LEARNING A BAYESIAN STRUCTURE TO MODEL ATTITUDES TOWARDS BUSINESS CREATION AT UNIVERSITY
Some scholars consider entrepreneurship as a key factor to optimise the development of human communities (e.g., Shapero, 1985). From a psychological point of view, entrepreneurship might be considered as an attitudinal phenomenon (e. g., Bird, 1988; Shapero & Sokol, 1982). In other words, entrepreneurial behaviour depends on intention, which depends in turn on attitudes, normative beliefs and some related constructs. The main objective of this paper is to test a theoretical model of business creation based on the attitudes perspective. In order to assess the likelihood of that model, we use some of the techniques implemented in the bnlearn software (Nagarajan, Scutari & Lèbre, 2013) to learn Bayesian networks. Entrepreneurial attitude models have already been developed in the literature using Bayesian networks (e.g., López & García, 2012; López, Ramírez & Casado). However, even though we aim to follow a methodological approach similar to that used by Krueger, Reilly & Carsrud (2000), we improve on it through our choice of statistical techniques. Our results are useful in two ways - firstly, theoretical, and secondly, practical. From a theoretical point of view, we can provide the scientific community with further evidence supporting an entrepreneurial attitudes model. On the other hand, the Bayesian network generated may be helpful to potentiate or optimize entrepreneurship in practice.
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