A Comparative Test of Two Employee Turnover Prediction Models

Accurate employee turnover prediction models are critical in the early detection of unanticipated turnover, and thus giving managers sufficient time to deal with turnover related management issues. The logit and probit models have been successfully applied to solve nonlinear classifying and regression problems. However, the feasibility of applying to voluntary turnover prediction still has not been sufficiently explored. Consequently, a numerical example involving voluntary turnover data from a motor marketing enterprise in central Taiwan is employed, and the empirical results reveal that the proposed models have high prediction capabilities. Accordingly, these two models also provide a promising alternative for predicting employee turnover in human resource management