• 품질경영학회지
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• 제32권3호
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• pp.68-80
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• 2004

This paper purports to uncover the underlying attributes used by customers to gauge service quality. Data was collected by administering questionnaires to 50 respondents and then analyzed by using Multidimensional Scaling methodology. The findings indicate that there are two primary dimensions to service quality. This analysis helped determine us two alternatives to naming the dimensions. Experience properties of service and Price value of the service, or Responsiveness of service provider employees and Reliability of service providers.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2004년도 품질경영모델을 통한 가치 창출
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• pp.639-645
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• 2004

This paper purports to uncover the underlying attributes used by customers to gauge service quality. Data was collected by administering questionnaires to 50 respondents and then analyzed by using Multidimensional Scaling methodology. The findings indicate that there are two primary dimensions to service quality. A considerable analysis helped determine two alternatives to naming the dimensions: Experience properties of service and Price value of the service, or Responsiveness of service provider employees and Reliability of service providers.

• 정보관리학회지
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• 제29권2호
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• pp.45-70
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• 2012

개체들 사이의 관계를 저차원 공간에 매핑하는 다차원척도법을 수행하기 위한 다양한 방법과 알고리즘이 개발되어왔다. 그러나 PROXSCAL이나 ALSCAL과 같은 기존의 기법들은 50개 이상의 개체를 포함하는 데이터 집합을 대상으로 개체 간의 관계와 군집 구조를 시각화하는데 있어서 효과적이지 못한 것으로 나타났다. 이 연구에서 제안하는 군집 지향 척도법 CLUSCAL(CLUster-oriented SCALing)은 기존 방법과 달리 입력되는 데이터의 군집 구조를 고려하도록 고안되었다. 50명의 저자동시인용 데이터와 85개 단어의 동시출현 데이터에 대해서 적용해본 결과 제안한 CLUSCAL 기법은 군집 구조를 잘 식별할 수 있는 MDS 지도를 생성하는 유용한 기법임이 확인되었다.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1135-1143
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• 2007

The singular value decomposition and the spectral decomposition are the useful methods in the area of matrix computation for multivariate techniques such as principal component analysis and multidimensional scaling. These techniques aim to find a simpler geometric structure for the data points. The singular value decomposition and the spectral decomposition are the methods being used in these techniques for this purpose. In this paper, the singular value decomposition and the spectral decomposition are compared.

• 응용통계연구
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• 제30권4호
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• pp.567-578
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• 2017

일반적으로 그룹화된 다변량자료는 다변량 분산분석(multivariate analysis of variance; MANOVA)을 사용하여 그룹 간 차이를 검정할 수 있다. 그러나 만약 다변량 분산분석의 기본적인 가정이 위배되면 이 방법은 적절하지 못하다. 이 경우 다양한 거리로부터 그룹화된 비유사성을 계산한 후 다차원척도법(multidimensional scaling; MDS), 거리분석(analysis of distance; AOD) 그리고 비모수적 기법인 순열검정(permutation test)을 적용하여 문제를 해결할 수 있다. 다차원척도법은 비유사성으로부터 개체들의 좌표를 계산해주며 거리분석은 이 좌표를 활용하여 그룹구조를 파악하는데 유용하다. 특히 비유사성의 측도로 유클리드 거리를 사용하면 거리분석은 다변량 분산분석과 수리적으로 매우 밀접한 연관관계를 맺는다. 따라서 본 연구에서는 그룹화된 비유사성에 다차원척도법과 거리분석을 적용하여 그룹 내와 그룹 간의 구조를 파악하고 순열검정을 위한 새로운 검정통계량을 제안하려 한다. 덧붙여 유클리드 거리를 활용한 비유사성을 통해 거리분석과 다변량 분산분석과의 수리적 연관성을 고찰하고자 한다.

• 응용통계연구
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• 제25권4호
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• pp.613-620
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• 2012

In most cases of multidimensional scaling(MDS), the distances or dissimilarities among units are assumed to be symmetric. Thus, it is not an easy task to deal with asymmetric distances. Asymmetric MDS developed so far face difficulties in the interpretation of results. This study proposes a much simpler asymmetric MDS, that utilizes the notion of "altitude". The analogy arises in mountaineering: It is easier (more difficult) to move from the higher (lower) point to the lower (higher). The idea is formulated as a quantification problem, in which the disparity of distances is maximally related to the altitude difference. The proposed method is demonstrated in three examples, in which the altitudes are visualized by rainbow colors to ease the interpretability of users.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.665-676
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• 2014

