Global Entrepreneurship Monitor Dataset Research Articles

On the circular entrepreneurship across continents: An analysis of terms of business descriptors

AbstractThis study analyzes circular entrepreneurship trends across global regions using the 2014–2018 Global Entrepreneurship Monitor dataset. Content analysis of business descriptors from 79,663 unique entrepreneurs was used to position each startup within the 9R's framework. The results show that startups are mainly associated with “repurpose” and “recover”, which are less desirable for circularity. We further define circular entrepreneurs as those with the top 10% highest weighted score in circular strategies according to the type of business they run. The BERTopic approach is applied to identify specific business topics for these entrepreneurs. Similarities (North America and Latin America & the Caribbean) and differences (Europe) in popular topics are found across regions. Lastly, regression analysis reveals that entrepreneurial perception and the presence of role models are key factors driving circular entrepreneurship.

Impact of the SECI Entrepreneurial Development Model on Entrepreneurial Activities: Unleashing Entrepreneurial Knowledge Creation Potential

This study uses a novel idea of the entrepreneurial development process using the SECI framework that addresses how implicit and explicit entrepreneurial knowledge is transformed into new startups. There are four distinct modes: socialization, externalization, combination, and internalization. This study analyzes the influence of the SECI entrepreneurial development model on entrepreneurial activities across the globe, utilizing the data set from the Global Entrepreneurship Monitor (GEM). The GEM data set is an extensive and dependable resource that provides information on all facets of entrepreneurial development, including entrepreneurial activity, attitudes, intentions, and contextual factors, including government policies and social environment. The study utilizes panel data and examines the underlying hypotheses. The findings reveal the underlying process of entrepreneurial endeavors through the SECI framework. This study enhances the existing body of knowledge on knowledge management and entrepreneurship by presenting empirical evidence that supports the validity and practicality of the SECI framework in various settings. The study has practical implications for policymakers, scholars, and practitioners aiming to cultivate a culture of innovation and entrepreneurship.

Predicting entrepreneurial activity using machine learning

This study evaluates the predictability of entrepreneurial activity using machine learning. We compare different supervised machine learning techniques: decision tree, random forest, artificial neural network, k-nearest neighbor, extreme gradient boosting tree ensemble, and naïve Bayes, as well as run the traditional multiple logistic regression for obtaining a baseline and estimating their relative model prediction performance on a Global Entrepreneurship Monitor dataset of 1,192,818 individuals from 99 countries. By comparing different machine learning techniques, we predict out-of-sample opportunity-motivated entrepreneurial activity with an overall accuracy ranging from 70.1% to 91.2%. The results demonstrate that the extreme gradient boosting tree ensemble is superior in predicting opportunity-motivated entrepreneurial activity. Finally, a global surrogate model reveals that knowing an entrepreneur, entrepreneurial self-efficacy, and opportunity recognition are the three most important features for predicting opportunity-motivated entrepreneurial activity. For comparison purposes, we perform the same analyses for necessity-motivated entrepreneurial activity. The results reveal that the extreme gradient boosting tree ensemble is also the best-performing technique in predicting this form of entrepreneurial activity with a 96.5% accuracy.

The impact of culture on small tourism businesses’ access to finance: the moderating role of gender inequality

Access to finance to stay competitive is a salient challenge for small and medium-sized enterprises (SMEs). Few studies examine how cultures (i.e. social norms and customs) in different countries influence various channels for SMEs’ external financing (i.e. formal and informal). In particular, gender inequality, such as in terms of gender disparities in health, empowerment, and the labor market in each country, can bias lenders’ perspectives of female SME owners. By incorporating pecking order, information cost, and lack-of-fit theories, this study uses the Global Entrepreneurship Monitor dataset and other secondary datasets to investigate the impact of culture and gender inequality on tourism and hospitality SME owners’ access to formal and informal financing. The results show that cultures that are more masculine than feminine encourage both formal and informal financing; however, cultures with high power distance boost informal financing and hinder formal financing. In addition, gender inequality moderates these cultural influences on access to finance. This study contributes to the SME literature and provides insights for governments and policymakers.

