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基于改进Kano模型的B2C网站顾客满意度影响研究 被引量:25

Research on Customer Satisfaction of B2C Website Based on Improved Kano Model
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摘要 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.
出处 《情报科学》 CSSCI 北大核心 2016年第2期83-86,共4页 Information Science
基金 国家社会科学基金项目(10BGL027)
关键词 KANO模型 顾客满意度 聚类 B2C网站 kano model customer satisfaction clustering B2C website
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参考文献15

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