the criteria were arranged into Saaty’s matrix, to which the following ap- plies: ≈ = …,  , 1, 2, 3iij j v s i j n v . (1) To calculate the weights, Saaty created an eigenvector corresponding to the largest ei- genvalue of the matrix A, the solution is then the normalized geometric mean of the matrix S, where vi is the weight of the i-th criterion (Wong et al., 2021). = = =  Π =  Π  ∑ 1 1 1 11 k k i i k k k j iji j v s . (2) Using a scale ranging from one to nine, the relationships between the chosen criteria were identified. The subjective evaluation of the significance of specific criteria is, of course, one of the downsides of this technique (which was eliminated calculating the consistency index). As the comparison of the criteria with itself equals to one, this matrix is consequently recipro- cal; there are always units on the major diagonal. Above this diagonal, the sorted values are ranked according to the subjective opinion of their relevance. Underneath this diagonal are their inverse values. The selected unput criteria domestic product, foreign direct investment, freedom of entrepreneurship, openness of the economy, infrastructure, innovation level, and degree of corruption were set as the maximising criteria for the application of the TOPSIS technique and unemployment, inflation, and taxation as minimising criteria. Maximization criteria are required for the TOPSIS analysis, thus, in the following stage, the minimization criteria must be replaced by maximisation criteria. In the subsequent phase, a weighted cri- teria matrix was created by multiplying each j-th column of the normalised criterion matrix by its respective weight vi . Following this, the ideal and baseline variants for each criterion can be calculated. The authors established the upper limit as the column’s maximum and the lower limit as its minimum. In the last phase, the Euclidean distance between the ideal +id variation and the base −id variant was calculated. Using the following formulas, the ideal and baseline variations were determined: ( )+ =    = − = …     ∑ 1 22 1 1, 2, 3 k i ij j i d w H i n ; (3) ( )− =    = − = …     ∑ 1 22 1 1, 2, 3 k i ij j i d w D i n . (4) After calculating the ideal and base variants, the relative indicators of the distance of variations from the base variant ic (0;1) were measured. − − + = + i i i i d c d d . (5) 130 K. Valaskova, M. Nagy. Macro-economic development of the EU countries in the context of performance... After calculating the relative indicators, variations were obtained and sorted in descend- ing order based on the decreasing values of the ci indicator, resulting in a comprehensive arrangement of all variants. The identification of these criteria and ordering the countries according to the level of the national competitiveness and development of the macroeconomic environment, the dis- criminant analysis was used, using the same input variables, to find a linear combination of features that characterizes or separates two groups of countries – with developed and competitive business environment and those with the deficient one. This method comprises a discriminant function that is premised on linear combinations of the predictor variables that offer the best discrimination between the groups of European countries. To use the discrimi- nant analysis, the basic assumptions of the input data must be met in our study: i) samples should be independent and unconnected to one another; ii) the variance-covariance matrices for each group should be the same, and the predictor variables should have a multivariate normal distribution; iii) as a group membership is assumed to be mutually exclusive (no case belongs to more than one group), it is presumed that cases cannot correspond to more than one group. 3. Research results and discussion To reach the main aim of the paper and following the methodological steps, the ci indicator was calculated for both periods (pre-pandemic and pandemic) using the selected macro-eco- nomic indicators which appropriately assess the quality and attractiveness of the business environment. As indicated in the methodology section of the paper, the analytical calculus is focused on ten important indicators which allow determining the development of the mac- roeconomic environment across the member states. Table 2 summarizes the results, based on the calculated ci indicator in the first analysed period. Table 2. Ranking of the EU countries in the period 