• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.181-191
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• 2024

Ports play a crucial role in the complex global supply chain. While many researchers have used social network analysis (SNA) to study active networks, there is a lack of SNA cohesion analysis specifically related to logistics and trade. Therefore, this study aims to identify time-series structural changes in all domestic import and export logistics networks, including regions, ports, and airports, by utilizing techniques such as k-core and community analysis. To carry out this analysis, we rely on data from the Korea Customs Service's Import and Export Logistics Statistical Yearbook spanning from 2004 to 2022. The findings from the k-core and community analysis indicate that the cohesion of the domestic import and export logistics network has continuously strengthened over time. Moreover, it reveals that regions, ports, and airports are becoming more cohesive and homogeneous, with Busan Port emerging as the central hub of a large community. These insights are expected to enhance our understanding of global logistics dynamics and contribute to the development of policies and sustainable import and export logistics processes.

• Proceedings of the Korean Association for Survey Research Conference
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• 2005.12a
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• pp.187-220
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• 2005

The purpose of this study is to analyze supporters' community formation motives/ Process/consumption experiences and community characteristics. For this purpose, this study collected the data using ethnographic interview. participant observation, documents and media reports. The results of this study show that supporters communities' formation and diffusion process were influenced by individual characteristics(e.g., personality, hobby and etc.), community characteristics(e.g.,team performance, star player, facilities and etc.) and external factors(ex: media movement etc.) and supporters have experienced various emotions such as intimacy. cohesion, pride and so on through various activities at on-line and off-line site. Community characteristics were classified into we-ness, rituals/traditions, moral responsibility. We found that we-ness influenced emotional dimensions such as joy, pleasure, fun and excitement. rituals and traditions made members feel passion. hope. love and vitality. and moral responsibility provided satisfaction. enthusiasm anxiety. regret and so on. Also, emotional attachment and brand loyalty were increased by these experiential aspects of community consumption.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.4
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• pp.1-8
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• 2022

This study aims to investigate the gap in accessibility to urban planning facilities between living spheres in local small and medium-sized cities. In this study, OD data between administrative dongs of public transportation users was constructed to analyze the living shpere, and community analysis was conducted based on cohesion between data. As a result of the analysis, it was confirmed that a total of 10 clusters (mid-living areas) were formed, and the topographical difference between the 11 middle living areas established in the existing Jinju City Basic Plan and the single living areas were actively exchanged to form a community with other administrative dongs. Next, the analysis of the service area of urban planning facilities for mid-living areas was conducted based on the road network. As a result of analyzing the area accessible within 5, 10, and 15 minutes, educational facilities, public facilities, cultural facilities, tourism, and green facilities could be reached within 15 minutes in most mid-living areas. On the other hand, there were many areas where access to transportation facilities, medical facilities, and cultural facilities was difficult within 15 minutes. In particular, the accessibility of the outer living area and the central living area were different. To improve the quality of life of citizens, using urban planning facilities in Jinju-si and establishing related plans in urban basic plans, it is necessary to conduct a study on service areas through network analysis.

• Journal of Information Management
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• v.40 no.3
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• pp.99-123
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• 2009

A core point of the KESLI consortium raises the participation score of the joining institute and improves the cohesive force and reliability to cope with prices continued rising of publishers, commonly and gives the actual profit to the joining institute by providing the base able to utilize the academic information with dispersion owning the national institutes. In this study the whole opinion of the consortium joining institute is collected in the future in order to deduce the reasonable and advantageous consortium model in which the consortium joining institute can be commonly applied. The facing task of the KESLI consortium is analyzed through a literature research, a questionnaire survey, a panel discussion and we try to present.

• Information Systems Review
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• v.18 no.3
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• pp.111-135
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• 2016

The major characteristic of open source software (OSS) is innovativeness. Innovativeness stems from the process of sharing and solving technical problems. This study analyzes the impact of voluntary participation and collaboration of OSS developers on sustained participation in the community based on organizational citizenship behavior and social capital theories. Based on Bolino et al. (2002) and Wasko and Faraj (2005), a research model and hypotheses are developed. A total of 152 OSS developers participated in the survey. The hypotheses are tested by LISREL modeling. The results of analysis show that royalty, social participation, and advocacy participation enhance or positively influence social capital. In addition, reciprocity and shared vision reinforce intention of sustained knowledge contribution. However, the result shows a statistically insignificant relationship between social participation and shared vision and between cohesiveness and intention of sustained knowledge contribution.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.