*Corresponding Author ENTREPRENEURIAL ACTIVITY IN SLOVENIA: THE ROLE OF GENDER AND HOUSEHOLD INCOME Ana Malnar* University of Rijeka, Croatia ana.malnar@efri.hr Karin Širec University of Maribor, Slovenia karin.sirec@um.si Abstract Entrepreneurial activity is considered an important aspect of the organization of industries most conducive to innovation and unrestricted competition and, at the same time, it is viewed as one of the most important factors in the economic progress of a country. Entrepreneurial activity depends, among other, on several individual factors. This paper investigates the correlation between entrepreneurial activity and individual predictors such as gender and household income based on the data from Global Entrepreneurship Monitor (GEM). The paper aims to help fill the gap in the literature by providing a quantitative analysis of the relationships and effects between entrepreneurial activity, gender, and household income in Slovenia. The empirical results show that the correlations between entrepreneurial activity and gender could not be confirmed, while the correlations between household income and entrepreneurial activity can be demonstrated for the bottom and the top third of the household income category. Key Words Entrepreneurial activity; gender; household income; Global Entrepreneurship Monitor. Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 2 INTRODUCTION Entrepreneurship can be defined as a phenomenon that involves identifying, evaluating and exploiting opportunities, which requires people to have different beliefs about the value of resources (Shane & Venkataraman, 2000). Both researchers and policy-makers have widely recognized the prominent role of entrepreneurship in an economy. Overall, entrepreneurship is seen as a key mechanism for boosting employment and productivity growth, increasing competitiveness and innovation in economies, and promoting social inclusion and equal opportunity (Svetek & Drnovsek, 2022). It is widely believed that entrepreneurial activity is an important aspect of the organization of industries most conducive to innovation and unrestricted competition (Stel et al., 2005), as well as one of the most important factors in a country's economic progress. Entrepreneurship can invigorate development by driving progress, bringing about change, and improving competition. In terms of a developing economy, entrepreneurs are an important resource as they also contribute to social development, act as problem solvers by bringing ground-breaking plans to the market, drive significant developments by bringing new products and services on the market, and create an attractive business climate by enabling the creation of new organizations (Voda et al., 2020). As recently as 2012, Slovenia had one of the lowest participation rates of women in early-stage entrepreneurial activities (last in Europe, second to last in the world). After 2018, women's early-stage entrepreneurial activity started to increase, reaching a new high in 2021. Therefore, we wanted to investigate if there are still gender differences and if we can identify the income level as an influencing factor. The aim of this study is to analyse the specific role of gender and household income as explanatory variables for early-stage entrepreneurial activity in Slovenia in 2021. Data from GEM (Global Entrepreneurship Monitor) is used, which includes the rate of Total Entrepreneurial Activity (TEA), which may be defined as the “percentage of 18-64 population who are either a nascent entrepreneur or owner-manager of a new business” (Bosma et al., 2021). This variable is measured uniformly across a range of countries covered by the research and represents a useful index for measuring the extent of “entrepreneurship”. The introductory section is followed by an overview of the concept of entrepreneurial activity and the individual factors of gender and household income, and hypotheses development. The following section provides a description of the research methodology and data. The paper ends with research findings and discussion followed by the conclusion. LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT There are numerous definitions of entrepreneurship in the literature, but there is no doubt that entrepreneurship has been an essential component of Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 3 economic development for quite some time. There are several observational studies (Johannessen et al., 2001) that focus on characterizing the idea of entrepreneurship and examining the positive relationship between innovative activities and economic indicators. An entrepreneur is usually characterized as a person who tries to seize an opportunity, provides the important means to start a business, and faces challenges (Bloch, 2020). As an innovator, an entrepreneur launches new products and developments, explores new business areas for existing products, and develops new advertising techniques (Steyaert & Hjorth, 2003). Entrepreneurship contributes to capital raising by pooling reserve funds and ventures, creating conditions for society to