2017–2019 (source: authors’ compilation) Ranking Country ci indicator Ranking Country ci indicator 1. Ireland 0.61724 14. Slovenia 0.42455 2. Denmark 0.61133 15. Spain 0.41637 3. Finland 0.60264 16. Poland 0.41341 4. Germany 0.58997 17. Hungary 0.41209 5. Sweden 0.58442 18. Czech Republic 0.41184 6. Netherlands 0.57102 19. Bulgaria 0.39413 7. France 0.52004 20. Latvia 0.39178 8. Austria 0.48961 21. Estonia 0.38611 9. Luxembourg 0.48335 22. Croatia 0.36243 10. Cyprus 0.48294 23. Greece 0.35218 11. Italy 0.45153 24. Lithuania 0.34163 12. Portugal 0.45028 25. Romania 0.30783 13. Belgium 0.42984 26. Slovak Republic 0.30055 Business, Management and Economics Engineering, 2023, 21(1): 124–139 131 The study indicates that Ireland is the country with the most appropriate business en- vironment. Consequently, Denmark, Finland, Germany and Sweden outperform in terms of competitiveness, economic freedom, innovation, corruption, and environmental performance. Comparing the top countries with those at the end of the ranking, the problematic charac- teristics of the Slovak Republic include economic growth, employment, inflation, tax policy, inadequate infrastructure, a low degree of innovation, and relatively high levels of corruption. Comparing Ireland and the Slovak Republic across the competitiveness pillars (International Institute for Management Development [IMD], 2022) reveals that company efficiency is the most problematic aspect (Figure 1). 0 20 40 60 80 100 Government efficiency Business efficiency Infrastructure Economic performance Ireland Slovakia Figure 1. Radar diagram for Ireland and Slovakia (source: authors’ compilation) The same procedure was followed for the calculation in the years 2020 and 2021. By calcu- lating the relative indicators, the variants were obtained, which were arranged in descending order according to the decreasing values of the ci indicator, thereby achieving a complete arrangement of all variants (Table 3). Table 3. Ranking of the EU countries in the period 2020–2021 (source: authors’ compilation) Ranking Country ci indicator Ranking Country ci indicator 1. Sweden 0.60850 14. Slovenia 0.43584 2. Denmark 0.60266 15. Portugal 0.42301 3. Finland 0.59755 16. Hungary 0.41219 4. Ireland 0.58733 17. Spain 0.41161 5. Netherlands 0.56231 18. Lithuania 0.40713 6. Germany 0.56158 19. Bulgaria 0.39388 7. France 0.54987 20. Czech Republic 0.39119 8. Austria 0.49602 21. Latvia 0.36868 9. Luxemburg 0.48031 22. Greece 0.36485 10. Cyprus 0.46389 23. Croatia 0.32744 11. Belgium 0.46119 24. Poland 0.32275 12. Italy 0.44027 25. Romania 0.30812 13. Estonia 0.43758 26. Slovak Republic 0.28781 132 K. Valaskova, M. Nagy. Macro-economic development of the EU countries in the context of performance... Table 3 presents similar results compared to the outputs in the pre-pandemic period, but there were some shifts, Sweden took the first place. Germany dropped out of the top five and was replaced by the Netherlands. If the country with the most and least appropriate business environments, Sweden and Slovakia, are compared, the areas of improvement can be determined (economic growth, employment, inflation, tax policy, insufficient infrastruc- ture, problems with innovation potential, and high corruption). Even in this analysis, it is appropriate to create a radar diagram (Figure 2) to reveal the weak points of Slovak business environment (IMD, 2022). 0 20 40 60 80 100 Government efficiencyInfrastructure Business efficiency Economic performance Sweden Slovakia Figure 2. Radar diagram for Sweden and Slovakia (source: authors’ compilation) After a better analysis of business-related indicators, Slovakia should increase overall la- bour productivity in all areas, increase the efficiency of small and medium-sized businesses, make greater use of digital tools and technologies, increase financial skills, attract, and retain talent, prevent brain drain (which hinders economic growth), attract talents from abroad, or open the national culture to new ideas. The analysis realized in the pandemic period shows, that Slovakia should primarily improve three of the four evaluated areas of government effec- tiveness, such as the level of debt, increasing transparency, reducing bureaucracy, addressing corruption, strengthening the rule of law, mitigating protectionist measures, implementing solutions in the parallel economy, and streamlining the operation of businesses. Regarding infrastructure: completion of