电子商务中基于聚类的顾客满意度影响因素分析  

Analysis of Influential Factors of Customer Satisfaction Based on Clustering in E-commerce

作　　者：杨波 黄晓兰 

机构地区：[1]广东财经大学华商学院信息工程系,广东广州511300 [2]广东财经大学信息学院,广东广州510320

出　　处：《湘潭大学自然科学学报》2018年第1期82-85,90,共5页Natural Science Journal of Xiangtan University

基　　金：广东省教育科研项目(2014GXJK174)

摘　　要：针对电子商务中顾客满意度影响因素的分析,提出一种基于RFM模型评分方法和聚类技术的影响因素分析方法 .首先,利用有序加权平均(OWA)方法来获得RMF模型中各变量的权重.然后,利用RFM模型对顾客的购买行为进行分析,给出各项评分,并使用模糊C均值(FCM)聚类技术对顾客进行聚类.接着,通过将每个聚类组的RFM值与平均RFM值进行比较,以此来发现流失的顾客类型.最后,对这些客户进行问卷调查来获得顾客不满意的主要因素.通过一个案例分析,提出方案能够准确找到顾客不满意因素,为电子商务公司提供有力依据.For the issues that the influencing factors analysis of customer satisfaction in e-commerce,an analyzing method of influencing factors based on the RFM model and clustering technique is proposed.Firstly,the ordered weighted average（OWA）method is used to obtain the weight of each variable in the RMF model.Then,the RFM model is used to analyze the customer＇s buying behavior,and give the scores,so that to can use the fuzzy C-means clustering（FCM）to cluster the customers.Next,the lost customer type is discovered by comparing the RFM value of cluster group with the average RFM value.Finally,aquestionnaire is conducted among these customers to find out the main factors of customer dissatisfaction.Through a case analysis,it is proposed that the solution can accurately find the customer dissatisfaction factors and provide a strong basis for e-commerce companies.

关 键 词：电子商务 满意度影响因素 RFM模型 模糊C均值聚类 

分 类 号：O224[理学—运筹学与控制论] F270[理学—数学]