CCHP Intelligent Optimization System of Enterprise Incentive Policy Based on Improved Apriori Algorithm

With the passage of time, the new generation of employees enters the workplace and gradually becomes the backbone of the enterprise. They are passionate and innovative, but their strong self-awareness and tendency to leave their jobs have brought a lot of management problems to the company. A sound incentive mechanism is the best way to reduce employee turnover and improve employee loyalty, which is of great significance for stabilizing the talent team of the enterprise. Company A is an e-commerce company in the growth stage, and the employee group is mainly young people, which also has the problem of high employee turnover rate, which hinders the rapid development of the company. Based on this, this paper constructs a research model with the incentive mechanism of company A as the independent variable and the employee loyalty of company A as the dependent variable based on the relevant theories. The improved Apriori algorithm was used to analyze the collected data by taking the employees of company A as the survey object, and finally the conclusion that the incentive mechanism of company A had a significant positive impact on the loyalty of its employees was finally obtained, which provided basic support for the CCHP intelligent optimization system of enterprise incentive policy in the next step.