thrive, contributing to adjusted territorial improvement of the country, and helping to reduce the convergence of monetary power owned by a single person (Kafaji, 2019). The entrepreneurial consumption offer in the form of new goods and services leads to new jobs, which affect the economy by contributing to an increase in national income through higher tax revenues and can be used for interest in various areas (Tleuberdinova et al., 2019). Entrepreneurial activity depends on a number of individual factors as well as regional and national aspects. Economics, political science, epistemology, sociology and cultural and institutional theory all recognize the importance of individual characteristics, sociocultural perceptions, cultural values, and regulatory and normative dimensions on the level of entrepreneurial activity in different countries (Santos et al., 2017). Moreover, entrepreneurial activity is a global economic and social phenomenon in which entrepreneurs take on various commitments and accept the risks associated with starting a new business, with the expectation that this attitude will have an impact and lead to higher levels of productivity and income (Leitão & Capucho, 2021). Entrepreneurs' motivation, inspiration, and enthusiasm for independence and freedom in their new ventures are crucial. However, the literature shows that more empirical studies are needed at the macro level to define the nature of institutional climate that determines entrepreneurial activity (Smallbone & Welter, 2020). Considering that entrepreneurship is one of the variables that contribute to structural change in nations, it can be considered as an important switch for economic turnaround and development, especially by strengthening the competitive elements and innovation frontier of small and medium enterprises (Stam et al., 2011). Chowdhury et al. (2019) state that entrepreneurship is fundamental to the vitality of economies, emphasising that enterprises are at the core of the scope and nature of entrepreneurial activity. Entrepreneurial activity in the form of various operating companies and self-employed individuals is consistently influenced by various determinants on the supply and demand side of the market (Dvouletý, 2021). Over the years, various authors have analysed entrepreneurial activity with the use of TEA 1 as part of the model in their work. Furthermore, new 1 Total early-stage Entrepreneurial Activity (TEA) is the % of 18-64 year old population that is either a nascent entrepreneur, or owner of a business. Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 4 business creation is assumed to be the result of individuals' decision to improve themselves, which is consistent with Schmitz’s (1989) theoretical framework. According to data from the 2020 and 2021 reports of GEM (Bosma et al., 2021), TEA includes early-stage entrepreneurs driven by opportunity, aged 18-64, who are driven to entrepreneurial ventures out of a need to become independent and increase their income, and early-stage entrepreneurs who engage in business creation because there are no accessible jobs (necessity-oriented entrepreneurs). TEA rates relate to opportunity and necessity distinguish between entrepreneurs who are driven to seek business opportunities from those whose entrepreneurial activity results from an inability to pursue other economic options (Voda et al., 2020). Gender as an enabler of entrepreneurial activity In addition to entrepreneurial activity, as measured by the TEA index, this study also considers predictors such as gender and household income. When one group in society does not start a business on an equal footing with other groups, it limits job creation, innovation, income accumulation, the availability of new products and services, and many different benefits that new businesses bring to the economy and society. There is a growing body of research on the role of gender in entrepreneurial activity, and the findings suggest that gender can have both facilitating and inhibiting effects on entrepreneurial activity. Research has shown that certain gender-related characteristics, such as risk-taking and access to networks, can promote entrepreneurial activity. For example, a study by Cooper et al. (1994) finds that men are more likely than women to start a business because they are more willing to take risks. Other research suggests that men have better access to networks and resources that can provide them with the support and resources they need to start and grow a business (Neumeyer et al., 2019). However, research has also identified a number of barriers that may limit women's entrepreneurial activity. These include societal expectations and stereotypes about women's roles and capabilities, as well as structural and institutional barriers such as access to funding and a lack of supportive policies and programs (Brindley, 2005). Overall, research findings suggest that gender can both promote and inhibit entrepreneurship and that efforts to promote and support female entrepreneurship may be necessary to level the playing field and ensure that women have