Using PCA and ANN to Identify Significant Factors and Modeling Customer Satisfaction for the Complex Service Processes

摘要：

This paper proposes a PCA and ANN based approach to identify significant influential quality factors and modeling customer satisfaction for complex service processes. Firstly, the performance evaluation index system includes initial factors and customer satisfaction degree is proposed, and then the measurement data are collected by questionnaires. Secondly, by using PCA, several preceding principal components (PCs) are extracted, which present about 90% contributions of the whole variations of initial factors. Thirdly, the extracted PCs are converted to new significant factors according to the corresponding coefficients of initial factors in each PC. Finally, BP network is applied to modeling the nonlinear relationship between the significant factors and customer satisfaction degree. The case study of the maintenance service process of an automobile 4S store shows that, the proposed approach can extracted the significant factors from lots of initial factors, and can exactly modeling the complex nonlinear relationship between influential factors and customer satisfaction as well.

作者: Qing-an CUI Xin WANG Hong-juan LI Xu KANG

作者单位: Institute of Management Engineering, Zhengzhou University, Zhengzhou, China

会议类型: 国际会议

会议名称: 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management(2011 IEEE 第十八届工业工程与工程管理国际会议 IEEM2011)

会议地点: 长春

会议语种:英文

页码: 1800-1804

在线出版日期: 2011-09-03（万方平台首次上网日期，不代表论文的发表时间）