road infrastructure, energy infrastructure, increasing digital and technological skills, increasing expenditures on research and development, increasing the transfer of knowledge, reducing the ecological footprint, utilising renewable resources, in- creasing expenditures on education, increasing the quality of higher education, and increas- ing literacy and language skills knowledge. However, these are the areas to be improved not only in Slovakia, but also other countries with deficiencies in the development and compet- itiveness of their business environment. Moreover, the economic impacts of the pandemic also had an effect on global competition as the overall calculated values of the ci indicator are lower (reflecting the overall macroeconomic development of the national business en- vironment) in the second analyzed period. Nonetheless, raising long-term economic growth rates and rising living standards require improving national competitiveness. Together with macroeconomic variables, the business environment, and customer demand, competitiveness Business, Management and Economics Engineering, 2023, 21(1): 124–139 133 factors alter (Boikova et al., 2021). The rising significance of digitization for businesses across all industries is indicative of these shifts (Gavurova & Megyesiova, 2022; Markova et al., 2022). The results achieved may be also confirmed by different world competitiveness rankings that measure the competitiveness performance (Zahorskyi et al., 2020) on a basis of vari- ous pillars (e.g. Global Competitiveness Index, Doing Business Index, World Competitiveness Ranking, Environmental Performance Index, etc.). Contrary to the critique that has frequently been made in the academic literature, competitiveness rankings are quite popular. Rankings presuppose that there are no regional variations in the factors that affect competitiveness. The list of determinants is supplied, and although each determinant’s weight is given, it is assumed that all nations would perform similarly despite the fact that a country’s real per- formance may differ for each factor. Thus, the use of macro-economic indicators to assess the national business environment seems to be a relevant measure. The study of Simionescu et al. (2021) on the EU countries in the period 2004–2018 indicated that the level of research and development expenditure, gross domestic product (GDP), foreign direct investments (FDI) and the innovation processes are the most significant drivers of the competitiveness which is in line with the indicators used in this study. Roszko-Wójtowicz and Grzelak (2020) in their study focused on the macro-economic stability and competitiveness of EU member states confirmed the importance of the DGP, FDI, registered unemployment rate and inflation rate in the assessment of the economic situation of EU countries. Dima et al. (2018) compared the global competitiveness index with selected macro-economic indicators and highlighted the role of innovation and research and development activities which significantly develop the competitiveness of EU countries. Moreover, the empirical analyses by Simionescu et al. (2017) proved that FDI promoted economic growth in all Central European countries as well as the expenditures on research and development. The amount of foreign direct investment (FDI) demonstrates the attractiveness of particular nations to foreign direct investors. Foreign direct investment is regarded as advantageous for host nations because it fills up the capital gap left by insufficient national savings. It introduces or spreads contemporary management systems and impacts an economy’s technological modernization. Foreign direct investment (FDI) is also seen to be a means of promoting economic development in impoverished areas, such as through the creation of new employment by foreign investors (Petricevic & Teece, 2019; Su et al., 2018; Altomonte & Ottaviano, 2011). Based on the analysis, the crucial factors (same input variables as in the TOPSIS method) influencing the development of the macroeconomic environment were set and determined. The discriminant analysis was then used to form a model, which could help assess and ex- amine the relationship between the business environment and significant determinants of development and, thus, determine the countries with developed and competitive business environment and those with the deficient one. After gathering all the data, a model was