equal opportunities to start and build businesses. While a number of research studies document a growing number of women entrepreneurs and women-owned businesses, the results show that men's entrepreneurial activity is still higher than women's (Tsyganova & Shirokova, 2010). Bosma et al. (2021) find that in most cases men are the ones who are more likely to start a business venture, although some examples prove otherwise, and there are others where the difference is small. When discussing the role of gender in the development of entrepreneurial activity, it is important to note that authors such as Voda et al. (2020) find that women's innovativeness and pioneering potential add to entrepreneurial development and the creation of new jobs. As indicated by Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 5 information presented by the European Commission (2019), women make up 52% of the absolute European population, but represent only 34.4% of the self-employed and 30% of start-up entrepreneurs. In addition, the results show that businesses run by women have the fastest development. Due to the importance of female businesses in the monetary and social development and improvement of a country, some authors take an all- encompassing viewpoint and utilize an appropriate structure suitable for understanding women’s businesses and the elements that add to the entrepreneurial movement (Brush et al., 2009). Moreover, the findings of a research conducted by Santos et al. (2017) show a notable impact of gender on entrepreneurial activity in its initial stages. Similarly, men are more bound to take part in the initial stages of the entrepreneurial movement than women. Moreover, Özdemir and Karadeniz (2011) focus on business visionaries in Turkey and show that men with higher pay and training levels can identify business opportunities and have a higher probability of becoming entrepreneurs. The authors note that entrepreneurs in Turkey are predominately men and that men are twice as likely to become entrepreneurs than women. Likewise, Haus et al. (2013) analyse gender differences in entrepreneurial intentions and activities of entrepreneurs in Europe and the United States. and find that the average entrepreneurial intention is higher among men than women. Although important, gender differences in entrepreneurial intentions and activities were too small to adequately explain the differences in starting ventures. There is some empirical research data suggesting that there may be differences between men and women in the motives for entrepreneurship. However, it should be noted that these differences may vary depending on the specific context and individual circumstances. In their study by Greene et al. (2003), find that men are more likely to start a business to achieve financial gain, while women are more likely to start a business to pursue their passion or to fill a need in the marketplace. Another study by Wong-MingJi et al. (1999) argues that men are more likely to start businesses to gain status and power, while women are more likely to start businesses to achieve work-life balance and to have control over their own careers. It should be noted that these results should be interpreted with caution, as there may be other factors that contribute to differences in motives for entrepreneurship between men and women, such as cultural and societal expectations and biases. In addition, it is likely that there is a high degree of overlap between men's and women's motives for starting a business. Given the importance of gender to entrepreneurship, the study proposes to test the following hypothesis: H1: Men are more likely to engage in early – stage entrepreneurial activity than women. Household income as an enabler of entrepreneurial activity Household income can play a role in enabling entrepreneurial activity in several ways. For example, higher household income may provide Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 6 individuals with the financial resources and stability needed to start a business, as well as the ability to take risks and withstand potential financial losses. There is empirical research data supporting the relationship between household income and entrepreneurial activity. A study by Gaglio & Katz (2001) finds that individuals with higher income and education are more likely to be entrepreneurial. Another study argues that individuals from higher- income households are more likely to start a business, especially in industries with higher start-up costs (Nandamuri & Gowthami, 2013). In addition, individuals with higher household incomes are more likely to report having the financial resources needed to start a business, such as access to capital and savings. On the other hand, authors such as Hurst and Lusardi (2004) find that the relationship between income and entry into entrepreneurship is flat across most of the wealth distribution, while only at the top end of the wealth distribution-after the ninety-fifth percentile-can a positive relationship be found. Other research also suggests that household income may be a predictor of