基于组合赋权和改进TOPSIS法的新生代知识型员工离职预警模型研究
A Study on the Turnover Early-warning Model of the New Generation Knowledge Workers Based on Combination Empowerment and Improved TOPSIS Method

基于新生代知识型员工离职率居高不下的现状，从个体因素、组织因素、工作因素、宏观环境因素四个方面选取了新生代知识型员工离职预警指标，采用FAHP与信息熵相结合的方式确定了各预警指标的权重，并将改进的TOPSIS法与3σ理论相结合，构建了新生代知识型员工离职预警模型，最后结合223份调查问卷对模型进行了验证，准确率达到82.5%，表明该模型具有较好的预警效果。
Considering the high turnover rate of the new generation knowledge workers, this paper attempts to construct an early-warning model for the evaluation of the turnover intention of them. We selected the evaluation criteria according to the factors that influence employee turnover, which can be classified into four categories(individual, job-related, organizational and environmental), and determined the criteria weights by combining Fuzzy Analytic Hierarchy Process (FAHP) and Entropy method. We also adopted TOPSIS method and the Pauta criterion to identify the grade of turnover risk of each employee. The proposed early-warning model was tested on a sample of 223 new generation knowledge employees, and the results of which showed a satisfactory effect with an accuracy of 82.5 percent.