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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/87494

    Title: 資料探勘應用於電視購物代言人推薦機制之研究
    Other Titles: The study of data mining approach implementing on recommendation mechanism of TV shopping endorser
    Authors: 黃淑芳;Huang, Shu-Fang
    Contributors: 淡江大學管理科學學系企業經營碩士在職專班
    廖述賢;Liao, Shu-Hsien
    Keywords: 資料探勘;關聯法則;推薦機制;電視購物;代言人光譜;商業智慧;data mining;association rule;Recommendation mechanism;TV shopping;Endorsers spectrum;Business Intelligence
    Date: 2012
    Issue Date: 2013-04-13 11:15:30 (UTC+8)
    Abstract: 科技的進步改變了人們的生活型態,電視購物逐漸被消費者所接受。依據經濟部統計台灣的無店面零售業從2002年的819億元成長到2011年的1,755億元,電視購物在過去幾年內快速成長和普及化,消費者越來越依賴在電視購物台購買商品,電視購物己逐漸成為未來消費的主要模式,電視購物台營運表現也十分驚人。
      本研究採用問卷調查法,以900位的電視購物消費者為研究對象,問卷回收之後資料建立關聯性資料庫,以SPSS Clementine為分析工具,透過資料探勘做集群分析以找出消費者輪廓,並運用關聯法則瞭解消費者對於電視購物代言人及商品的光譜現象。並依據消費者輪廓及偏好描繪出產品行銷知識地圖及代言人行銷知識地圖,由知識地圖中,發掘出不同集群之間的購買動機、交易機制偏好等需求,找出最佳的代言組合並進行推薦,進一步整合成企業不可或缺的商業智慧。
    Nowadays, the technology improvement has changed people’s lifestyle and it has made that consumers gradually accepted television (TV) shopping . According to statistics by Ministry of Economic Affairs, non-store retailing market in Taiwan has grown from NT$81.9 billion in 2002 to NT$175.5 billion in 2011. Obviously, TV Shopping become popular and also develops rapidly over the past few years. More and more consumers rely on TV shopping to purchase products for their needs. TV Shopping will be the main purchase model in the future.
    The study used questionnaires to 900 samples TV shopping consumers for the study, questionnaires were collected data to create relational database to the SPSS Clementine analysis tool. In order to identify consumers’ contour by cluster analysis K-Means. Furthermore, it utilizes association rules (Apriori) to realize how consumers Endorsers spectrum and Product spectrum between in TV shopping. It can be outlined the knowledge map of product marketing and Endorsers marketing in TV shopping based on consumers contour and preference. From knowledge map, it can discover the purchase motivation in different cluster, transaction preference or other demands. Thus, it can acquire the best advertising combination and proceed with recommendation; meanwhile, it is helpful to create the essential business intelligence via further integration.
    According to the database, it researches the recommendation pattern of consumers behavior in TV shopping. TV shopping, customer contour and product operation, it sums up four business models in TV shopping: new marketing strategy, penetration strategy, low-cost strategy, quality product strategy, and the study anticipates that the related enterprise in TV shopping can offer new views about TV shopping market and then grow more vigorous development in TV shopping market.
    Appears in Collections:[管理科學學系暨研究所] 學位論文

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