A Study On The Turnover Forewarning Of The New-generation Knowledge Employees

In the era of knowledge economy, the new-generation knowledge employees has gradually become the main force of society construction, and played an increasingly important role in the development of enterprises. However, they are usually characterized as maverick, self-centered, free-spirited, restless and frequent job-hopping, which greatly threatened the stability in the workplace. How to identify and determine the potential crisis caused by the work status and psychological state of the new-generation knowledge employees, and to control various incentives that may lead to such crisis at a reasonable level as well as to avoid core employees of this kind moving against the enterprises’healthy development, have become the key issues for enterprises to build core competitiveness and to gain competitive advantages.The purpose of this paper is to propose an early-warning model for turnover risk assessment of new generation knowledge employees. Based on existing studies on causes of employee turnover, combining with factor analysis, an turnover forewarning index system for the new-generation knowledge employees is constructed, and the index weight is determined by combination weighting of fuzzy analytical hierarchy process(FAHP) and information entropy method. Considering the subjectivity of expert scoring on the conventional TOPSIS, we made some adjustments through transforming employees’linguistic assessment information into numerical decision matrix, then the relative closeness coefficient of each employee can be calculated. On that basis, the upper and lower limits of each warning zone is given by three sigma principle. Finally, through questionnaires and follow-up survey, we came to the results that the proposed turnover early-warning model is fairly effective and accurate.In general, the empirical results showed that the average turnover intention of the new-generation knowledge employees is of high degree, and the individual factors combined with environmental factors played an significant role in their turnover decision. We also found differences of turnover intention existing in individual variables, including sex, marital status, education, job title, tenure. Although we didn’t find significant correlation between turnover intention and employee’s age as well as business type. And when it comes to regional difference, the turnover intention of new-generation employees increased from the western undeveloped regions to the eastern coast of China. Based on this, we present relevant management recommendations, which have a certain significance and reference value for companies managing the new-generation knowledge employees more effectively.