ABSTRACT

Previous work on the relationships between entrepreneurship education, prior entrepreneurial exposure and entrepreneurial action has resulted in mixed findings. However, this work typically relies on linear models which may not adequately account for the relationships. Therefore, we explore artificial neural networks (ANN) to test non-linear relationships and compare these results with a linear regression model to understand the previous mixed findings. Data from 125 entrepreneurship graduates in Zambia revealed that a non-linear model best explained the variation in entrepreneurial action, whereby the relationship was cubic. These results explain some of the previously mixed findings and demonstrate the importance of educators, policy makers and scholars paying attention to non-linear relationships when aiming to promote and further understand entrepreneurship. Therefore, this paper has implications for educational initiatives aiming to augment entrepreneurship education, while also contributing to the development of theory explicating the relationship between entrepreneurial exposure, education and action.

摘要

以前有关创业精神教育，先前创业经历和创业行动之间关系的研究得出了不同的结论。但是，这项工作通常依赖于线性模型，该模型可能不足以说明这些关系。因此，我们探索了人工神经网络（ANN）以测试非线性关系，并将这些结果与线性回归模型进行比较，以了解先前的混合发现。来自赞比亚125位创业学毕业生的数据显示，非线性模型最能解释创业行为的变化，因此这种关系是立方的。这些结果解释了以前的一些混合发现，并证明了教育工作者的重要性，政策制定者和学者在促进和进一步了解企业家精神时要注意非线性关系。因此，本文对于旨在加强企业家精神教育的教育举措具有重要意义，同时也为阐明企业家风险，教育与行动之间的关系的理论发展做出了贡献。