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題名:使用顧客知識於行銷之決策支援系統
作者:洪健文
作者(外文):Chien Wen
校院名稱:國立成功大學
系所名稱:工業與資訊管理學系碩博士班
指導教授:林清河
學位類別:博士
出版日期:2008
主題關鍵詞:決策支援系統個人化促銷類神經網路電子商務資料探勘Personalized PromotionArtificial Neural NetworksDecision Support SystemData MiningElectronic Commerce
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隨著網際網路及電子商務的發展,企業得以與顧客進行一對一接觸並提供電子化的服務。然而,網際網路的便利性卻使得競爭對手遠多於傳統的行銷市場,顧客也因選擇性增多而忠誠度降低,因此,如何吸引及留住網際網路上的顧客對企業而言不啻為一大挑戰。
提供個人化顧客服務以符合顧客需求是一種解決問題的方式。,本文提出一個決策支援系統以幫助企業,使其能於網際網路中提供個人化顧客行銷,以符合顧客個人化的消費需求,藉此達到刺激顧客購買意願,以增加銷售量。本文提出的決策支援系統架構包含三個構成要素:(1) 行銷策略; (2) 促銷類型模組; (3) 個人化促銷產品。
制定行銷策略,並以銷售促銷策略及定價策略為理論基礎;其次,先利用類神經網路中的自適應共振理論(Adaptive Resonance Theory Network, ART)進行市場區隔後,再運用資料探勘技術中的關聯規則探勘(Association Rule Mining)及序列型樣探勘(Sequential Pattern Mining)有效率地分析顧客(包括所有顧客、族群顧客以及個別顧客)消費行為,找出候選促銷產品;最後,利用評估指標對候選促銷產品進行評估以產生最終的促銷產品。另一方面,除了個人化顧客的促銷產品外,本文亦加入差別定價之概念,個人促銷產品的促銷價將隨個別顧客不同的特徵而調整。盼能藉由以上主動的個人化促銷及差別定價,提高顧客忠誠度,增加企業利潤。
With the development of the Internet and Electronic Commerce (EC), businesses have overcome the capable of serving customers electronically. However, the convenient of Internet makes the competitors in Internet more than in traditional market. The customers’ loyalty is so low that it is a difficult problem for a business to attract and retain customers.
One solving approach is to provide the responsive personalized service to satisfy the customer demand. Hence, we propose a decision support system to assist businesses. The business can provide personalized promotion in Internet; that is to say, different customers will be promoted different products for conforming to individual customer’s demand. Our system consists of three components: (1) marketing strategies, (2) promotion patterns model, and (3) personalized promotion products.
We first set up the marketing strategies, and take the sales promotion strategies and pricing strategies among marketing strategies as a base theory. Secondly, we apply data mining techniques to analyze the customers’ behaviors efficiently for discovering candidate promotion products. In the end, we evaluate the candidate promotion products by using the evaluation indicators among personalized promotion products. The system will generate final promotion products which be expected to enhance customer satisfaction and loyalty.
中文部分

孫衙聰(1997)「國內電子型錄現況調查與企業建構電子型錄架構模式之探討」國立台灣工業技術學院,碩士論文,民國八六年六月。

柯特勒(Philip Kotler) 原著,張在山譯(1998),非營利事業之策略性行銷,國立編譯館。

安迅資訊公司(2000)。「整合企業經營策略與顧問關係管理」。電子化企業。民89年1月。頁20-25。

劉京偉(2000)。知識管理的第一本書。台北:商周。譯自 Arthur Andersen Business Consulting。

范惟翔(2001)。「顧客知識管理,市場導向與行銷績效之關係研究」。中正大學企業管理 研究所博士論文。民國90年6月。

黃士盈、賴士奇(2001)。「強化金融服務業的顧客關係管理贏取顧客的終身價值,顧客關係管理深度解析」。ARC遠擎管理顧問公司編。

何雍慶(2003),實用行銷管理,華泰。

蕭富峰(2003),如何進行促銷,遠流出版。

徐振軒(2003),「網際網路上促銷模式之研究」,碩士論文,國立中山大學資訊管理研究所。

魏啟林(2004),策略行銷,時報文化。

周文賢(2005),行銷管理 : 市場分析與策略規劃,智勝文化。

麥可.裴瑞(Michael J. A. Berry) ,戈登. 林諾夫(Gordon Linoff)原著;彭文正譯(2005),資料採礦: 顧客關係管理暨電子行銷之應用,數博網出版,維科總經銷。

