1. NCCU Academic Hub
  2. 學術產出
  3. 商學院
  4. 學位論文
  5. Item

學術產出-學位論文

文章檢視/開啟

書目匯出

Google ScholarTM

政大圖書館

引文資訊

TAIR相關學術產出

題名 資料採礦技術之商業應用研究-以航空公司會員系統為例
作者 盧世銘
Lu,Shih-Ming
貢獻者 劉文卿
Liou,Wen-Chin
盧世銘
Lu,Shih-Ming
關鍵詞 資料探勘
資料採礦
叢集分析
會員系統
航空公司
Data Mining
FFP
Clustering
Frequent Flyer Program
Airlines
日期 2003
上傳時間 18-九月-2009 14:47:43 (UTC+8)
摘要 關係行銷或是一對一行銷是目前行銷領域上廣泛被討論的議
題，企業要如何透過有效的辨識、區隔、互動以及客制化來量身打造
顧客專屬的個人化產品與服務內容，並強化其重複消費動機及忠誠，
為目前各種產業爭相積極追求的目標，此外，由於微利時代風暴，各
產業無不希望透過顧客價值的辨識與經營，實現以更有效、更低的成
本的差異化行銷策略來創造高收益的企業經營目標，以航空產業如此
資本密集，高固定成本，低變動成本以及不對稱的供需平衡，誰掌握
低成本領導與差異化策略優勢，便能決戰存續於二十一世紀超競爭時
代之中。
由於資訊科技、網際網路以及資料探勘技術的臻於成熟， 充份
發揮了跨國、即時、深度滲透與互動的特性，使得關係行銷、一對一
行銷的實現變得更加有效而可行。本研究希望從顧客價值的認定、顧
客忠誠策略以及資料探勘技術的探討，來思考如何運用於航空公司會
員系統的顧客區隔，同時，希能透過航空公司產業通路架構、全球旅
行社訂位系統(CRS)的發展現狀、微妙的航空公司間策略聯盟以及不
同航空公司所提供的會員酬賓計劃內容的探討與陳述，初略地對個案
公司的所在環境進行策略性分析，以建議其所需採取投入關係行銷的
主要焦點客層。
緊接著， 利用資料探勘工具中的分群技術， 選定有效的指標變
數，針對某一區間的會員交易資料進行分群，藉由研究各群會員所蘊
含的特殊屬性，如營收貢獻、產品特性、通路喜好以及消費行為等等，
依據前述所定義的目標客層，以創造顧客價值為目標，精確建立目標
客戶群，並據以設計不同的行銷策略與產品組合，逐步深耕建立完整
會員關係行銷資料庫。
最後， 對於本研究所無法觸及的研究議題， 概略指出後續可能
的研究方向與建議。
Customer Relationship Management and data mining in this hyper-competitive
era have revealed a lot of interesting and innovative opportunities to enrich the
capability of company to realize and provide customer value. They touch the most
critical issue of the enterprise, “How can we create and sustain successful
advantage, and maximize profitability by leveraging new technologies ?＂In this
thesis, we will focus on the application of data mining in the FFP of the airlines
industry, and look over the differences among FFP members to discover the
implicative needs of FFP customers.
First of all, we start discussion on literature review in chapter two, which was
divided into three parts: customer loyalty strategy, customer value and data mining.
In this chapter, we put emphasis on the concepts and definitions of above topics, and
they would be helpful to us to select and decide key variables in the following data
mining practice.
Chapter three of this thesis is to introduce the structure and characteristics of
the airlines industry, the history of Computerized Reservation System(CRS), the
airlines strategy alliance and the FFP system, and to figure out the way to understand
the existing threats and opportunities.
Chapter four, which was abode by the steps of data mining process, defines
business issues and collects around one year`s FFP historical transaction data to
establish the target data and perform an actual data mining practice. In this real
practice, we use the demographic cluster function of IBM Intelligent Mining tool to
do member clustering. We select net revenue, first and business class spending rate,
reservation booking designator and customer activation as analytical variables to
perform FFP member clustering. Each variable has been well equipped with weight
and method to produce best cluster pattern.
Finally, according to the mining results we have explored and interpreted, we
provide our draft recommendations about marketing planning and mix activities from
the perspectives of FFP members clustering.
參考文獻 英文部分：
1. Dennis L. Duffy, “Customer Loyalty Strategies”, Journal of
Consumer Marketing, Vol. 15 1998, pp 435~448.