As social media draws attention as a business tool, organizations, large or small, are trying to exploit social media in their business. However, lack of understanding the characteristics of each social media led them to develop a naive strategy for dealing with social media. Thus, this study aims to deepen the understanding by comparatively analyzing how social media users perceive (the image of) each social media. Facebook, Twitter, YouTube, Blogs, Communities and Cyworld were chosen for our study and data from 132 respondents were analyzed using multidimensional scaling technique. The results show that there are meaningful differences in users' perception of social media attributes, which are grouped into four; information feature, motivation, promotion tool, usability. It is also analyzed whether such differences can be found between male and female users. (Such differences are also analyzed in both male and female users' perceptions.) Further, we discuss some implications of the research results for both practitioners and researchers.

• 한국식생활문화학회지
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• 제15권1호
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• pp.51-58
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• 2000

This study is designed to 1) understand customers' choice behavior and preference of foodservices in campus and 2) provide recommendation on management strategies for university foodservice manager. Individual interview and focus group interview were used to identify important selection attributes. The questionnaire was developed and distributed to 480 Yonsei university students and statistical data analysis was completed using SPSS WIN/7.5 for descriptive analysis, multidimensional scaling and conjoint analysis. The results of this study were summarized as follows: Students evaluated four foodservices in different ways, and strength/weakness points could be identified from the evaluation patterns. Most students(51.1%) were frequently used 'A' foodservice, though they preferred other foodservices, and cost, mainly, caused the difference. Perceptual map from multidimensional scaling showed that preference and patronage were close with different attributes. Cost was most relatively important attribute to select foodservice in campus from conjoint analysis. Therefore, relative importance of attributes should be considered in customer preference survey for constructing management plan.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권4호
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• pp.427-431
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• 2010

다차원 척도법(multidimensional scaling)은 고차원의 데이터를 낮은 차원의 공간에 매핑(mapping)하여 데이터 간의 유사성을 표현하는 방법이다. 이는 주로 자질 선정 및 데이터를 시각화하는 데 이용된다. 그러한 다차원 척도법 중, 전통 다차원 척도법(classical multidimensional scaling)은 긴 수행 시간과 큰 공간을 필요로 하기 때문에 객체의 수가 많은 경우에 대해 적용하기 어렵다. 이는 유클리드 거리(Euclidean distance)에 기반한 $n{\times}n$ 상이도 행렬(dissimilarity matrix)에 대해 고유쌍 문제(eigenpair problem)를 풀어야 하기 때문이다(단, n은 객체의 개수). 따라서, n이 커질수록 수행 시간이 길어지며, 메모리 사용량 증가로 인해 적용할 수 있는 데이터 크기에 한계가 있다. 본 논문에서는 이러한 문제를 완화하기 위해 GPGPU 기술 중 하나인 CUDA와 분할-정복(divide-and-conquer)기법을 활용한 효율적인 다차원 척도법을 제안하며, 다양한 실험을 통해 제안하는 기법이 객체의 개수가 많은 경우에 매우 효율적일 수 있음을 보인다.

• 한국의류학회지
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• 제14권2호
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• pp.129-136
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• 1990

The purpose of the study was to develope brand positioning map for ladies' ready-to-wear, to find out evaluative criteria in perception and preference to brands, and to persent the relationship between consumer's characteristics and brand preference. Subjects were selected for the housewives of middle and high socioeconomic classes living in Seoul area. A questionnaire including items of life style, self image, similarity between brands, preference degree to brands, and demographic variables was developed for the empirical study. The questionnaire was administrated to 137 housewives during fall in 1989. Data were analyzed by cluster analysis and multidimensional scaling method. The study had two research problems. The first research problem was to construct a brand perceptual map for ladies' ready-to-wear brands, selected for the study The perceptual map was constructed on the basis of brand similarity scores by multidimensional scaling method. As a result, brands were grouped into 4 clusters, and evaluative criteria for perceptual map were found to be fashionability (classic- fashionable) and familiarity (familiar-unfamiliar). The second problem was to construct a brand preference map for ladies' ready-to-wear brands, selected for the study. The preference map was constructed on the basis of brand preference scores by multidimensional scaling method. As a result, the brands were grouped into 4 clusters and evaluative critiera for preference map were found to be fashionability (unfashionable-fashionable) and image to age (mature-young directed). Also was shown the relationship among self image, age, socioeconomic class, and brand preference. The multidimensional scaling method was found to be useful as well as valid instrument for brand positioning research and the result can be utilized for establishing strategies for ladies' ready-to-wear brands.