developed using the SPSS Statistics. As indicated in the methodology section, the basic as- sumptions should be considered. Tests of equality of group means revealed, that out of all ten input variables only one of them is an appropriate discriminant – the volume of foreign direct investments (p-value 0.038). The results of the Box’s M test verify that the variance-co- variance matrices for each group of countries is the same (p-value 0.073). The overall quality of the discriminant model was verified by the canonical correlation (0.873) and its test of the 134 K. Valaskova, M. Nagy. Macro-economic development of the EU countries in the context of performance... statistical significance (p-value 0.007). Using the unstandardized coefficients of the canonical discriminant function, it is possible to set the resulting discriminant function of the prediction model for EU countries, which has the form: = − + ⋅30.4 0.035 .Z FDI (5) The SPSS program uses the model constant to calculate the centroids, thereby making a targeted correction so that the weighted average of the centroids (weighted by the number of countries in each group) is equal to zero. The result is then determined by comparing the Z-score values with zero, a positive value represents a developed business environment, and a negative value is for the business environment with some deficiencies. The results of the discriminant analysis proved the importance of the foreign direct investments in the de- velopment of the competitive business environment within the EU countries. Horobet et al. (2021) identified FDI as the most important predictor form a set of 15 macro indicator in the Central European countries which shapes the competitiveness in this environment. The same result was achieved in the study by Majeed et al. (2021) who claimed that FDI influence financial development and has significant implications on the competitiveness of an economy which was proved on a data from 1990 to 201 using the method of panel cointegration and causality analysis. Hakhverdyan and Shahinyan (2022) affirmed that FDI and import trade are major aspects of the technological diffusion. Based on the observations of macroeconomic variables in more than 50 countries in the 20-year period they confirmed the influence of FDI on country competitiveness. Nonetheless, FDI seem to be a source of national competi- tiveness (Gugler & Brunner, 2007). The TOPSIS investigation determined that Ireland and Sweden offer the most suited busi- ness environments, compared to the business environment in Slovakia, which should be significantly improved in specific aspects. Based on the selected data, discriminant analysis revealed that the level of the foreign direct investments is the most appropriate macro-eco- nomic parameter to determine the performance and competitiveness of the business envi- ronment. Conclusions As part of the assessment of the dynamics of economic development in the countries of the European Union in the context of the sustainability and competitiveness of small and me- dium-sized enterprises, the analysis of the business environment led to the conclusion that Slovakia has certain competitiveness gaps and that the business environment is not wholly favourable for small and medium-sized enterprises. The competitiveness of the economy, economic freedom, innovation, corruption, envi- ronmental performance, and population contentment are the primary determinants of the growth of the economic and commercial environment. A lot of elements determine the busi- ness environment; on the one hand, there are individual characteristics that disclose the company’s competitive edge. In addition to external variables affecting the business, the government primarily impacts the business through the enactment of pro-business laws. Re- garding global issues, it is the capacity of businesses to adapt to foreign situations. Foreign direct investments are a crucial factor in influencing the quality of the business climate. Via Business, Management and Economics Engineering, 2023, 21(1): 124–139 135 direct foreign investments, the standard of life of the populace rises; through the expansion of employment, there is an infusion of new technology; and so forth. The contribution of corporate income taxes to the state budget is an indirect advantage of direct foreign in- vestments. Foreign direct investments have a significant impact on the macroeconomic en- vironment, as well