2. Nigel Magson, “Database Workshop : Determining and measuring
customer value”, The Journal of Database Marketing, Volume 6
Number 1 1998, pp24 ~ pp33..
3. H. Michael Chung; Paul Gray, ”Special section : Data Mining”,
Journal of Management Information Systems, Summer 1996, pp11 ~
pp 16.
4 ..
Rex S Toh;Peter Raven , ”Perishable asset revenue management :
Integrated internet marketing strategies…”, Transportation Journal,
Summer 2003, pp30 ~ pp40..
5. Goodman, John, “Leveraging The Customer Database To Your
Competitive Advance”, Direct Marketing, Dec. 1992, pp26 ~ pp27.
6. Department of Transportation, “Computer Reservation System(CRS)
Regulations : Final Rule”, January 2004.
7. Jyh-Yih Yang, Abby Liu, “Frequent Flyer Program : a case study of
China airlines’s marketing initiative – Dynasty Flyer Program”,
Tourism Management, November 2002.
8. Gary Mason, Nick Barker, “Buy now fly later : an investigation of
airlines frequent flyer programmes”, Tourism Management, 1996,
pp219 ~ pp223.
9. Berger, P. and Nasr N. I., “Customer Lifetime Value: Marketing
Models and Application,” Journal of Interactive Marketing, 12(1),
Winter 1998.
10. Veandko, James & Russo, Andrew(1999), “Data Mining and
Modeling As a Marketing Activity”, Direct Marketing, pp.52-55.
11. Mark Marple, Michael Zimmerman, “A customer retention
strategy”, Mortgage Banking, Aug 1999, pp45~49.
12. Keith J. Mason, “Marketing low-cost airlines services to business
travellers”, Journal of Air Transport Management, 2001, pp103 ~
pp109.
13. Barkin, Thomas I., Hertzell O. Staffan, and Stephanie J.
Young(1995),” Facing Low-cost Competitors: Lessons from US
Airlines”, The McKinsey Quarterly, Number 4, pp. 87-99.
14. Holbrook, K.B., “Customer Value-A Framework for Analysis and
Research”, Advance in Consumer Research, Vol.23, 1996,
pp.138-142.
15. Everitt, B.S., “Cluster Analysis,” John Wiiley & Sons,Inc.,1993.
16. Jain, A. K. and Dubes, R. C., “Algorithm for Clustering Data,”
Prentice Hall, 1988.
17. Kaufman, L. and Rousseeuw, P.J., “Finding Groups in Data: An
Introduction To Cluster Analysis,” John Wiley & Sons, Inc., New
York,NK, 1990.
18. Hinneburg and D. A. Keim, “An Efficient Approach to Clustering
in Multimedia Databases with Noise,” Proc. 4th Int. Conf. on
Knowledge Discovery and Data Mining, New York, AAAI Press,
1998.
19. Groth, Robert（ 1999） , Data Mining: Building Competitive
Advantage, NJ: Prentice Hall PTR.
20. IATA,”Prorate Manual : Passenger”,International Air Transport
Assosciation, December, 2003.
21. IBM, “IBM Intelligent Miner for Data”, IBM,Version 8.1, 2002.
中文部分：
1 ..
