Apply Cluster Analysis and Association-Rule Techniques to Analyze the Content Architecture of E-tailing Websites

碩士 === 開南管理學院 === 資訊管理系碩士班 === 94 === In recent years the information technique change quickly make the electronic commence prosperous and create the new generation of shopping style - E-tailing. However, the low barriers make the E-tailing in a competitive and crowded. Hence, the critical successfu...

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Bibliographic Details
Main Authors: Chih-Hua Su, 蘇芝嬅
Other Authors: CHI-I HSU
Format: Others
Language:zh-TW
Published: 2006
Online Access:http://ndltd.ncl.edu.tw/handle/93238322098247317140
Description
Summary:碩士 === 開南管理學院 === 資訊管理系碩士班 === 94 === In recent years the information technique change quickly make the electronic commence prosperous and create the new generation of shopping style - E-tailing. However, the low barriers make the E-tailing in a competitive and crowded. Hence, the critical successful factor of the E-tailing is to understand and satisfy the need of the customer to establish the strengthen web sites. The method to carry out our study was using a content analysis and ICDT ( Information、Communication 、Distribution and Transaction space ) model to analysis the difference of E-tailing, web content, and the service between Taiwan and Mainland China to contribute the framework of E-tailing. Then we find the advantage of different clusters between the Taiwan and Mainland China. The result via cluster analysis combines with association rule analysis shows that (1) The E-tailing between Taiwan and Mainland China must focus on provide the personal service and build community. (2) The E-tailing between Taiwan and Mainland China need to provide more communication way or service of customer. (3) The E-tailing in Mainland China should pay attention to provide complete privacy and security policy of web sites. Finally, the research also analysis the execution rate in four distinct area of virtual marketspace between Taiwan and Mainland China. The execution rate show as follow: 69.8%、70.8%、59.3% 、44.7% 、64.6%、54.2%、47.2% and 33.7%.