as on the business environment of European countries, which should not be omitted. If states want to improve their performance and competitiveness in the global market, it is necessary to increase the level of foreign direct investment, which is a challenge for the policy maker within the country’s economic policy, while their management requires a long-term plan. The availability of an educated, qualified, productive and flexible domestic workforce has a significant impact on attracting foreign direct investment with a positive impact on the development of the economy. The increase and maintenance of foreign direct investments depends mainly on the improvement of the business environment, its immuta- bility and transparency. The unavailability of newer and more thorough sources that may improve and deepen the analysis is one of the limits of this study. There is also potential for a broader comparison of nations, even though the comparison of the entire European Union can be considered a representative sample. Therefore, the future of this research may include non-EU countries as well as other indicators, also under the influence of the evolution of the world’s most recent technological achievements – Industry 4.0 and its transition to phase 5.0, the comprehension and application of which would be extremely beneficial for the countries with some deficien- cies in the competitive business environment. Acknowledgements This research was financially supported by the Slovak Research and Development Agen- cy – Grant Vega 1/0121/20: Research of transfer pricing system as a tool to measure the performance of national and multinational companies in the context of earnings manage- ment in conditions of the Slovak Republic and V4 countries and faculty institutional research 1/KE/2022: Analysis of the determinants of indebtedness and profitability of business entities in the European area. Funding This research received no external funding. Conflicts of interest The authors declare no conflict of interest. Author contributions All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication. 136 K. Valaskova, M. Nagy. Macro-economic development of the EU countries in the context of performance... Data availability statement The data presented in this study are available on request from the corresponding author. References Altomonte, C., & Ottaviano, G. I. P. (2011). The role of international production sharing in EU productivity and competitiveness. EIB Papers, 16(1), 62–88. Abdul-Rashid, S. H., Sakundarini, N., Ghazilla, R. A. R., & Thurasamy, R. (2017). The impact of sustainable manufacturing practices on sustainability performance Empirical evidence from Malaysia. International Journal of Operations & Production Management, 37(2), 182–204. https://doi.org/10.1108/IJOPM-04-2015-0223 Belas, J., Çera, G., Dvorsky, J., & Cepel, M. (2021). Corporate social responsibility and sustainability issues of small- and medium-sized enterprises. Corporate Social Responsibility and Environmental Manage- ment, 28(2), 721–730. https://doi.org/10.1002/csr.2083 Benítez-Márquez, M. D., Sánchez-Teba, E. M., & Coronado-Maldonado, I. (2022). An alternative index to the global competitiveness index. PLoS ONE, 17(3), e0265045. https://doi.org/10.1371/journal.pone.0265045 Boikova, T., Zeverte-Rovza, S., Rivza, P., & Rivza, B. (2021). The determinants and effects of competitive- ness: The role of digitalization in the European economies. Sustainability, 13(21), 11689. https://doi.org/10.3390/su132111689 Brieger, S. A., Anderer, S., Fröhlich, A., Baro, A., & Meynhardt, T. (2020). Too much of a good thing? On the relationship between CSR and employee work addiction. Journal of Business Ethics, 166(2), 311–329. https://doi.org/10.1007/s10551-019-04141-8 Buyukozkan, G., & Karabulut, Y. (2018). Sustainability performance evaluation: Literature review and future directions. Journal of Environmental Management, 217, 253–267. https://doi.org/10.1016/j.jenvman.2018.03.064 Cantele, S., & Cassia, F. (2020). Sustainability implementation in restaurants: A comprehensive model of drivers, barriers, and competitiveness-mediated effects on firm performance. International Journal of Hospitality Management, 87, 102510. https://doi.org/10.1016/j.ijhm.2020.102510 Cheng, Y. H., Chang, K. C., Cheng, Y. S., & Hsiao, C. J. (2022). How green marketing influences customers’ green behavioral intentions in the context of hot-spring hotels. Journal