Leyland F. Pitt, T. Ewing&Pierre Berthon, 李田樹譯，「提高顧客
的終身價值」， 世界經理文摘， 2001 年2 月， 第34~52 頁。。
2 .. ARC 遠擎管理顧問公司，「顧客關係管理深度解析」，遠擎管理顧
問股份有限公司， 2001 年。。
3 .. M.J.Xavier, 李茂興, 沈孟宜譯，「策略性行銷」，弘智，2001 年。。
4 .. Philip Kotler, 方世榮譯，「行銷管理」， 東華書局， 2003 年。。
5. 丁惠民，「顧客智能的功能應用模式與價值體系」，ARC 遠擎管理
顧問公司， 2001 年11 月， 第12-21 頁。
6. Richard J Roiger, Michael W. Geatz，曾新穆, 李建億譯，「資料探
勘」， 東華書局， 2003 年。。
7. 林義堡，「運用資訊科技推動顧客關係管理」，電子化企業經理人
報告， 第35-42 頁， 2000 年。
8. 蔡名皇，「電子商務經營模式之研究」，國立台北大學企業管理學
系碩士論文， 2000 年。
9. 蕭正平，「顧客關係行銷的發展與實務」，國立臺灣大學商學研究
所碩士論文， 2000 年。
10.. 黃文昇，「在網際網路的旅遊業經營型態」，國立台灣大學商學研
究所碩士論文， 1998 年。
11.. 鄭昭敏，「航空公司哩程累計酬賓計劃與顧客忠誠度關係行銷之
研究」， 國立台灣大學商學研究所碩士論文， 1996 年。
網站部分：
1 .. www.. c hii na - a ii r ll ii ne s .. c om
2 .. www.. e va a ii r.. com
3 .. www.. c a tt ha y pa c ii f ii c .. c om
4 .. www.. s iin ga p or e a ii r.. com
5 .. www.. o n ewo r ll d .. c om
6 .. www.. s tt a r a ll ll ii a nc e .. com
7 .. www.. s k ytt e am.. c om
8 .. www.travelocity.com
9 .. www.priceline.com
1 0 .. www.orbitz.com
1 1 .. www.. ll a s ttmii n u tt e s .. com
描述 碩士
國立政治大學
經營管理碩士學程(EMBA)
90932603
92
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0090932603
資料類型 thesis
dc.contributor.advisor 劉文卿zh_TW
dc.contributor.advisor Liou,Wen-Chinen_US
dc.contributor.author (作者) 盧世銘zh_TW
dc.contributor.author (作者) Lu,Shih-Mingen_US
dc.creator (作者) 盧世銘zh_TW
dc.creator (作者) Lu,Shih-Mingen_US
dc.date (日期) 2003en_US
dc.date.accessioned 18-九月-2009 14:47:43 (UTC+8)-
dc.date.available 18-九月-2009 14:47:43 (UTC+8)-
dc.date.issued (上傳時間) 18-九月-2009 14:47:43 (UTC+8)-
dc.identifier (其他 識別碼) G0090932603en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/35346-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經營管理碩士學程(EMBA)zh_TW
dc.description (描述) 90932603zh_TW
dc.description (描述) 92zh_TW
dc.description.abstract (摘要) 關係行銷或是一對一行銷是目前行銷領域上廣泛被討論的議
題，企業要如何透過有效的辨識、區隔、互動以及客制化來量身打造
顧客專屬的個人化產品與服務內容，並強化其重複消費動機及忠誠，
為目前各種產業爭相積極追求的目標，此外，由於微利時代風暴，各
產業無不希望透過顧客價值的辨識與經營，實現以更有效、更低的成
本的差異化行銷策略來創造高收益的企業經營目標，以航空產業如此
資本密集，高固定成本，低變動成本以及不對稱的供需平衡，誰掌握
低成本領導與差異化策略優勢，便能決戰存續於二十一世紀超競爭時
代之中。
由於資訊科技、網際網路以及資料探勘技術的臻於成熟， 充份
發揮了跨國、即時、深度滲透與互動的特性，使得關係行銷、一對一
行銷的實現變得更加有效而可行。本研究希望從顧客價值的認定、顧
客忠誠策略以及資料探勘技術的探討，來思考如何運用於航空公司會
員系統的顧客區隔，同時，希能透過航空公司產業通路架構、全球旅
行社訂位系統(CRS)的發展現狀、微妙的航空公司間策略聯盟以及不
同航空公司所提供的會員酬賓計劃內容的探討與陳述，初略地對個案
公司的所在環境進行策略性分析，以建議其所需採取投入關係行銷的
主要焦點客層。
緊接著， 利用資料探勘工具中的分群技術， 選定有效的指標變
數，針對某一區間的會員交易資料進行分群，藉由研究各群會員所蘊
含的特殊屬性，如營收貢獻、產品特性、通路喜好以及消費行為等等，
依據前述所定義的目標客層，以創造顧客價值為目標，精確建立目標
客戶群，並據以設計不同的行銷策略與產品組合，逐步深耕建立完整
會員關係行銷資料庫。
最後， 對於本研究所無法觸及的研究議題， 概略指出後續可能
的研究方向與建議。		zh_TW
dc.description.abstract (摘要) Customer Relationship Management and data mining in this hyper-competitive
era have revealed a lot of interesting and innovative opportunities to enrich the
capability of company to realize and provide customer value. They touch the most
critical issue of the enterprise, “How can we create and sustain successful
advantage, and maximize profitability by leveraging new technologies ?＂In this
thesis, we will focus on the application of data mining in the FFP of the airlines
industry, and look over the differences among FFP members to discover the
implicative needs of FFP customers.
