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    題名: 應用資料採礦於零售藥局產業之商品關聯分析-以Q連鎖藥局為例
    Application of product association in pharmaceutical retailing industry – a case study of Q Pharmacy
    作者: 韋菁蕙
    貢獻者: 鄭宇庭
    韋菁蕙
    關鍵詞: 資料採礦
    連鎖藥局
    關聯規則
    市場區隔
    Data mining
    Chained pharmacy
    Association rule
    Market segmentation
    日期: 2017
    上傳時間: 2018-03-02 12:07:03 (UTC+8)
    摘要: 社會型態變遷和醫療技術的進步,台灣生育率和死亡率逐年下降,整體人口結構開始呈現高齡化傾向。行政院國家發展委員會推估,臺灣將於 2018 年進入高齡社會, 2026 年邁入超高齡社會。行政院主計總處2016年家庭收支調查報告就指出,每戶家庭消費支出中醫療保健支出比重近20年持續增長。隨著臺灣邁入高齡社會,每戶家庭的醫療保健需求只會繼續增加。
    許多醫療零售企業因應此趨勢採取了各類佈局策略,例如某連鎖藥局品牌與便利超商合作推出複合型藥局,使藥局便利化,提升民眾購買可及性與便利性。由此可見,未來只會有越來越多競爭者覬覦醫療產業商機而加入競爭。Q連鎖藥局成立數十載,透過現有交易資料資訊化所得到的有價值資訊,我們可以在此類生存淘汰賽之前強化體質并取得優勢。本研究透過關聯分析研究Q連鎖藥局位於北、中、南三個地區的各門市交易資料,找出三個地區顧客所購買的商品關聯組合并比較其差異,透過此差異提出在地化的商品管理建議,提升商品管理與行銷活動效益。
    研究結果顯示北中南三個地區的顧客所購買的商品組合有所差異,其中北部和南部地區的差異最大。根據研究結果,本研究提出四點建議:北中南三個地區個別設立不同商品專區、根據不同地區之關聯分析結果進行優惠活動差異化、以中部地區為倉庫物流中心而中北與中南分界地區設立次要倉庫以及根據不同地區之關聯分析結果調整門口附近貨架商品陳列。
    With the improvements of modern medical techniques and the changes of social formation, resulting in both birth rate and mortality rate decrease in past few decades, which causes the overall demographic structure begins to show an aging tendency. According to Taiwan National Development Council, in 2018, Taiwan will become an aged society, and turning into hyper-aged society in 2026. The family income and expenditure report published by Directorate General of Budget, Accounting and Statistics, Executive of R.O.C in 2016 stated the expenses of family on health care perspective has increased in past two decades. The needs of health care and medical service increases as Taiwan population aging.
    Most of the companies in this industry made strategic moves to adapt to this trend. For instance, the renowned chained-pharmacy cooperates with the second largest convenience chain-store in Taiwan, launched multifunctional pharmacy store in order to facilitate pharmacy services and increase accessibility to customers. By gathering computerization and data mining, we are able to acquire valuable information before survival knockout in this industry happens. In this study, through the product association analysis, we study the transaction data of 93 Q pharmacy stores located in the northern, central, and southern regions, find out the association rules of the goods purchased by customers in this three regions and compare their differences, to point out localization product management and marketing recommendations
    The results show that there are differences in product association rules between the northern, central and southern regions, with the largest difference between northern and southern regions. According to the results of the study, the study proposed four suggestions. Firstly, the three regions shall establish of different commodity areas. Secondly, to implement differentiation of preferential activities based on the results of related analysis in different regions. Thirdly, to set up a warehouse as logistics center at central region while north-central and southern boundary areas set up a secondary warehouse. Lastly, to adjust the near entrance shelves display of goods based on the correlation study results in different regions.
    參考文獻: 一、 中文文獻
    1. 方世榮譯(1998)。行銷管理學:分析,計劃,執行與控制(Kotler, P.)第九版。臺北:東華。
    2. 行政院主計總處(2017)。105年家庭收支調查報告。
    3. 行政院國家發展委員會(2016)。中華民國人口推估(105-150年)。
    4. 吳宛臻(2007)。台灣社區藥局關鍵成功因素與經營績效之研究。中國醫藥大學醫務管理學研究所,碩士論文。
    5. 吳靜芳,王超弘(2015)。利用因素分析及AMOS探究台北地區健保藥局、複合式藥局及藥妝店之服務滿意度。東吳大學企業管理研究所碩士論文。
    6. 李錦炯(2003)。獨立型藥局與連鎖藥局經營管理之比較研究。淡江大學商學院暨管理學院高階主管管理碩士學程,碩士論文。
    7. 許宗清(2009)。台灣地區航空公司市場區隔之研究。國立高雄海洋科技大學航運管理研究所,碩士論文。
    8. 郭佩雯(2004)。連鎖藥局關鍵成功因素的探討。國立台灣大學公共衛生學院醫療機構管理研究所,碩士論文。
    9. 陳振茂(1995)。行銷學。巨浪出版社。
    10. 曾憲雄、蔡秀滿、蘇東興、曾秋蓉、王慶堯(2005)。資料探勘。旗標科技股份有限公司。
    11. 黃茂景(2007)。連鎖藥妝業經營關鍵成功因素之研究。中山大學高階經營碩士班,碩士論文。
    12. 廖述賢與溫志皓(2009)。資料採礦與商業智慧。雙葉書廊。
    13. 衛生福利部(2017)。中華民國105年醫療機構現況及醫院醫療服務量統計。
    14. 盧淑惠(2003)。台灣連鎖藥局成長策略與關鍵成功因素之關聯性研究。中原大學企業管理研究所,碩士論文。
    15. 謝邦昌(2014)。SQL Server資料採礦與商業智慧-適用SQL Server 2014/2012。碁峰出版社。
    16. 謝邦昌、鄭宇庭(2016)。零售業資料採礦:R及Excel運用。新陸書局。

    二、 英文文獻
    1. Berry, M. & G. Linoff, (1997), “Data Mining Techniques for Marketing, Sales and Customer Support,” John Wiley and Sons, New York.
    2. Curt, H., (1995), “The Deville’s in The Detail: Techniques, Tool and Applications for Data Mining and Knowledge Discovery-Part 1,” Intelligent Software Strategies, 6(9), p3.
    3. Kotler, P., (1982), “Marketing for Nonprofit Organizations. Englewood Cliffs., New Jersey: Prentice-Hall Inc.
    4. Kotler, P., (1991). Marketing Management: Analysis, Planning, Implementation, and Control. 7th ed., New Jersey: Prentice-Hall.
    5. Miller, P., (2004), “Segmentation: Identification, intuition, and implementation,” Industrial Marketing Management, 33, pp.779.
    6. Stanton, W. J., (1983), Fundamentals of Marketing. (6th ed.) McGraw- Hill.
    7. Wendell, R. S., (1956), “Product Differentiation and Market Segmentation as Alternative Marketing Strategy,” Journal of Marketing, 21, 3-8.
    描述: 碩士
    國立政治大學
    企業管理研究所(MBA學位學程)
    104363122
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G1043631223
    資料類型: thesis
    顯示於類別:[企業管理研究所(MBA學位學程)] 學位論文

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