of Tourism and Services, 24(13), 190–208. https://doi.org/10.29036/jots.v13i24.352 Cieslik, A., & Michalek, J. (2018). Firm-level determinants of direct and indirect exports: empirical evidence for C.E.E. and M.E.N.A. countries. Economic Research-Ekonomska Istraživanja, 31(1), 982–996. https://doi.org/10.1080/1331677X.2018.1436452 Dima, A. M., Begu, L., Vasilescu, M. D., & Maassen, M. A. (2018). The relationship between the knowledge economy and global competitiveness in the European Union. Sustainability, 10(6), 1706. https://doi.org/10.3390/su10061706 Du, S., Yu, K., Bhattacharya, C. B., & Sen, S. (2017). The business case for sustainability reporting: Evidence from stock market reactions. Journal of Public Policy & Marketing, 36(2), 313–330. https://doi.org/10.1509/jppm.16.112 Elkington, J. (1994). Towards the sustainable corporation: Win-win-win business strategies for sustain- able development. California Management Review, 36(2), 90–100. https://doi.org/10.2307/41165746 Evangelista, R., Guerrieri, P., & Melicani, V. (2014). The economic impact of digital technologies in Europe. Eco- nomics of Innovation and New Technology, 23(8), 802–824. https://doi.org/10.1080/10438599.2014.918438 Gajanova, L., Nadanyiova, M., Musat, M., & Bogdan, A. (2020). The social recruitment as a new opportunity in the Czech Republic and Slovakia. Ekonomicko-manazerske spektrum, 14(1), 65–76. https://doi.org/10.26552/ems.2020.1.65-76 Gavurova, B., & Megyesiova, S. (2022). Sustainable health and wellbeing in the European Union. Frontiers in Public Health, 10, 851061. https://doi.org/10.3389/fpubh.2022.851061 https://doi.org/10.1108/IJOPM-04-2015-0223 https://doi.org/10.1002/csr.2083 https://doi.org/10.1371/journal.pone.0265045 https://doi.org/10.3390/su132111689 https://doi.org/10.1016/j.jenvman.2018.03.064 https://doi.org/10.1016/j.ijhm.2020.102510 https://doi.org/10.1080/1331677X.2018.1436452 https://doi.org/10.3390/su10061706 https://doi.org/10.1509/jppm.16.112 https://doi.org/10.2307/41165746 https://doi.org/10.1080/10438599.2014.918438 https://doi.org/10.26552/ems.2020.1.65-76 https://doi.org/10.3389/fpubh.2022.851061 Business, Management and Economics Engineering, 2023, 21(1): 124–139 137 Grewal, J., Hauptmann, C., & Serafeim, G. (2021). Material sustainability information and stock price in- formativeness. Journal of Business Ethics, 171, 513–544. https://doi.org/10.1007/s10551-020-04451-2 Guerrero, M., & Espinoza-Benavides, J. (2021). Does entrepreneurship ecosystem influence business re-entries after failure? International Entrepreneurship and Managerial Journal, 17, 211–227. https://doi.org/10.1007/s11365-020-00694-7 Gugler, P., & Brunner, S. (2007). FDI effects on national competitiveness: A cluster approach. International Advances in Economic Research, 13(3), 268–284. https://doi.org/10.1007/s11294-007-9091-1 Hajduova, Z., Hurajova, J., Smorada, M., & Srenkel, L. (2021). Competitiveness of the selected countries of the EU with a focus on the quality of the business environment. Journal of Competitiveness, 13(4), 43–59. https://doi.org/10.7441/joc.2021.04.03 Hakhverdyan, D., & Shahinyan, M. (2022). Competitiveness, innovation and productivity of the country. Marketing and Management of Innovations, 1, 108–123. https://doi.org/10.21272/mmi.2022.1-08 Horobet, A., Popovici, O. C., & Belascu, L. (2021). Shaping competitiveness for driving FDI in CEE countries. Romanian Journal of European Affairs, 21(2), 48–68. International Institute for Management Development. (2022). IMD World Digital Competitiveness Ranking 2022. Switzerland. Isensee, C., Teuteberg, F., Griese, K. M., & Topi, C. (2020). The relationship between organizational culture, sustainability, and digitalization in SMEs: A systematic review. Journal of Cleaner Production, 275, 122944. https://doi.org/10.1016/j.jclepro.2020.122944 Jayarathna, C. P., Agdas, D., Les, D., & Miska, M. (2022). Exploring sector-specific sustainability indicators: A content analysis of sustainability reports in the logistics sector. European Business Review, 34(3), 321–343. https://doi.org/10.1108/EBR-02-2021-0047 Khazei, M., Azizi, M., & Zali, M. (2021). How performance of top companies are related on Global Com- petitiveness Index? Journal of Global Entrepreneurship Research, 11, 129–139. https://doi.org/10.1007/s40497-021-00276-z Kiselakova, D., Sofrankova, B., Cabinova, V., Onuferova, E., & Soltesova, J. (2018). The impact of R&D expenditure on the development of