English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 51275/86342 (59%)
造訪人次 : 8147054      線上人數 : 53
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/87535

    題名: 資料採礦於便利商店推薦機制之研究
    其他題名: The study of data mining on recommendation mechanism for the convenience stores
    作者: 許哲維;Hsu, Che-Wei
    貢獻者: 淡江大學管理科學學系碩士班
    廖述賢;Liao, Shu-Hsien
    關鍵詞: 推薦機制;促銷;代言人;組合產品;商業智慧;資料採礦;recommendation mechnisam;Promotion;endorers;Bundling;Business Intelligence;data mining
    日期: 2012
    上傳時間: 2013-04-13 11:22:44 (UTC+8)
    摘要: 隨著國民所得提高及經濟快速成長,工作型態的轉變讓忙碌上班族越來越多,導致「三餐老是在外」的外食人口數量大增。對於外食族來說,利用便利超商填飽肚子已是生活中不可或缺的一部份。目前外食族商機日益擴大,鮮食冷藏、非酒精飲料以及麵包產品推陳出新的速度比一般產品要快上得多,而由於產品同質性極高,光是選購就必須花上一些時間。因此,業者要如何精準地了推薦適當的的產品組合給目標客群、如何運用合適的產品廣告代言人來吸引目標客群、或是利用品牌延伸來提升競爭優勢,便是目前值得研究的議題。
    Rapid economic growth with increasing national income causes more and more busy workers to choose to be out-eaters. Going to convenience stores (CVS) for food is indispensable to out-eaters’ lives. As the out-eaters’ market expands, the speed of launching new products, such as fresh frozen, non-alcoholic beverages and bread, is faster than others.
    However, due to awide variety of products, it takes much time for consumers to choose products what they want to have for lunch or dinner. Thus, it is an essential issue for CVS owners to know how to accurately recommend them appropriate products and to choose right endorsers for brand or product to attract target consumers as well as do brand extension to enhance the competitive advantage? Therefore, cusomization or one-to-one marketing plays an important role in stisfing consumer’s needs.
    Data mining is a powerful new technology with great potential to help companies focus on the most important information in the data they have collected about the behavior of their customers and potential customers. In this study, we divide consumers into three groups by their consumer profile and then discover each group has different product mixes preference, products endorses as well as new products which are suitbabl to launch based on data mining and association rules.
    顯示於類別:[管理科學學系暨研究所] 學位論文


    檔案 大小格式瀏覽次數



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