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  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 國際企業學系
Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/28401
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???org.dspace.app.webui.jsptag.ItemTag.dcfield???ValueLanguage
dc.contributor.advisor任立中
dc.contributor.authorYa-Yun Tengen
dc.contributor.author鄧雅云zh_TW
dc.date.accessioned2021-06-13T00:07:15Z-
dc.date.available2008-07-26
dc.date.copyright2008-07-26
dc.date.issued2007
dc.date.submitted2007-07-28
dc.identifier.citationAnderson, Chris (2006), “The Long Tail: Why the Future of Business is Selling Less of More”
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Bhatnagar, Amit and Ghose, Sanjoy (2004), “An Analysis of Frequency and Duration of Search on the Internet,” The Journal of Business, 77, 2, pp.311
Cespedes, Frank V. and Smith H. Jeff (1993), “Database Marketing: New Rules for Policy and Practice,” Sloan Management Review; Summer 1993; 34, 4; pp.7
Colombo, Richard and Weina Jiang (1999), “A Stochastic RFM Model,” Journal of Interactive Marketing, 13, 3(Summer), 2-12
Hsu, Jui-Ping (2005), “The Website Browsing Behavior: a Concept of Concentration,” Master Thesis of National Tsing Hua University
Huang, Mei-Chen (2003), “The Analysis of Customer Value Migration Path in Database Marketing,” Master Thesis of National Taiwan University
Huang, Je-Sheng (2007), “Modeling Concentration Degree on the Most Valuable Customers for E-Commerce Sites,” Unpublished Doctorial Dissertation of National Taiwan University
Johnson, Eric J., Bellman, Steven and Lohse, Gerald L. (2003), “Cognitive Lock-In and the Power Law of Practice,” Journal of Marketing. Vol. 67, pp.62-75
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Lee, Chang-Wei (2001), “Customer Valuation in Database Marketing: An Empirical Study of 3C Distributor,” Master Thesis of National Taiwan University
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Moe, Wendy W. (2003), “Buying, Searching, or Browsing: Differentiating Between Online Shoppers Using In-Store Navigational Clickstream,” Journal of Consumer Psychology, 13 (1&2). pp.29-39
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Motoya-Weiss, Mitzi M., Glenn B. Voss and Dhruv Grewal (2003), “Determinants of Online Channel Use and Overall Satisfaction with a Relational, Multichannel Sevice Provider,” Journal of the Academy of Marketing Science, 31(4), pp.448-458
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Schmittlein, David C., Cooper, Lee G. and Morrison, Donald G. (1993), “Truth in Concentration in the Land of (80/20) Laws,” Marketing Science, Vol. 12, No. 2, pp.167-183
Schlooser, Ann E., White, Tiffany B. and Lloyd, Susan M. (2006), “Converting Web Site Visitors into Buyers: How Web Sites Investment Increase Consumer Trusting Beliefs and Online Purchase Intentions,” Journal of Marketing, 70(April), pp.133-148
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Shao, Kung-Hsin (2003), “The Customized New Product Recommendation System in Database Marketing,” Master Thesis of National Taiwan University
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Swaminathan, V., Lepkowska-White, E. and Rao, B. P. (1999), “Browsers or Buyers in Cyberspace? An Investigation of Factors Influencing Electronic Exchange,” Journal of Computer-Mediated Communications, 5(2), available at: www.ascusc.org/jcmc/vol5/issue2/swaminathan.htm.
Tsai, Hsin-Ching (2004), “資料庫行銷應用於非營利組織之顧客關係管理-以醫療服務為例,” Master Thesis of National Taiwan University
Tsai, Chih-An (2005), “Customer Valuation in Database Marketing—An Empirical Study of Fueling Behavior,” Master Thesis of National Taiwan University
Tseng, Chin-Yu (2003), “The Interdependency Analysis of Purchase Amount and Interpurchase Time in Database Marketing,” Master Thesis of National Taiwan University
Wu, Szu-Ying (2003), “Customer Value Analysis of Home Electrical Appliances,” Master Thesis of National Chiao Tung University
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/28401-
dc.description.abstract本篇論文主要是利用網路交易資料庫,以Modified Gini係數的概念(反羅倫茲曲線—Inverted Lorenz Curve),計算出購買次數(Purchasing frequency)、平均購買金額(Monetary value)、造訪網站次數(Visits)以及平均瀏覽網頁數(Page views)的顧客集中度,來分析顧客的網路購物及資訊搜尋行為。並以amazon.com於2004年的實際交易資料進行分析。
依照遞減排序的購買次數和平均購買金額分別計算出造訪次數及瀏覽頁數的Modified Gini係數(MG),將其和購買次數及購買金額的MG(MGF & MGM)相除,可得出顧客搜尋資訊的行為導向,和購買行為的診斷,進而可依顧客特性制定行銷策略或設計網站外觀、購物流程。
zh_TW
dc.description.abstractAbstract
Customer concentration issues are important for online companies. We’re interested in whether concentrations can provide a new perspective to e-commerce websites in order to understand the behaviors of customers and make suitable marketing strategies. Therefore, in this thesis, we use the Modified Gini Coefficient to calculate the customer concentrations of purchasing frequency, monetary value, visits and page views. Furthermore, we propose a diagnostic strategy of comparing MGs pair by pair to analyze the searching propensity of customers. In this way, we can understand the behaviors of customers according to different dimensions of customer concentrations. Websites can make marketing strategies based on the analytical results, which enable companies to segment and target profitable customers more precisely.