葉日武(2005),行銷學 : 理倫與實務,前程企業管理公司。

英文部分

Aaker, D. A. (1996), “Measuring Brand Equity Across Products and Markets, ” California Management Review, Vol. 38, No. 3, pp.103-120.

Adrian, B., Rangar, S. and Lutz K. “Customer Knowledge Management – Improving Performance of Customer Relationship Management with Knowledge Managemet,” Proceedings of the 37th Hawaii International Conference on System Sciences, 2004.

Agrawal, R., and Srikant, R. (1994), “Fast Algorithms for MiningAssociation Rules,”Proc. of the 20th International Conference on Very Large Databases, Santiago, Chile.

Agrawal, R., Srikant, and R. (1995), “Mining Sequential Pattern,” Proc. of the 11th International Conference on Data Engineering, Taiwan, pp. 3-14.

Allen,C., Kania, D., and Yaeckel, B.(2005), Internet World Guide to One- To-One Web Marketing, John Wiley & Sons.

American Marketing Association (1963), Marketing Definition: Blossary of Marketing Term (Chicago, IL: American Marketing Association).

Anand S.S., Patrick A.R., Hunges J.G, Bell D.A. ( 1998) , "A Data Mining Methodology for Cross-Sales ", Knowledge-Based System 10, pp. 449-461.

Andrew, H., Arvind, M. and Albert, H. “Knowledge Management: An Organizational Capabilities Perspective,” Journal of Management Information System, (18:1),2001, pp.185-214.

Arie Segev, Judith Gebauer, and Carrie Beam ( 1998 ) , "Procurement in the Internet Age - Current Practices and Emerging Trends", The Fisher Center for Information Technology & Management Hass School of Business University of California, Berkeley.

Balabanovic, M., and Shoham, Y. (2005), “Fab: Content-Based, Collaborative Recommendation,” Communications of ACM, Vol. 40, No. 3,pp. 66-72.


Beem, E. R., and Shaffer, H. J. (1981), “Triggers to Customer Action- Some Elements in a Theory of Promotional Inducement,” Marketing Science Institute, pp.81-106.

Benjan P.-C. Yen, Robin C.W.Kong. ( 2002 ) , " Personalization of Information Access for Electronic Catalogs on The Web", Electronic Commerce and Applications 1, pp. 20-40

Berry, M., and Linoff, G. S. (2007), Data mining techniques: for marketing, sales, and customer support, John Wiley & Sons.

Berson, A., Smith,S.J., and Thearling, K.(2005), Building Data Mining Applications for CRM, McGraw-Hill, USA.

Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., and Zanasi, A. (2003), Discovering Data Mining from Concept to Implementation, Prentice Hall PTR.

Campbell, L., and Diamond, W. D. (2001), “Framing and Sales Promotions: The CHARACTERISTICS OF a Good Deal,” Journal of Consumer Marketing, Vol. 7, No. 4, pp. 25-31.

Carprnter, G.A., and Grossberg, S. (1988), “The ART of Adaptive Pattern Recognition by Self-Organizing Neural Network,” IEEE Computer, Vol. 21, No. 3, pp. 77-88.

Carrie Bean, Arie Segev, and J. George Shanthikumar (1996) "Electronic Negotiation through Internet-based Auctions", The Fisher Center for Information Technology & Management Hass School of Business University of California, Berkeley.

