• Korea Trade Review
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• v.47 no.6
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• pp.55-69
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• 2022

Within the worse of the environment, Climate change caused by global warming is becoming serious around the world, and green logistics to pursue sustainable development in the logistics sector are receiving more and more attention. Along with the acceleration of the global economy, eco-friendly issues are playing an increasingly important role in the logistics industry, and various policy measures are being pursued to establish the green logistics system. This study aims to analyze research trends in eco-friendly logistics, and the SNA methodology was applied by extracting keywords from 518 domestic and foreign papers from 2013 to August 2022. The period is divided into three stages: 2013-2015, 2016-2019, and 2020-2022, and 'logistics' and 'sustainable development' were derived as top logistics eco-friendly keywords at all stages. Besides, In the first stage(2013-2015), the term 'environmental performance' and 'freight transport' attracted the attention of scholars. In the second stage(2016-2019), keywords such as 'third-party logistics' and 'lean logistics' have attracted the attention of scholars. In the third stage(2020-2022), the 'internet of things' and 'circular economy' received the attention of scholars. In line with the growth of the economy, it was confirmed that research related to eco-friendly logistics is gradually expanding to a sustainable concept. Based on this study, it is possible to grasp the research trends of the academic community to cope with recent environmental changes and provides reference materials to consider future research directions.

• The Research Journal of the Costume Culture
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• v.28 no.4
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• pp.562-571
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• 2020

Intermedia refers to the convergence of media. The advance of intermedia has not only facilitated the delivery of brand messages in contemporary fashion shows but also facilitated interactive communication. This study investigated the mediating roles played by various media in fashion and fashion shows, focusing on the phenomenon of intermedia in contemporary fashion shows. To investigate the impact of intermedia on contemporary fashion shows, we conducted a social network analysis-a promising approach for research into fashion trends. Analyzing 159 fashion-related articles published in the 2000s, we extracted intermedia-related words (n=253). The relation-ships between keywords made an analysis of between centrality, and cluster variables applied Clauset-Newman-Moore by using KrKwic and NodeXL programs. The results of the between centrality analysis indicated that the most important factors in contemporary fashion shows are "models" and "stages." We found that the impacts of intermedia on contemporary fashion shows can be divided into four categories: "model performance," "symbolic stage management," "new media utilization," and "convergence in arts." Our analysis thus identified considerable synergy between the characteristics of intermedia and contemporary fashion shows. These results have found intermedia-related commonalities in intermedia and fashion show, and this might increase customer interest in fashion, a positive outcome for the fashion industry.

• Journal of the Korean Society for Library and Information Science
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• v.42 no.4
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• pp.243-268
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• 2008

This study considers the availability, accessibility, and efficacy of social services for migrant workers. First, it examines migrant workers needs and how they choose to fulfill these. Second, this study grasps about how they can connect the social services and what constructive peculiarities social networks they have by using SNA(Social Network Analysis) it is revealed that migrant workers rely more on informal support groups such as family, friends, co-workers, etc. rather than formal support networks, e.g. those provided by the state. This tendency is demonstrated especially, Libraries as formal supporting organization have no connection related with other organizations. It shows that they have role limited as a supporter of giving information and knowledge in a public.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.97-112
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• 2021

Purpose: The purpose of this paper is to analyze the technology convergence and its characteristics, focusing on the defense technologies in South Korea. Methods: Patents applied by the Agency for Defense Development (ADD) during 1979~2019 were utilized in this paper. Information Entropy analysis has been conducted on the patents to analyze the usability and potential for development. To analyze the trend of technology convergence in defense technologies, Social Network Analysis(SNA) and Association Rule Mining Analysis were applied to the co-occurrence networks of International Patent Classification (IPC) codes. Results: The results show that sensor, communication, and aviation technologies played a key role in recent development of defense science and technology. The co-occurrence network analysis also showed that the convergence has gradually enhanced over time, and the convergence between different technology sectors largely emerged, showing that the convergence has been diversified. Conclusion: By analyzing the patents of the defense technologies during the last 30 years, this study presents the comprehensive perspectives on trends and characteristics of technology convergence in defense industry. The results of this study are expected to be used as a guideline for decision making in the government's R&D policies in defence industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3571-3587
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• 2021

For accurately analysing and forecasting the social networks of China's political, economic and social power elites, it is necessary to develop a database that collates their information. The development of such a database involves three stages: data definition, data collection and data quality maintenance. The present study recommends distinctive solutions in overcoming the challenges that occur in existing comparable databases. We used organizational and event factors to identify the Chinese power elites to be included in the database, and used their memberships, social relations and interactions in combination with flows data collection methodologies to determine the associations between them. The system can be used to determine the optimal relationship path (i.e., the shortest path) to reach a target elite and to identify of the most important power elite in a social network (e.g., degree, closeness and eigenvector centrality) or a community (e.g., a clique or a cluster). We have used three social network analysis tools (i.e., R, UCINET and NetMiner) in order to find the important nodes in the network. We compared the results of centrality rankings of each tool. We found that all three tools are providing slightly different results of centrality. This is because different tools use different algorithms and even within the same tool there are various libraries which provide the same functionality (i.e., ggraph, igraph and sna in R that provide the different function to calculate centrality). As there are chances that the results may not be the same (i.e. centrality rankings indicating the most important nodes can be varied), we recommend a comparison test using different tools to get accurate results.

