淡江大學機構典藏:Item 987654321/102854
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62822/95882 (66%)
Visitors : 4023901      Online Users : 967
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/102854


    Title: Mining marketing knowledge to explore social network sites and online purchase behaviors
    Authors: Liao, Shu-Hsien;Hsiao, Pei-Yuan;Li, Chien-Wen;Lin, Yun-Fei
    Contributors: 淡江大學管理科學學系
    Date: 2015-07-24
    Issue Date: 2015-05-07 17:48:48 (UTC+8)
    Publisher: Taylor & Francis Inc.
    Abstract: Social network sites (SNS), as web-based services, allow users to make open or semiopen profiles within the systems they are part of, to see lists of other people in the group, and to see the relationships of people within different groups. As the development of Internet applications has matured, developing and evaluating business models on social network sites has become a critical issue because these sites can be an innovative source for online marketing. Most studies in Taiwan on the behavior or marketing on SNS focus on either advertising or marketing, without picturing the overall scenario. Thus, this study investigates SNS as a research subject, and explores users’ online and purchase behaviors in the cybercommunity. For this, the study uses the Apriori algorithm as an association rules approach, and cluster analysis for data mining, to categorize four kinds of online user behavior and generate purchase behavior patterns and rules. The results suggest that online users’ SNS and purchase behavior knowledge are critical for the development of online business models.
    Relation: Applied Artificial Intelligence 29(7), pp.679-732
    DOI: 10.1080/08839514.2015.1051892
    Appears in Collections:[Department of Management Sciences] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML184View/Open
    Mining marketing knowledge to explore social network sites and online purchase behaviors.pdf2344KbAdobe PDF33View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.

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