entrepreneurial success. For example, a study by Bae et al. (2014) finds that individuals from households with higher incomes are more likely to achieve greater success in their ventures. Overall, the results suggest that household income may be an important factor enabling entrepreneurial activity and success. However, it should be noted that other factors such as education, skills, and access to resources and networks may also play a role in enabling entrepreneurial activity. The relationship between household income levels and levels of entrepreneurial activity is necessarily complex, both within and across economies. Financial wealth in the form of household income is another important precursor to entrepreneurial activity. Not only are high-income households more able to provide the necessary financial resources for entrepreneurial activity, but high-income households are also more likely to have more entrepreneurial growth opportunities because of their social status (Dunn & Holtz-Eakin, 2000). Exogenous influences (such as demographics, society, characteristics, financial support, and culture) affect attitudes and indirectly affect intentions and behaviours to become entrepreneurs (Shapero, 1982). Among the exogenous factors, the household may be considered as one of the most important because it acts as a backstop for the entrepreneur. Several studies (Evans & Jovanovic, 1989) argue that a lack of financial resources in the form of household income limits entrepreneurial activity. High-income economies, like high-income individuals, tend to have more opportunities and better access to the resources needed to take advantage of those opportunities. On the other hand, starting one's own business in a high-income economy can involve high opportunity costs in terms of foregone wages, while social security systems can break the direct link between work and income. In low-income economies, as with low-income individuals, there are likely to be fewer alternative sources of income, so starting one's own business may be an economic necessity (Bosma et al., 2021). Individuals whose family's incomes are higher might be keen on more worthwhile business opportunities than low-income individuals, as monetary Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 7 abundance may provide the better quality of living. Higher level of financial resources gives more significant monetary assets, permitting business visionaries to attempt bigger endeavours prior to looking for outer sources of funding. However, when resources are unavailable or low, development is challenging to accomplish, whether or not inspiration is available (Carreón- Gutiérrez & Saiz-álvarez, 2019). On the other hand, Kim et al. (2006) find no significant effect of household income and wealth on entrepreneurship entry. Following the above reasoning, the second hypothesis is stated as follows: H2: Household income is positively and significantly associated with early – stage entrepreneurial activity. DATA AND METHODOLOGY The Global Entrepreneurship Monitor (GEM) database provides insights into the characteristics of entrepreneurs, ranging from standard sociodemographic characteristics to more specific entrepreneurial characteristics, perceptions, and attitudes. In this study, the focus is on data related to entrepreneurial activity as well as gender and household income as factors influencing entrepreneurial activity. The data used in this study were collected as part of the National Adult Population Survey. In this study, the research is based on the GEM dataset for Slovenia from 2021, which includes 2000 observations. The dependent variable used in this study is entrepreneurial activity (it indicates how entrepreneurial societies actually are). To quantify the level of entrepreneurial activity, the proxy variable for total early-stage entrepreneurial activity (TEA) was utilized. The variable incorporates the classification of the population aged 18-64 that is either actively trying to start a new business or is involved with a business that is less than three and a half years old. Estimated as a dichotomous variable that takes the value of "1" if respondents affirm their involvement in early-stage entrepreneurial activities and "0" otherwise. The aforementioned approach of measuring entrepreneurial activities with a single proxy item is widely accepted and used by researchers (Voda et al., 2020). Regarding household income, this GEM variable categorizes household income into thirds according to the national distribution (lowest 33%, middle 33%, highest 33%). The annual income of the whole household, including the respondent, must be guaranteed. Among the start-ups, those who belong to the upper third of household income are represented with high expectations (Carreón-Gutiérrez & Saiz-álvarez, 2019). The variable gender can appear as “1” (for the male gender) and “2” (for the female gender). The hypotheses are tested using the binary logistic regression for predicting the probability of the effects of the previously stated influencing factors on entrepreneurial activity. The SPSS 20 software