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자료유형
학술저널
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동아시아경상학회 East Asian Journal of Business Economics East Asian Journal of Business Economics 제7권 제2호
발행연도
2019.1
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21 - 30 (10page)

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Purpose - In this work, we categorize the 21 shopping items which foreign tourists purchase in South Korea and monitor the level of dissimilarity (or similarity) between each item by utilizing distance matrix, and both hierarchical and k-means cluster analyses, respectively, based on the eight purpose of visit attributes (Leisure & Vacation, Health & Treatment, Religion & Pilgrimage, Shopping, Visit, Business, Education, ETS) in 2017. In addition, multidimensional scaling (MDS) method may come by visual display for mining appearance of proximities among twenty one shopping items based on eight attributes of purpose of visit. Research design, data, and methodology - This study is carried out in 2017 by Ministry of Culture, Sports and Tourism and conduct a face-to-face survey of foreign tourists from 20 countries who purchase shopping items in South Korea. CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0 are used to perform this work. Results - We ascertain that twenty one shopping items can be classified into five similar groups (clusters) which have homogeneous traits by going through two-step cluster analysis. We can position homogeneous places of cluster and twenty one shopping items joining each cluster. Conclusions - We can relatively assess patterns and characteristics of each shopping item, come by useful information in activating shopping tour based on the actual state of recognition of foreign tourists and practically apply to each tourism industry on underlying results.

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