en
dc.description.provenanceMade available in DSpace on 2021-06-13T00:07:15Z (GMT). No. of bitstreams: 1
ntu-96-R94724056-1.pdf: 1287052 bytes, checksum: 4ab50bd05e1d8d1e49d440c924eecba3 (MD5)
Previous issue date: 2007
en
dc.description.tableofcontentsContent
中文摘要 …………………………………………………………………I
Abstract …………………………………………………………………II
Content…………………………………………………………………III
List of Tables ……………………………………………………………V
List of Figures …………………………………………………………VI
I. Introduction ………………………………………………………… P.1
1-1 Background …………………………………………………………………… P.1
1-2 Research Motivation ……………………………………………………………P.4
1-3 Research Purpose ………………………………………………………………P.4
1-4 Research Procedure ………………………………………………………………P.7
II. Literature Review……………………………………………………P.8
2-1 Customer Relationship Management (CRM)……………………………………P.8
2-1.1 CRM Perspectives and Definitions …………………………………………P.9
2-1.2 CRM Framework and Implementation………………………………………P.11
2-2 Database Marketing ……………………………………………………………P.13
2-2.1 Definitions of Database Marketing…………………………………………P.13
2-2.2 Functions and Benefits of Database Marketing ……………………………P.15
2-3 Customer Concentration Issues ………………………………………………P.17
2-3.1 80/20 Rule …………………………………………………………………P.18
2-3.2 The Long Tail ………………………………………………………………P.20
2-3.3 Concentration Evaluations Indices …………………………………………P.24
2-4 Customer’s Search Propensity and Behaviors Online …………………………P.34
III. Research Methodology……………………………………………P.39
3-1 The Inverted Lorenz Curve and Modified Gini Coefficient ……………………P.39
3-2 Customer Concentration on Purchase Frequency ………………………………P.42
3-2.1 The Benchmark Concentration of Purchasing Frequency (MGF) …………P.43
3.2.3 Concentration of Page Views on Purchasing Frequency (MGPF) ……………P.44
3-3 Customer Concentrations on Monetary Value …………………………………P.45
3-3.1 The Benchmark Concentration of Monetary Value (MGM) …………………P.45
3-2.2 Concentration of Visits on Monetary Value (MGVM) ………………………P.46
3-2.3 Concentration of Page Views on Monetary Value (MGPM) …………………P.46
3-4 Diagnosis of Concentration Degree ……………………………………………P.47
3-4.1 Concentration Degree Ratio on Purchasing Frequency by Comparing Visits P.48
3-4.2 Concentration Degree Ratio on Purchasing Frequency by Comparing Page Views ………………………………………………………………………………P.50
3-4.3 Concentration Degree Ratio on Monetary Value by Comparing Visits ……P.52
3-4.4 Concentration Degree Ratio on Monetary Value by Comparing Page Views P.54
3-4.5 Summary of Diagnostic Strategies from Concentration Degree Ratio ……P.56
IV. Data Analysis……………………………………………………P.57
4-1 Data Description ………………………………………………………………P.57
4-1.1 Source of Data ………………………………………………………………P.57
4-1.2 Descriptive Statistics ………………………………………………………P.58
4-2 Aggregate Customer Concentration ……………………………………………P.63
4-2.1 All Samples (30,317 Machine IDs) …………………………………………P.63
4-2.2 Buyers ………………………………………………………………………P.67
4-3 Customer Concentration on Purchasing Frequency ……………………………P.72
4-3.1 Total Samples ………………………………………………………………P.72
4-3.2 Buyers ………………………………………………………………………P.80
4-4 Customer Concentration on Monetary Value …………………………………P.87
4-4.1 Total Samples ………………………………………………………………P.87
4-4.2 Buyers ………………………………………………………………………P.94
V. Conclusions………………………………………………………P.101
5-1 Discussion ……………………………………………………………………P.101
5-2 Strategic Implications …………………………………………………………P.104
5-4 Further Researches ……………………………………………………………P.105
5-3 Research Limitations …………………………………………………………P.105
References……………………………………………………………P.108
Appendix……………………………………………………………P.112
dc.language.isoen
dc.subject資料庫行銷zh_TW
dc.subject顧客集中度zh_TW
dc.subject網路書店zh_TW
dc.subjectGINI係數zh_TW
dc.subject亞馬遜zh_TW
dc.subjectDatabase marketingen
dc.subjectamazon.comen
dc.subjectGINI Coefficienten
dc.subjectE-Commerceen
dc.subjectCustomer Concemtrationen
dc.title網路資料庫行銷之顧客集中度分析—以amazon.com為例zh_TW
dc.titleCustomer Concentration Analysis in Internet Database Marketing: An Empirical Study of amazon.comen
dc.typeThesis
dc.date.schoolyear95-2
dc.description.degree碩士
dc.contributor.oralexamcommittee周建亨,陳靜怡
dc.subject.keyword資料庫行銷,顧客集中度,網路書店,GINI係數,亞馬遜,zh_TW
dc.subject.keywordDatabase marketing,Customer Concemtration,E-Commerce,GINI Coefficient,amazon.com,en
dc.relation.page112
dc.rights.note有償授權
dc.date.accepted2007-07-30
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept國際企業學研究所zh_TW
Appears in Collections:國際企業學系

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