First of all, we start discussion on literature review in chapter two, which was
divided into three parts: customer loyalty strategy, customer value and data mining.
In this chapter, we put emphasis on the concepts and definitions of above topics, and
they would be helpful to us to select and decide key variables in the following data
mining practice.
Chapter three of this thesis is to introduce the structure and characteristics of
the airlines industry, the history of Computerized Reservation System(CRS), the
airlines strategy alliance and the FFP system, and to figure out the way to understand
the existing threats and opportunities.
Chapter four, which was abode by the steps of data mining process, defines
business issues and collects around one year`s FFP historical transaction data to
establish the target data and perform an actual data mining practice. In this real
practice, we use the demographic cluster function of IBM Intelligent Mining tool to
do member clustering. We select net revenue, first and business class spending rate,
reservation booking designator and customer activation as analytical variables to
perform FFP member clustering. Each variable has been well equipped with weight
and method to produce best cluster pattern.
Finally, according to the mining results we have explored and interpreted, we
provide our draft recommendations about marketing planning and mix activities from
the perspectives of FFP members clustering.		en_US
dc.description.tableofcontents 航空產業商業模式..............................................................................全球旅行社訂位系統之沿革與現況航空公司產業聯盟..............................................................................航空公司會員酬賓系統.....................................................................概念性思考架構...................................................................................、資料採礦實作範例...............................................................................................................................................................................................................................................................................資料採礦作業程序..............................................................................目錄第一章、緒論...........................................................................................................2 第一節研究背景與動機.....................................................................................2 第二節研究目的...................................................................................................3 第三節研究方向與範圍.....................................................................................3 第四節研究架構與程序.....................................................................................4 第二章、理論與文獻探討...................................................................................6 第一節顧客忠誠度策略文獻探討..................................................................6 第二節顧客價值文獻探討................................................................................9 第三節資料採礦(DATA MINING)相關技術研討........................................11 第三章、航空產業環境探討.............................................................................15 第一節15 第二節.............................................16 第三節18 第四節21 第五節26 第四章30 第一節研究架構30 第二節研究方法31 第三節35 第四節人口統計叢集分析..............................................................................39 第五節資料探勘結果綜合評析.....................................................................56 第五章、結論與建議...........................................................................................62 第一節研究結果與結論...................................................................................62 第二節研究限制.................................................................................................63 第三節後續研究之建議...................................................................................64 參考文獻.....................................................................................................................65 英文部分：..............................................................................................................65 中文部分：..............................................................................................................67 網站部分：..............................................................................................................68
