Entrepreneurial success factors: An exploratory study based on Data Mining Techniques

Since 2007, the CCEE Entrepreneurship Centre has developed a supporting program for entrepreneurs. A preliminary analysis to determine if the venture was successful or a failure is made to improve the program's management. In this article, the authors identify the main factors associated with entrepreneurship's success, and how they can anticipate entrepreneurship's performance. The case study is based on a survey data applied to the Entrepreneurship Program participants. The two data mining techniques are decision trees and logistic regression. The results were consistent across both techniques. The findings show that the two most important elements to predict entrepreneurship's success are funding and previous experience as self-employed. The results provided very useful insight about the best ways to support entrepreneurship, how to encourage entrepreneurs, and define tools or activities to impact positively ventures success in Uruguay, since similar studies have not been developed.