臺灣博碩士論文加值系統

因應寬頻網路時代來臨與世界化趨勢，開放固網業務已成為我國電信自由化之重點項目，而客服中心扮演的角色即是公司與客戶之間的橋樑，除了一般性的提供客戶基本的服務外更有訊息管理、統計分析與行銷推廣等弁遄A因此客服中心須能夠迅速反應客戶的需求。本研究旨在研擬電信市場開放後之競爭環境下，ISP（Internet Service Provider）如何強化服務品質，洞燭機先，預先改善缺失；本研究所提出的ISP客服知識庫系統可以自客戶服務資料倉儲中將客戶詢問的問題分門別類，將較多客戶反應的問題加以統計分析，改善服務的品質，並將服務所產生記錄加以處理產生知識，將知識涵豪閹VR（Interactive Voice Response）及企業內外網站、維運單位的障礙分析管理，並提供管理階層做決策支援的資訊，藉以建立符合客戶服務之知識與分享傳承知識，期藉由客服知識庫系統改進傳統ISP客服中心的缺失，在有限的人力條件下，降低客戶服務成本、減少客戶等候服務時間、提昇客服專業知識水平，建構出整合式客戶服務平台。

In accordance to the approaching of broadband network era and globalization tendency, liberalization of telecommunication business in Taiwan has been a key project in telecommunication marketing. The Call Center acts as a bridge connecting enterprises and customers. It not only provides general basic services, but do provide information management, statistic analysis and telemarketing, etc. Therefore, customer center has to be able to rapidly response customer requirements. The purpose of this research is to interpret how ISPs(Internet Service Provider) could improve their service quality, forecast on customer needs and improve its efficiency in a highly competitive environment. This research proposed the ISP Customer Knowledge Base system to be allowed to classify questions from the Customer Service Data Warehouse. The system forms customers frequently responded questions to the statistical analysis in order to improvement service quality and also accumulate service records to produce necessary knowledge. This knowledge can apply to IVR (Interactive Voice Response), enterprise''s website and system maintaining department for problem solving. It also offers management level with decision support in order to construct qualified information for customer service and knowledge management. Furthermore, it is hoped that under limited human resource, an integrated customer care platform can reduce the customer care cost, decrease customer waiting time and increase the professional knowledge of customer care representatives.

第一章 緒論
第一節 研究背景與動機1
第二節 研究目的2
第三節 論文章節說明3
第二章 背景知識與相關文獻
第一節 客戶關係管理4
第二節 客服中心系統6
第三節 ISP客服中心工作流程10
第四節 資料倉儲12
第五節 資料探勘14
第六節 知識管理17
第三章 問題說明
第一節 ISP客服中心問題分析19
第二節 IVR 設計缺失22
第三節 客服人員服務品質25
第四章 解決方案－導入客服知識庫系統
第一節 系統整體解決方案30
第二節 知識庫系統架構分析設計31
第三節 客服知識庫系統實作42
第五章 系統導入與驗證服務品質改善
第一節 導入知識庫系統對客服人員服務的改善47
第二節 利用寬頻障礙資料超市規劃IVR 49
第三節 知識庫系統對客服中心的影響57
第六章 結論與建議
第一節 研究貢獻59
第二節 實驗限制60
第三節 未來研究方向60
參考文獻
中文部分62
英文部分63

