• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.11
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• pp.1605-1614
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• 2002

The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality. In order to implement the purpose of this study, Jeans market had been segmented by the mixture regression model, and price response function was calibrated for each segment. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables. Data were co]looted from the sample of the 23o undergraduate and graduate students in Seoul. For the data analysis, mixture regression model, conjoint analysis, and t-test were used. As a result, jeans market was divided into 5 segments. Segment 1,2,3 were allocated into the group not using the level of price as the quality indicator while segment 4,5 were done into the other group. Significant differences existed between two groups in product attributes, not in demographic variables. Mixture model and conjoint analysis were proved to be an effective set of tools in market segmentation.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.73-91
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• 2007

We investigate factors that influence the choice of high-share brands(HSBs) vs. low-share brands(LSBs) among various product and consumer characteristics related to brand-share perceptions. Specifically, using 8 product categories varying in terms of purchase decision involvement, we show how the influencing factors vary across the categories. At the general level that cover all the 8 categories, our hierarchical Bayesian regressions analysis shows that factors that favor high-share brands are purchase decision involvement, search goods, experience goods, price-quality relationship, positive network externalities, and price-prestige beliefs. Conversely, consumers who value variety seeking and need for uniqueness favor low-share brands. The effects of these factors, however, vary across product categories. The identification of these characteristics can help brand managers establish a more effective brand-share strategy in such areas as setting an optimal market share goal, extending a brand, and developing ad copy. Furthermore, our consumer segmentation analysis demonstrates the general market has two distinct segments - (1) a segment composed of HSB buyers(86%) and (2) a segment composed of LSB buyers(14%). The two segments are also shown to have different significant factors that explain their brand choice. Our segmentation analysis can help marketers establish a marketing strategy that targets a specific segment of interest.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.4
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• pp.782-794
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• 1997

The purpose of study were 1) to find whether brand loyalty is reasonable measurement for market segmentation or not, 2) to know consumers' purchasing behavior by marketsegmentation, 3) to draw preference jean product. Objects were 462 high school students who live in Seoul and random sampling referred from "Korean school guide book". The questionnaires were selected from the previous studies and various bibliographies. For statistic analysis, percentage, average, ANOVA, x2-test, Duncantest, paired t-test, and multiple regression were used by SAS package. The results of this study were as follows. 1) Consumers were classified into affective brand loyalty group, familiar brand loyalty group, habitual brand loyalty group, brand interest but no brand loyalty group, and no brand loyalty group. 2) There were notable differences in clothes purchasing behavior variable through market segments' purchasing (requency, price. 3) The most Prefered jean Product is 80,000 won, domestic well-known brand, baggy style and preferable jean product shows different when it classified brand loyalty.d loyalty.

• Journal of the Korean Regional Science Association
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• v.12 no.2
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• pp.37-57
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• 1996

Intra-metropolitan spatial segmentation of the labor marker requires barriers of mobility on both supply and demand side of the local labor marker. The phenomena of spatial segmentation of the labor market are particularly applied to the secondary workers rather than to the primary workers. Supply side barriers include the costs of obtaining job information regarding jobs outside of the immediate area, commuting costs, and barriers to residential mobility. Demand side barriers include site-specific technology and product demand, and discrimination. In this paper, I discuss these barriers and examine their implications for differences in segmentation by demographic and skill groups at the intra-metropolitan scale. In particular, I apply a job search model to examine supply side barriers such as information and commuting costs, and an implicit contract model to explain demand side barriers such as dual/internal labor market and firms' (re) location strategies.

• International Commerce and Information Review
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• v.11 no.4
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• pp.129-149
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• 2009

The interest in wine has been increasing because of raised standard of living, increased leisure time, raised interest in health. Therefore, a few wine related tourism product has introduced to public including wine train to Young-dong region and overseas wine tour package. This study focused on motivation to visit overseas wine tour package in order to segment target wine tourism countries. As a result, three different markets were segmented and they showed different characteristics with regard to demographics, tourism behavior, and preferred wine tourism countries.

