The impact of culture on entrepreneurship: machine learning analysis

Abstract

Entrepreneurship is one of the main pillars of the economy and it has a substantial role to pay in economic development by creating new jobs and opportunities, driving innovation, and developing new markets, products, and services. This study aims to better understand the motivations of people who choose to undertake entrepreneurial activity and to try to pinpoint some of the key factors that move them to do so. Three independent data sets (the GEM, WVS and Hofstede) were computed and significant correlations with Total Early-Stage Entrepreneurial Activity (TEA) noted. Machine learning techniques were applied to the data sets in different regression models to show that the most important relationship between the different variables is the TEA with Perceived Capabilities (PC).