A neural network-based method for prediction of employee turnover in high-tech industries

摘要

Because of rapid revolution of high-tech industries,structure of industries and the competitive relationship have been changed,employees have to endure long-term work pressures,and many of them resigned their jobs at last. Porter (1986) suggested an informal network within an organization indicating that the turnover employee not only lowers the morale of the workpeople,but also provokes their colleagues to quit as a chain reaction. Renewal of products can easily be copied,but the collaborative structure within an organization could not be ready to duplicate. Turnover of employee may affect the current workers' morale,and contribute to the decreased capacity of the industry. Thus,in this study,high-tech industrial employees were examined to find out the factors that are related to their involuntary turnover. Subsequently,those employees' historical data were then run through neural network to find out an applicable model and which factor is likely to predict employees' turnover.