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This study aims to examine the externalities from regional home-ownership to individual-level entrepreneurship.

The paper links individual-level data from the Finnish Income Distribution Statistics for years 1990-1992 to regional home-ownership proportions. Probit models of entrepreneurship with regional home-ownership and appropriate control variables as regressors are estimated. A rental housing market deregulation experiment which caused exogenous variation in regions’ home-ownership is exploited to identify the causal effects on entrepreneurship.

Results show that higher home-ownership in a region leads to greater entrepreneurship. Further analyses together with the fact that homeownership tends to have detrimental labour market effects suggest that homeownership encourages entrepreneurship by leading to less paid work opportunities. These results are in line with those of earlier literature that self-employment and entrepreneurship, especially during bad economic times, are partly motivated by bad employment opportunities.

This study presents novel results on the externalities that home-ownership has on entrepreneurship. These externalities are shown to be important enough that they need to be considered when assessing the economic effects of various policies that affect the prevalence of owner-occupied housing. The instrumental variables’ estimates are the first causal estimates in the literature and the bias resulting from assuming exogeneity is shown to be nonnegligible.

Entrepreneurial activity is a phenomenon that increases the economic growth of countries and improves their social welfare. The economic development levels of countries have significant effects on these entrepreneurial activities. This research examines which institutional and macroeconomic variables explain early-stage entrepreneurship activities in developed and developing economies.

The authors conducted panel data analysis on the data from the Global Entrepreneurship Monitor (GEM) and International Monetary Fund (IMF) surveys covering the years 2009–2018.

First, the authors' results reveal that cognitive, normative and regulatory institutions and macroeconomic factors affect early-stage entrepreneurial activity in developed and developing countries differently. Second, the authors' findings indicate that cognitive, normative and regulatory institutions affect early-stage entrepreneurship more positively in developed than developing countries. Finally, the authors' results report that macroeconomic factors are more effective in early-stage entrepreneurial activity in developing countries than in developed countries.

This study provides a better understanding of the components that help explain the differences in entrepreneurship between developed and developing countries regarding institutions and macroeconomic factors. In this way, it contributes to developing entrepreneurship literature with the theoretical achievements of combining institutional theory and macroeconomic indicators with entrepreneurship literature.

Based on institutional theory, this study aims to analyze the influencing mechanisms of the institutional environment in the digital context on technology entrepreneurship.

Using data from the Global Entrepreneurship Monitor, World Bank and World Economic Forum, this study builds a multilevel database covering 79 countries and 97,146 individuals from 2013 to 2017. A mixed-effects logistic regression model with the fixed part and random part was chosen to test the hypotheses in this study. The mixed-effects logistic regression model used in this study includes a random intercept with random effects at the country level, while the robustness test considers a more complex two-level model with a random intercept plus random slope.

The findings indicate that different dimensions of the institutional environment in the digital context have different effects on individual technology entrepreneurship. The analysis shows that exposure to digital networks and innovative culture positively influences technology entrepreneurship. However, intellectual property rights protection has a negative impact on technology entrepreneurship. Furthermore, the government digitalization has different effects on above relationships. When a government digitalization is higher, there will be a weaker positive relationship between exposure to digital networks and technology entrepreneurship. When a government digitalization is higher, there will be a stronger positive relationship between innovative culture and technology entrepreneurship. When a government digitalization is higher, there will be a weaker negative relationship between Intellectual property rights protection and technology entrepreneurship. Finally, the effect of innovative culture on technology entrepreneurship in the digital context is stronger for females than for males.

The aforementioned findings contribute to a better understanding of the theoretical logic underlying digital factors affecting the institutional environment and technology entrepreneurship and act as a reference for the country in terms of raising its scientific and technological levels and promoting economic structure transformation in the digital era.

The purpose of this paper is to employ a longitudinal approach to assess the effects of entrepreneurship education (EE) on students’ entrepreneurial intentions (EIs) through the constructs of the theory of planned behaviour (TPB), which include attitudes towards behaviour (ATB), subjective norms (SN) and perceived behavioural control (PBC). Specifically, this study aims to achieve two objectives: first, to determine if students’ ATB, SN, PBC and EIs would increase significantly after their exposure to EE; and second, to establish whether students’ ATB, SN and PBC mediate the relationship between EE and their EIs.

This longitudinal study employed a one-group pretest-posttest experimental research design. A self-reported questionnaire was administered to a randomly selected sample of 250 National Diploma students from five polytechnics in the North Central part of Nigeria before and after they were exposed to EE. To achieve the objectives of this study, repeated-measures t-test and partial least squares structural equation modelling were performed using Statistical Package for the Social Sciences and SmartPLS, respectively, for data analysis.

The results of the paired-samples t-test showed that students’ ATB, SN, PBC and EIs increased significantly after their exposure to EE. Also, further data analysis revealed that EE had a significantly positive relationship with students’ ATB, SN, PBC and EIs. Similarly, the results of the structural model indicated that ATB had a significantly positive link with students’ EIs and also mediated the relationship between EE and students’ EIs. SN and PBC had a positive but not statistically significant relationship with students’ EIs and did not mediate the relationship between EE and students’ EIs.

