• Korean journal of food and cookery science
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• v.29 no.4
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• pp.367-376
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• 2013

The objectives of this study are to provide the food market of internet shopping malls with effective marketing data, to provide basic data for the development of related fields of the study, and ultimately to increase the satisfaction of food consumers of internet shopping malls. To achieve the object of this research, a cluster analysis of the research subjects was carried out based on the following 5 factors of food purchasing attribute that had been deduced by a factor analysis by the types of food purchasers: quality characteristics, informativity, convenience, price and diversity. According to the result of the cluster analysis, the research subjects were classified into the 2 clusters of diversity and informativity. The deduced 2 clusters, together with age and occupation among general characteristics, were used as independent variables to find out food purchasing behaviors and satisfaction at internet shopping malls. The results are as follows: Regarding the frequency of food purchasing experiences at internet shopping malls according to occupation, the highest frequency was shown by those involved in service, sales and self-employed businesses; whereas regarding the frequency according to age, those in their 30s and 40s showed the highest frequency. The total amount of money spent on food purchasing for 1 year at internet shopping malls was shown to increase as age increased. The frequency of the purchasing experiences of agricultural products and fish products was shown to be higher as age increased. However, overall purchase satisfaction was highest among those in their 30s, while lowest among those in their 40s. Regarding satisfaction by the types of food purchased via internet shopping malls, satisfaction was relatively higher with common foods and functional foods, while lower with fish products. Taken together, it was concluded that purchasing behaviors at internet food shopping malls, such as the frequency of purchasing experiences and purchase amount, varied depending on age rather than purchasing attribute. Accordingly, in order to vitalize internet food shopping malls, it would be necessary to provide customized food shopping information for individual age groups.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.71-81
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• 2010

The problem of finding clusters is widely used in numerous applications, such as pattern recognition, image analysis, market analysis. The important factors that decide cluster quality are the similarity measure and the number of attributes. Similarity measures should be defined with respect to the data types. Existing similarity measures are well applicable to numerical attribute values. However, those measures do not work well when the data is described by categorical attributes, that is, when no inherent similarity measure between values. In high dimensional spaces, conventional clustering algorithms tend to break down because of sparsity of data points. To overcome this difficulty, a subspace clustering approach has been proposed. It is based on the observation that different clusters may exist in different subspaces. In this paper, we propose a new similarity measure for clustering of high dimensional categorical data. The measure is defined based on the fact that a good clustering is one where each cluster should have certain information that can distinguish it with other clusters. We also try to capture on the attribute dependencies. This study is meaningful because there has been no method to use both of them. Experimental results on real datasets show clusters obtained by our proposed similarity measure are good enough with respect to clustering accuracy.

• Journal of the Korean association of regional geographers
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• v.7 no.1
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• pp.35-50
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• 2001

Since remotely sensed images of coastal wetlands are very sensitive to spatial resolution, it is very important to select an optimum resolution for particular geographic phenomena needed to be represented. Scale is one of the most important factors in spatial analysis techniques, which is defined as a spatial and temporal interval for a measurement or observation and is determined by the spatial extent of study area or the measurement unit. In order to acquire the optimum scale for a particular subject (i.e., coastal wetlands), measuring and representing the characteristics of attribute information extracted from the remotely sensed images are required. This study aims to explore and analyze the scale effects of attribute information extracted from remotely sensed coastal wetlands images. Specifically, it is focused on identifying the effects of scale in response to spatial resolution changes and suggesting a methodology for exploring the optimum spatial resolution. The LANDSAT TM image of Sunchon Bay was classified by a supervised classification method, Six land cover types were classified and the Kappa index for this classification was 84.6%. In order to explore the effects of scale in the classification procedure, a set of images that have different spatial resolutions were created by a aggregation method. Coarser images were created with the original image by averaging the DN values of neighboring pixels. Sixteen images whose resolution range from 30 m to 480 m were generated and classified to obtain land cover information using the same training set applied to the initial classification. The values of Kappa index show a distinctive pattern according to the spatial resolution change. Up to 120m, the values of Kappa index changed little, but Kappa index decreased dramatically at the 150m. However, at the resolution of 240 m and 270m, the classification accuracy was increased. From this observation, the optimum resolution for the study area would be either at 240m or 270m with respect to the classification accuracy and the best quality of attribute information can be obtained from these resolutions. Procedures and methodologies developed from this study would be applied to similar kinds and be used as a methodology of identifying and defining an optimum spatial resolution for a given problem.

• Journal of Distribution Science
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• v.10 no.12
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• pp.25-34
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• 2012

