• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.71-101
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• 2017

Since late 2016, protectionism has been a major trend in world trade with the Great Britain exiting the European Union and the United States electing Donald Trump as the 45th president. Consequently, there has been a huge public outcry regarding the negative prospects of heavy industry firms in Korea, which are highly dependent upon international trade with Western countries including the United States. In light of such trend and concerns, we have tried to predict business performance of heavy industry firms in Korea with data regarding trade policy of the United States. United States International Trade Commission (USITC) levies countervailing duties and anti-dumping duties to firms that violate its fair-trade regulations. In this study, we have performed data analysis with past records of countervailing duties and anti-dumping duties. With results from clustering analysis, it could be concluded that trade policy trends of the Unites States significantly affects the business performance of heavy industry firms in Korea. Furthermore, we have attempted to quantify such effects by employing long short-term memory (LSTM), a popular neural networks model that is well-suited to deal with sequential data. Our major contribution is that we have succeeded in empirically validating the intuitive argument and also predicting the future trend with rigorous data mining techniques. With some improvements, our results are expected to be highly relevant to designing regulations regarding heavy industry in Korea.

• The Journal of Information Systems
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• v.30 no.1
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• pp.21-44
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• 2021

Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.265-274
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• 2017

This paper examines the problems of big data analysis education and suggests ways to solve them. Big data is a trend that the characteristic of big data is evolving from V3 to V5. For this reason, big data analysis education must take V5 into account. Because increased uncertainty can increase the risk of data analysis, internal and external structured/semi-structured data as well as disturbance factors should be analyzed to improve the reliability of the data. And when using opinion mining, error that is easy to perceive is variability and veracity. The veracity of the data can be increased when data analysis is performed against uncertain situations created by various variables and options. It is the node analysis of the textom(텍스톰) and NodeXL that students and researchers mainly use in the analysis of the association network. Social network analysis should be able to get meaningful results and predict future by analyzing the current situation based on dark data gained.

• Health Policy and Management
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• v.23 no.1
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• pp.78-89
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• 2013

This study empirically analyze efficiency and productivity changes of public hospitals of Korea using data envelopment analysis/Window model and global Malmquist indices model. We use the ten-year data from 2001 to 2010 of 30 regional public hospitals listed database from the Association of Korean Regional Public Hospitals. The main focuses are to reveal whether the technical inefficiency are improved as time goes by, and efficiency and productivity are affected by environmental factors. The results can be summarized as follows. First, the efficiencies of public hospitals rise in trend as time passes. Second, regional public hospitals show the different average efficiencies according to their regional type, hospital type, operational type, medicaid type, and demand and supply conditions by Mann-Whitney U-tests. Third, technical efficiency changes mainly contribute to 4.4% annual average growth rate of productivity of regional public hospitals during that period. Our findings have some policy implications. It is confirmed that there exist some environmental inefficiencies, and those inefficiencies can not be overcome through just improving the inner management system. Thus, policy and institutional changes are necessary for regional public hospitals to improve efficiency and productivity overall.

• Journal of the Geological Society of Korea
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• v.54 no.6
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• pp.631-640
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• 2018

To understand the formation and evolution of a sedimentary basin in basin analysis and modelling studies, it is important to analyze the thickness and age range of sedimentary layers infilling a basin. Because the compaction effect reduces the thickness of sedimentary layers during burial, basin modelling studies typically restore the reduced thickness using the relation of porosity and depth (compaction trend). Based on the compilation plots of published compaction trends of representative sedimentary rocks (sandstone, shale and carbonate), this study estimates the compaction trend ranges with exponential curves and equations. Numerical analysis of sedimentary compaction is performed to evaluate the variation of porosity and layer thickness with depth at key curves within the compaction trend ranges. In sandstone, initial porosity lies in a narrow range and decreases steadily with increasing depth, which results in relatively constant thickness variations. For shale, the porosity variation shows two phases which are fast reduction until ~2,000 m in depth and slow reduction at deeper burial, which corresponds to the thickness variation pattern of shale layers. Carbonate compaction is characterized by widely distributed porosity values, which results in highly varying layer thickness with depth. This numerical compaction analysis presents quantitatively the characteristics of porosity and layer thickness variation of each lithology, which influence on layer thickness reconstruction, subsidence and thermal effect analyses to understand the basin formation and evolution. This work demonstrates that the compaction trend is an important factor in basin modelling and underlines the need for appropriate application of porosity data to produce accurate analysis outcomes.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.108-113
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• 2024

The purpose of this study is to analyze user perceptions of tourism platforms through big data. Data were collected from Naver, Daum, and Google as big data analysis channels. Using semantic network analysis with the keyword 'tourism platform,' a total of 29,265 words were collected. The collection period was set for two years, from August 31, 2021, to August 31, 2023. Keywords were analyzed for connected networks using TexTom and Ucinet programs for social network analysis. Keywords perceived by tourism platform users include 'travel,' 'diverse,' 'online,' 'service,' 'tourists,' 'reservation,' 'provision,' and 'region.' CONCOR analysis revealed four groups: 'platform information,' 'tourism information and products,' 'activation strategies for tourism platforms,' and 'tourism destination market.' This study aims to expand and activate services that meet the needs and preferences of users in the tourism field, as well as platforms tailored to the changing market, based on user perception, current status, and trend data on tourism platforms.

