臺灣博碩士論文加值系統

隨著電子商務的發展，網路已被零售商視為一個嶄新的銷
售管道，線上型錄的設計因此成為網路零售的重要課題。
雖然多數的線上零售網站都提供產品蒐尋功能，但是對於
無特定目標而瀏覽網站的消費者卻沒有太大的幫助。設計
良好的線上型錄可以幫助瀏覽者進行網路購物。
我們提出兩階段的線上品類管理方法來設計線上型錄。第
一階段，以考慮顧客購買行為的品類管理方法來分析顧客
需求；更進一步以區隔出的產品群來形成起始的線上型
錄，放置在網站結構越上層的產品群表示越受到顧客的喜
好。第二階段則是利用顧客的網上瀏覽行為進行網站結構
的調整，隨著時間的改變會動態地改變產品的位置。
最後我們應用實際網路零售商的資料庫來驗證兩階段的線
上品類管理方法，結果顯示線上型錄確實會隨著顧客偏好
而改變，表現出他們不同的偏好。因此我們提出的方法不
但提供了研究者一個很好的研究方向，更對網路零售商提
出一個具體可行的線上型錄設計方法。

The Internet with growing electronic commerce is regarded as
a new selling channel for retailers. Online catalog organization has
become an important issue for e-tailing business development.
While most online retailing web sites provide assistance for
searchers who know exactly what they are seeking, little has been
done to aid browsers who take a more open-minded and
exploratory approach to navigation. Good design of online catalogs
is essential for browsers to shop over the web.
In this paper, we propose a two-phase approach to the design
of online catalogs. In the first phase, the idea of category
management that analyzes customers’ purchasing behaviors is
employed to construct a customer-centered online catalog.
Cluster-based market segmentation helps determine the web
hierarchy with clusters of products in higher levels indicating more
interesting to customers. The second phase is to dynamically adjust
the hierarchy when customers’ preference indicated by browsing
patterns is changed.'Relative access' that reflects the popularity of
web pages is used as a basis to make online catalog adaptation.
Finally, we apply this approach to real-world data collected at
Galleze.com by Blue Martini Software. It shows that our approach
can result in meaningful online catalog organization for customers
to navigate. Our study therefore provides a good direction for
researchers in designing online catalogs. Furthermore, e-tailing
practitioners can apply our approach easily and gain benefits from
such a design.

Table of Contents
I. Introduction………………………………………………………………………1
1.1 Overview………………………………………………………………………1
1.2 Organization of this Paper………………………………………………………3
II. Literature Review…………………………………………………………………4
2.1 Electronic Retail…………………………………………………………………4
2.2 Category Management…………………………………………………………6
2.3 Market Segmentation……………………………………………………………9
2.4 Cluster Analysis………………………………………………………………12
2.5 Adaptation of Web Organization………………………………………………18
III. Online Category Management………………………………………………20
3.1 Step One: Category Determination and Purchasing Data Collection…………21
3.2 Step two: Data Extraction with RFM Variables………………………………23
3.3 Step three: Cluster Analysis…………………………………………………25
3.4 Step four: Initial Online Catalog Construction………………………………27
3.5 Step five: Browsing Data Collection…………………………………………30
3.6 Step Six: Adaptive Online Catalog.………………………………………32
3.7 Issues of New Products…….…………………………………………………34
IV. Applications and Results………………………………………………………36
4.1 Data Sources……………………………………………………………………36
4.2 An Illustrated Example…………………………………………………………38
4.3 other Results…………………………………………………………………48
V. Conclusions……………………………………………………………………………55
5.1 Concluding Remarks…………………………………………………………55
5.2 Future Work……………………………………………………………………56
References…………………………………………………………………………57
Appendix A: Analytical Hierarchy Process……………………………………62
Appendix B: Prototype Online Catalog……………………………………………………66

References
Aldenderfer, M. S. and Blashfield, R. K. “Cluster Analysis: Quantitative Applications in the Social Sciences”. (Beverly Hills; Sage Publication, 1984)
Anderberg, M., “Cluster Analysis for Application”. (New York; Academic Press, 1973)
Bandyopadhyay, S. and Divakar, S. “Incorporating Balance of Power in Channel Decision Structure: Theory and Empirical Application”. Journal of Retailing and Consumer Services, Vol.6, 1999, pp. 79-89.
