Analyzing Big Data in Entrepreneurship: Replicating and Extending Evans and Leighton (1989)

Abstract

Analyzing big data requires the use of more powerful big data analytical techniques. The risk of not employing such techniques is that we misunderstand the true relationships in fundamental issues. In the study, we replicate and extend Evans and Leighton (1989) to revisit the entrepreneurial entry problem using a traditional logistic regression and one type of big data techniques – random forests. Through comparing the discrepant findings of these two models, we assert the benefits of using contemporary approaches to handle big data in revisiting fundamental questions in entrepreneurship.