• Knowledge Management Research
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• v.18 no.1
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• pp.67-81
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• 2017

As the important breakthrough continues in the field of machine learning and artificial intelligence recently, there has been a growing interest in the analysis and the utilization of the big data which constitutes a foundation for the field. In this background, while the economic value of the data held by the corporates and public institutions is well recognized, the research on the evaluation of its economic value is still insufficient. Therefore, in this study, as a part of the economic value evaluation of the data, we have conducted the economic value measurement of the data generated through the small business guarantee program of Korean Federation of Credit Guarantee Foundations (KOREG). To this end, by examining the previous research related to the economic value measurement of the data and intangible assets at home and abroad, we established the evaluation methods and conducted the empirical analysis. For the data value measurements in this paper, we used 'cost-based approach', 'revenue-based approach', and 'market-based approach'. In order to secure the reliability of the measured result of economic values generated through each approach, we conducted expert verification with the employees. Also, we derived the major considerations and issues in regards to the economic value measurement of the data. These will be able to contribute to the empirical methods for economic value measurement of the data in the future.

• Journal of Korea Trade
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• v.25 no.7
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• pp.19-40
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• 2021

Purpose - This paper's purpose is to investigate how foreign ownership and innovation affect firm value. Design/methodology - Firm innovation is defined as operational efficiency, which is calculated by adopting data envelopment analysis (DEA). Additionally, R&D intensity is included as a measure of innovation in the analysis. We used firm-level data from manufacturing companies in Korea. The sample comprised 3,753 firm-year observations for every year in the period 2003-2017. Findings - We found that foreign ownership and innovation are positively related to firm value (Tobin's Q). Foreign ownership moderates innovation's contribution to firm value, implying that foreign ownership may enhance the value relevance of firm innovation. In addition, we found that firm innovation partially mediates the relationship between foreign ownership and firm value. Originality/value - This highlights the important role of foreign investors' monitoring; wherein foreign investors enhance firm value by facilitating firm innovation. Our results suggest that foreign ownership can be crucial for innovation and may serve to address weak ownership structures.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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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.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.763-774
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• 2006

The purpose of this study is to identify relationship among service quality, service value and customer satisfaction of food service industries. The respondents included 120 customers of K-restaurant in the survey. Data were analyzed by confirmatory factor analysis and cause-effect analysis among the constructs. After research model testing, the following results was obtained : Service Value was influenced directly and positively by the service quality. And customer satisfaction was influenced directly and positively by the service value. But customer satisfaction was not influenced directly and positively by the service quality.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.315-321
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• 2011

Gene expression microarray data often include multiple missing values. Most gene expression analysis (including gene clustering analysis); however, require a complete data matric as an input. In ordinary clustering methods, just a single missing value makes one abandon the whole data of a gene even if the rest of data for that gene was intact. The quality of analysis may decrease seriously as the missing rate is increased. In the opposite aspect, the imputation of missing value may result in an artifact that reduces the reliability of the analysis. To clarify this contradiction in microarray clustering analysis, this paper compared the accuracy of clustering with and without imputation over several microarray data having different missing rates. This paper also tested the clustering efficiency of several imputation methods including our propose algorithm. The results showed it is worthwhile to check the clustering result in this alternative way without any imputed data for the imperfect microarray data.

• The Research Journal of the Costume Culture
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• v.23 no.3
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• pp.468-483
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• 2015

Fast fashion brand marketers should develop marketing strategies that effectively satisfy the values consumers seek when purchasing fast fashion brands. This study aimed to identify the consumption value factors of fast fashion brands and to reveal the value factors that influence attitudes toward purchasing fast fashion brands. Data were gathered by surveying university students in the Seoul metropolitan area using convenience sampling. Three hundred and five questionnaires were used in the statistical analysis, which consisted of exploratory factor analysis using SPSS and confirmatory factor analysis and path analysis using AMOS. The factor analysis revealed the following six value factors: Emotional value, social value, price/value for money, durability value, eco-value, and consistency value. The fit statistic for the six-factor model was quite acceptable. Two of the six value factors, emotional value and price/value for money, positively influenced attitudes toward purchasing fast fashion brands. The overall fits of the revealed model suggested that the model fit the data well. The results suggested that fast fashion marketers need to understand the value factors that motivate consumers to purchase fast fashion brands. In addition, marketers should focus their efforts on satisfying emotional value and price/value for money in order to establish their brands in the increasingly competitive fast fashion industry.