圖次
圖1-1 ： 本論文研究架構.........................................................................................5
圖2-1 ： TRANSACTION VELOCITY AND SIZE MATRIX..................................................8
圖2-2 ： 資料策略階層圖.......................................................................................12
圖2-3 ： DATA MINING RESEARCH MODEL..............................................................13
圖3-1 ： 航空產業的通路結構與營運模式...........................................................16
圖3-2 ： 全球主要CRS 間夥伴關係圖................................................................18
圖3-3 ： 策略聯盟矩陣...........................................................................................21
圖3-4 ： 概念性思考架構.......................................................................................27
圖3-5 ： 顧客區隔行銷策略...................................................................................28
圖4-1 ： 研究架構圖...............................................................................................30
圖4-2 ： 資料探勘架構與流程...............................................................................31
圖4-3 ： 資料探勘處理程序模型...........................................................................35
圖4-4 ： 特定叢集分群結果(叢集7).....................................................................46
圖4-5 ： 特定叢集分群結果(叢集6).....................................................................47
圖4-6 ： 特定叢集分群結果(叢集14)...................................................................48
圖4-7 ： 特定叢集分群結果(叢集1).....................................................................49
圖4-8 ： 特定叢集分群結果(叢集15)...................................................................51
圖4-9 ： 特定叢集分群結果(叢集4).....................................................................52
圖4-10 ： 特定叢集分群結果(叢集13).................................................................53
圖4-11 ： 特定叢集分群結果(叢集2)...................................................................54
圖4-12 ： 特定叢集分群結果(叢集0)...................................................................56
圖4-13 ： 概念性分析架構.....................................................................................58
圖4-14 ： 概念性分析架構之各叢集分析圖.........................................................59
圖4-15 ： 決策行動分析圖.....................................................................................61
圖4-16 ： 策略性行動方案建議圖.........................................................................61
表次
表3-1 ： 全球各主要CRS 基本資料彙總表.........................................17
表3-2 ： 全球主要航空策略聯盟彙整表..................................................19
表3-3 ： 全球主要航空策略聯盟常客優惠服務彙整表..................................20
表3-4 ： 長榮航空FFP 計劃相關資料表...............................................22
表3-5 ： 中華航空FFP 計劃相關資料表........................................................23
表3-6 ： 新加坡航空FFP 計劃相關資料表..........................................24
表3-7 ： 國泰航空FFP 計劃相關資料表...............................................25
表3-8 ： 「顧客關係管理」系統架構.......................................................28
表4-1 ： 作用欄位變數定義.........................................................................32
表4-2 ： RBD 屬性分群表...........................................................................34
表4-3 ： 資料欄位說明表..............................................................................37
表4-4 ： 人口統計叢集化採礦功能一般參數設定表...........................39
表4-5 ： 作用欄位參數設定值.....................................................................39
表4-6 ： 「人口統計叢集化分群」結果彙整表....................................40
表4-7 ： 「各叢集人口統計叢集化分群」結果總體分析表..........................42
表4-8 ： 「各叢集作用欄位變數分析統計表」....................................43
