• The Journal of Economics, Marketing and Management
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• v.11 no.5
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• pp.45-55
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• 2023

Purpose: As one of the continuous studies on the offline distribution industry, the purpose of this study is to find ways for offline stores to respond to the growth of online shopping by identifying research trends on department stores. Research design, data and methodology: To this end, this study conducted word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and dynamic topic modeling using Python 3.7 on a total of 551 English abstracts searched with the keyword 'department store' in scienceON as of October 10, 2022. Results: The results of word frequency analysis and co-occurrence frequency analysis revealed that research related to department stores frequently focuses on factors such as customers, consumers, products, satisfaction, services, and quality. BERTopic and LDA analyses identified five topics, including 'store image,' with 'shopping information' showing relatively high interest, while 'sales systems' were observed to have relatively lower interest. Conclusions: Based on the results of this study, it was concluded that research related to department stores has so far been conducted in a limited scope, and it is insufficient to provide clues for department stores to secure competitiveness against online platforms. Therefore, it is suggested that additional research be conducted on topics such as the true role of department stores in the retail industry, consumer reinterpretation, customer value and lifetime value, department stores as future retail spaces, ethical management, and transparent ESG management.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.263-287
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• 2021

Researches on inequality in Korean society has been sporadically conducted in various areas. In this study, research trend related to inequality was analyzed through basic statistical analysis, co-occurrence analysis, and main path analysis using articles related to inequality from Korea citation index. In basic statistical analysis, key authors, journals, and articles are identified. In co-occurrence analysis, income inequality, educational inequality, welfare inequality, and policy on inequality were identified as main topics. Main path analysis showed two research trends after 2004. One was research trend on economic inequality, and the other was on health inequality and social structural inequality.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.33-38
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• 2021

The convergence trend is the core of the 4th industrial revolution, and due to such expectations and possibilities, various countermeasures are being sought in diverse fields. This study conducted a quantitative analysis to identify the trend of convergence research over the past 10 years. Specifically, major research keywords were extracted, word cloud techniques were applied, and visualized to identify trends in academic research on convergence. To this end, research papers from 2012 to 2020 published in journal of digital convergence were investigated. The analysis period was divided into two periods: the former 4 years(2012-2015) and the latter 4 years(2016-2019) to confirm the difference in research trends. In addition, the research papers of 2020 were analyzed in order to more clearly understand the changes in the research trend of the last year due to the COVID-19. The results of this study are significant in that they can be used as useful basic data for future research and to understand research trends as keywords in the field of convergence.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.65-73
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• 2013

In the simulation output analysis, bootstrap method is an applicable resampling technique to insufficient data which are not significant statistically. The moving block bootstrap, the stationary bootstrap, and the threshold bootstrap are typical bootstrap methods to be used for autocorrelated time series data. They are nonparametric methods for stationary time series data, which correctly describe the original data. In the simulation output analysis, however, we may not use them because of the non-stationarity in the data set caused by the trend such as increasing or decreasing. In these cases, we can get rid of the trend by differencing the data, which guarantees the stationarity. We can get the bootstrapped data from the differenced stationary data. Taking a reverse transform to the bootstrapped data, finally, we get the pseudo-samples for the original data. In this paper, we introduce the applicability of bootstrap methods to the time series data having trend, and then verify it through the statistical analyses.

• The Journal of Economics, Marketing and Management
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• v.10 no.6
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• pp.27-37
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• 2022

Purpose: The purpose of this study is to derive various ways to realize customer satisfaction for the development of the service industry by exploring research trends related to customer satisfaction, which is presented as an important goal in the service industry. Research design, data and methodology: To this end, 1,456 papers with English abstracts using scienceON were used for analysis. Using Python 3.7, word frequency and co-occurrence analysis were confirmed, and topics related to research trends were classified through BERTopic and LDA. Results: As a result of word frequency and co-occurrence frequency analysis, words such as quality, intention, and loyalty appeared frequently. As a result of BERTopic and LDA, 11 topics such as 'catering service' and 'brand justice' were derived. As a result of trend analysis, it was confirmed that 'brand justice' and 'internet shopping' are emerging as relatively important research topics, but CRM is less interested. Conclusions: The results of this study showed that the 7P marketing strategy is working to some extent. Therefore, it is proposed to conduct research related to acquisition of good customers through service price, customer lifetime value application, and customer segmentation that are expected to be needed for the development of the service industry.