Purpose - This study examines college students' perceived choice attributes in traditional markets and the relationship quality. We study the relationships between attributes that common people look for while choosing a store (e.g., product, service, advertising, and atmosphere), consumption emotion, consumer's value, and relationship quality. Research design, data, methodology - In order to verify the relationship between choice attributes and relationship quality, and moderating (i.e., consumption emotion) and mediating effects (i.e., customer value), we collected data from 202 consumers in Gyeonggi province to test the theoretical model and its hypotheses. For this purpose, this study, utilized an empirical methodology. Results - First, contrary to the previous research findings involving college students, this study observed that four factors of store choice attributes at a traditional market were important to consumers in heightening the relationship quality. Specifically, product (β = .608, p < .01), service (β = .351, p < .01), advertising (β = .237, p < .01), and atmosphere (β = .425, p < .01) are significantly related to relationship quality. Second, consumers selected product (β =. 521, p < .01) as the most important attribute. Atmosphere (β = .254, p < .01) and service division (β = .148, p < .05), in this order, are the other important factors in this regard. However, advertising (β = -.112, p = .100) is not statistically significant. To improve and develop the relationship quality with consumers, traditional markets should ensure supply of suitable products and goods, improve store atmosphere by modernizing facilities, and educate merchants to improve their services. Third, the results of the moderating effects, although marginally statistically significant, suggest that for the consumers with low consumption emotion for traditional markets, an affirmative experience of products and store atmosphere heightens their values. In addition, the consumers having low consumption emotion who could promote consumer values were found to improve and develop a marginally significant relationship quality. Finally, the study revealed that the consumer's value exhibited a complete mediation effect in the relationships between service and relationship quality, and advertising and relationship quality and a partial mediation effect in the relationships between product and relationship quality, and atmosphere and relationship quality. Conclusions - Consumer satisfaction is important to increase the competitiveness of traditional markets, and products and store atmosphere are important attributes to increase the relationship quality. Specifically, merchants should supply different products, modernize their facilities, and improve store atmosphere to compete in traditional markets. In addition, traditional markets should provide value and competitive prices to attract consumers, and should maximize the consumer's value and promote the consumption emotion. Traditional markets should evolve to accommodate changes in the consumer's value and invest in not only functional elements but also symbolic elements.

• Proceedings of the Korea Association of Information Systems Conference
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• 2004.05a
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• pp.257-260
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• 2004

소프트웨어 아키텍처는 소프트웨어 컴퍼넌트와 이들 컴퍼넌트들 간의 상호 관계를 나타내는 시스템의 전체적인 구조이다. 이때 완성된 시스템이 품질에 대한 요구를 만족시키는 시스템인지의 여부를 결정하는 아키텍처의 평가가 매우 중요하다. 그러나 평가 과정에서 아키텍처에 대한 부적절하거나 모호한 표현으로 인해 광범위한 응용에서는 않은 제약이 따른다. 그러므로 본 논문에서는 소프트웨어 아키텍처를 평가하기 위해 준비하고, 실행하고, 완료하는 세 가지 단계 제시한다. 이들 단계를 수행함에 따라 품질 속성의 획득에 많은 영향을 주는 아키텍처의 설계 결정을 중심으로 체계적인 아키텍처 평가가 이루어질 수 있다.

• The Research Journal of the Costume Culture
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• v.8 no.2
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• pp.183-196
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• 2000

The purpose of this study was to identify cosemetics purchasing behavior of male college students by clothing involvement. A questionnaire was administered to 246 male collage students living in Taegu and Seoul during September of 1999. Data were analyzed by using frequency, cross tabulation, t-test, χ²-test and factor analysis. The results of this study were as follows : First, the consumers are classified into two categories by clothing involvement ; 65.5% of the highly involved consumers and 34.5% of the lowly involved consumers. Second, the factors of selecting cosmetics were fragrance, quality and price. Third, the major information sources of cosmetics are TV, magazines, outdoor advertisements, newspapers, subway, radio and internet in order of importance. Fourth, high clothing involved group was more fashion oriented and showed more impulsive purchasing attribute.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.101-106
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• 2014

New control charts under repetitive sampling are proposed, which can be used for variables and attributes quality characteristics. The proposed control charts have inner and outer control limits so that repetitive sampling may be needed if the plotted statistic falls between the two limits. Particularly, the new np and variable X-bar control charts under repetitive sampling are considered in detail. The in-control and out-of-control average run lengths are analyzed according to various process shifts. The performance of the proposed control charts is compared with the existing np and the X-bar control charts in terms of the average run lengths.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.31-34
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• 2001

The customer unsatisfaction in the new products exists, though the most of enterprises using QFD. It is mainly caused by the failure of corrective determination of technical importance rating(TIR). To derive the technical importance rating, the impact of the fulfillment of design requirements on the satisfaction of customer requirements must first be quantified. This has been accomplished through the use of a 1-3-9 or a 1-5-9 scale and ignored the peak of the house of quality(HOQ). In this paper we suggested the methodology reflecting effectiveness among engineering characteristics and adjusting the relationship strength between customer attribute(CA) and engineering characteristic (EC), by using limit probability and PCMR(pairwise comparison and median rank). With using this method, the determination of TIR would be more suitable for the voice of customers objectively. Here negative correlation is ignored.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.65-73
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• 2011

In rough set literatures, methods for inducing minimal rules from a given decision table have been proposed. When the decision attribute is ordinal, inducing rules about upward and downward unions of decision classes is advantageous in the simplicity of obtained rules. However, because of independent applications of the rule induction method, inclusion relations among upward/downward unions in conclusion parts are not inherited to the condition parts of obtained rules. This non-inheritance may debase the quality of obtained rules. To ensure that inclusion relations among conclusions are inherited to conditions, we propose two rule induction approaches. The performances of the proposed approaches considering the inclusion relations between conclusions are examined by numerical experiments.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.65-77
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• 2017

The purpose of this paper is to develop a model of level evaluation for data governance that can diagnose and verify level of insufficient part of operating data governance. We expanded the previous study related on attribute indices of data governance and developed a level model of evaluation and items. The model of level evaluation for data governance is the level of evaluation and has items of 400 components. We used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a level evaluation model for data governance at the early phase. This paper will be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.