is used to perform the analysis. The dichotomous dependent variable takes the value "1" with a probability of success q (where 1 represents participation in TEA) or the Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 8 value "0" with a probability of 1-q (no participation in entrepreneurial activities). This form of analysis is applied because the dependent variable is dichotomous. Figure 1: Graphical form of hypotheses Figure 1 represents the graphical form, while regression model can be presented in the stochastic form in the formula (1) as follows: log ( 𝜋 ( 𝑦 ) 1 − 𝜋 ( 𝑦 ) ) = 𝛽 0 + 𝛽 1 𝑥 1 + 𝛽 2 𝑥 2 ( 1) Where: y - dependent variable: value of the TEA index x1 - independent variable: gender x2 - independent variable: household income β0, β1, β2 – value of the regression coefficients Based on the priory stated the formula takes the form (2): log ( 𝜋 ( 𝑇𝐸𝐴 ) 1 − 𝜋 ( 𝑇𝐸𝐴 ) ) = 𝛽 0 + 𝛽 1 𝑔𝑒𝑛𝑑𝑒𝑟 + 𝛽 2 ℎ𝑜𝑢𝑠𝑒 ℎ𝑜𝑙𝑑 𝑖𝑛𝑐𝑜𝑚𝑒 ( 2) RESEARCH RESULTS AND DISCUSSION In this section, the results of the hypotheses testing are presented and discussed. From the case processing summary, the sample size is N=1771, which means that 229 cases are missing from the 2000 cases originally recorded. Furthermore, the coding of the dependent variable shows that the dependent variable is indeed dichotomous, ranging from 0 to 1 depending on whether the respondents selected "no" or "yes" as their answer to the question about entrepreneurial activity. Further on, categorical variables coding represents a description of the coding of additional variables included in the logistic regression equation for those categorical variables that have more than two possible values. The variable related to the household income appears in the lowest 33% tile in 646 cases, in the middle 33% tile in 580 cases and in the top 33% tile in 545 cases. Individuals living in households that belong to the top third are the Gender Household Income Entrepreneurial Activity Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 9 category with which we will compare the remaining individuals below. Variable (1) describes households in the bottom third and variable (2) describes households in the middle third, while the gender variable has only two possible values. Omnibus tests of model coefficients contain the values for the chi-squared statistic and significance level. Since stepwise logistic regression or blocking were not used the results for step, model, and block are identical. The value in the Sig. column is the probability of obtaining the chi-squared statistic if the null hypothesis is true, comparing the p-value to a critical value of 0.05. Since the significance level of 0.012 is less than 0.05, the overall model is statistically significant. Omnibus tests of the model coefficients can be considered significant since p < 0.05, confirming the causal relationship of the proposed model and the hypothesis that the β- coefficients are different from zero. In addition, the model summary shows the values of the "pseudo" R- squares, since the logistic regression does not have the R-square normally found in OLS regression. The Cox & Snell R-squared is based on the logical probability for the model compared to the logical probability for a baseline model. Furthermore, Cox & Snell R-squared and Nagelkerke R-squared indicate that the variables under consideration explain a significant amount of the variance in entrepreneurial activity. To determine how much of the variance of the dependent variable is explained by the observed binary logistic model, the values of Cox and Snell's R-squared and Nagelkerke R- squared were analysed. The explained variance of the criterion in the model ranges from 0.6% to 1.9%, depending on the observed measure, but it is generally considered that Nagelkerke R-squared is the preferred measure for the analysis of explained variance in binary models, since the second measure cannot reach the value 1 and the explained variance is expressed by values between 0 and 1. The model summary shows the variance of information explained by the standard binary logistic model, i.e., the amount of unexplained information that remains after fitting the model. The result of 1.9% explained variance in the model is not entirely satisfactory. The value of the variance indicator (-2LL=682.95) suggests the statistical acceptability and adequacy of the model at this step. The classification shows the analysis of the quality of the model as a whole - percentage of correct classifications. Assuming the results of the logistic regression and the obtained equation, the "calculated" value of the variable "Total involved in early-stage entrepreneurial activity" would be correct 95.1% of the time (i.e., 0 if it is also 0 in the data; or 1 if it is also 1 in data). The data regarding the variables in the equation can be seen in Table 1, including information on the significance level and odds ratio. Table 1: Variables in the Equation Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 1 * Fender -,308 ,224 1,890 1 ,169 ,735 GEMHHINC 7,645 2 ,022 GEMHHINC(1) -,724 ,295 6,030 1 ,014 ,485 Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 10 GEMHHINC(2) ,015 ,251 ,004 1 ,952 1,015 Constant -2,309 ,356 41,936 1 ,000 ,099 * Variable(s) entered on step 1: gender, GEMHHINC. Table 1 demonstrates that the variable “gender” is not statistically significant, since the Sig. > 0.05, therefore the hypothesis H1 cannot be proved. Regarding the variable “household income”, the hypothesis H2 can be proved only in the sections of the lowest 33% and in the top 33%, where the significance level < 0.05, while the significance level of Sig. = 0.952 shows that the middle 33% in the household income category do not support the hypothesis H2. The odds ratio for the bottom third of household income (Exp(B)= 0.485) shows that the surveyed population is 0.4 times more likely to engage in entrepreneurial activity than the population in the top third of household income. Based on the above principle, it can be said that hypothesis H1 cannot be proved, while hypothesis H2 can be proved for the lowest and the highest third of the household income category. Looking at the previous research in Chapter 2, especially Subchapter 2.1, it can be seen that the results for Hypothesis H1 obtained through this research do not support the findings of Bosma et al. (2021), Santos et al. (2017), and Haus et al. (2013), which state that men are more likely to be entrepreneurial. Considering the results of testing hypothesis H1, the obtained results are more related to the research of Voda et al. (2020) and Brush et al. (2009), which stated that women are more likely to be entrepreneurial due to their psychological characteristics. Having the priory stated results in mind, there are a number of ways to support and promote female entrepreneurship through policies that governments and other organizations can adopt. Examples include loans, grants, and investment capital specifically targeted to women-owned businesses, or the provision of business development and training programs, including mentoring programs, incubators, and accelerators that provide women entrepreneurs with the skills and knowledge they need to succeed. In addition, it is important to combat unconscious bias by having governments and organizations undertake initiatives to raise awareness and promote equality in the workplace. This could include training programs for business owners and employees on diversity and inclusion. Furthermore, work-life balance can be promoted through policies such as paid family leave and flexible work arrangements to support women who want to balance work and family. Governments and organizations can create an ecosystem that supports and encourages female entrepreneurship by organizing networking events, promoting women-led businesses, and partnering with organizations that support women in business. It is important to note that these policies should be tailored to the specific needs and challenges of women entrepreneurs in a given context. The results obtained for hypothesis H2 can be interpreted in different ways or even considered contradictory. Since hypothesis H2 was confirmed for the lowest and the top third of household income, the following explanation can be given: The relationship between entrepreneurial activity and the respondent population from the lowest 33% of income can be Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 11 explained by the need of these people to engage in entrepreneurial activity and in this way contribute to financial well-being. This does not preclude their potential entrepreneurial intention or enthusiasm, but rather suggests that necessity plays an important role in their business creation. Policy implications can be one of the tools to encourage low-income individuals to engage in opportunity driven entrepreneurship. There are a number of policy actions that governments and other organizations can take to support and encourage entrepreneurship among low-income individuals, including initiatives such as loans, grants, and investment capital. Tools also include business development and training programs that act as mentors, incubators, and accelerators to provide low-income entrepreneurs with the skills and knowledge they need to succeed. Access to education and training can also be an important step, as low-income individuals may not have the same access to education and training as higher-income individuals. Governments and organizations can provide affordable or free education and training programs to help low-income individuals acquire the skills needed to start and run a business. In addition, participants from the top 33% of household income can be characterized as those who are entrepreneurial by choice, based on internally created or externally identified opportunities and potential. Since financial wealth is not the only reason for this group of entrepreneurs to start a new business, various motives and drivers for their engagement in starting a new business can be discussed. The results of this study should also be considered in the context of its limitations in terms of time scope and number of variables covered. The fact that only the year 2021 