Globally there are 252 million women owned businesses and entrepreneurs today. As of 2019, there were 13 million women-owned businesses in the US alone. And over 5.5 million of those 13 million businesses are owned by women from minority groups.

Here are some small business statistics on how they are generally financed.

This statistic shows the total early-stage entrepreneurial activity (TEA) rate in Asian countries in 2021. An economy’s total early-stage entrepreneurial activity (TEA) rate is defined as the prevalence rate of individuals in the working age population who are actively involved in business startups, either in the phase in advance of the birth of the firm, or the phase spanning 42 months after the birth of the firm. In 2021, the early-stage entrepreneurial activity (TEA) rate in South Korea was **** percent.

The Global Entrepreneurship Monitor [GEM] research program was developed to provide comparisons among countries related to participation of adults in the firm creation process. The initial data was assembled as a pretest of five countries in 1998 and by 2012 over 100 countries had been involved in the program. The initial design for the GEM initiative was based on the first US Panel Study of Entrepreneurial Dynamics, and by 2012 data from 1,827,513 individuals had been gathered in 563 national samples and 6 specialized regional samples. This dataset is a harmonized file capturing results from all of the surveys. The procedure has been to harmonize the basic items across all surveys in all years, followed by implementing a standardized transform to identify those active as nascent entrepreneurs in the start-up process, as owner-managers of new firms, or as owner-managers of established firms. Those identified as nascent entrepreneurs or new business owners are the basis for the Total Entrepreneurial Activity [TEA] or Total Early-Stage index. This harmonized, consolidated assessment not only facilitates comparisons across countries, but provides a basis for temporal comparisons for individual countries. Respondents were queried on the following main topics: general entrepreneurship, start-up activities, ownership and management of the firm, and business angels (angel investors). Respondents were initially screened by way of a series of general questions pertaining to starting a business, such as whether they were currently trying to start a new business, whether they knew anyone who had started a new business, whether they thought it was a good time to start a new business, as well as their perceptions of the income potential and the prestige associated with starting a new business. Demographic variables include respondent age, sex, and employment status.

Who gets to be an entrepreneur? In this next set of entrepreneurial statistics, you’ll see that anyone can become an entrepreneur.

The paper deals with the potential relationship between higher education and entrepreneurial activities. Universities and other higher education institutions could be seen as boosting entrepreneurship in the region. University graduates could be more often involved in starting up a new business and the university itself could commercialize their innovations by creating academic spin-off companies. The paper aims to examine the potential effect of higher education on the probability of starting a business as well as its further success. Based on the data for 40 EU and non-EU countries, retrieved from a Eurobarometer survey, we conducted probit and IV probit regressions. These have tested the assumed relationship between higher education and entrepreneurial activities. Our results strongly suggest that higher education can often be very beneficial for starting up a new business and this seems to be one of the factors determining the success of new businesses. Furthermore, those respondents who attended courses related to entrepreneurship appear to be more active in starting-up a business and this seems to be also positively correlated with the company's future success. Interestingly, university graduates from Brazil, Portugal and India in particular, tend to appreciate the role that their universities have played in acquiring the skills to enable them to run a business.

As of 2022, approximately eight percent of the population in Indonesia aged 18 to 64 years were involved in early-stage entrepreneurship activities. Meanwhile, around 5.7 percent owned established businesses for over 3.5 years.

HT: New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 0.065 Number in 2010. This records an increase from the previous number of 0.052 Number for 2009. HT: New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 0.036 Number from Dec 2006 (Median) to 2010, with 5 observations. The data reached an all-time high of 0.065 Number in 2010 and a record low of 0.035 Number in 2006. HT: New Business Density: New Registrations per 1000 People Aged 15 to 64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Haiti – Table HT.World Bank: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations registered in the calendar year.; ; World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).; Unweighted average; For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

When it comes to running the business itself, these are the 3 big challenges that entrepreneurs face.