中文部分
[1]于還莒，應用資料探勘技術於一對一行銷系統，國立台灣大學資訊工程學系碩士論文，2001。
[2]尹維銘、林盈達，告別網路塞車的三大技術，網路通訊，1998/8。
[3]元智大學商業智慧實驗室，http://gimy.no-ip.org/bilab/，2005。
[4]交通部電信總局， http://www.dgt.gov.tw，2005。
[5]沈桂鳳，應用灰關聯分析於資料倉儲中實體化視域之動態挑選，義守大學資訊管理學系碩士論文，2004。
[6]周文卿，資料倉儲－企業拓展商業智慧領域的基石，經營決策論壇，第24期，http://www.gss.com.tw/eis/，2001/3。
[7]周欣欣譯，Jerry Honeycutt 原著，知識管理策略與應用，華彩軟體公司，2000。
[8]洪明洲譯，James Brain Quinn, Jordan J. Baruch & Karen Anne Zien原著，知識管理與創新，商周出版社，2000/10/6。
[9]胡宗聖、陳如玲、盧美君，華南金融控股公司的客戶關係管理，華南金控市場行銷處，http://lottery.hncb.com.tw/monthly/mon016/01602.pdf ，專題論述，第16期，頁12-25, 2004。
[10]許史金譯，Arthur Andersen Business Consulting著，知識管理推動實務，商周出版，2001。
[11]陳怡伶，2005全球寬頻上網戶1億5千萬，http://www.find.org.tw/，2005/3/8。
[12]微軟顧問群編著，知識管理技術導覽、成幼案例與解決方案，台灣微軟公司發行，2001。
[13]經濟部， E?Commerce 網際網路商業應用計畫，http://www.ec.org.tw，2001。
[14]趙民德，關於Data Mining，中央研究院統計科學研究所， http://www.cdms.org.tw/B.htm，1999。
[15]劉志峰，ADSL障礙分析與維修探究，國立交通大學經營管理研究所碩士論文，2002。
[16]賴士奇、吳嘉哲、劉揚愷、楊子匯譯，深化顧客關係管理，遠擎管理顧問股份有限公司，2001。
[17]錢世明，資訊科技應用與中華電信系統，2005/3。
[18]羅志明，運用CRM來實現管理大師的夢，品質管制月刊，頁57-61， 2001。
英文部份
[1]A. Bhatia, Roadmap to Implementation for CRM, White Paper, Business Analyst (ERP) Infosys Technologies Ltd., http://www.crmassist.com, 1999.
[2]AltiGen Communications , http://www.altigen.com/, 2005.
[3]D. Warner, J. N. Richter, S.D. Durbin, and B. Banerjee, "Mining user session data to facilitate user interaction with a customer service knowledge base in RightNow Web," Proceeding of the seventh ACM SIGKKD International Conference on Knowledge discovery and data mining, pages 462-472, 2001.
[4]Data System Corp., http://www.databasesystemscorp.com, 2005.
[5]Federal Communications Commission, http://www.fcc.gov/voip/, 2005.
[6]G. Linoff and Michael J. A. Berry, Data Mining Techniques for Marketing, Sale and Customer Support, Wiley, 1997.
[7]G. Robert, Data Mining, Prentice Hall Inc., 1998.
[8]H. Bernett and M.L. Jaramillo, "Assessing Web-enabled call center technologies," IT Professional, Vol. 3, No. 3, pages 24-30, May-June 2001.
[9]J. Han and M. Kamber, Data Mining concepts and Techniques, Morgan Kaufmaun, 2001.
[10]J. Reisman, "Web site design: less is more," IT Professional, Vol. 1, No. 5, pages 63–64, September-October, 1999.
[11]M.S. Chen, J. Han, and S.Y. Philip "Data Mining: An Overview from a Database Perspective," IEEE Transaction on Knowledge and Data Engineering, Vol. 8, No. 6, pages 866-883, December, 1996.
[12]M.S. Chen, J.S. Park, and P.S. Yu, "Efficient Data Mining for Path Traversal Patterns," IEEE Transaction on Knowledge and Data Engineering, Vol. 10, No. 2, pages 209-221, April, 1998.
[13]P.A. Laplante, T. Costello, S. Pawan, S. Bindiganavile and M. Landon, "The who, what, why, where, and when of IT outsourcing," IT Professional, Vol. 6, No. 1, pages 19–23, January-February, 2004.
[14]R. Agrawal, and R. Srikant, "Mining Sequential Patterns," Proceedings of International Conference on Data Engineering, Taipei, Taiwan, pages 3-14, March, 1995.
[15]R. Agrawal, T. Imielinski, and A. Swami, "Mining Associations between Sets of Items in Massive Databases," Proceedings of the ACM SIGMOD International Conference on Management of Data, Washington D.C., pages 207-216, May, 1993.
[16]R.E. Wayland and P.M. Cole, Customer Connections: New Strategies for Growth, Harvard Business School Press, Boston, 1997.
[17]R.T. Ng and J. Han., "Efficient and Effective Clusting Methods for Spatial Data Mining," Proceeding of International Conference on Very Large Data Bases, pages 144-155, September, 1994.
[18]S. Chaudhuri and U. Dayal, "An Overview of Data Warehousing and OLAP Technology," SIGMOD Record, Vol. 26, No. 1, pages 65-74, 1997.
[19]SBC Communications Inc., http://www.sbc.com, 2005.
[20]W.C. Peng and M.S. Chen, "Developing data allocation schemes by incremental mining of user moving patterns in a mobile computing system," IEEE transactions on Knowledge and Data Engineering, Vol. 15, No. 1, pages 70-85, February, 2003.
[21]W.H. Inmon and C. Kelley, Rdb/VMS: Developing the Data Warehouse, QED Publishing Group, Boston, Massachussetts, 1993.
[22]W.Y. Lin, P.S. Wu, and Y.H. Tao, "A model of building data warehouse for customer relationship management," Journal of Information Management Concepts, Systems, and Applications, Vol. 6, No.1, pages 99-115, 2004.