was included in the study might be too short a time period to obtain truly representative results, especially when 2021 can still be considered a (post-)pandemic year and certainly differs from the objective reality before the pandemic. CONCLUSION Entrepreneurial activity is a financial and social peculiarity around the world, in which entrepreneurs assume various obligations and take the risks associated with the creation of a new venture, trusting that this venture will have an impact and contribute to higher levels of efficiency and income (Leitão & Capucho, 2021). Based on the literature review, the paper provides insight into the relationships between entrepreneurial activity and its predictors in terms of gender and household income. The paper aims to help fill the aforementioned gap in the literature by providing a quantitative analysis of the relationships and effects between entrepreneurial activity, gender and household income in Slovenia. As mentioned above, gender differences in early – stage entrepreneurial activity are decreasing and that may be the reason why the empirical results of the paper show that the correlations between entrepreneurial activity and gender in Slovenian sample could not be confirmed. On the other hand, the correlation between household income and entrepreneurial activity can be demonstrated for the lowest and the top Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 12 third of the household income category. By examining the factors that influence entrepreneurial activity, this approach contributes to the existing literature by reviewing the results regarding the influence of gender and household income. The results regarding the gender dimension are not consistent with some previous research, but may highlight the work of other authors who have a different view of the role of masculinity and femininity in business creation. In addition, the results related to household income open up new research questions on motivation and opportunity perceptions among entrepreneurs with the lowest and highest household incomes. Future research questions should clarify whether the difference in household income, and thus entrepreneurial activity, depends on the motivation for the entrepreneurial venture; do opportunity costs, opportunity perceptions and motivation play different roles in different income groups. However, further research should be conducted to gain deeper insight into the relationships. In addition, the study's limitation to measuring direct relationships between the above concepts and the sample limited to a single country provides a starting point for future research directions that could cover a longer time span and include samples from additional countries, either in the surrounding area or at the European Union level. The differences in the intensity of entrepreneurial activity by gender structure underscore the need to include other dimensions when assessing the extent to which the entrepreneurial environment enhances participation in entrepreneurial activities by all. As far as gender differences are concerned, the entrepreneurial environment should also ensure conditions that allow for a more equal organization of family life (child care, kindergarten, meals at school and at work, more intensive use of maternity leave by fathers, care for the elderly, cultural attitudes towards the role of women in the family and the like). REFERENCES Bae, T. J., Qian, S., Miao, C., & Fiet, J. O. (2014). The Relationship Between Entrepreneurship Education and Entrepreneurial Intentions: A Meta-Analytic Review. Entrepreneurship: Theory and Practice, 38(2). https://doi.org/10.1111/etap.12095 Bloch, H. (2020). The theory of economic development. In Schumpeter’s Price Theory. https://doi.org/10.4324/9781315724744-2 Bosma, N., Hill, S., Ionescu-Somers, A., Kelley, D., Guerrero, M., & Schott, T. (2021). Global Entrepreneurship Monitor 2020/2021 Global Report. In GEM. Brindley, C. (2005). Barriers to women achieving their entrepreneurial potential: Women and risk. International Journal of Entrepreneurial Behaviour and Research, 11(2). https://doi.org/10.1108/13552550510590554 Brush, C. G., de Bruin, A., & Welter, F. A. (2009). A gender—A ware frame work for women’s entrepreneurship. Int. J. Gend. Entrep., 1, 8–24. Carreón-Gutiérrez, J. P., & Saiz-álvarez, J. M. (2019). Opportunity motivation and growth aspirations of Mexican entrepreneurs: The moderating role of the household income. Sustainability (Switzerland), 11(22). https://doi.org/10.3390/su11226288 Chowdhury, F., Audretsch, D. B., & Belitski, M. (2019). Institutions and Entrepreneurship Quality. Entrepreneurship: Theory and Practice, 43(1). https://doi.org/10.1177/1042258718780431 Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 13 Cooper, A. C., Gimeno-Gascon, F. J., & Woo, C. Y. (1994). Initial human and financial capital as predictors of new venture performance. Journal of Business Venturing, 9(5). https://doi.org/10.1016/0883-9026(94)90013-2 Dunn, T., & Holtz-Eakin, D. (2000). Financial capital, human capital, and the transition to self- employment: Evidence from intergenerational links. Journal of Labor Economics, 18(2). https://doi.org/10.1086/209959 Dvouletý, O. (2021). A First Year’s Impact of the Pandemic on the Czech Entrepreneurial Activity. Foresight and STI Governance, 15(4). https://doi.org/10.17323/2500- 2597.2021.4.52.60 European Commission. (2019). 