A Paradigm Shift in Unemployment Based on the Role of Business Ownership: Ghana as Case

Both researchers and policymakers have given the relationship between entrepreneurship and unemployment a lot of thought. The changes in the area of unemployment in the country has caused many people to move into owning their businesses. This activity has initiated a relief to the government since its responsibility is to create lucrative jobs to its citizens. This paper seeks to address the paradigm shift in unemployment in Ghana, the role of business ownership. The study explained the determinants of unemployment, and the entrepreneurship drive to unravel unemployment in the country. Using a cross-sectional dataset, the study focused on Ghana’s economic growth as well as the country’s unemployment rate. Using an online survey of 400 respondents and data from the Ghana Statistical Service (GSS) and the Global Entrepreneurship Monitor dataset as its key element in addressing the usefulness of the study. The researcher investigated a paradigm shift in unemployment using the SPSS tool (version 23.0) and regression for the data analysis. With a Cronbach Alpha of 0.898 which explains the reliability statistics of the study variables, the research result shows that at a coefficient of 0.73, Business ownership will have an aid to employment rate with a highly significant P-value of 0.000. Recommendation from the study is that Policymakers should investigate and assess the elements that influence entrepreneurship by placing reduction on the interest put on loan offered to young entrepreneurs.

A Global Entrepreneurship Efficiency Benchmarking and Comparison Study based on National Systems of Entrepreneurship and Early-Stage Business: A Data Envelopment Analysis Approach

National Systems of Entrepreneurship is defined as a nation’s resource allocation structure leading to entrepreneurial behaviors. However, the existing indicators of national framework conditions may have limitations in comparing the entrepreneurial efficiency of countries. Based on institutional theory, this paper presents a model to examine the efficiency of entrepreneurial activities stemming from the given conditions of a country and find benchmarks based on data envelopment analysis by scrutinizing inputs and outputs with static efficiency, dynamic efficiency, and strategic quadrant analysis. For this purpose, the study utilizes the Global Entrepreneurship Monitor dataset from 2015 to 2020 for 24 countries and presents the research questions regarding the differences in global entrepreneurial efficiencies, the countries for benchmarking, and the implications for entrepreneurial activities. The research implications suggest that diversifying the views on entrepreneurial efficiency may be valuable, and policymakers may focus on institutional conditions and entrepreneurial efficiency regarding the activity of early-stage businesses.

Prevalence of the born-global phenomenon in different countries: an integrated perspective

Purpose The main purpose of this study is to analyze how factors such as innovation, entrepreneurial spirit and motivation, as well as various economic and environmental factors, affect the creation of born-global (BG) companies. Design/methodology/approach The research model was tested through logistic regression techniques to a sample obtained from the Global Entrepreneurship Monitor data set for the period from 2007 to 2016. Findings Empirical findings suggest that innovation, entrepreneurial spirit and motivation, as well as government policies, contribute to a company’s likelihood of becoming BG. Originality/value Recent research has shown interest in the development of explanatory models of BG firms that allow the study of how context and institutions affect the development of international business activities. Following an integrative and a multidisciplinary approach with a temporal dimension, this study expands the literature by comparing countries with different income levels and analyzing macroeconomic aspects along with certain characteristics of the entrepreneur and the environment as possible determinants. This study provides a better understanding of the prevalence of the BG business phenomenon by paying attention to country characteristics and how they affect the traits of individuals.

The human development index predicts female entrepreneurship rates

Purpose– Past research has identified a negative association between national income and female entrepreneurship rates. Data from Global Entrepreneurship Monitor (GEM) 2012 are analyzed to determine whether the Human Development Index (HDI) predicts female entrepreneurship rates. The purpose of this paper is to indicate how other socioeconomic variables that measure human development interact with national income to predict female entrepreneurship rates.Design/methodology/approach– Data were drawn from the 2012 GEM data set, which provides information on female entrepreneurship rates in 61 countries. To test relevant hypotheses, dependent and socio-demographic variables were sourced from international databases to perform quantitative cross-country regression analyses.Findings– National income significantly predicted female entrepreneurship rates in the univariate analysis. However, this relationship became non-significant when development indices were added to the model. In contrast, the HDI, the Gender Inequality Index, and national religious composition were robust, significant predictors.Practical implications– This study presents evidence that human and gender development indices, and national religious composition, are better predictors of female entrepreneurship rates than national income. Thus, studies on female entrepreneurship rates should account and adjust for human development and gender equality indices. As religiosity continues to be pervasive within multiple nations, policymakers should consider this when developing interventions geared toward promoting female entrepreneurship.Originality/value– This paper identifies factors other than economic determinism to explain variance in female entrepreneurship rates and demonstrates that human development and gender inequality indices are better predictors of female entrepreneurship rates.

