期刊名称：Iranian Journal of Information Processing & Management
印刷版ISSN：2251-8223
电子版ISSN：2251-8231
出版年度：2017
卷号：33
期号：1
页码：241-274
出版社：Iranian Research Institute for Information and Technology
摘要：Nowadays, some of the most important things that made companies to pay attention to the customer satisfaction is the competition in the world and companies struggles to achieve sustainable competitive advantage and strategic superiority over their competitors. The aims of this research is to identify the customer’s requirement in Nyazco online shopping and cluster these customers based on two methods, k-means algorithm and fuzzy Kano model, in order to offer products according to each customer’s needs. In this study, 1090 record of customers were examined for data mining of these customers in the period of 7 months, and four clusters of customers were defined. To measuring the customers’ satisfactions, the fuzzy Kano questionnaire was designed and randomly assigned to 168 customers, who were selected based on Cochran formula, and finally, the requirement of each clusters were investigated and classified by using fuzzy Kano model. The results of this research show the category of some characteristics are different between some clusters and are the same between other clusters. Also, the satisfaction and dissatisfaction score is calculated for each cluster. The results of this study indicate that the customers of third cluster are more important for this site because the transaction frequencies of these customers and the total amount of purchasing are high. The result of this study will help other online shopping centers for better presentation of goods to different customers.
关键词：Online-Shopping ; Data Mining ; Clustering ; Fuzzy Kano Pattern
