基于贝叶斯网络模型的公司高级管理人员薪酬满意度分析

摘要

The Bayesian network model was constructed by introducing Bayesian network into the analysis of compensation satisfaction and referring to the variables put forward by Heneman. We forecast and diagnose the compensation satisfaction of s CPA by the way of causal reasoning and diagnostic reasoning. The result shows that Bayesian network works well in describing the relationship of data, which is helpful to forecast and diagnose cause-effect relations of data, and it is proved that the Bayesian network is effective in practice.%以Heneman提出的薪酬满意度的几个考察维度为参考变量，将贝叶斯网络引入薪酬满意度分析中，构建贝叶斯网络模型，通过因果推理和诊断推理对S公司的薪酬满意度进行预测和诊断，并对实证结果进行分析。研究结果表明，贝叶斯网络用图形的方法描述数据间的相互关系，语义清晰，可理解性强，有助于利用数据间的因果关系进行预测与诊断，贝叶斯网络的应用效果也是比较令人满意的。