• Fashion & Textile Research Journal
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• v.8 no.4
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• pp.407-412
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• 2006

In order to check ordinary trend of a research for old ages, it was collected and analyzed against old ages. Out of a research papers from 1995 to 2005 issued for 6 scientific journals in clothing and textiles areas which were listed on KOREA RESEARCH FOUNDATION. The results were as follows. First, the research papers for 11 years from surveyed scientific journals were totally 5,711 papers, and It were only 71 papers for old ages to be reviewed and surveyed, which slightly occupied 1.24% from whole papers. Second, yearly ranges of research paper against old ages were shown to be down-trend, as it recorded 2.75% in 1995, however it falls on 0.77% in terms of the increasing aspect of clothing and textiles research paper numbers. Third, a paper for each research areas ranged in turn, as clothing construction, fashion merchandising socio-psychology of clothing, etc. If we see in detail area, the research for somatotype and role occupied 37.4% from all researches against old ages. Accordingly it needs more various kinds of study. Fourth, The Koreav Society of Clothing and Textiles paper occupied 40.8% from whole scientific journals, which was obviously shown. Fifth, each sex distribution for researched old ages noted almost old women (77.5%), but cover 9.9% for old men. Therefore it required much more researches for old men, we thought.

• Health Policy and Management
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• v.33 no.3
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• pp.363-369
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• 2023

The term "catastrophic health expenditure" means assessing the extent to which medical costs cause financial hardship for households. The aim of this research is to analyze the percentage of households that faced severe financial strain due to medical expenses from 2006 to 2021. This was achieved by utilizing data obtained from the National Survey of Tax and Benefit (NaSTaB), Korea Health Panel (KHP), and Households Income and Expenditure Survey (HIES). A trend analysis was conducted to examine the percentage of households that experienced catastrophic healthcare expenses. The households that experienced the catastrophic health expenditure was 2.49% in 2021 using the NaSTaB data. The trend analysis yielded a statistically significant result, indicating a decreasing trend (annual percent change [APC], -4.79; p<0.0001) in the proportion of households facing catastrophic health expenditures. Also, the results of the 2019 KHP and the 2021 HIES showed 1.09% and 2.44% for the households that experienced catastrophic health expenditure. The trend was increased according to the KHP (APC, 0.55; p=0.0004) and the HIES (APC, 7.04; p<0.0001). As a result, this study proposes that sustained attention and further interventions are necessary to ease the economic pressure caused by catastrophic health expenses, particularly for low-income households.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.65-82
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• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• Journal of Families and Better Life
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• v.28 no.5
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• pp.197-208
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• 2010

This study examines the 'Attitude towards Money' research trends and suggests future research issues and implications through a contents analysis. To accomplish the study object, 4 analysis categories were selected based on reference study to review the research subject, methods of data collection, research objects, and an analysis of the methods, found in 31 articles in journals and dissertations from 1996 to 2009. The were made in early 1990, (an increase in related research since 2000); however, the object of study is too limited, with an overemphasis on research methods and quantitative research methods. The research method of most articles was mainly limited to the quantitative study. Based on the results, research directions and research limitations were suggested for future leisure research.

• The Journal of Economics, Marketing and Management
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• v.10 no.6
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• pp.1-7
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• 2022

Purpose: The purpose of this study is identifying the research trends of degree papers related to the beauty industry and providing information which can contribute to the development of the domestic beauty industry and the direction of various research about beauty industry. Research design, data and methodology: This study used 154 academic papers and 189 academic papers with English abstracts out of 299 academic papers. All of these papers were found by searching for the keyword "beauty industry" in ScienceON on August 15, 2022. For the analysis, BERTopic and LDA (Latent Dirichlet Allocation) analysis were conducted using Python 3.7. Also, OLS regression analysis was conducted to understand the annual increase and decrease trend of each topic derived with trend analysis. Results: As a result of word frequency analysis, the frequency of satisfaction, management, behavior, and service was found to be high. In addition, it was found that 'service', 'satisfaction' and 'customer' were frequently associated with program and relationship in the word co-occurrence frequency analysis. As a result of topic modeling, six topics were derived: 'Beauty shop', 'Health education', 'Cosmetics', 'Customer satisfaction', 'Beauty education', and 'Beauty business'. The trend analysis result of each topic confirmed that 'Beauty education' and 'Health education' are getting more attention as time goes by. Conclusions: The future studies must resolve the extreme polarization between the structure of the small beauty industry and beauty stores. Furthermore, the researches have to direct various ways to create the performance of internal personnel. The ways to maximize product capabilities such as competitive cosmetics and brands are also needed attentions.