Entrepreneurial intention of public hospital dentists and its importance factors: a study based on machine learning and binary logistic regression

Abstract

As China's economic level continues to grow, people's standard of living is improving along with their awareness of oral health. The increased demand for high-quality dental services provides good opportunities for dentists to start their own businesses. Despite the rapid growth of private dental practices in China, more research is still needed to gain insight into the distinctive characteristics and influencing factors of dentists' entrepreneurial behavior. In this study, the entrepreneurial intention of dentists (the person's intention to leave the public hospital system and enter the private institution) was analyzed by collecting relevant questionnaires from public hospitals in five major cities of Guangdong Province, and the relationship between the entrepreneurial intention of dentists and their personal characteristics was analyzed using XGBoost method and binary logistic regression method. A total of 505 dentists' survey data were included in this study, and the top 5 influencing factors of importance were obtained based on the research analysis. Experiments showed that the importance-related features obtained in this study can play a high predictive role and have favorable stability, with an accuracy of more than 82% in XGBoost, decision tree and random forest classification algorithms. The prediction model of dentists' entrepreneurial intention based on machine learning algorithm is of high practical significance and can be incorporated into the screening and decision-making of dentists' entrepreneurial intention status. Based on this method, the entrepreneurial intention of relevant individuals can be accurately grasped, so that appropriate measures can be taken to promote the development and management of the industry.