The findings of this study provide interesting implications for EE and entrepreneurship policies in Nigeria. More specifically, the findings provide some practical implications for the Nigerian government and the EE curriculum developers. To achieve greater impact of EE on students’ EIs at the tertiary education level, the Nigerian government should incorporate EE into the curricula at the primary and secondary education levels. Equipping students at the primary and secondary education levels with entrepreneurial knowledge, competencies and skills would enable them to develop a strong entrepreneurial mindset even before they gain admission to tertiary institutions.

It is one of the few studies that have tested empirically both the direct and the indirect effects of EE on students’ EIs in a single study. Thus, it helps to further clarify the links between EE and EIs. Besides, it is among the first studies to adopt a longitudinal approach to assess the effects of EE on students’ EIs through the constructs of the TPB (i.e. ATB, SN and PBC) in the Nigerian context.

Motivated by a lack of evidence regarding the effect of migration on entrepreneurship in a highly informal country, such as Colombia, this paper has a twofold purpose. First, it explores how Venezuelan immigration affects entrepreneurial activity in Colombian regions. Second, it intends to shed light on this relationship, by distinguishing between formal and informal sectors.

With a sample of 1,776,063 individuals, from the Labor Survey Gran Encuesta Integrada de Hogares (GEIH) from the Departamento Administrativo Nacional de Estadística (DANE), the authors employ an instrumental variable approach to account for the selection of immigrants into locations with more or less desirable conditions.

The results suggest Venezuelan immigration positively influences self-employment and own-account workers, but negatively affects employers. However, once these immigrants proliferate in the informal sector, the effects increase.

This paper brings new insights into the intersection between immigration, unofficial economies, and entrepreneurship. First, while the prior literature focuses on migration from developing to developed countries, migratory flows between developing economies and its effects on local entrepreneurial activity remain unexplored. Second, although informality is mostly common in developing countries, little (albeit growing) evidence of its role in the relationship between migration and entrepreneurship research exists. Finally, the authors bring together these two phenomena to enhance our understanding of different types of entrepreneurial activities when immigration and informality take place. Policy implications are derived from these insights.

As an important engine of economic growth, the digital economy is bringing new opportunities for the promotion of entrepreneurship. However, key questions regarding the extent of the effect of the digital economy on entrepreneurship remain unanswered. This study examines how the digital economy influences entrepreneurship in China using provincial data from 2011–2020, applying convergence tests and spatial econometric models.

Based on theoretical analysis and using macro provincial data covering the period of 2011–2020, we adopt a diversified empirical analytical method and apply a combination of the convergence trend test, spatial auto correlation test, and spatial Durbin model to test the research hypotheses.

First, there is spatial correlation between the digital economy and entrepreneurship. Second, the overall trend of China’s digital economy shows s convergence, with the whole country and the eastern region showing absolute β convergence and the whole country as well as the central and western regions showing β conditional convergence. Third, the digital economy can significantly promote entrepreneurship and has spatial spillover effects. Moreover, higher education has a negative moderating effect on the process of digital economy empowering entrepreneurship.

Studying the spatially correlated impacts of the digital economy on entrepreneurship enhances our understanding of its contribution to economic growth. Policy-makers can use these findings to develop targeted digital infrastructure investments in lagging provinces, guide entrepreneurs to better grasp the opportunities of the digital economy, and provide support for innovation and entrepreneurship. The findings also could offer Chinese experience that can be used to guide developing countries in utilizing the digital economy to enable entrepreneurship.

This paper expands and enriches the analytical focus on digital economy-empowered entrepreneurship and complements the current theoretical research on the moderating effect of the digital economy in empowering entrepreneurship.

