Modelling academic entrepreneurial intention with Bayesian networks / Modelado de la intención emprendedora académica con redes bayesianas

Abstract

Abstract Entrepreneurship serves as an engine for the economy and has sparked a great deal of scholarly interest since the Enlightenment. Today, universities play an essential role in knowledge transfer as drivers that promote this phenomenon. The objective of this study is to compare different theoretical models that seek to explain the variables involved in entrepreneurial intention among university faculty using an automatic structural learning method of Bayesian networks. The sample was comprised of 1,068 professors from Spanish public universities between the ages of 24 and 77 (M = 43.54, SD = 9.78). The results show that the variables that directly predict entrepreneurial intention are self-efficacy, desirability, attitude and social norm. These results are interesting for further exploring knowledge of the variables involved in the process of entrepreneurship at the university level and proposing systems to foster entrepreneurship.