文章基本信息

标题：Entrepreneurial Competence: Using Machine Learning to Classify Entrepreneurs
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作者：Clariandys Rivera-Kempis ; Leobardo Valera ; Miguel A. Sastre-Castillo 等
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2021
卷号：13
期号：15
页码：8252
DOI：10.3390/su13158252
语种：English
出版社：MDPI, Open Access Journal
摘要：Competencies are behaviors that some people master better than others, which makes them more effective in a given situation. Considering that entrepreneurship translates into behaviors, the competency-based approach expresses attributes necessary in the generation of such behaviors with greater precision. By virtue of the dynamic and complicated nature of entrepreneurial phenomena and, especially, of the numerous data sets and variables that accompany the entrepreneur, it has become increasingly difficult to characterize it. In this study, we use predictive analysis from the machine learning approach (unsupervised learning) in order to determine if the individual is an entrepreneur, based on measures of 20 attributes of entrepreneurial competence relative to classification and ranking. We investigated this relationship using a sample of 6649 individuals from the Latin American context and a series of algorithms that include the following: logistic regression, principal component analysis, ranking and classification of data using the Ward method, linear discriminant analysis, and Gaussian regression among others.