Entrepreneurship: Analysis by Country Through Machine Learning Techniques





entrepreneurship ecosystem, machine learning, patterns direction, innovation process, clusters, technology, absorption


This research aims to analyze entrepreneurship worldwide through the dimensions and pillars of the entrepreneurship ecosystem of each country, identifying the contribution and patterns of behavior and correlation within the entrepreneurship ecosystem. This analysis intends to show the main actions that countries have carried out in support of entrepreneurship and entrepreneurs. The tool used to analyze is machine learning, where various algorithms are applied. The evidence shows that the most relevant pillars in the entrepreneurial ecosystem are I. Opportunity Startup, II. Technology Absorption, III. Risk Acceptance, IV. Risk Capital and V. Process Innovation. The pillars that best correlate are I. Competition and Opportunity Startup, II. Opportunity Startup, and Risk Acceptance, III. Opportunity Startup and Technology Absorption, IV. Cultural Support and Opportunity Startup, and V. Opportunity Startup and Risk Capital. The present work aims to provide knowledge to decision-makers in both the public and private sectors to channel public policies that support entrepreneurs in this time of crisis and promote the generation and strengthening of entrepreneurial activity. Although there are still no reliable GEI data for the years 2020 to 2022, the economic crisis generated by the stagnation in the development of the countries has reduced support for entrepreneurs, which in many cases can be a key factor for the rescue of the most disadvantaged countries.

Author Biography

Antonia Terán-Bustamante, Universidad Panamericana

Researcher at the Faculty of Business Sciences.