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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/33046

    Title: The research of data mining techniques applied to one to one marketing of information appliances
    Other Titles: 資料探勘應用於資訊家電之一對一行銷之研究
    Authors: 蕭世忠;Hsiao, Shih-chung
    Contributors: 淡江大學管理科學研究所碩士班
    廖述賢;Liao, Shu-hsien
    Keywords: 資料探勘;一對一行銷;資訊家電;關聯性資料庫;Apriori演算法;Two-step集群分析;CART決策樹;data mining;one to one marketing;information appliances;relational database;Apriori algorithmn;Two-step clustering analysis;Classification and Regression Trees
    Date: 2007
    Issue Date: 2010-01-11 03:11:05 (UTC+8)
    Abstract: 隨著近年來的資訊匯流發展趨勢和資訊家電的蓬勃發展,加上持續的網路科技爆炸,3C產業(電腦、通訊和電子產品)的產品已由以往的昂貴奢侈品變成了21世紀大眾日常生活的平價必需品。這項資訊革命伴隨著現今發熱的全球化透明市場效應不但大幅的提昇了3C產業內的競爭困難,且由於科技產品、新購買和付費方法、激烈的競爭和更多的行銷管道降低了廣告和大眾行銷法手的有效性,因此如今人們需要的是個人行銷,又稱為一對一行銷。
    As information technologies converges and information devices become more powerful, along with the continuing network technology’s boom, the 3C (Computer, Communication, and Consumer electronics) industry’s products have became from a luxurious product to an essential product of daily needs for most people in the 21st century. This digital revolution accompanied with today’s increasingly globalized market have not only raised the competition difficulty within the 3C industry, but also lowered the effectiveness of the traditional mass marketing due to changing households, complex technology-based products, new ways to shop and pay, intense competition, additional channels, and declining advertising effectiveness. Personal marketing is what the customers want nowadays.
    Accordingly, practitioners who want to reach a win-win strategy under such conditions must somehow distinguish their products and services from those of their competitors, and increase customers’ satisfaction by fulfilling their needs and preferences, thus obtaining higher loyalties and profits.
    The purpose of this research was to assist marketers of 3C industry at improving their competitiveness by reaching such win-win strategy in today’s highly competitive markets through effective utilization of customers’ data. This research has built a relational database and utilized various data mining techniques to help analyze, understand, and visualize the huge amounts of stored data about customers. Valuable information, knowledge patterns and rules have been extracted, analyzed, and interpreted from customers’ database by using Apriori algorithmn, Two-step clustering analysis, and CART (Classification and Regression Trees) as needed.
    Consequently, reports, conclusions, and map of marketing have been drawn at the end suggesting to the marketers the need to obtain customer knowledge and feedback from the demand side and use them as a knowledge resource for establishing suitable one to one marketing offers, mix of products, and future product developments.
    Appears in Collections:[Department of Management Sciences] Thesis

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