We argue that entrepreneurship research should use meta-analysis to integrate the findings of the field. A meta-analytical approach has several advantages as compared with narrative reviews: First, narrative reviews are likely to bias empirical evidence because they are limited by the information-processing capacities of the reviewers (Tett, Jackson, & Rothstein, 1991). This is often a downward bias leading to the conclusion of little positive knowledge in the field. For example, frequency counts of significant results ignore sampling errors of individual studies, reliability problems of instruments, range restrictions of samples, dichotomization of continuous variables, imperfect construct validity, and extraneous factors (Hunter & Schmidt, 2004). These issues usually result in a higher incidence of Type II errors (i.e., rejecting the hypothesis wrongly). Thus, narrative reviews are more likely to lead to the conclusion that there are no relationships between independent and dependent variables in entrepreneurship when in fact they are (Hunter & Schmidt, 1990; Tett et al., 1991). Second, meta-analysis accumulates studies based on a set of explicit decision rules and, therefore, is less biased by subjective perceptions of the reviewer than narrative reviews. Meta-analyses require judgments as well, e.g., when defining the area of the study or coding moderator variables. However, the decisions are public and open to criticism and replication by other scientists (Johnson & Eagly, 2000). Third, meta-analysis is based on many studies and, thus, avoids the influence of single studies. Fourth, meta-analysis controls for sampling error variance and, thus, controls for power deficits of individual studies (Hunter & Schmidt, 2004). For example, the Brockhaus and Nord (1979) study is frequently cited in the entrepreneurship literature for providing evidence that there is no relationship of personality characteristics with entrepreneurship. However, this study is based on a small sample of 31 business owners and therefore, has serious statistical power problems. Noteworthy, the effect sizes of small samples are less precise in estimating a population value than effect sizes of larger samples. Fifth, meta-analyses can correct many errors of individual studies (Hunter & Schmidt, 2004). Since meta-analyses estimate population correlations between given variables, it is important to correct for errors of studies (e.g., unreliability, range restriction, and sampling error) to achieve unbiased estimates. Sixth, meta-analysis allows an assessment of the magnitude of relationships and, thus, provides more precise and often comparable assessments of the validity of concepts. Thus, meta-analyses support the assessment of the practical significance of findings. Seventh, meta-analysis tests for variations in relationships across studies and, therefore, allows an assessment of the generalizeability of effects. If the size of reported relationships varies considerably between different studies, there will be context conditions that account for these variations. These context conditions are moderators that affect the size of relationships. The moderators may include study characteristics, method moderators, and theoretical moderators. Thus, meta-analyses also help to identify areas for new studies. Finally, meta-analysis techniques allow to test more than one independent and/or moderator variable by using methods based on regression analysis (Lipsey & Wilson, 2001). Using such procedures allows to estimate the independent contribution of variables on results, to control for methodological variables, and to test the interactions between moderator variables.

This study aims to examine how entrepreneurship education influences intentions for starting a technology venture among science, technology, engineering and mathematics (STEM) students with particular attention to gender differences. This study builds on the model of entrepreneurial event and social role theory to assess the impact of entrepreneurship education on feasibility, desirability and intentions for technology entrepreneurship.

The hypotheses are tested with a sample of 879 Bulgarian science and engineering students from 15 universities. To test the models, this study uses ordinary least squares and logistic regressions with robust standard errors and Hayes mediation analysis with bootstrap bias-corrected confidence interval estimations for indirect effects. Two-stage Heckman regressions to control for sample selection bias and other robustness checks including propensity score matching were used.

Results show that entrepreneurship education, measured as participation in an entrepreneurship course, has a stronger impact on feasibility, desirability and intentions for technology entrepreneurship for female STEM students compared to their male counterparts. As such, this study supports the notion that entrepreneurship education could be part of a solution to counteract societal norms that position technology entrepreneurship as a less desirable and/or less feasible choice for women in STEM. However, attention should be paid to the operationalization of entrepreneurship education, as other measures of entrepreneurship education (role models, entrepreneurship education support) did not have a moderation effect with gender.

The authors assume a positive correlation between entrepreneurial intentions and entrepreneurial behavior. Future studies should include actual entrepreneurial behavior to paint a more complete picture of the effect of entrepreneurship education.

Little is known about the role of entrepreneurship education in the field of technology entrepreneurship, and even less about the potential gender differences in entrepreneurship education among STEM students. The study contributes to the literature by examining factors that could help close the persistent gender gap in technology entrepreneurship.

This paper aims to, drawing on the theory of planned behaviour (TPB), explore the effects of entrepreneurial role models on entrepreneurial intention (EI) and its antecedents and examines the question of whether the effects vary by gender.

Data were collected from a sample of 331 students at seven universities in Iran. Structural equation modelling and bootstrap procedure were used to analyse the data.

Consistent with the TPB, our results show entrepreneurial role models to indirectly influence EIs via the antecedents of intention. No gender differences in the relationship between perceived behaviour control and EIs were found, but gender did moderate the other relationships within the TPB. Attitude towards entrepreneurship was a weaker predictor and subjective norms a stronger predictor of EIs for female students than for their male counterparts. Furthermore, perceived behaviour control and attitudes towards entrepreneurship were more strongly influenced by role models for females as opposed to male students.

Future studies should go beyond examining the mere fact of knowing entrepreneurial role models to examine the mechanisms underlying the relationship between role models and EIs.

The results of this study have clear implications for both educators and policymakers.

The study contributes to the entrepreneurship literature by incorporating entrepreneurial role models and gender into the TPB and investigating their mediating and moderating effects within the model.

Despite the recognized importance of entrepreneurship for organizational wealth creation, research has devoted minimal attention to investigating this area. This study contributes to a better understanding of the relationship between corporate entrepreneurship and wealth creation by developing and testing a normative model, which clarifies the nature of the influences of corporate entrepreneurship and its environmental and organizational antecedents on organizational performance. The findings of structural equation modeling, based on mail survey data from 477 Slovenian firms, demonstrate that corporate entrepreneurship and some its contingencies make a difference in organizational wealth creation, growth and profitability.