Modeling Entrepreneurial Intentions in Moroccan Higher Education: Bridging Academia and Entrepreneurship with Artificial Neural Networks.

This study explores the determinants influencing entrepreneurial intentions among higher education students in Morocco, utilizing both traditional statistical methods and Artificial Neural Networks (ANN) to predict entrepreneurial intention. The research focuses on variables such as desirability, social norms, self-concept, and academic context, and assesses their impact on students' propensity toward entrepreneurship. A survey was conducted with 300 engineering and master's students from Higher School of Textile and Clothing Industries (ESITH) in Casablanca. The statistical analysis revealed significant relationships between entrepreneurial intention and factors such as desirability, social norms, and self-concept, while the feasibility factor showed a limited influence. ANN was employed to model the complex, non-linear relationships between these variables, providing deeper insights into the predictive dynamics of entrepreneurial intentions. The ANN model demonstrated high accuracy, highlighting the importance of desirability and social norms as primary drivers, followed by self-concept and academic context. The study concludes with recommendations to enhance entrepreneurial intention through targeted educational strategies, emphasizing the role of practical experiences and skill-building programs. This research contributes a novel approach to understanding and fostering entrepreneurship in academic settings through the integration of ANN, offering predictive modeling capabilities that could inform future educational policies and entrepreneurial programs.