• Human Ecology Research
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• v.60 no.1
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• pp.1-20
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• 2022

This paper presents a social network analysis of changes in Home Economics education content loaded on YouTube before and after the outbreak of COVID-19. From January 1, 2008 to June 30, 2021, a basic analysis was conducted of 761 Home Economics education videos loaded on YouTube, using NetMiner 4.3 to analyze important keywords and the centrality of video titles and full texts. Before COVID-19, there were 164 Home Economics education videos posted on YouTube, increasing significantly to 597 following the emergence of the pandemic. In both periods, there was more middle school content than high school content. The content in the child-family field was the most, and the main keywords were youth and family. Before COVID-19, a performance evaluation indicated that the proportion of student content was high, whereas after the outbreak of the disease, teacher content increased significantly due to the effect of distance learning. However, compared with video use, the self-expression and participation of users were lower in both periods. The centrality analysis indicated that in the title, 'family' exhibited a high degree of both centrality and eigenvector centrality over the entire period. Degree centrality of the video title was found to be high in the order of class, online, family, management, etc. after the outbreak of COVID-19, and the connection of keywords was strong overall. Eigenvector centrality indicated that career, search, life, and design were influential keywords before COVID-19, while class, youth, online, and development were influential keywords after COVID-19.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.165-173
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• 2021

The purpose of this study was to provide directions to help enter and expand long-distance routes by analyzing the characteristics of AirAsia X's network construction with Malaysia Airlines. To this end, long-distance route data was extracted from the OAG Schedule Analyzer and the network was analyzed on a two-period basis using SNA. Since AirAsia X's entry into long-range routes, Malaysia Airlines has steadily reduced its routes across the entire region. On the other hand, it is analyzed that AirAsia X is building an expanded network by increasing its network in Northeast Asia instead of ultra-long range routes. Studies have shown that LCCs also have potential growth in the long-distance route market of less than 7,000 km. The results of this study may help LCC establish a long-distance market entry and network deployment strategy.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.117-127
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• 2020

Recently, proving insurance fraud has become increasingly difficult because it occurs intentionally and secretly via organized and intelligent conspiracy by specialists such as medical personnel, maintenance companies, insurance planners, and insurance subscribers. In the case of car accidents, it is difficult to prove intentions; in particular, an insurance company with no investigation rights has practical limitations in proving the suspicions. This paper aims reveal that the detection of organized and conspired insurance fraud, which had previously been difficult, could be dramatically improved through conspiring insurance fraud detection modeling using social network analysis and visualization of the relation between suspected group entities and by seeking developmental research possibilities of data analysis techniques.

• The Journal of Bigdata
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• v.6 no.1
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• pp.1-12
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• 2021

The rapid growth of mobile-based online shopping and the appearance of untact business initiated by COVID-19 has led to an explosive increase in demand for logistics services such as delivery services. In order to respond to the rapidly growing demand, most logistics and distribution companies are working to improve customer service levels through the establishment of a full-filament center in the city center. However, due to social factors such as high land prices and traffic congestion, it becomes more difficult to establish the logistics facilities in the city center. In this study, it has been proposed the way to choose the candidate locations for the shared distribution centers among the space nearby the tall-gate which can be idle after the smart tolling service is widely extended. In order to evaluate the candidate locations, it has been evaluated the centralities of all candidates using social network analysis (SNA). To understand the result considering the characteristics of centrality, the network structure was regenerated based on the distance and the traveling time, respectively. It is possible to refer the result of evaluation based on the cumulative relative importance to choose the best set of candidates.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.155-164
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• 2017

While many countries are implementing various policies regarding the logistics network in Eurasia, China has presented "the Belt and Road" Initiative, a development strategy that focuses on connectivity and close cooperation between China and Eurasia. With more than 60 countries participating in the project, China is expected to have a major influence on logistical infrastructure development in Eurasia. This study analyzed the railway stations network using social network analysis (SNA) methodology. We collected data from major railway lines in Eurasia (TAR, TEN-T, TRACECA, GMS) and established a network of 994 railway stations in 65 countries. This study presented the general characteristics of major railway stations from the perspective of SNA and compared the Chinese network with Eurasian networks. To review the railway networks in China and Eurasia, the top 30 stations were selected based on degree centrality and betweenness centrality. Top "degree centrality" stations included Bangkok (Thailand), Tbilisi (Georgia), Baku (Azerbaijan), Kunming (China), and Bucharest (Romania). Top "betweenness centrality" stations were Baku and Alyat (Azerbaijan), Baoji and Turpan (China), Qarshi (Uzbekistan), and Kas (Turkey). In China, Kunming, Nanning, and Gejiu stations have higher degree centrality while betweenness centrality was higher in Baoji, Kunming, and Lanzhou stations. "The Belt and Road" project advocated by China envisions expansion of transportation infrastructure connections throughout Eurasia, but more emphasis is likely to be placed on connectivity that benefits China. In this regard, studies on key bases of international logistics need to consider relative significance within the Chinese network.