Berry, M. J. and Linoff, G., “Data Mining Techniques: For Marketing, Sales, and Customer Support”. (New York: Wiley Computer Publishing, 1997)
Blattberg, R., Fox, E., and Purk, M. “Category Management-Complete Set”. (Washington, DC: Food Marketing Institute, 1995)
Bradlow, E. T. and Rao, V. R. “A Hierarchical Bayes Model for Assortment Choice”. Journal of Marketing Research, Vol.37, 2000, pp. 259-268.
Brodley, C. and Kohavi, R., KDD Cup 2000 Data, School of Electronic and Computer Engineering, Purdue University, and Blue Martini Software, 2000. [Online] Available: http://www.ecn.purdue.edu/KDDCUP/
Broniarczyk, S. M., Hoyer, W. D., and McAlister, L. “Consumers’ Perceptions of the Assortment Offered in a Grocery Category: The Impact of Item Reduction”. Journal of Marketing Research, Vol.35, 1998, pp. 166-176.
Catledge, L. D. and Pitkow, J. E., “Characterizing Browsing Strategies in the World-Wide Web ”. Computer Networks and ISDN systems, Vol.27, 1995, pp. 1065-1073.
Ceri, S., Fraternali, P., and Bongio, A., “Web Modeling Language: A Modeling Language for designing Web sites”. Computer Networks, Vol. 33, 2000, pp. 137-157.
Dussart, C. “Category Management: Strengths, Limits and Developments”. Journal of European Management, Vol.16, 1998, pp. 50-62.
Eppen, G. D., Gould, F. J., Schmidt, C. P., Moore, J. H., and Weatherford, L. R. “Introductory Management Science: Decision Modeling with Spreadsheets”. 5th edition. (Upper Saddle River, NJ; Prentice Hall, Inc., 1998)
Evans, M. B. “Guidelines for Web Design”. (1998) [Online] Available: http://response.restoration.noaa.gov/webmastr/thissite.html
Everitt, S. B., “Cluster Analysis 3rd edition”. (London: E. Arnold; Halsted: New York; John Wiley & Sons Inc., 1993)
Fayyad, U., Piatetsky-Shapiro, G., and Smyth, P. “The KDD Process for Extracting Useful Knowledge from Volumes of Data”. Communication of ACM, Vol.39, 1996, pp. 27-34.
Frederiksen, L. “Catalogers Go.com: How to do it right online”. Direct Marketing, Vol.63, 2000, pp. 30-36.
Garofalakis, J.; Kappos; P., and Mourloukos, D. “Web site optimization using page popularity”. IEEE Internet Computing, Vol.3-4, 1999, pp. 22 –29.
Gerbert, P., Schneider, D., and Birch A. “The Age of E-tail”. (Mill Street, Oxford; Capstone Publishing Ltd., 1999)
Green, P. and Krieger, A. M. “Alternative approaches to cluster-based market segmentation”. Journal of the Market Research Society, Vol.37, 1995, pp. 221-238.
Ha, S. H. and Park, S. C. “Application of Data Mining Tools to Hotel Data Mart on the Internet for Database Marketing”. Expert Systems with Applications, Vol.15, 1998, pp. 1-31.
Huizingh, E. K.R.E. “The Content and Design of Web Sites: An Empirical Study”. Information & Management, Vol.37, 2000, pp. 123-134.
Jiang, J. J., Klein, G., and Pick, R. A. “A Marketing Category Management System: A Decision Support System Using Scanner Data”. Decision Support Systems, Vol.23, 1998, pp. 259-271.
Johnson, M., “From Understanding Customer behavior to Testing Category Strategies”. Journal of the Market Research Society, Vol. 41, No. 3, 1999. pp. 259-288.
Julander, C-R. “Basket Analysis: A New Way of Analyzing Scanner Data”. International Journal of Retail and Distribution Management, Vol. 20, No. 7, 1992, pp. 10-18.
Kahan, R. “Using Database Marketing Techniques to Enhance Your One-to-one Marketing Initiatives”. Journal of Consumer Marketing, Vol.15, 1998, pp. 491-493.
Kalakota, R. and Whinston, A. B. ”Electronic Commerce: A Manager’s Guide”. (Reading, Massachusetts; Addison-Wesley, 1997), pp. 217-250.
Kotler, P. “Marketing Management: Analysis, Planning, Implementation, and Control”. (Englewood Cliffs, N.J.: Prentice Hall, 1984), pp. 250-276
Lee, D. H., Kim, S. H., and Ahn, B. S. “A Conjoint Model for Internet Shopping Malls Using Customer’s Purchasing Data”. Expert Systems with Applications, Vol.19, 2000, pp. 59-66.