global competitiveness within the CEE EU countries. Journal of Competitiveness, 10(3), 34–50. https://doi.org/10.7441/joc.2018.03.03 Kiselakova, D., Sofrankova, B., Gombor, M., Cabinova, V., & Onuferova, E. (2019). Competitiveness and its impact on sustainability, business environment, and human development of EU (28) countries in terms of global multi-criteria indices. Sustainability, 11, 3365. https://doi.org/10.3390/su11123365 Kliestik, T., Belas, J., Valaskova, K., Nica, E., & Durana, P. (2020). Earnings management in V4 countries: The evidence of earnings smoothing and inflating. Economic Research-Ekonomska Istrazivanja, 34(1), 1452–1470. https://doi.org/10.1080/1331677X.2020.1831944 Lu, J., Rodenburg, K., Foti, L., & Pegoraro, A. (2022). Are firms with better sustainability performance more resilient during crises? Business Strategy and the Environment, 31(7), 3354–3370. https://doi.org/10.1002/bse.3088 Majeed, A., Jiang, P., Ahmad, M., Khan, M. A., & Olah, J. (2021). The impact of foreign direct investment on financial development: New evidence from panel cointegration and causality analysis. Journal of Competitiveness, 13(1), 95–112. https://doi.org/10.7441/joc.2021.01.06 Markova, I., Kubas, J., Buganova, K., & Ristvej, J. (2022). Usage of sorbents for diminishing the negative impact of substances leaking into the environment in car accidents. Frontiers in Public Health, 10, 957090. https://doi.org/10.3389/fpubh.2022.957090 Moktadir, A., Ahmadi, H. B., Sultana, R., Zohra, F. T., Liou, J. J. H., & Rezaei, J. (2020). Circular economy practices in the leather industry: A practical step towards sustainable development. Journal of Cleaner Production, 251, 119737. https://doi.org/10.1016/j.jclepro.2019.119737 Nagypal, C. N. (2014). Corporate social responsibility of Hungarian SMEs with good environmental prac- tices. Journal of East European Management Studies, 19(3), 327–347. https://doi.org/10.5771/0949-6181-2014-3-327 Nogueira, M. C., & Madaleno, M. (2021). New evidence of competitiveness based on the global compet- itiveness index. Economic Bulletin, 41(2), 788–797. https://doi.org/10.1007/s10551-020-04451-2 https://doi.org/10.1007/s11294-007-9091-1 https://doi.org/10.7441/joc.2021.04.03 https://doi.org/10.21272/mmi.2022.1-08 https://doi.org/10.1016/j.jclepro.2020.122944 https://doi.org/10.1108/EBR-02-2021-0047 https://doi.org/10.1007/s40497-021-00276-z https://doi.org/10.7441/joc.2018.03.03 https://doi.org/10.3390/su11123365 https://doi.org/10.1080/1331677X.2020.1831944 https://doi.org/10.1002/bse.3088 https://doi.org/10.7441/joc.2021.01.06 https://doi.org/10.3389/fpubh.2022.957090 https://doi.org/10.5771/0949-6181-2014-3-327 138 K. Valaskova, M. Nagy. Macro-economic development of the EU countries in the context of performance... Olczyk, M., Kuc-Czarnecka, M., & Saltelli, A. (2022). Changes in the Global Competitiveness Index 4.0 methodology: The improved approach of competitiveness benchmarking. Journal of Competitiveness, 14(1), 118–135. https://doi.org/10.7441/joc.2022.01.07 Petricevic, O., & Teece, D. J. (2019). The structural reshaping of globalization: Implications for strategic sectors, profiting from innovation, and the multinational enterprise. Journal of International Business Studies, 50(9), 1487–1512. https://doi.org/10.1057/s41267-019-00269-x Porter, M. E. (1998). Clusters and the new economics of competition. Harvard Business Review. Pourghasemi, H. R., Pradhan, B., & Gokceoglu, C. (2012). Application of fuzzy logic and analytical hierar- chy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran, Nat. Hazards, 63(2), 965–996. https://doi.org/10.1007/s11069-012-0217-2 Rajnoha, R., & Lesnikova, P. (2022). Sustainable competitiveness: How does global competitiveness index relate to economic performance accompanied by the sustainable development? Journal of Competi- tiveness, 14(1), 136–154. https://doi.org/10.7441/joc.2022.01.08 Roszko-Wójtowicz, E., & Grzelak, M. M. (2020). Macroeconomic stability and the level of competitiveness in EU member states: A comparative dynamic approach. Oeconomia Copernicana, 11(4), 657–688. https://doi.org/10.24136/oc.2020.027 Saaty, R. W. (1987). The analytical hierarchy process – what it is and how it is used. Mathematical Mod- elling, 9(3–5), 161–176. https://doi.org/10.1016/0270-0255(87)90473-8 Safar, L., Sopko, J., Bednar, S., & Poklemba, R. (2018). Concept of SME business model for industry 4.0 environment. TEM Journal, 7(3), 