Malaysia New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 2.262 Number in 2016. This records a decrease from the previous number of 2.332 Number for 2015. Malaysia New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 2.286 Number from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 2.438 Number in 2007 and a record low of 2.209 Number in 2006. Malaysia New Business Density: New Registrations per 1000 People Aged 15 to 64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Malaysia – Table MY.World Bank.WDI: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations registered in the calendar year.; ; World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).; Unweighted average; For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

Canada CA: New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 9.834 Number in 2022. This records a decrease from the previous number of 10.334 Number for 2021. Canada CA: New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 8.241 Number from Dec 2017 (Median) to 2022, with 6 observations. The data reached an all-time high of 10.334 Number in 2021 and a record low of 0.204 Number in 2017. Canada CA: New Business Density: New Registrations per 1000 People Aged 15 to 64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations (or its equivalent) registered in the calendar year.;World Bank's Entrepreneurship Database (https://www.worldbank.org/en/programs/entrepreneurship).;Unweighted average;For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.

Abstract This study aimed to carry out a bibliometric analysis of the production on International Entrepreneurship IE based on perspectives of the thematic structure of the field using thematic mapping techniques to model the knowledge produced in it. Data from the scientific production on the subject were collected from Scopus and Web of Science databases. Three thematic maps representing the periods of 1995-2004, 2005-2014 and 2015-2022 were yielded in the study. The discussion of results concludes that IE is a research area that has grown significantly since the second period, showing a considerable increase in publications from 127 in the first period to 1,042 in the second. This increase remained constant reaching 1,934 in the third and final period. The themes that stood out the most and were most representative in the field of IE were: performance of companies in IE, innovation, knowledge, entrepreneurial companies, entrepreneurial orientation, management, strategy, model and export behavior. A conceptual variation of the themes was also observed with the performance theme standing out, maintaining a high representativeness in the three periods analyzed with displacements between the basic themes – transversal – and the driving themes. Another highlight was the capabilities theme, which, over time, resulted in the dynamic capabilities theme. As emerging themes, performance, entrepreneurial orientation, entrepreneurship, impact and management appear. Based on the results and conclusions of this study, a research agenda is proposed.

In Europe, the share of the adult population involved in the early stage of a start-up varied between 14 percent in Latvia and *********** in Poland. The total early-stage entrepreneurial activity (TEA) rate is defined as the prevalence rate of individuals in the working age population who are actively involved in business startups, either in the phase in advance of the birth of the firm (nascent entrepreneurs), or the phase spanning 42 months after the birth of the firm (owner managers of new firms).

This dataset provides comprehensive statistics and insights on the impact of business planning, funding success rates, software market growth, exit strategies, and gender-based disparities in entrepreneurship. It explores how strategic business plans influence funding, growth, and operational success, supported by key metrics and global trends projected through 2032.

Italy IT: New Business Density: New Registrations per 1000 People Aged 15 to 64 data was reported at 2.648 Number in 2016. This records an increase from the previous number of 2.577 Number for 2015. Italy IT: New Business Density: New Registrations per 1000 People Aged 15 to 64 data is updated yearly, averaging 2.221 Number from Dec 2006 (Median) to 2016, with 11 observations. The data reached an all-time high of 2.648 Number in 2016 and a record low of 1.906 Number in 2012. Italy IT: New Business Density: New Registrations per 1000 People Aged 15 to 64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank.WDI: Businesses Registered Statistics. New businesses registered are the number of new limited liability corporations registered in the calendar year.; ; World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).; Unweighted average; For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