MacQueen, J. B., “Some Methods for Classification and Analysis of Multivariate Observation”. Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, 1967, pp. 281-297.
Markus, C. “A Practical yet Meaningful Approach to Customer Segmentation”. Journal of Consumer Marketing, Vol.15, 1998, pp. 494-504.
Milligan, G. W. and Cooper, M. C., “An examination of procedures for determining the number of clusters in a data set”. Psychometrika, Vol. 50, 1985, pp. 159-179.
Mojena, R. “Hierarchical Grouping Methods and Stopping Rule: An Evaluation”. Computer Journal, Vol. 20, 1977, pp. 359-363.
Neilson, “Category Management: Positioning Your Organization to Win”. (Lincolnwood, Chicago; NTC Business Books, 1992)
Newell, F. “The New Rules of Marketing: How to Use One-to-one relationship marketing to be the leader in your industry”. (New York; McGraw-Hill Companies, Inc., 1997)
Norris, M., West S., and Gaughan, K. “eBusiness Essentials: Technology and Network Requirements for the Electronic Marketplace”. (Baffins Lane, Chichester; John Wiley & Sons Ltd, 2000) pp. 39-44.
Perkowitz, M. and Etzioni, O. “Towards adaptive Web sites: Conceptual framework and case study”. Artificial Intelligence, Vol.118, 2000, pp. 245-275.
Piatetsky-Shapiro, G. and Frawley, W. J. “Knowledge Discovery in Database”. (Menlo Park, Calif.: AAAI Press; Cambridge, Mass.: MIT Press, 1991)
Punj, G. and Stewart, D. W. “Cluster Analysis in Marketing Research: Review and Suggestions for Application”. Journal of Marketing Research, Vol.20, 1983, pp. 134-148.
Radice, C. “Moving to Customer Category Management”. Progressive Grocer, Vol.76, 1997, pp. 69-72.
Russell, G. J. and Kamakura, W. “Modeling Multiple Category Brand Preference with Household Basket Data”. Journal of Retailing, Vol. 73, 1997, pp. 439-461.
Saarenvirta, G. “Data Mining to Improve Profitability”. CMA Management, Vol.72, 1998, pp. 8-12.
Saaty, T. L. “The Analytical Hierarchy Process: Planning, Priority, Setting, Resource Allocation ”. (New York; London: McGraw-Hill International Book Co., 1980)
Schaffer, C. M. and Green, P. E. “Cluster-based Market Segmentation: Some Further Comparisons of Alternative Approaches”. Journal of the Market Research Society, Vol.40, 1998, pp. 155-163.
Schmid, J. and Boyle, L. “Catalog creative: The RFMP way”. Target Marketing, Vol.21, 1999, pp. 38-41.
Schmid, J. and Alan, W. “Catalog database marketing done right”. Target Marketing, Vol.19, 1995, pp. 34-36.
Sedgewick, R. “Algorithms in C”. 3rd edition. (Reading, Massachusetts; Addison-Wesley Inc., 1998)
Sneath, P. “The Application of Computers to Taxonomy”. Journal of General Microbiology, Vol. 17, (1957), pp. 201-226.
Stockburger, D. W., “Multivariate Statistics: Concepts, Models and Applications”. Southwest Missouri State University, 1997. [Online]: http://www.psychstat.smsu.edu/multibook/mlt00.htm
Suh, E. H., Noh, K. C. and Suh, C. K. “Customer List Segmentation Using the Combined Response Model”. Expert Systems with Applications, Vol.17, 1999, pp. 89-97.
Tiernan, B. “E-tailing”. (North Wacker Drive; Chicago; Dearborn Financial Publishing Ltd., 1999) pp. 253-474.
Vesanto, J. and Alhoniemi, E. “Clustering of the Self-Organizing Map”. IEEE Transactions on Neural Networks, Vol.11, 2000, pp. 586-600.
Ward, J. H. Jr. “Hierarchical Grouping to Optimize an Objective Function”. Journal of American Statistical Association, Vol.69, 1963, pp. 236-244.
Yang, D., Sung, W. K., Yiu, S. M., Cheung, D., Ho, W. S., Lam, T. W., Lee, S. D. “ Construction of online catalog topologies using decision trees”. Advanced Issues of E-Commerce and Web-Based Information Systems, (2000), pp. 223 –230.
Zenor, M. J. “The Profit Benefits of Category Management”. Journal of Marketing Research, Vol.31, 1994, pp. 202-213.