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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/64935

    Title: Mining customer knowledge for direct selling and marketing
    Authors: Liao, Shu-Hsien;Chen, Yin-Ju;Hsieh, Hsin-Hua
    Contributors: 淡江大學經營決策學系
    Keywords: Direct marketing;Direct selling;Data mining;Association rules;Cluster analysis;Database marketing
    Date: 2011-05
    Issue Date: 2011-10-20 16:11:48 (UTC+8)
    Publisher: Kidlington: Pergamon
    Abstract: Direct marketing is an effective marketing method. To compare with the expensive media advertisements, direct marketing could provide exclusive products and services for specific consumers. Also, this method could reduce transaction costs. The communication channel is diverse because virtual shop stores and online shopping are springing up. Therefore, this study proposes the application of Internet marketing to the direct selling industry and the cosmetics market in Taiwan. This study implements association rules and cluster analysis as approaches for data mining. By doing so, we analyze consumer adumbration, lifestyle habits and purchasing behavior. Finally, this study finds some models including cluster consumer purchase preference and demand in order to generate different marketing alternatives for decisions. These research results can help attract more direct marketing firms to open up broader markets and earn higher profits for direct selling.
    Relation: Expert Systems with Applications 38(5), pp.6059–6069
    DOI: 10.1016/j.eswa.2010.11.007
    Appears in Collections:[Department of Management Sciences] Journal Article

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