表4-9 ： 「各叢集輔助欄位人口統計資料分析統計表」.................44
表4-10 ： 「各叢集輔助欄位行為屬性資料分析統計表」...............45
表4-11 ： 各叢集淨營收分組統計表.........................................................56
表4-12 ： 各叢集互動關係分組統計表....................................................56
表4-13 ： 各叢集網路訂位比例表....................................................................57
表4-14 ： 特定叢集特徵分析表..................................................................57		zh_TW
dc.format.extent 49266 bytes-
dc.format.extent 245265 bytes-
dc.format.extent 122938 bytes-
dc.format.extent 1094966 bytes-
dc.format.extent 254296 bytes-
dc.format.extent 325115 bytes-
dc.format.extent 558067 bytes-
dc.format.extent 1040535 bytes-
dc.format.extent 252192 bytes-
dc.format.extent 302710 bytes-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0090932603en_US
dc.subject (關鍵詞) 資料探勘zh_TW
dc.subject (關鍵詞) 資料採礦zh_TW
dc.subject (關鍵詞) 叢集分析zh_TW
dc.subject (關鍵詞) 會員系統zh_TW
dc.subject (關鍵詞) 航空公司zh_TW
dc.subject (關鍵詞) Data Miningen_US
dc.subject (關鍵詞) FFPen_US
dc.subject (關鍵詞) Clusteringen_US
dc.subject (關鍵詞) Frequent Flyer Programen_US
dc.subject (關鍵詞) Airlinesen_US
dc.title (題名) 資料採礦技術之商業應用研究-以航空公司會員系統為例zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 英文部分：zh_TW
dc.relation.reference (參考文獻) 1. Dennis L. Duffy, “Customer Loyalty Strategies”, Journal ofzh_TW
dc.relation.reference (參考文獻) Consumer Marketing, Vol. 15 1998, pp 435~448.zh_TW
dc.relation.reference (參考文獻) 2. Nigel Magson, “Database Workshop : Determining and measuringzh_TW
dc.relation.reference (參考文獻) customer value”, The Journal of Database Marketing, Volume 6zh_TW
dc.relation.reference (參考文獻) Number 1 1998, pp24 ~ pp33..zh_TW
dc.relation.reference (參考文獻) 3. H. Michael Chung; Paul Gray, ”Special section : Data Mining”,zh_TW
dc.relation.reference (參考文獻) Journal of Management Information Systems, Summer 1996, pp11 ~zh_TW
dc.relation.reference (參考文獻) pp 16.zh_TW
dc.relation.reference (參考文獻) 4 ..zh_TW
dc.relation.reference (參考文獻) Rex S Toh;Peter Raven , ”Perishable asset revenue management :zh_TW
dc.relation.reference (參考文獻) Integrated internet marketing strategies…”, Transportation Journal,zh_TW
dc.relation.reference (參考文獻) Summer 2003, pp30 ~ pp40..zh_TW
dc.relation.reference (參考文獻) 5. Goodman, John, “Leveraging The Customer Database To Yourzh_TW
dc.relation.reference (參考文獻) Competitive Advance”, Direct Marketing, Dec. 1992, pp26 ~ pp27.zh_TW
dc.relation.reference (參考文獻) 6. Department of Transportation, “Computer Reservation System(CRS)zh_TW
dc.relation.reference (參考文獻) Regulations : Final Rule”, January 2004.zh_TW
dc.relation.reference (參考文獻) 7. Jyh-Yih Yang, Abby Liu, “Frequent Flyer Program : a case study ofzh_TW
dc.relation.reference (參考文獻) China airlines’s marketing initiative – Dynasty Flyer Program”,zh_TW
dc.relation.reference (參考文獻) Tourism Management, November 2002.zh_TW
dc.relation.reference (參考文獻) 8. Gary Mason, Nick Barker, “Buy now fly later : an investigation ofzh_TW
dc.relation.reference (參考文獻) airlines frequent flyer programmes”, Tourism Management, 1996,zh_TW
dc.relation.reference (參考文獻) pp219 ~ pp223.zh_TW
dc.relation.reference (參考文獻) 9. Berger, P. and Nasr N. I., “Customer Lifetime Value: Marketingzh_TW
dc.relation.reference (參考文獻) Models and Application,” Journal of Interactive Marketing, 12(1),zh_TW
dc.relation.reference (參考文獻) Winter 1998.zh_TW
dc.relation.reference (參考文獻) 10. Veandko, James & Russo, Andrew(1999), “Data Mining andzh_TW
dc.relation.reference (參考文獻) Modeling As a Marketing Activity”, Direct Marketing, pp.52-55.zh_TW
dc.relation.reference (參考文獻) 11. Mark Marple, Michael Zimmerman, “A customer retentionzh_TW
dc.relation.reference (參考文獻) strategy”, Mortgage Banking, Aug 1999, pp45~49.zh_TW
dc.relation.reference (參考文獻) 12. Keith J. Mason, “Marketing low-cost airlines services to businesszh_TW
dc.relation.reference (參考文獻) travellers”, Journal of Air Transport Management, 2001, pp103 ~zh_TW
dc.relation.reference (參考文獻) pp109.zh_TW
