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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/54566
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/54566


    Title: 建立資料倉儲與資料採礦實現洞察力行銷之研究--以個案公司為例說明
    Authors: 劉映蘭
    Liu, Ying Lan
    Contributors: 季延平
    Chi, Yen Ping
    劉映蘭
    Liu, Ying Lan
    Keywords: 資料倉儲
    資料採礦
    洞察力行銷
    STP
    Data Warehouse
    Data Mining
    Insight Driven Marketing
    STP
    Date: 2011
    Issue Date: 2012-10-30 11:21:20 (UTC+8)
    Abstract: 提供以顧客為導向的服務、提升顧客價值成為各企業經營策略的出發點,因此了解顧客特徵、需求、行為成為首要任務。
    隨著經濟發展,台灣整體用電需求不斷攀升,同時電力產業亦須面對全球燃料價格上漲的現況,政府邁向低碳經濟時代,推出一系列相關政策,於我國電力結構中占有重要地位的台灣電力公司也開始思考如何在需求及成本皆提升的環境下,繼續維持穩定供電,提供以用戶為導向的服務。
    本文即以台電公司為個案,以資料倉儲與資料採礦技術進行【用戶區隔】了解台電用戶特徵、【選擇目標用戶】找出優先服務的用戶對象及【產品定位】推薦適合目標用戶用電特徵之電價及優惠方案,實現行銷活動STP分析過程之研究。
    Providing customer-oriented services and elevating customer value have became the starting point of business strategy. Therefore, understanding customer characteristics, requirements, and behavior has become the primary task.
    As the overall demand for electricity rises constantly in Taiwan along with economic development, electric power industries have to face the surging fuel prices. To put low carbon economy into practice, the government has launched various policies. Taiwan Power Company, which plays an important role in the electric power structure in Taiwan, started thinking about how to provide stable power and customer-oriented services under the circumstances both demand and cost increase.
    Based on the case of Taiwan Power Company, this research investigated customer segmentation - to understand customer characteristic, customer targeting - to find out the prior customer, and product positioning - to recommend target customer appropriate tariff and preferential tariff treatment through data warehouse and data mining technology. The purpose of the research was to achieve STP analysis in marketing process.
    Reference: 中文參考文獻
    1. 王派洲(譯)(民97)。資料探勘 - 概念與方法(原作者:Jiawei Han, Micheline Kamber)。滄海。(原著出版年:2006)
    2. 台灣電力公司(民99)。99年台灣電力公司顧客服務白皮書。
    3. 台灣電力公司(民101)。台電月刊101年5月號。第59-60頁。
    4. 台灣電力公司(民99)。台灣電力公司歷史發展與組織架構。101年6月,取自 http://www.taipower.com.tw。
    5. 台灣電力公司。台灣電力公司負載管理說明。101年6月,取自http://www.taipower.com.tw/big/Knowledge_world/FAQ/part6.htm。
    6. 吳旭智、賴淑貞(譯)(民90)。資料採礦理論與實務 - 顧客關係管理的技巧與科學。(原作者:Michael J. A. Berry, Gordon S. Linoff)。維科圖書有限公司。(原著出版年:1997)
    7. 郭志隆、張芳菱(譯)(民97)。資料探勘- Introduction to Business Data Mining。(原作者:David Louis Olson)。麥格羅‧希爾。(原著出版年:2007)
    8. 范惟翔(民96)。現代行銷管理理論與實務。新加坡商湯姆生亞洲私人有限公司。第7-8頁。
    9. 國家政策研究基金會(民98)。 國政研究報告-因應地球暖化之台灣能源政策規劃建議。101年3月,取自http://www.npf.org.tw/post/2/5952。
    10. 經濟部能源局(民99)。經濟部能源局2010年12月能源報導。
    11. 經濟部能源局(民101)。經濟部能源局2012年3月能源統計月報。

    英文參考文獻
    1. Gary L. Lilien, Arvind Rangaswamy, “Marketing Engineering: Computer-Assisted Marketing Analysis Planning”, Addison Wesley, 1997, pp.57-58.
    2. Jiawei Han, Micheline Kamber, “Data Mining: Concepts and Techniques”, Morgan Kaufmann Publishers, August 2000.
    3. Kotler, Philip, “Marketing Insights from A to Z: 80 Concepts Every Manager Needs to Know”, John Wiley & Sons, Inc., 2003, pp.39.
    4. Lach J., “Data mining digs in”, American Demographics, volume 21, number 7, July 1999, pp. 38-45.
    5. Ralph Kimball, Joe Caserta , “The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning”, Wiley, 2004.
    6. Robert C. Blattberg, Byung-Do Kim, Scott A. Neslin, “Database Marketing: Analyzing and Managing Customers”, Springer, 1 edition, 2009.
    7. SAP , “Insight: The Critical Path to Competitive Differentiation for Growing Companies”, IDC executive brief, Jun 30, 2011.
    8. Surajit Chaudhuri, Umeshwar Dayal, “An Overview of Data Warehouse and OLAP Technology”, SIGMOD Record, Vol. 26, No. 1, 1997, pp. 65-74.
    9. William H. Inmon, “Building the Data Warehouse”, Wiley, 3 edition, 2002.
    10. Yin, Robert K., “Case Study Research: Design and Methods”, Sage, 2002.
    Description: 碩士
    國立政治大學
    資訊管理研究所
    99356014
    100
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0099356014
    Data Type: thesis
    Appears in Collections:[資訊管理學系] 學位論文

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