• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.5
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• pp.547-558
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• 2004

The purposes of this study were to classify shopper types based on clothing shopping orientations and to identify the differences in store selection criteria and demographic characteristics by shopper types. The questionnaire was administered to female and male undergraduate and graduate students living in Seoul. Of 330 returned questionnaires, 319 were used in the statistical analysis which were factor analysis, cluster analysis, $\chi$$^2$-test, and One-way ANOVA. The results of this study were as follows: 1) Clothing shopping orientations had six factors: recreational shopping, name conscious shopping, economic shopping, fashion oriented shopping, convenience shopping. and individualistic shopping. Cluster analysis identified that clothing shopping orientations had four groups: recreational cluster, individualistic cluster, demanding shopper cluster, and convenient brand conscious shopper cluster. 2) Clothing shopping orientations were significantly different in relation to the demographic characteristics such as gender, major field of study, expenditure on clothing, pocket money, and family income level. 3) Store selection criteria had five factors: service quality, physical store environment, sales personnel, shopping convenience, and other attractions. 4) There were significant differences in physical store environment, shopping convenience, and other attractions according to the shopper clusters.

• Fashion & Textile Research Journal
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• v.10 no.5
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• pp.644-651
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• 2008

The health of foot is connected with individual's health and affects men's activity. In order to develope comfort socks, both foot size and foot shape must be considered. The purpose of this study was to categorize men's foot shape according to age using men's foot scan data (with 2005 Size Korea). Factor analysis, Cluster analysis, ANOVA, and Duncan's test were performed for statistical analysis of the data by SPSS Win 12.00 program. The results are as follows. 1. Nine factors constituting the men's foot were extracted through factor analysis and those factors comprised 77.7% of total variance. 2. On the basis of the cluster analysis, four different foot shapes were categorized. Cluster 1 was characterized by large in toe and ankle size. Cluster 2 was characterized by short foot length, low foot height, and small foot breadth/girth. Cluster 3 was characterized by large and high in foot height. Cluster 4 was characterized by short in foot length and large in foot breadth/girth. 3. Distribution of four foot shape clusters from 20 to 70 years in age above were categorized. For the 20 to 29 years in age, cluster 2, while for the over 30 years in age cluster 4 or cluster 3 is the most dominant foot type. A foot breadth in the 50 years over is wider size range than that in the below 49 years. The foot figures of elderly men over 60 years were smaller than those of below 60 years.

• Journal of Korean Clinical Nursing Research
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• v.29 no.3
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• pp.337-347
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• 2023

Purpose: The objectives of this study were to categorize the conflict management types of preceptor nurses and determine the effects of these types on preceptors' role perception and core competencies. Methods: Data was collected from 192 preceptor nurses with at least two years experiences in general hospitals, from July 1 to July 31, 2022. Conflict management type, preceptor role perception, and core competency were investigated using structured instruments. The data was analyzed using K-means cluster analysis, Independent samples t-test, One-way ANOVA with Scheffé's test, and multiple regression analysis. Results: The conflict management types were categorized into four types; comprehensive type (cluster 1), integrating, obliging, compromising type (cluster 2), undifferentiated type (cluster 3) and obliging, avoiding type (cluster 4). The effect of conflict management types on preceptors' role recognition occurred in the following order of cluster 2 (integrating/obliging/compromising type), cluster 1 (comprehensive type), and cluster 4 (obliging/avoiding type). Next, cluster 1 (comprehensive type), cluster 2 (integrating/obliging/compromising type), and cluster 4 (obliging/avoiding type) were shown in the order of the impact on the core competencies of the preceptor. Conclusion: When preceptor nurses use a mixture of various attributes of conflict management evenly, they have been shown to demonstrate effective preceptor role recognition and core competencies. Therefore, it is proposed that future development of conflict management training programs for preceptor nurses should begin with identifying their conflict management type, followed by creating a program that addresses any deficiencies.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.189-213
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• 2017

This study seeks to critically examine the significance and limits of the cluster adaptive cycle model for analysis of cluster evolution and to propose research issues for future analysis of cluster evolution based on this critical examination. Until the 1980s, research on industrial complexes including clusters was based on a 'static perspective' that focuses on the aspect of economic space at a specific point in time, but the research paradigm has recently shifted to a 'dynamic perspective' focusing on 'evolution' of 'complex adaptive systems'. As a result, the adaptive cycle model has attracted attention as an analysis tool of dynamically evolving clusters. However, the cluster adaptive cycle model has emerged by being appropriately modified and expanded according to the properties of the cluster and its evolution. The cluster adaptive cycle model is a comprehensive analysis framework that identifies the characteristics of cluster evolution in terms of resource accumulation, interdependence, and resilience and classifies cluster evolution paths into six different categories. Nevertheless, there is still a need for further discussion and supplementation in terms of theoretical and empirical research to expand and deepen the model. Therefore, research issues for future analysis of cluster evolution are to specify and elaborate the cluster evolution model, to emphasize the concept of resilience, and to verify the applicability and usefulness of the model through empirical research.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1057-1068
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• 2003

