A Model to Predict Employee Turnover Rate: Observing a Case Study of Chinese Enterprises

Employee turnover is a main focus in human resource management (HRM) because understanding it can be useful in providing decision support to managers. The goal of our study was to predict the amount of employee turnover based on certain variables. The properties of employees and job positions are represented by two variables. A state-transition mode is applied to describe an employee?s job state and the type of turnover. We propose a conditional semi-Markov (SMK) model for calculating the conditional amount of employee turnover. Then, we provide a data set of employee records to illustrate how these models work in reality and how the proposed method can be valuable to managers for developing recruitment plans, promotion rules, and retirement regulations.