Cho, Y. H., Kim, J. K., and Kim, S. H. (2002),“A Personalized Recommender System Based on Web Usage Mining and Decision Tree Induction,”Expert Systems with Applications, Vol. 23, pp. 329-342.

Davenport, T.H. and Prusak, L. Working Knowledge : How Organizations Manage What They Know, Boston : Harvard Business School Press, 1998.

Davis, K.R. (1981), Marketing Management, John Wiley & Sons.

Dean, R. (2003), Personalizing your web site, available at http://www. builder.com/business/personal.

Fayyad, U. (2005), “Data Mining and Knowledge Discovery in Databases: Implications for Scientific Databases,” Proc. of the 9th International Conference on Scientific and Statistical Database Management, pp. 2–11.

Gibbert, M., Leibold, M.and Gilbert P. “Five Styles of Customer Knowledge Management,and How Smart Companies Use Them To Create Value,” European Management Journal(20:5), 2002, pp.459-469

Goldberg, D., Nichols, D., Oki, B. M. and Terry, D. (2002), “Using collaborative filtering to weave an information tapestry,” Communications of the ACM, Vol. 35, No.12, pp.61-70.

Han, J. and Kamber, M. (2007), Data Mining: Concepts and Techniques, Morgan Kanfamann Publishers.

Han, J., Pei, J., Mortazavi-Asl, B., Chen, Q., Dayal, U., and Hsu, M.C. (2000), “ FreeSpan: Frequent Pattern-Projected Sequential Pattern Mining,” Proc. of the International Conference on Knowledge Discovery and Data Mining, Boston, MA.

Henning, G.., Malte, G.. and Lutz, K. “Towards Customer Knowledge Management –Integrating Customer Relationship Management and Knowledge Management concepts, ” The Second International Conference on Electronic Business , 2002.

Hoffman, D., and Novak, T.P. (2007), “A New Marketing Paradigm for 102 Electronic Commerce.” The Information Society, Vol. 13, pp. 43-54.

Iyer, G. R, Miyazaki, A. D., Grewal, D., and Giordano, M. (2002),“Linking Web-based Segmentation to Pricing Tactics” Journal of Product & Brand Management, Vol. 11, No. 5, pp.288 – 302.

Kaufman, L., and Rousseeuw, P.J. (2000), Finding Groups in Data: an Introduction to Cluster Analysis, John Wiley & Sons

Keller A.N.,Genesereth M.R.( 1997), "Using Information to Create a Housewares virtual Catalog" , International Journal of Electronic Commerce and Business Media 7 (4) , pp. 41-44.

Konstan, J. A., Miller, B. N., Maltz, D., Herlocker, J. L., Gordon, L. R. and Riedl, J. (1997), “GroupLens: applying collaborative filtering to usenet news,” Communications of the ACM, Vol.40, No.3, pp.77-87.

Krulwich, B. and Burkey, C. (2006), “Learning user information interests through extraction of semantically significant phrases,” Procs. of the AAAI Spring Symposium on Machine Learning in Information Access.

Kung, M., Monroe, K. B., and Cox, J. L. (2002), “Pricing on the Internet,” Journal of Product & Brand Management, Vol. 11, No. 5, pp. 274 – 288.

Lang, K. (2006), “Newsweeder: Learning to filter netnews,” Proc. of 12thInternational Conference on Machine Learning, pp. 331-339.

Lawrence, R.D. (2006), Almasi, G.S., Kotlyear, V., Viveros, M.S., and Duri, S.S., “Personalization of Supermarket Product Recommendations,” Data Mining and Knowledge Discovery, pp.11-32.

Leonard-Barton, D. Wellspring of Knowledge : Building and Sustaining the Sources of innovation, Boston : Harvard Business School Press,1995.

Nagle, Thomas T. and Holden, Reed K. (2005), The strategy and tactics of pricing: a guide to profitable decision making, Prentice Hall.