2019, Female Entrepreneurs. 2019, Female Entrepreneurs. Evans, D. S., & Jovanovic, B. (1989). An Estimated Model of Entrepreneurial Choice under Liquidity Constraints. Journal of Political Economy, 97(4). https://doi.org/10.1086/261629 Gaglio, C. M., & Katz, J. A. (2001). The Psychological Basis of Opportunity Identification: Entrepreneurial Alertness. Small Business Economics, 16(2). https://doi.org/10.1023/A:1011132102464 Greene, P. G., Hart, M. M., Gatewood, E. J., Brush, C. G., & Carter, N. M. (2003). Women entrepreneurs: moving front and center: An overview of research and theory. Coleman White Paper Series, 3. Haus, I., Steinmetz, H., Isidor, R., & Kabst, R. (2013). Gender effects on entrepreneurial intention: A meta-analytical structural equation model. Int. J. Gend. Entrep., 130–156. Hurst, E., & Lusardi, A. (2004). Liquidity constraints, household wealth, and entrepreneurship. Journal of Political Economy, 112(2). https://doi.org/10.1086/381478 Johannessen, J. A., Olsen, B., & Lumpkin, G. T. (2001). Innovation as newness: What is new, how new, and new to whom? European Journal of Innovation Management, 4(1). https://doi.org/10.1108/14601060110365547 Kafaji, M. (2019). Capacity to innovate as driver for innovation enhanced growth. International Journal of Entrepreneurship, 23(1). Kim, P. H., Aldrich, H. E., & Keister, L. A. (2006). Access (not) denied: The impact of financial, human, and cultural capital on entrepreneurial entryin the United States. Small Business Economics, 27(1). https://doi.org/10.1007/s11187-006-0007-x Leitão, J., & Capucho, J. (2021). Institutional, economic, and socio-economic determinants of the entrepreneurial activity of nations. Administrative Sciences, 11(1). https://doi.org/10.3390/admsci11010026 Nandamuri, P., & Gowthami, C. H. (2013). The impact of household income on being a potential entrepreneur. SCMS Journal of Indian Management, 10(3), 75-85. Neumeyer, X., Santos, S. C., Caetano, A., & Kalbfleisch, P. (2019). Entrepreneurship ecosystems and women entrepreneurs: a social capital and network approach. Small Business Economics, 53(2). https://doi.org/10.1007/s11187-018-9996-5 Özdemir, Ö, & Karadeniz, E. (2011). Investigating the factors affecting total entrepreneurial activities in Turkey. Metu Stud. Dev., 275–290. Santos, S. C., Caetano, A., Spagnoli, P., Costa, S. F., & Neumeyer, X. (2017). Predictors of entrepreneurial activity before and during the European economic crisis. International Entrepreneurship and Management Journal, 13(4). https://doi.org/10.1007/s11365-017- 0453-8 Schmitz, J. A. (1989). Imitation, Entrepreneurship, and Long-Run Growth. Journal of Political Economy, 97(3). https://doi.org/10.1086/261624 Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1). https://doi.org/10.5465/AMR.2000.2791611 Shapero, A. (1982). Social dimensions of entrepreneurship. In C. Kent, D. Sexton and K. Vesper, eds., The Encyclopedia of EntrepreneurshipThe Encyclopedia of Entrepreneurship. Smallbone, D., & Welter, F. (2020). A Research Agenda for Entrepreneurship Policy. In A Research Agenda for Entrepreneurship Policy. https://doi.org/10.4337/9781786430946 Stam, E., Suddle, K., Hessels, S. J. A., & van Stel, A. J. (2011). High Growth Entrepreneurs, Public Policies and Economic Growth. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1019429 Advances in Business-Related Scientific Research Journal, Volume 14, No. 1, 2023 14 Stel, A. van, Carree, M., & Thurik, R. (2005). The effect of entrepreneurial activity on national economic growth. Small Business Economics, 24(3). https://doi.org/10.1007/s11187-005- 1996-6 Steyaert, C., & Hjorth, D. (2003). New movements in entrepreneurship. In New Movements in Entrepreneurship. https://doi.org/10.4337/9781781951200 Svetek, M., & Drnovsek, M. (2022). Exploring the Effects of Types of Early-Stage Entrepreneurial Activity on Subjective Well-Being. Journal of Happiness Studies, 23(1). https://doi.org/10.1007/s10902-021-00392-3 Tleuberdinova, A., Shayekina, Z., Salauatova, D., Amerkhanova, A., & Ramashova, A. (2019). Expert assessment of entrepreneurial activity development: A case study. Entrepreneurship and Sustainability Issues, 7(2). https://doi.org/10.9770/jesi.2019.7.2(56) Tsyganova, T., & Shirokova, G. (2010). Gender Differences in Entrepreneurship: Evidence From Gem Data. Organizations and Markets in Emerging Economies, 1(1). https://doi.org/10.15388/omee.2010.1.1.14309 Voda, A. I., Butnaru, G. I., & Butnaru, R. C. (2020). Enablers of entrepreneurial activity across the european union-an analysis using GEM individual data. Sustainability (Switzerland), 12(3). https://doi.org/10.3390/su12031022 Wong-MingJi, D. J., Sullivan, S. E., & Brush, C. G. (1999). Women Entrepreneurs: Moving beyond the Glass Ceiling. The Academy of Management Review, 24(3), 585–589.