Title page for etd-0726100-171545


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URN etd-0726100-171545
Author Tzyy-Ching Yang
Author's Email Address No Public.
Statistics This thesis had been viewed 5350 times. Download 3255 times.
Department Information Management
Year 1999
Semester 2
Degree Ph.D.
Type of Document
Language zh-TW.Big5 Chinese
Title Applying Shopping Cart Data to Web Marketing Communication Decisions
Date of Defense 2000-06-24
Page Count 136
Keyword
  • Online Shopping Data
  • Shopping Cart Data
  • Web Marketing
  • Electronic Commerce
  • Marketing Communication
  • Abstract  A very distinguished point of online marketing is that it can
    collect data about the consumers* shopping processes rather than
    the shopping results only. That is, it cannot only collect order
    data but also the browsing and shopping cart data. So far, the
    browsing records have been used to analyze the Web server traffic. 
    However, regarding the analysis of shopping cart data, it has not
    been found in any marketing research yet. The purpose of this
    study is trying to verify the value of shopping cart data by
    examining whether it can improve the performance of the marketing
    communication decisions.
     According to Source-Message-Media-Receiver (SMMR) communication
    model, there are three important Web marketing communication decisions. 
    These decisions are who are the target customers, what message should
    be communicated, and how to communicate. For each above marketing
    communication decision, in order to check whether the data from
    shopping cart can improve its performance, this research proposed
    an algorithm that integrates the shopping cart data into each decision
    process. Three hypotheses have been proposed in terms of the value of
    each new proposed algorithm. Three experiments have been implemented
    to test these hypotheses.
     The results reveal that the proposed algorithms can improve the
    performance of the marketing communications decisions. However, it is
    only a starting point to integrate the shopping cart data into the
    marketing research. As the online shopping becomes more popular, it
    is worthwhile to put more efforts to understand the details about the
    value of the online shopping cart data.
    Advisory Committee
  • Feng-Yang Kuo - chair
  • Ting-Ping Liang - co-chair
  • Heng-Li Yang - co-chair
  • Hong-Gee Chen - co-chair
  • Chih-Ping Wei - co-chair
  • Hsiangchu Lai - advisor
  • Files
  • 全.pdf
  • indicate in-campus access immediately and off_campus access in a year
    Date of Submission 2000-07-26

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