宾馆员工工作满意感影响因素研究——人工神经网络方法

An Research on the Influential Factors of Hotel Employees' Job Satisfaction:an Artificial Neutral Network Approach

本文采用实证的方法,通过因子分析、人工神经网络方法和逻辑回归分析,对宾馆员工工作满意感的影响因素及其影响程度进行研究。本项研究得出以下结论:(1)宾馆员工工作满意感的影响因素有8类,在这8类影响因素中,工作本身对员工工作满意感的影响最大,其后依次是主管管理风格、宾馆政策及实施、同事关系、宾馆经营、个人能力发挥、培训与晋升、工作报酬;(2)人工神经网络方法的预测正确率高于回归分析方法的预测正确率,并且前者的模型拟合优度要优于后者,这说明人工神经网络方法在分析宾馆员工工作满意感时,优于回归分析方法。

This article applied the empirical method, conducted a factor analysis and used Artificial Neural Network approach and Logistic Regression analysis to study the factors that influence hotel employee＇ s job satisfaction and the degree of the influences. The results of the study are： （1） there are 8 factors influencing employees＇ job satisfaction. Among these, Work Itself bears the highest degree of influence on employees＇ job satisfaction, followed by Management Style, Policies and Implementation, Relationship among Co-workers, Hotel Operation, Individual Capability, Chances for Training and Promotion, and Pay. （2） It is found that the validity of Artificial Neural Network approach is higher than that of Logistic Regression Analysis, and Goodness-of-fit （R^2） of the former is superior to that of the later. These results indicate that Artificial Neural Network approach is more suitable for analyzing employees＇ job satisfaction than Logistic Regression Analysis.