dc.relation.reference (參考文獻) 13. Barkin, Thomas I., Hertzell O. Staffan, and Stephanie J.zh_TW
dc.relation.reference (參考文獻) Young(1995),” Facing Low-cost Competitors: Lessons from USzh_TW
dc.relation.reference (參考文獻) Airlines”, The McKinsey Quarterly, Number 4, pp. 87-99.zh_TW
dc.relation.reference (參考文獻) 14. Holbrook, K.B., “Customer Value-A Framework for Analysis andzh_TW
dc.relation.reference (參考文獻) Research”, Advance in Consumer Research, Vol.23, 1996,zh_TW
dc.relation.reference (參考文獻) pp.138-142.zh_TW
dc.relation.reference (參考文獻) 15. Everitt, B.S., “Cluster Analysis,” John Wiiley & Sons,Inc.,1993.zh_TW
dc.relation.reference (參考文獻) 16. Jain, A. K. and Dubes, R. C., “Algorithm for Clustering Data,”zh_TW
dc.relation.reference (參考文獻) Prentice Hall, 1988.zh_TW
dc.relation.reference (參考文獻) 17. Kaufman, L. and Rousseeuw, P.J., “Finding Groups in Data: Anzh_TW
dc.relation.reference (參考文獻) Introduction To Cluster Analysis,” John Wiley & Sons, Inc., Newzh_TW
dc.relation.reference (參考文獻) York,NK, 1990.zh_TW
dc.relation.reference (參考文獻) 18. Hinneburg and D. A. Keim, “An Efficient Approach to Clusteringzh_TW
dc.relation.reference (參考文獻) in Multimedia Databases with Noise,” Proc. 4th Int. Conf. onzh_TW
dc.relation.reference (參考文獻) Knowledge Discovery and Data Mining, New York, AAAI Press,zh_TW
dc.relation.reference (參考文獻) 1998.zh_TW
dc.relation.reference (參考文獻) 19. Groth, Robert（ 1999） , Data Mining: Building Competitivezh_TW
dc.relation.reference (參考文獻) Advantage, NJ: Prentice Hall PTR.zh_TW
dc.relation.reference (參考文獻) 20. IATA,”Prorate Manual : Passenger”,International Air Transportzh_TW
dc.relation.reference (參考文獻) Assosciation, December, 2003.zh_TW
dc.relation.reference (參考文獻) 21. IBM, “IBM Intelligent Miner for Data”, IBM,Version 8.1, 2002.zh_TW
dc.relation.reference (參考文獻) 中文部分：zh_TW
dc.relation.reference (參考文獻) 1 ..zh_TW
dc.relation.reference (參考文獻) Leyland F. Pitt, T. Ewing&Pierre Berthon, 李田樹譯，「提高顧客zh_TW
dc.relation.reference (參考文獻) 的終身價值」， 世界經理文摘， 2001 年2 月， 第34~52 頁。。zh_TW
dc.relation.reference (參考文獻) 2 .. ARC 遠擎管理顧問公司，「顧客關係管理深度解析」，遠擎管理顧zh_TW
dc.relation.reference (參考文獻) 問股份有限公司， 2001 年。。zh_TW
dc.relation.reference (參考文獻) 3 .. M.J.Xavier, 李茂興, 沈孟宜譯，「策略性行銷」，弘智，2001 年。。zh_TW
dc.relation.reference (參考文獻) 4 .. Philip Kotler, 方世榮譯，「行銷管理」， 東華書局， 2003 年。。zh_TW
dc.relation.reference (參考文獻) 5. 丁惠民，「顧客智能的功能應用模式與價值體系」，ARC 遠擎管理zh_TW
dc.relation.reference (參考文獻) 顧問公司， 2001 年11 月， 第12-21 頁。zh_TW
dc.relation.reference (參考文獻) 6. Richard J Roiger, Michael W. Geatz，曾新穆, 李建億譯，「資料探zh_TW
dc.relation.reference (參考文獻) 勘」， 東華書局， 2003 年。。zh_TW
dc.relation.reference (參考文獻) 7. 林義堡，「運用資訊科技推動顧客關係管理」，電子化企業經理人zh_TW
dc.relation.reference (參考文獻) 報告， 第35-42 頁， 2000 年。zh_TW
dc.relation.reference (參考文獻) 8. 蔡名皇，「電子商務經營模式之研究」，國立台北大學企業管理學zh_TW
dc.relation.reference (參考文獻) 系碩士論文， 2000 年。zh_TW
dc.relation.reference (參考文獻) 9. 蕭正平，「顧客關係行銷的發展與實務」，國立臺灣大學商學研究zh_TW
dc.relation.reference (參考文獻) 所碩士論文， 2000 年。zh_TW
dc.relation.reference (參考文獻) 10.. 黃文昇，「在網際網路的旅遊業經營型態」，國立台灣大學商學研zh_TW
dc.relation.reference (參考文獻) 究所碩士論文， 1998 年。zh_TW
dc.relation.reference (參考文獻) 11.. 鄭昭敏，「航空公司哩程累計酬賓計劃與顧客忠誠度關係行銷之zh_TW
dc.relation.reference (參考文獻) 研究」， 國立台灣大學商學研究所碩士論文， 1996 年。zh_TW
dc.relation.reference (參考文獻) 網站部分：zh_TW
dc.relation.reference (參考文獻) 1 .. www.. c hii na - a ii r ll ii ne s .. c omzh_TW
dc.relation.reference (參考文獻) 2 .. www.. e va a ii r.. comzh_TW
dc.relation.reference (參考文獻) 3 .. www.. c a tt ha y pa c ii f ii c .. c omzh_TW
dc.relation.reference (參考文獻) 4 .. www.. s iin ga p or e a ii r.. comzh_TW
dc.relation.reference (參考文獻) 5 .. www.. o n ewo r ll d .. c omzh_TW
dc.relation.reference (參考文獻) 6 .. www.. s tt a r a ll ll ii a nc e .. comzh_TW
dc.relation.reference (參考文獻) 7 .. www.. s k ytt e am.. c omzh_TW
dc.relation.reference (參考文獻) 8 .. www.travelocity.comzh_TW
dc.relation.reference (參考文獻) 9 .. www.priceline.comzh_TW
dc.relation.reference (參考文獻) 1 0 .. www.orbitz.comzh_TW
dc.relation.reference (參考文獻) 1 1 .. www.. ll a s ttmii n u tt e s .. comzh_TW