| 英文摘要 |
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. |
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