CLEARANCE CERTIFICATE NUMBER: 2020FOBREC828

The rising unemployment rate is one of many challenges facing South Africa, especially among the youth. Government and business leaders are faced with the task of curbing this epidemic, as it is increasingly affecting the status of the country in terms of slow economic growth and a high crime rate. Entrepreneurship has been identified as an important aspect of many countries’ economic models, to enhance economic activity and create employment for the growing population worldwide. Across the globe, many universities are tasked with increasing their entrepreneurship content in their programmes to create more young entrepreneurs and curb the rising unemployment statistics. Entrepreneurship education and exposure thereof have a positive effect on students’ intention to become entrepreneurial savvy. Entrepreneurship programmes that promote knowledge, skills and a particular set of attributes, have a positive effect on the overall entrepreneurial intention of university students hence this study is guided by the Social Cognitive Theory and Bandura’s Agentic theory which depicts that career goals and choices are self-efficacy related and motivation by self-belief of an individual’s talent and abilities can control their goals. Entrepreneurship education has become a global phenomenon, with the intention to improve societies and the economy. There are various studies done in Asia, America, Europe and central to north Africa regarding entrepreneurship in general and entrepreneurship education, but the literature lacks data, especially from a South African context. This quantitative study sought to investigate the entrepreneurial knowledge, skills and attributes that agile hospitality students require to succeed in the tourism and hospitality industry, especially as entrepreneurs. The study used a quantitative research approach following a positivist paradigm. The study employed a descriptive cross-sectional research design, incorporating a quantitative survey using an online questionnaire. First, the researcher conducted documentary reviews in the form of Hospitality Management learning guides to familiarize and identify the entrepreneurship outcomes, teaching methods and modalities in the module. The reviews along with the literature review helped the researcher develop an understanding of the module and develop a list of entrepreneurial questions included in the questionnaire. The study focused on hospitality management students as a sample, at an institution of Higher Learning offering Hospitality Management. The questionnaire was distributed to a total of 400 students and the response was 228, thus giving a response rate of 57%. The data gathered was analysed using Statistical Package for Social Sciences version 28. Descriptive and inferential statistics were then presented, followed by a confirmatory factor analysis and regression model. The study sample showed that there were more female than male students (73%). Together, the average age of the respondents was between 21 and 25 years (62%). The results from the questionnaire showed out of the three years of study, first-year students dominated by 46% above second- and third-year students. With regards to ethnicity, there was a vast difference between the groups where African participants were a majority of 82%. The participants needed to notify whether the choice of hospitality management was their first, second or third choice, just over half of the respondents indicated it as their first choice (58%). The factor analysis showed 7 factors that need to be taken as those that influence entrepreneurial knowledge, skills and attributes. From the data collected, information regarding their knowledge, skills and attributes was questioned. Information such as business aspirations mainly indicated the student’s intention to start a business was because they believe in themselves (60.09%), the know they are hard workers (55.26%), passion is what drives them (51.75%) and above all the students advocate determining their own future (64.91%). The students felt that entrepreneurship education in the hospitality management course has developed a need for achievement in them (49.12%), time management ability (48.25%) and problem-solving ability (47.81%). Data was collected to understand how entrepreneurial teaching methods have enhanced the students’ capabilities in the course, and students regarded mentorship by entrepreneurs and industry interaction as a significant aspect (40.79%). Teaching techniques enhancing the student’s mindset entrepreneurial capabilities indicated that students would prefer to interact more frequently with small business development agencies (39.91%), interact with successful entrepreneurs (38.60%) and felt that adding the entrepreneurship component to more than one subject would be beneficial in stimulating the mind towards a future in entrepreneurship (38.16%). The participants have shown an understanding concerning their entrepreneurship mindset based on their learning, for example knowing that running a business takes a lot of hard work and sacrifice (77.63%), also the confidence in their abilities like being able to assess strengths and weaknesses of a business (51.32%), students are confident in understanding the mindset of consumers (50.88%) and can see themselves starting a business (67.98%). The main findings revealed that entrepreneurship education influences self-efficacy, attitude towards becoming and entrepreneur and entrepreneurial confidence coupled with an entrepreneurial mindset. The responses also showed that more students would rather have a programme that incorporated more practice and influence of outside stakeholders, like mentors and entrepreneurs with profitable businesses. Generally, higher education institutions should develop programmes that incorporate entrepreneurial capabilities, that foster knowledge, skills, and attributes that would encourage students to become entrepreneurial.

Financial overview and grant giving statistics of Global Alliance for Entrepreneurship and Business Deve

All the datasets uploaded contain all the variables required for the analysis carried out in the paper titled: “The impact of entrepreneurship training and credit on labour market outcomes of disadvantaged youth” psm_DP_Labd This dataset contains all the variables used to match the propensity scores. 1_Promise_single_974_DP_Labd This dataset has variables regarding ownership of businesses, savings and expenditure. 2_Promise_roster_974_DP_Labd Variables covering all the demographic characteristics are all gathered in this dataset. 3_Promise_q10_occup_974_DP_Labd Variables regarding employment are all in this dataset. 4_Promise_q12_loan_974_DP_Labd All the variables pertaining to loan are filed in this dataset.

Provide the public with an understanding of applying for microenterprise startup loans.