Nash, D., and A.Stema-Karwat, " An application of DEA to measure branch cross selling efficiency " , Computer Operations Resaerch pp. 385-392.

Nonaka, I. and Takechi, H. The knowledge-Creation Company, New York : Oxford University, 1995.

Park, J.S., Chen, M.S., and Yu, P.S. (2005), “An Effective Hash Based Algorithm for Mining Association Rules,” Proc. of the ACM SIGMOD International Conference on Management of Data, pp. 175-186

Pei, J., Han, J., Mortazavi-Asl, B., Pinto, H., Chen, Q., Dayal, U. and Hsu, M. (2007), “PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth,”Proc. of the International Conference of Data Engineering, pp. 215-224.


Peppers, D., Rogers, M. and Dorf, B. Is Your Company Ready For One-to-one Marketing ?, Harvard Business Review, 1999.

Philip, K. (2000), Principles of marketing, Prentice Hall.

Reinschmidt, J., Gottschalk, H., Kim, H., and Zwietering, D. (2006), “Intelligent Miner for Data: Enhance Your Business Intelligence,” IBMInternational Technical Support Organization, USA.

Rollins, M. and Halinen, A. “Customer Knowledge Management Competence: Towards a Theoretical Framework,” Proceedings of the 38th Hawaii International Conference on System Sciences, 2005.

Rucker, J. and Polenco, M. J. (2007), “Siteseer: personalized navigation for the web,” Communications of the ACM, Nol.40, No.3, pp.73-76.

Senge, P. Sharing Knowledge, Executive Excellence,1997

Shan, L. P. and Jae-Nam L. “Using E-CRM for a unified view of the customer ,” CACM(64:4), 2003, pp.95-99.

Shardanand, U. and Maes, P.(2005), “Social Information Filtering :Algorithm for Automating “Word of Mouth”,” Proc. of International Conference on Human Factors in Computing Systems, pp.210-217.

Shaw, M.J.,Subramaniam C., Tan G.W. and Welge M.E. “Knowledge management and data mining for marketing,” Decision Support Systems(31:1), 2001, pp. 127-137.

Smallwood, J.E. (2002), “The Product Life Cycle: A Key to Strategic Market Planning,” MSU Business Topics, winter, pp. 29-35.

Smith, K.G., Mitchell, T.R. and Summer, C.E. (1985), “Top Level Management Priorities in Different Stages of the Organizational Life Cycle,” Academy of Management Journal, Vol. 28, No. 4, pp. 799-820.

Smith, W. (1956), “Product Differentiation and Market Segmentation as Alternative Marketing Strategies,”Journal of Marketing, Vol. 21, pp. 3-8.

Spek, R.V.D. and Spijkervet, A. A Knowledge Management: Dealing Intelligently with Knowledge, Knowledge Management Network, 1997.

Stanoevska-Slabeva K., Schmid B. (2000) , " Internet Electronic Product Catalogs: an Approach Beyond Simple Keyword and Multimedia" , Computer Networks 32pp. 701-715.

Swift, R.S. Accelerating Customer Relationships Using CRM and Relationship Technologies, Prentice-Hall, 2001.

Surprenant, C.F. and Solomon, M.R. (1987),“Predictability and Personalization in the Service Encounter,”Journal of Marketing, vol. 51, pp. 86-89.

Terveen, L., Hill, W., Armento, B., McDonald D. and Creter, J. (2007) “PHOAKS: a system for sharing recommendations,” Communications of the ACM ,Vol.40, No.3, pp.59-62.

Triantaphyllou, E. (2005), Multi-Criteria Decision Making Methods: A Comparative Study, Kluwer Academic Publishers.

Yu, P.S. (2003), “Data Mining and Personalization Technologies,” Proc. of the 6th International Conference on Database Systems for Advanced Applications, pp. 6-13.

Zadeh, L.A. (1965), “Fuzzy Sets,” Information and Control, Vol. 8, No. 3, pp. 338-353.
 
 
 
 
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