Results of using principal component analysis prior to cluster analysis are compared with results from applying agglomerative clustering algorithm alone. The retrieval ability of the agglomerative clustering algorithm is improved by using principal components prior to cluster analysis in some situations. On the other hand, the loss in retrieval ability for the agglomerative clustering algorithms decreases, as the number of informative variables increases, where the informative variables are the variables that have distinct information(or, necessary information) compared to other variables.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.15-26
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• 2002

The purpose of this study was to classier the somatotype of late middle-aged women and to analyze the characteristics of each somatotype. The subjects were 337 late middle-aged women and their age range os from 45 to 59 fears old. Data were collected through anthropometry and photometry and analyzed by factor analysis, cluster analysis and discriminant analysis. The results were as follows; 1. The result of factor analysis indicated that 9 factors were extracted through factor analysis and those factors comprised 83.56 percent of total valiance. 2. Using factor scores, cluster analysis was carried out and the subject were classified into 4 cluster. Each cluster was classified as their body front and side view contour. Type 1 is tall, slim, and lower balk is flat on the side. Type 2 is standard and lean-back type on the side. Type 3 is standard height and weight, H type in front, and belly-protruded on the side. Type 4 is short, fat, and the side is hip-protruded. 3. According to the stepwise discriminant analysis, the 9 important items in classifying the somatotype of the late middle-aged women are as follows ; lower back tilt angle, hip depth(back) -back waist depth(back), bust depth(fore) - anterior waist depth(fore), jugular fossa point(fore), upper back tilt angle, burst breadth -waist breadth, right shoulder tilt, height of shoulder - height of anterior waist, abdomen breath. The correct classification rate for these items is as exact as 84.62%.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.451-461
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• 2008

In this study, factor and cluster analysis have been conducted to group the differences in Korean view on national economic policy in the sample of the 2006 Korean General Social Survey (KGSS). According to the 2006 KGSS, the 6 items with a 5-point Likert scale include the questions about whether or the extent to which each respondent supports the specific types of governmental economic policy. In our study, at first, the factor analysis has converted the original 6 items into the 3 composite variables that account for 81% in the total variability. As the second step of factor analysis, factor scores have been computed. Then, the K-means cluster analysis based on the factor scores has been conducted to group the survey respondents into the 3 clusters. In particular, the cross-tabulation analysis has shown that the distribution of the 3 clusters varies with the respondents' socio-demographic characteristics.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.3
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• pp.333-340
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• 1998

The purpose of this study was to classify the lower body somatotype based on the side view and to analyze the characteristics of each somatotype. The subject were 234 Korean Junior High School Girls. Data were collected through photographic sources and analyzed by factor analysis, cluster analysis and analysis of variance. The result of factor analysis indicated that 4 factors were extracted through factor analysis and those factorscomprised 73.5% of total variance. Using factor scores, cluster analysis was carried out and the subject were classified into 3 clusters. Each cluster was classified as their lower bobs side view contour.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.222-230
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• 2023

The purpose of this study is to provide basic data on sports entertainment programs by collecting data on unstructured data generated by Naver and Google for SBS entertainment program 'Women Who Score Goal', which began regular broadcast in June 2021, and analyzing public perceptions through data mining, semantic matrix, and CONCOR analysis. Data collection was conducted using Textom, and 27,911 cases of data accumulated for 16 months from June 16, 2021 to October 15, 2022. For the collected data, 80 key keywords related to 'Kick a Goal' were derived through simple frequency and TF-IDF analysis through data mining. Semantic network analysis was conducted to analyze the relationship between the top 80 keywords analyzed through this process. The centrality was derived through the UCINET 6.0 program using NetDraw of UCINET 6.0, understanding the characteristics of the network, and visualizing the connection relationship between keywords to express it clearly. CONCOR analysis was conducted to derive a cluster of words with similar characteristics based on the semantic network. As a result of the analysis, it was analyzed as a 'program' cluster related to the broadcast content of 'Kick a Goal' and a 'Soccer' cluster, a sports event of 'Kick a Goal'. In addition to the scenes about the game of the cast, it was analyzed as an 'Everyday Life' cluster about training and daily life, and a cluster about 'Broadcast Manipulation' that disappointed viewers with manipulation of the game content.

• Journal of the military operations research society of Korea
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• v.6 no.2
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• pp.89-127
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• 1980

The multivariate analysis techniques of cluster analysis are examined in this article. The theory and applications of the techniques and computer software concerning these techniques are discussed and sample jobs are included. A hierarchical cluster analysis algorithm, available in the IMSL software package, is applied to a set of data extracted from a group of subjects for the purpose of partitioning a collection of 26 attributes of a weapon system into six clusters of superattributes. A nonhierarchical clustering procedure were applied to a collection of data of tanks considering of twenty-four observations of ten attributes of tanks. The cluster analysis shows that the tanks cluster somewhat naturally by nationality. The principal componant analysis and the discriminant analysis show that tank weight is the single most important discriminator among nationality although they are not shown in this article because of the space restriction. This is a part of thesis for master's degree in operations research.