• Journal of Information Technology Services
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• v.21 no.1
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• pp.145-161
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• 2022

The data is a key catalyst for the development of the fourth industry, and has been viewed as an essential element of the new industry, with technology convergence such as artificial intelligence, augmented/virtual reality, self-driving and 5 G. This will determine the price and value of the data as the user uses data in which the data is based on the context of the situation, rather than the data itself of the past supplier-centric data. This study began with, what factors will increase the value of data from a user perspective not a supplier perspective The study was limited to public data and users conducted research on users using data, such as analysis or development based on data. The study was designed to gauge the value of data that was not studied in the user's perspective, and was instrumental in raising the value of data in the jurisdiction of supplying and managing data.

• Journal of Ocean Engineering and Technology
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• v.34 no.1
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• pp.26-36
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• 2020

An extreme value analysis of metocean data which include wave, wind, and current data is a prerequisite for the operation and survival of offshore structures. The purpose of this study was to provide information about the return wave, wind, and current values for the Barents Sea using extreme value analysis. Hindcast datasets of the Global Reanalysis of Ocean Waves 2012 (GROW2012) for a waves, winds and currents were obtained from the Oceanweather Inc. The Gumbel distribution, 2 and 3 parameters Weibull distributions and log-normal distribution were used for the extreme value analysis. The least square method was used to estimate the parameters for the extreme value distribution. The return values, including the significant wave height, spectral peak wave period, wind speed and current speed at surface, were calculated and it will be utilized to design offshore structures to be operated in the Barents Sea.

• Journal of the Korean Statistical Society
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• v.25 no.1
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• pp.49-66
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• 1996

The singular value decomposition is one of the most useful methods in the area of matrix computation. It gives dimension reduction which is the centeral idea in many multivariate analyses. But this method is not resistant, i.e., it is very sensitive to small changes in the input data. In this article, we derive the resistant version of singular value decomposition for principal component analysis. And we give its statistical applications to biplot which is similar to principal component analysis in aspects of the dimension reduction of an n x p data matrix. Therefore, we derive the resistant principal component analysis and biplot based on the resistant singular value decomposition. They provide graphical multivariate data analyses relatively little influenced by outlying observations.

• Human Ecology Research
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• v.59 no.2
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• pp.245-259
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• 2021

The purpose of this study was to analyze big data to identify the sub-dimensions of ethical consumption, as well as the consumption value associated with ethical consumption that changes over time. For this study, data were collected from Naver and Daum using the keyword 'ethical consumption' and frequency and matrix data were extracted through Textom, for the period January 1, 2016, to December 31, 2018. In addition, a two-way mode network analysis was conducted using the UCINET 6.0 program and visualized using the NetDraw function. The results of text mining show increasing keyword frequency year-on-year, indicating that interest in ethical consumption has grown. The sub-dimensions derived for 2014 and 2015 are fair trade, ethical consumption, eco-friendly products, and cooperatives and for 2016 are fair trade, ethical consumption, eco-friendly products and animal welfare. The results of deriving consumption value keywords were classified as emotional value, social value, functional value and conditional value. The influence of functional value was found to be growing over time. Through network analysis, the relationship between the sub-dimensions of ethical consumption and consumption values derived each year from 2014 to 2018 showed a significantly strong correlation between eco-friendly product consumption and emotional value, social value, functional value and conditional value.