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題名:應用資料探勘方法中的分群分析技術來探究高階健檢客戶之型態組成以進行客戶關係管理--以臺北某醫學中心之高階健檢客戶為例
書刊名:健康管理學刊
作者:王建智陳銘樹 引用關係徐正容
作者(外文):Wang, Chien-chihChen, Ming-shuHsu, Cheng-jung
出版日期:2008
卷期:6:1
頁次:頁49-59
主題關鍵詞:資料探勘顧客關係管理分群分析高階健檢Data miningCustomer relationship managemantCluster analysisHigh level health examination
原始連結:連回原系統網址new window
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  • 被引用次數被引用次數:期刊(3) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:3
  • 共同引用共同引用:6
  • 點閱點閱:96
隨著人口老化與經濟M型化,預防醫學的觀念日趨受到重視,加上目前各大醫學中心均極力發展非健保給付的自費醫療,高階健康檢查或健康管理服務已經蔚為潮流。目前各大醫院均開始致力於研究目標族群的組成並針對其需求發展出適切的服務,哪些族群應屬於高階健檢之目標客群乃是件極為重要的事。透過科學的資訊工具與方法找出真正的目標客群,研究其真正需求才能進一步做到客戶關係管理。本研究利用資料探勘的分群技術對某醫學中心2005~2006年共計1127筆消費金額超過一萬元的高階健檢客戶所填寫的滿意度問卷,針對人口學變項、消費動機與滿意度資料進行分群分析。分群方法採用二階段法,第一階段以華德法作分群,決定群組個數,第二階段再以K-means法進行群集。透過分群技術進行研究樣本分析後,該院高階健檢主要呈現出三種型態的客群,第一型相似分數為40.42%,該群為女性年紀大約在50~64歲,教育程度在高中職。第二型相似分數為38.80%,該群為男性年紀大約在35~49歲,教育程度在大學且多為公司主管或幹部。第三型相似分數為20.78%,該群為男性年紀大約在50~64歲,教育程度在大學以上且多為公司高階主管。再了解主要客群的組成後,加上其對該院健檢滿意度與消費動機,本研究在結論即訂出相關的顧客關係管理策略。
The evolution of population aging and M-shaped society lead to a wide acceptance of preventive medicine. Added by the enthusiasm of self-paid medical service market among leading medical centers, high level health examination has become a modern popularity. For the development of customer-oriented medical services, major hospitals are making efforts to analyze the compositional profile of customers. The qualification of customer groups of high level health examination has become one of the greatest interests. A scientific and technical approach is necessary for customer group characterization and customer relationship management. Cluster analysis technique is utilized for data mining. The sample comprised of 1127 questionnaires in a customer service satisfaction survey on health examination customers with payment over NT$ 10,000 dollars from 2005 to 2006 in a single medical center. Demographic features, consumer motivation, and satisfaction are variables for cluster analysis. A two-way clustering procedure is employed. The first step is cluster size determination by Ward’s method, followed by the second step of K-means clustering. The cluster analysis of the sample data yields three classes of the high level examination customers. Customers in the class I, with class resemblance score of 40.42%, are females, typically aged 50 to 64 years, and educations of high school or vocational high school. The class II, with class resemblance score of 38.80%, is composed of males, aged 35 to 49 years, with educations of university, and often managers and major employees. The class III, with class resemblance score of 20.78%, is composed of males, aged 50 to 64 years, educations of at least university, and mostly managers and executive employees. The clarification of major customer partitions is the basis of further analysis of health examination satisfaction and consumer motivation factors, as well as the final goal of hospital policy on customer relationship management.
期刊論文
1.張丁才、陳佳鈴(20050700)。應用資料探勘於壽險業之客戶分群研究。中華管理學報,電子商務專刊,67-74。new window  延伸查詢new window
2.Zhou, F.、Bisgard, K. M.、Yusuf, H. R.、Deuson, R. R.、Bath, S. K.、Murphy, T. V.(2002)。Impact of Universal Haemophilus Influenzae Type b Vaccination Starting at 2 Months of Age in the United States: An Economic Analysis。Pediatrics,110(4),653-661。  new window
3.翁振益、張德儀、鄭光遠、鍾碧姮、林雅藝(20060600)。資料探勘技術應用於航空業顧客再搭意願區隔與服務滿意項目組合之分析。觀光研究學報,12(2),139-154。new window  延伸查詢new window
4.羅麗君(1996)。健檢的定義。中華民國醫檢會報,11(3),55-56。  延伸查詢new window
5.Tehrani, N.(2002)。Publisher's Outlook: The Essence of CRM Success。Customer Interaction Solutions,21(1),2-4。  new window
學位論文
1.周佩蓁(2005)。以決策樹分析顧客滿意度之研究(碩士論文)。育達商業技術學院。  延伸查詢new window
2.侯世環(2002)。醫療院所顧客關係管理架構之建立及實證(碩士論文)。國立交通大學。  延伸查詢new window
3.楊清潭(2006)。應用類神經網路於健康檢查顧客忠誠度之研究(碩士論文)。銘傳大學。  延伸查詢new window
4.江士彥(2002)。醫療顧客關係管理之顧客需求與滿意度分群分析--以國內某準醫學中心為例(碩士論文)。元智大學。  延伸查詢new window
5.李智峰(1997)。健檢服務業現況與經營策略分析(碩士論文)。長庚醫學暨工程學院。  延伸查詢new window
6.張瑋倫(2000)。應用資料挖掘學習方法探討顧客關係管理問題(碩士論文)。輔仁大學。  延伸查詢new window
7.陳麗君(2003)。應用資料探勘技術於信用卡黃金級客戶之顧客關係管理(碩士論文)。元智大學。  延伸查詢new window
圖書
1.曾憲雄(2006)。資料探勘。臺北:旗標出版社。  延伸查詢new window
2.Berry, M. J. A.、Linoff, G. S.(1997)。Data Mining Technique Techniques: For Marketing, Sales and Customer Support。New York:John Wiley and Sons Inc。  new window
 
 
 
 
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