• Journal of the Korean Society of School Health
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• v.17 no.1
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• pp.85-95
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• 2004

Objectives : The aim of this study was to identify the trend of school health research by analyzing articles related to school health for the last 10 years. this information can be used to guide research direction for the future. Methods : This study is a descriptive study that analyzed annual data. using an objective frame of evaluation about the methodology and research domain in each paper, all the papers included in the journals concerning school health from January 1993 to December 2000 were analyzed. The data was processed statistically by frequency and percentage. Results : 455 papers in 9 journals related to school health were published. The Journal of the Korean Society of School Health had 204 articles, the highest number of any journal. most of the articles were descriptive, but the number of experimental studies increased over time. the most common research subjects were students were the greatest ones, but the trend to study both parents and teachers increased near the end of the sampling period. the most common selection of subjects appeared to be based on convenience, but probability sampling gradually increasing annually. the most common research instrument was the questionnaire and the reliability and the validity of instruments were described in approximately half of the studies. The survey was the most commonly used method of data collection. The papers that met ethical issue in data collection were less than those that did not. In addition, the papers that provided the rationale for the calculation of sample size were less than those that did not. parametric statistics were the main methods of data analysis, but some advanced statistics were used more often than simple descriptive statistics in the latter part of the sampling period. In general, limit of the studies were not frequently mentioned but more recommendations were made. regarding the characteristics of the research area, the assesment domain was remarkable. The rate of school health problem assesment was the highest among research subjects. Sex- related subjects were the highest in detail research subjects. Conclusions : The research of school health has increased quantitatively, but it is difficult to ascertain its qualitative development. Therefore, on the basis of the research completed up until now, more school-based intervention studies and longitudinal studies need to be another target for the evaluation of the effects of the school health service. as well, policy suggestion through international and cross-sectional comparison studies are needed to assist in the establishment of the long term direction of school health.

• Journal of the Korean Society of Costume
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• v.52 no.5
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• pp.31-45
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• 2002

In this paper. the focus is laid on identifying preferred wedding dress image and its co-relationship with self image of female university students. the biggest potential customer group in the industry. As for the research method. it conducted both review of literature and empirical research method. Through the former approach, four main research questions were derived : 1) What is the preferred wedding dress image of female university students\ulcorner 2) What is the relationship between real self-image and preferred wedding dress image\ulcorner and 3) that between ideal self-image and preferred wedding dress image\ulcorner 4)What is the relationship between the consistency level of the two self-images and preferred wedding dress image\ulcorner In the empirical mode of research, 404 surveys were counted in the final analysis among 450 questionnaires completed by female undergraduate students in Seoul and Chun-an city. Collected data analyzed using factor analysis. frequency analysis. descriptive analysis. scheffe test. multiple-regression analysis and t-test. Results are as follows: first, the sophisticated image was most preferred among female students, followed by elegant splendor. lovable and chaste, feminine and decorative, and characteristic and sexy image. This result indicates how wedding dress trend has a keen sensibility to general fashion trend just like the trend of outfits for everyday life. Secondly, the research results indicated consistent level of co-relationship among the real and ideal self-image and the preference of wedding dress image. And the last the level of consistence between the ideal self-image and the real self-image directly related to the preference level of wedding dress image, showing almost no significance.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.365-371
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• 2010

The research purpose of this paper is to afford a base data and a research direction for the effective conflict management. For this, this article analyzed the conflict research trend in the field of public administration. According to empirical analysis, the main research results are as follows. First, a published article number go on increasing in proportion to publication year. Second, a one-research paper have showed 71.2% of all papers because of limited researcher in the field of conflict research. Third, research paper which did not receive a research expenses have showed 73.1% of all papers. Fourth, research paper that used a empirical analysis and case study have showed 80.8% of all papers in the methodology of conflict. Fifth, the research purpose that aimed to propose an alternative and practical analysis have showed 91.3% of all papers. Sixth, about the research contents, it have showed each 50.0%(administration/institution and facilities location), 80.8%(interorganization conflict), 76.0%(intergovernment, between government and public), 64.5%(with local government) in a field, a level, a party, a relation of the conflict.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.3
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• pp.37-53
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• 2019

The purposes of this study were to investigate Chinese female consumers' shopping orientation and clothing shopping behaviors on the internet and to find the differences in internet shopping behaviors of consumer groups segmented by clothing shopping orientation. The subjects were 417 women in their 20s and 30s from the Gillim Province, China. The research method was a survey, and the questionnaire consisted of a clothing shopping orientation subscale, clothing, their shopping behaviors via the internet, and the subjects' demographic characteristics. For data analysis, a frequency analysis, a cross-tab analysis, a factor analysis, a cluster analysis, ANOVA, and Duncan's multiple range test were performed. The results of this study were as follows. The clothing shopping orientation was derived using five factors (trend pursuit, pleasure pursuit, brand pursuit, economic pursuit, and convenience pursuit). Chinese female consumers were classified into three groups (hedonic group, ambivalent group, and practical group) by clothing shopping orientation. These three groups showed many significant differences in their clothing shopping behaviors on the internet. The hedonic group preferred the specialty and cross-border shopping malls, and considered product quality and trend as their main purchase motives. The ambivalent group considered the convenience of the purchase and trend as important motives as compared to the other groups, and they use more various product selection criteria. The practical group considered low price and convenience and the search simplicity of various products as major purchase motives. In addition, the hedonic and ambivalent groups had a higher purchase satisfaction and purchase intention from internet shopping than the practical group. This study suggested that clothing shopping orientation is one of the useful segmentation variables and fashion marketers needed to establish differentiated marketing strategies for each consumer group that is segmented by clothing shopping orientation.