| Summary/Abstract |
Entrepreneurs and entrepreneurship are essential for new wealth creation and economic growth, particularly in developing countries. The objective of this study is to develop a model to identify the determinants of entrepreneurship, and reveal how it can be predicted based on individual characteristics, family environment, and social environment. Employing 16 sets of machine learning algorithms on data collected from the Chinese General Social Survey in 2017, we find the best-performing algorithms (i.e., lasso, ridge, and elastic net regression) and examine the effects of the feature variables on entrepreneurship. Overall, this study provides significant theoretical underpinnings for entrepreneurship research, and offers insights for individuals and policymakers by revealing various drivers of entrepreneurship.
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