MODELLING ENTREPRENEURIAL ATTITUDES IN WOMEN ENTREPRENEURS WITH BAYESIAN NETWORKS

This journal talk about modelling entrepreneurial attitudes in women entrepreneurs. As can be seen, Model I containing variables referred to resources and opportunity feasibilities produces the better results. That model is able to correctly classify woman entrepreneurs in 75% of the cases. Additionally, logarithmic loss and quadratic loss measurements are the lower and the spherical payoff is the higher compared with the other two models. On the other hand, Model II (considering resources feasibility alone) and Model III (modeling opportunity feasibility) yield similar goodness of fit parameters. These results suggest that Model I considering feasibility as a composite construct of two different types of feasibilities (opportunity and resources) is a better model than those taking into account either of the dimen-sions separately. The most striking result in this research is that the differentiation between opportunity and resources feasibility is useful to predict entrepreneurial intention. Given that Model I produced better goodness of fit parameters, that could conclude feasibility is, at least for women entrepreneur, integrated by a dimension of opportunity and another one of resources. As can be appreciated, and as it is predicted by the theory, opportunity feasibility, desirability and resources feasibility are the three most influential variables in the model.