Explaining the Entrepreneurial Orientation of Agricultural Students Based on Cognitive Capabilities: A Hybrid Approach Using Structural Equation Modeling and Artificial Neural Networks
This study employs a novel approach to investigate the role of specialized cognitive components, specifically opportunity recognition capability, entrepreneurial creativity, and risk management capability within the framework of behavioral models, aiming to assess their explanatory power regarding individual entrepreneurial orientation among agricultural students. To this end, data collected from participants in entrepreneurship courses (bootcamps) at the Incubation Center of the Khuzestan University of Agricultural Sciences and Natural Resources were analyzed using a hybrid methodology combining Structural Equation Modeling (PLS-SEM) and Artificial Neural Networks (ANN). The research findings confirmed the pivotal role of entrepreneurial creativity as the strongest predictor of students' entrepreneurial orientation. Furthermore, the results of the Importance-Performance Map Analysis (IPMA) indicated that while opportunity recognition capability demonstrates satisfactory performance, enhancing risk management skills is an inevitable necessity for consolidating students' entrepreneurial mindset. The neural network analysis results, by confirming non-linear relationships, increased the model's predictive accuracy in explaining students' startup intentions and demonstrated the superiority of this hybrid approach in overcoming the limitations of traditional linear methods. Ultimately, this research showed that given the strategic importance of cognitive competencies, universities and incubation centers should focus on improving students' problem-solving skill sets and enhancing their mental resilience when designing educational modules. It is recommended that educational policymakers address performance gaps by facilitating the path of knowledge transfer to the market and focusing on specialized mentorship, particularly for students in less developed regions, thereby providing the necessary foundation for the emergence of a new generation of innovative entrepreneurs in the agricultural ecosystem.
Sobhani, S. M. J., PayandePour, N., & Jaberi, M. (2026). Explaining the Entrepreneurial Orientation of Agricultural Students Based on Cognitive Capabilities: A Hybrid Approach Using Structural Equation Modeling and Artificial Neural Networks. Education and Management of Entrepreneurship, (), -. doi: 10.22126/eme.2026.13692.1289
MLA
Seyed Mohammad Javad Sobhani; Negin PayandePour; Masoumeh Jaberi. "Explaining the Entrepreneurial Orientation of Agricultural Students Based on Cognitive Capabilities: A Hybrid Approach Using Structural Equation Modeling and Artificial Neural Networks". Education and Management of Entrepreneurship, , , 2026, -. doi: 10.22126/eme.2026.13692.1289
HARVARD
Sobhani, S. M. J., PayandePour, N., Jaberi, M. (2026). 'Explaining the Entrepreneurial Orientation of Agricultural Students Based on Cognitive Capabilities: A Hybrid Approach Using Structural Equation Modeling and Artificial Neural Networks', Education and Management of Entrepreneurship, (), pp. -. doi: 10.22126/eme.2026.13692.1289
VANCOUVER
Sobhani, S. M. J., PayandePour, N., Jaberi, M. Explaining the Entrepreneurial Orientation of Agricultural Students Based on Cognitive Capabilities: A Hybrid Approach Using Structural Equation Modeling and Artificial Neural Networks. Education and Management of Entrepreneurship, 2026; (): -. doi: 10.22126/eme.2026.13692.1289
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