Heterogeneity in entrepreneurial intent: the role of gender across countries

PurposeThis paper aims to improve knowledge of individual heterogeneity in affecting the entrepreneurial attitude, taking socioeconomic drivers under control thanks to a cross-country analysis. The authors operate a “selection” of proxy for individual heterogeneity, mainly based on gender, demographical features, personal attitude and intrinsic motivation.Design/methodology/approachThis exploration is supported by an empirical analysis based on the Global Entrepreneurship Monitor (GEM), for the period 2001-2012, and for a selection of 37 countries. It is expected that gender and further individual variables have an impact on the probability to become a nascent entrepreneur (e.g. age, level of education, self-confidence, social perception of self-employment as career choice). This paper evaluates the degree of consistency of these variables across very dissimilar countries.FindingsGender and confidence on own skill play a significant and consistent effect on the entrepreneurial attitude, so these personal features are,per se, the driving-strength of entrepreneurial intent. Conversely, fear of failure and belief on the status are not always statistically significant, or not homogenous in their relationship: socioeconomic or country-specific characteristics are strong and sort out in an unpredictable relationship between these variables and the willingness to run new ventures.Research limitations/implicationsA limited selection of individual features constrained by availability of information from the GEM data set.Practical implicationsThe motivation of this paper is to focus-back attention on intra-individual features that may affect entrepreneurship and to support evidence of whether individual heterogeneity is able to affect the entrepreneurial attitude, taking socioeconomic drivers under control.Social implicationsAn institutional and political commitment should be intensified to reduce the waste of opportunities that is associated with any forms of self-exclusion from entrepreneurship, such as those based on gender (being women) or (low) self-esteem.Originality/valueDue to the “individual” perspective, this paper adds to previous studies that exploited the GEM data set because they mostly follow an institutional conceptual framework.

A quantitative critique of Kerlin’s macro-institutional social enterprise framework

Purpose– The purpose of this paper is to provide the first large data-set regression analysis to test Kerlin’s (2013) macro-institutional social enterprise framework in relation to the country social enterprise models that flow from it. Kerlin (2013) offers a conceptual framework for country social enterprise models that allows countries to retain their unique understanding of social enterprise and better understand the factors influencing its development.Design/methodology/approach– This paper draws on the theory of historical institutionalism and multiple global datasets to test formal hypotheses on the relationship between macro-institutional factors and the size of the social enterprise sector across countries. Social enterprise data were obtained from the 2009 Global Entrepreneurship Monitor dataset. Hypotheses were tested using logistic hierarchical linear modeling.Findings– Results provide support for the framework at a significant level. Nearly half of the variance in the size of the social enterprise sector can be attributed to countries-level factors. We also find that the size of the social enterprise sector varies by economic competitiveness rank, size of the welfare state and collectivist cultural orientation.Research limitations/implications– The countries included in this study are not representative of the global landscape. Researchers are encouraged to test the framework with a more representative sample of countries, including those in the Global South.Practical implications– The paper includes implications for policy makers and researchers seeking to facilitate cross-regional dialogue, the transfer and support of social enterprises and research.Originality/value– This paper fulfills an identified need to advance the field of social enterprise by quantitatively testing established frameworks.

New Zealand’s perfect storm of entrepreneurship and economic development

Applying a grounded-theory approach to analyzing the Global Entrepreneurship Monitor (GEM) data, we attempt to explain why New Zealand exhibits only a moderate level of economic development despite its high level of entrepreneurship. By statistically analyzing why 34 other countries in the 2005 GEM dataset exhibit small deviations from the classical quadratic curvilinear relationship between entrepreneurship and economic development, we develop a better understanding of the entrepreneurial framework conditions underlying New Zealand’s large deviation from this trend line. Based on our findings from the GEM data we make policy recommendations that could aid in moving New Zealand (and other countries) closer toward the trend line and thus promote economic development.