Characterisation of Youth Entrepreneurship in Medellín-Colombia Using Machine Learning
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MDPI
Materia
Artificial intelligence Machine learning Data mining K-mean Youth entrepreneurship
Date
2023-06-29Referencia bibliográfica
Ojeda-Beltrán, A.; Solano-Barliza, A.; Arrubla-Hoyos, W.; Ortega, D.D.; Cama-Pinto, D.; Holgado-Terriza, J.A.; Damas, M.; Toscano-Vanegas, G.; Cama-Pinto, A. Characterisation of Youth Entrepreneurship in Medellín- Colombia Using Machine Learning. Sustainability 2023, 15, 10297. [https://doi.org/10.3390/ su151310297]
Sponsorship
AUIP (Iberoamerican University Association for Postgraduate Studies)Abstract
The aim of this paper is to identify profiles of young Colombian entrepreneurs based on
data from the “Youth Entrepreneurship” survey developed by the Colombian Youth Secretariat. Our
research results show five profiles of entrepreneurs, mainly differentiated by age and entrepreneurial
motives, as well as the identification of relevant skills, capacities, and capabilities for entrepreneurship,
such as creativity, learning, and leadership. The sample consists of 633 young people aged
between 14 and 28 years in Medellín. The data treatment was approached through cluster analysis
using the K-means algorithm to obtain information about the underlying nature and structure of
the data. These data analysis techniques provide valuable information that can help to better understand
the behaviour of Colombian entrepreneurs. They also reveal hidden information in the
data. Therefore, one of the advantages of using statistical and artificial intelligence techniques in
this type of study is to extract valuable information that might otherwise go unnoticed. The clusters
generated show correlations with profiles that can support the design of policies in Colombia to
promote an entrepreneurial ecosystem and the creation and development of new businesses through
business regulation.