基于改进Kano模型的B2C网站顾客满意度影响研究

Research on Customer Satisfaction of B2C Website Based on Improved Kano Model

主要研究了B2C电子商务网站满意度影响因素。首先结合MUG模型构建了B2C网站顾客满意度研究假设模型,采用单样本T检验和因子分析对该模型加以检验,并确定了指标项及其初始重要度;其次,针对与满意度呈非线性关系的两类属性指标,提出了细分化属性归类方法和相应的线性化调整系数计算方法,并用以对筛选出的B2C网站顾客满意度指标项初始重要度进行调整,最终得到影响B2C网站顾客满意度的关键指标。

The main purpose of this paper is to explore the critical factors influencing consumer satisfaction on a B2C web- site. Firstly, a hypothesis model of customer satisfaction on B2C website is proposed based on Microsoft MUG model and is verified by using both one-sample T-test and factor analysis. Thus the customer satisfaction index system of B2C is ob- tained; Then, by combining clustering algorithm and the idea of importance degree of user requirements, an improved Kano model with subdivided attributes classification method is proposed. Finally, the critical factors influencing customer satis- faction on B2C website are obtained by adjusting the initial importance degree of customer satisfaction indexes according to the attribute classification based on improved Kano model.