Özet:

The United Nations Development Programme (UNDP) defines entrepreneurship as an important factor in achieving Sustainable Development (SD). The aim of this study is to analyze the factors affecting entrepreneurship activities in Turkey in terms of SD by applying machine learning, which is a relatively new method in social sciences, and using Global Entrepreneurship Monitor (GEM) data. According to the results of the Random Forest model, working status, knowing another entrepreneur, one’s opinion about one’s own knowledge and skills, need/obligation and age are important factors for being an entrepreneur. Also, household income and population, the employment status, gender, education level, and the engagement in intra-company entrepreneurial activity of the person at the time of the survey were also determined as important factors. According to the results of the Stochastic Gradient Boosting, it is observed that regional development and conditions in Turkey affect the probability of individuals to become entrepreneurs. This research analyzes and extends the previous results of Özdemir and Karadeniz (2011) and Karadeniz and Özçam (2018) from individual entrepreneur gains in the Turkish context for the first time through the application of machine learning algorithms. Entrepreneurial activities should be planned within the framework of policies that support sustainable development.

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