Entrepreneurial success factors: An exploratory study based on Data Mining Techniques
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Abstract
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 tech- niques. The findings show that the two most important elements to predict entrepreneurship’s success are fun- ding and previous experience as self-employed. The results provided very useful insight about the best ways to support entrepreneurship, how to encoura- ge entrepreneurs, and define tools or activities to impact positively ventures success in Uruguay, since similar stu- dies have not been developed.
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