Classification of Effectuation Thinking Level in Entrepreneurship of Local Endemic Poultry Breeders in Sistan and Baluchestan Province Using the Naive Bayes Algorithm

Nowadays, the most important feature of entrepreneurship behavior is known as the form of intellectual architecture named effectuation. In this regard, current empirical research attempts to use a machine algorithm to classify the levels of effectuation thinking among rural small business owners in the field of local poultry breeding in Sistan and Baluchestan province. To this end, 191 units out of 360 were sampled and studied. The main objective of this research was to find a combination of different demographic and behavioral variables/components of entrepreneurial ecosystems affecting the classification level of effectuation among rural business owners. The research tool for measuring the research variables was a standard questionnaire that its validity and reliability were tested and confirmed. The main method of data analysis was Naive Bayes algorithm of the machine learning which was implemented using R software. The results of the classification of effectuation as the main indicator of entrepreneurial thinking showed that the variables, including prior experience, focusing on poultry breeding as the main job, capacity of the production unit, access to cooperation and market network, entrepreneurial self-efficacy, motivation, innovation in the market, human capital, and financial capital at their high levels resulted in high level of effectuation thinking. Therefore, it can be concluded that a combination of behavioral and demographic variables as well as ecosystem components can capture the entrepreneurial behavior . Based on research findings, some suggestions were proposed to develop the supportive climate of rural nascent entrepreneurs.