Modelling Entrepreneurial Intentions and Attitudes towards Business Creation among Emirati Students Using Bayesian Networks

Abstract

Purpose: Entrepreneurial intentions have been a major focus of research that have been studied using generic models. The paper will use Bayesian Networks to model entrepreneurial intentions as it provides an advantage over classical methods. Methodology: A cross-sectional study was conducted among a random sample of 324 Emirati University students by implementing the Unsupervised Structural Learning algorithm to build the Model. Findings: Entrepreneurial intentions are highly affected by attitude, self-efficacy, subjective norms, and opportunity feasibility. Whereas obstacles and university opportunity feasibility are the variables whose influence on entrepreneurial intention is less. Originality: This study looked at entrepreneurship intention and attitudes among students who are not yet entrepreneurs using Bayesian networks as a new technique and see how this can affect their intention in stating a business. Conclusions are stemming from the existing Emirati social construct (people-centric society of the Arab world, rather than system-centric society of the Western world). This has created value-added contribution of the paper to the research questions.