626–637. https://doi.org/10.18421/TEM73-20 Simionescu M., Lazányi K., Sopkova G., Dobes, K., & Balcerzak A. P. (2017). Determinants of economic growth in V4 countries and Romania. Journal of Competitiveness, 9(1), 103–116. https://doi.org/10.7441/joc.2017.01.07 Simionescu, M., Pelinescu, E., Khouri, S., & Bilan, S. (2021). The main drivers of competitiveness in the EU-28 countries. Journal of Competitiveness, 13(1), 129–145. https://doi.org/10.7441/joc.2021.01.08 Stam, E., & van de Ven, A. (2021). Entrepreneurial ecosystem elements. Small Business Economics, 56, 809–832. https://doi.org/10.1007/s11187-019-00270-6 Su, D. T., Nguyen, P. C., & Christophe, S. (2019). Impact of foreign direct investment, trade openness and economic institutions on growth in emerging countries: The case of Vietnam. Journal of International Studies, 12(3), 243– 264. https://doi.org/10.14254/2071-8330.2019/12-3/20 Teece, D. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enter- prise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640 Valaskova, K., Androniceanu, A.-M., Zvarikova, K., & Olah, J. (2021a). Bonds between earnings manage- ment and corporate financial stability in the context of the competitive ability of enterprises. Journal of Competitiveness, 13(4), 167–184. https://doi.org/10.7441/joc.2021.04 Valaskova, K., Gajdosikova, D., & Pavic Kramaric, T. (2022). How important is the business environment for the performance of enterprises? Case study of selected European Countries. Central European Business Review, 11(4), 85–110. https://doi.org/10.18267/j.cebr.300 Valaskova, K., Kliestik, T., & Gajdosikova, D. (2021b). Distinctive determinants of financial indebtedness: Evidence from Slovak and Czech enterprises. Equilibrium. Quarterly Journal of Economics and Economic Policy, 16(3), 639–659. https://doi.org/10.24136/eq.2021.023 Vatamanescu, E. M., Dabija, D. C., Gazzola, P., Cegarra-Navarro, J. G., & Buzzi, T. (2021). Before and after the outbreak of Covid-19: Linking fashion companies’ corporate social responsibility approach to consumers’ demand for sustainable products. Journal of Cleaner Production, 327, 129465. https://doi.org/10.1016/j.jclepro.2021.128945 Virglerova, Z., Homolka, L., Smrcka, L., Lazanyi, K., & Kliestik, T. (2017). Key determinants of the quality of business environment of Smes in The Czech Republic. E & M Ekonomie a Management, 20(2), 87–101. https://doi.org/10.15240/tul/001/2017-2-007 Wong, D. T. W., & Ngai, E. W. T. (2021). Economic, organizational, and environmental capabilities for business sustainability competence: Findings from case studies in the fashion business. Journal of Business Research, 126, 440–471. https://doi.org/10.1016/j.jbusres.2020.12.060 https://doi.org/10.7441/joc.2022.01.07 https://doi.org/10.1057/s41267-019-00269-x https://doi.org/10.1007/s11069-012-0217-2 https://doi.org/10.7441/joc.2022.01.08 https://doi.org/10.24136/oc.2020.027 https://doi.org/10.1016/0270-0255(87)90473-8 https://doi.org/10.7441/joc.2017.01.07 https://doi.org/10.7441/joc.2021.01.08 https://doi.org/10.14254/2071-8330.2019/12-3/20 https://doi.org/10.1002/smj.640 https://doi.org/10.7441/joc.2021.04 https://doi.org/10.18267/j.cebr.300 https://doi.org/10.24136/eq.2021.023 https://doi.org/10.1016/j.jclepro.2021.128945 https://doi.org/10.15240/tul/001/2017-2-007 https://doi.org/10.1016/j.jbusres.2020.12.060 Business, Management and Economics Engineering, 2023, 21(1): 124–139 139 Yumei, H., Iqbal, W., Nurunnabi, M., Abbas, M., Jingde, W., & Chaudhry, I. S. (2021). Nexus between cor- porate social responsibility and firm’s perceived performance: evidence from SME sector of developing economies. Environmental Science and Pollution Research International, 28(2), 2132–2145. https://doi.org/10.1007/s11356-020-10415-w Zahorskyi, V., Lipentsev, A., Mazii, N., Bashtannyk, V., & Akimov, O. (2020). Strategic directions of state as- sistance to enterprises development in Ukraine: Managerial and financial aspects. Financial and Credit Activity-Problems of Theory and Practice, 2(33), 452–462. https://doi.org/10.18371/fcaptp.v2i33.207230 Zhang, G., & Browne, M. W. (2012). Dynamic factor analysis with ordinal manifest variables. In Statisti- cal methods for modelling human dynamics: An interdisciplinary dialogue (pp. 241–264). Routledge. https://doi.org/10.4324/9780203864746 https://doi.org/10.1007/s11356-020-10415-w https://doi.org/10.18371/fcaptp.v2i33.207230 https://doi.org/10.4324/9780203864746 Bookmark 2