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    政大典藏 > College of Commerce > MBA Program > Theses >  Item 140.119/97126
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/97126


    Title: 應用資料採礦於連鎖藥局商品
    The Application of Data Mining on the Association of Pharmaceutical Products Through the Chain Pharmacies
    Authors: 王詠立
    Li, Wang Yung
    Contributors: 鄭宇庭
    王詠立
    Wang Yung Li
    Keywords: 資料採礦
    顧客價值
    關聯規則分析
    購買規則
    連鎖藥局
    Data Mining
    Customer Value
    Association Rule
    Chain Pharmacy
    Date: 2016
    Issue Date: 2016-06-01 13:58:16 (UTC+8)
    Abstract: 台灣連鎖藥通路已逐漸轉型為複合式藥局,除了購買處方藥以外,現今藥局銷售商品種類眾多且逐漸成為社區商店之型態,讓民眾一次性購足藥品、化妝品、食品及生活日用品等。顧客於門市消費後累積了大筆的顧客會員銷售資料,本研究結合大數據資料採礦之技術,應用在顧客購買行為與行銷策略之間的相應關係,並藉此了解顧客在藥局通路的消費型態,進而衍生出符合顧客需求的行銷組合方案。
    本研究藉由台灣某家連鎖藥局的銷售時點情報系統(POINT OF SALE, POS)資料分析顧客會員之購買行為,依據會員之購買日期、購買品項、購買金額等,應用資料採礦分析方法,先利用RFM模型分析顧客價值群的特性概況,再利用APRIORI演算法針對該連鎖藥局的八大類別商品銷售資料探討顧客會員購買產品的關聯規則,依照結果衍生出不同的商品銷售組合,並在門市執行有效的行銷策略以提升營業額。最後,依據研究結果對該家連鎖藥局提供銷售的策略及建議,作為該連鎖藥局業者後續經營之參考。
    The development of the domestic pharmacies in Taiwan has influenced by the government policy and logistics. Gradually, the traditional pharmacy had been replaced by the chain pharmacies to face the demands of products variety, customized and the consumer information.
    The members` purchase behaviors were analyzed in this study through the Point of Sale(POS) data from chain pharmacy headquarters. The purchase behaviors of the pharmacy members were analyzed based on purchase date, purchase item, amount of purchase etc. First, data regarding customer purchasing records are collected and widely known RFM model is used to evaluate the value for each customer. Second, an association rule mining tool, the Apriori algorithm, is used to analyze the relationship between customer purchasing records and products, to obtain hidden and useful purchasing rules for each product category.
    The association rules obtained can help the decision managers plan their new cross-selling strategies for products in future.
    第壹章 緒論 5
    第一節 研究背景與動機 5
    第二節 研究目的 5
    第三節 研究流程 6
    第貳章 文獻探討 8
    第一節 資料採礦之概述 8
    第二節 台灣藥局產業現況之概述 13
    第三節 顧客價值與關聯規則 18
    第參章 研究方法 21
    第一節 資料來源 21
    第二節 研究架構 21
    第三節 操作性變數定義 22
    第四節 分析方法 23
    第肆章 研究分析 30
    第一節 探索性分析 30
    第二節 各類別之會員顧客價值 45
    第三節 關聯規則分析 63
    第四節 銷售組合搭配 71
    第伍章 結論與建議 76
    第一節 結論 76
    第二節 建議 78
    參考文獻 80
    Reference: 參考文獻
    i. 中文文獻
    1. 行政院主計總處,中華民國稅務行業標準分類(第九次修訂)。
    2. 宋龍華,2008,應用資料採礦於智慧型統計資料庫系統,輔仁大學. 應用統計學研究所碩士論文。
    3. 流通快訊,『美妝、藥局、生活百貨』店數統計表,http://www.dnnt.com.tw
    4. 財政部,批發及零售業之營業收入項目分配。
    5. 經濟部統計處,2013, 商業經營實況調查報告。
    6. 劉世琪,2003,應用資料挖掘探討顧客價值-以汽車維修業為例,朝陽科技大學. 工業工程與管理系碩士論文。
    7. 謝邦昌、鄭宇庭與蘇志雄,2009,Data Mining概述以Clementine12.0為例, 中華資料採礦協會。

    ii. 英文文獻
    1. Agrawal, R., Imielinski, T. and Swami, A. (1993) “Mining association rules between sets of items in large databases,"Proceedings of ACM SIGMOD, pp. 207-216.
    2. Berry, M. and Linoff, G. (1997) Data Mining Techniques: For Marketing, Sales, and Customer Support, Wiley, NY.
    3. Han, J. and Kamber, W. (2001) Data Mining: Concepts and Techniques, Morgan Kaufmann, San Francisco, CA.
    4. IBM Corporation (2011), IBM SPSS Modeler CRISP-DM Guide, ftp://public.dhe.ibm.com/software/analytics/spss/documentation/modeler/14.2/en/CRISP_DM.pdf
    5. J. MacQueen (1967), “Some Methods for Classification and Analysis of Multivariate Observations,” Proc. Fifth Berkeley Symp. Math. Statistics and Probability, vol. 1, pp. 281-296.
    6. Kotler, P. (2003) Marketing Management, Prentice-Hall, New York .
    7. Woodruff, R. B. (1997) "Costomer Value: The Next Source for Competitive Advantage." Academy of Marketing Science 125: 139-153.
    Description: 碩士
    國立政治大學
    企業管理研究所(MBA學位學程)
    103363052
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0103363052
    Data Type: thesis
    Appears in Collections:[MBA Program] Theses

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