• Korean Management Science Review
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• v.19 no.1
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• pp.189-196
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• 2002

Data clustering is often one of the first steps in data mining analysis. It Identifies groups of related objects that can be used as a starling point for exploring further relationships. This technique supports the development of population segmentation models, such as demographic-based customer segmentation. This paper Purpose to present the development of two phase hierarchical clustering algorithm for group formation. Applications of the algorithm for product-customer group formation in customer relationahip management are also discussed. As a result of computer simulations, suggested algorithm outperforms single link method and k-means clustering.

• Journal of IKEEE
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• v.5 no.2 s.9
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• pp.211-220
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• 2001

This paper proposes a 2-D texture segmentation algorithm which is in close analogy to amplitude demodulation in communication systems. First, we show that it is theoretically possible to segment a multitexture image using an ideal filter followed by an amplitude demodulation block. However, in practice, the Gabor filter is used instead of the ideal filter because it has many desirable properties and especially it gives optimum space-bandwidth product. Our algorithm recovers all the texture regions containing the sinusoid with frequency to which the Gabor filter is tuned. We have demonstrated the discriminating power of our method in using a synthetic multitexture image. It is clear mathematically and easy to implement. Our method can be a good alternative to avoid many problems encountered in classifying the feature vectors in feature-based texture segmentation approaches.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.377-385
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• 2008

Nowadays, the demand of functional white milk has been augmented because of the widespread well-being popularity. Especially, in case of white milk, there are brisk efforts In segmentation of the functional product, in an effort to break through the limitation of creating new demands out of fixed demands and school meal service. The companies are also looking for the solution in the development of functional white milk in that they have no other way to increase the customers' demand, but the differentiation of the product, since the companies consider that content of white milks are exactly the same that there is no need to compete. Following this, the package design availed of the development of functional milk and took important charge of conveying and emphasizing the product's functional special quality and information to customers. Consequently, in this research, we will going to look at more desirable design differentiation strategy of functional milk by examining the basics of functional milk and by analysing the functional characteristic of current products and the expression strategy of package design.

• The Research Journal of the Costume Culture
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• v.14 no.4
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• pp.542-555
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• 2006

The main objective of this study was to investigate the relationship between benefits segmentation and knitwear purchasing behavior of college female students in the U.S. The questionnaires for this survey were developed to measure knitwear purchasing behavior and benefits segmentation. The questionnaire was administered to 119 female college students in the University of California. The data was analyzed by percentage, frequency, mean, factor analysis, Cluster Analysis and ANOVA, Duncan Multiple Range test. The female college students in the U.S. were classified into fourth subdivisions by the cluster analysis. In the case of fashion information sources of knit wear, significant differences were found according to benefits sought subdivision in observation of famous people's clothing, fashion articles in magazines and newspapers, TV advertisements, Newspaper advertisements, advice of salespeople, and Catalogs. The evaluation criteria of knit wear product of consumers were significantly different depending on benefits sought subdivision in design/style, quality of construction, fashionable, brand and store name, pleasing to others, prestige, and sexy. The store attributes of knitwear product of consumers were significantly different depending on benefits sought subdivision in friendliness of sales personnel, product knowledge of sales personnel, brand names, new fashion, and variety of products. The outlook for the industry of knitwear look to remain bright, there should be a continuous effort to research and invest in consumer satisfaction of knitwear.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.183-203
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• 1993

One of the most difficult and time-consuming stages in the development of the knowledge-based system is a knowledge acquisition. A splitting algorithm is developed to infer a rule-tree which can be converted to a rule-typed knowledge. A market segmentation may be performed in order to establish market strategy suitable to each market segment. As the sales data of a product market is probabilistic and noisy, it becomes necessary to prune the rule-tree-at an acceptable level while generating a rule-tree. A splitting algorithm is developed using the pruning measure based on a total amount of information gain and the measure of existing algorithms. A user can easily adjust the size of the resulting rule-tree according to his(her) preferences and problem domains. The algorithm is applied to a market segmentation problem of a medium-large computer market. The algorithm is illustrated step by step with a sales data of a computer market and is analyzed.