Research of Customer Satisfaction Index Model Based on PLS Algorithm

Customer Satisfaction measurement regular model is put forward by comparing with Customer Satisfaction measurement model at home and aboard. This paper presents the setup,estimation,assessment of Customer Satisfaction regular model and adapts PLS algorithm to estimate the parameters. The missing data processing method of Partial Weight Setup Newly is proposed to estimate missing values when outer estimate is processed. At last,the system is applied to evaluate some food company and get the standardized path coefficients. The results show that the model meets the Uni-dimensionality,has good expository ability as well as convergent validity and Good-Fit test. The case results prove the feasibility and validity of the model. It offers a useful approach for research of PLS path modeling and missing data processing.