A DATA MINING APPROACH TO UNDERSTAND FEMALE ENTREPRENEURS ACROSS THE GLOBE

Purpose: The aim of this study is to examine the pattern of women-owned businesses particularly whether country, age, education, citizenship, social class, income, and religion are associated with female entrepreneurship. Theoretical Framework: The study develops a global demographic model of female entrepreneurship using data mining techniques. Design/Methodology/Approach: The study employs a data mining approach on the World Values Survey Wave 7 2017-2020 data that includes 19575 working women in 56 countries. Findings: The results show that the backgrounds of female entrepreneurs are largely heterogenous from one country to another. The most significant factor that influences entrepreneurship is education level while the least is citizenship status. Research, Practical & Social Implications: The study contributes to model a specific set of attributes of female entrepreneurs for each country. Governments could establish appropriate policies to encourage female entrepreneurship that fits with the local environment and is unique to each country. Originality/Value: The study contributes to the use of data mining techniques for producing more comprehensive findings than statistical approaches that are commonly employed in business economics research.