Modelling Entrepreneurial Intentions and Attitudes towards Business Creation among Emirati Students Using Bayesian Networks
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Abstract
PURPOSE: Entrepreneurial intentions (EI) have been a major focus of research studied using generic models. This paper will use Bayesian Networks (BN) to model entrepreneurial intentions as they provide 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, while 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 to discover how this can affect students’ intention in starting a business. Conclusions stem 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 contributions of the paper to the research questions. © 2022 by all the authors of the article above.