• Knowledge Management Research
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• v.10 no.4
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• pp.43-60
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• 2009

The current study attempts to provide the field of knowledge management with theoretical grounds from the perspective of social network, resource dependency, and institutional theory. Social network theory considers that knowledge management plays a critical role in organizational innovation through the process of knowledge sharing/creation, communication systems, and a cooperative culture and trust, whereas resource dependency perceives knowledge management as contributing to cost reduction through the process of knowledge capture/storage, database systems, and reward/incentive systems. Plus, from the perspective of institutionalization, this study discusses that organizations can not benefit from knowledge management if it is adopted with the motive of isomorphic change. Finally, this study compares and integrates the three perspectives, and discusses the implications and limitations.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.1
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• pp.39-48
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• 2016

The tacit knowledge transfer cultivate the value and mount of tacit knowledge. The tacit knowledge transfer plays the most important role for improving the competitiveness of the organization. Despite the tacit knowledge transfer is very important, the research related with tacit knowledge transfer has not been actively carried out. The barriers to tacit knowledge transfer interfere with the tacit knowledge transfer. The barriers to tacit knowledge transfer are lack of understanding knowledge experts, heavy over-work, insufficient compensation, trust shortage and knowledge stickiness. In order to overcome the barrier of the tacit knowledge transfer, it is necessary to promote knowledge broker. The knowledge broker is the foundation for the tacit knowledge transfer and the critical success factor for efficient tacit knowledge transfer. However, most research related on the knowledge broker had focused on the degree, centrality and density of the knowledge network. The framework is needed to performance indicator for diagnosing the tacit knowledge transfer. Therefore, we suggest the knowledge broker framework based on the social network analysis.

• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.61-74
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• 2010

The knowledge sharing in a knowledge management process is much affecting generation and distribution of knowledge. Especially, the knowledge distribution is being revitalized with the center of social media service like twitter and library service 2.0 in the knowledge-based IT (Information Technology) environment. The present research analyzed the structure and characteristics of a social network inside an organization that is growing like an organism through self-organization through tools for SNA (Social Network Analysis) and multiple regression analysis of independent variables such as 1) a relationship between social network's structure and knowledge sharing, 2) a relationship between structural holes and knowledge sharing influence of centrality, 3) a relationship between individual ability and knowledge sharing of information technology and work recognition.

• Knowledge Management Research
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• v.22 no.1
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• pp.217-242
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• 2021

The purpose of this study is to examine the research trends in the filed of individual knowledge hiding through keyword network analysis. As individuals intentionally hide their knowledge beyond not sharing their knowledge in organizations and the research on knowledge hiding steadily spreads, it is necessary to examine the research trends regarding knowledge hiding behaviors. For keyword network analyses, we collected 346 kinds of 578 keywords from 120 articles associated with knowledge hiding behaviors. We also transformed the keywords to 86 nodes and 667 links by data standardizing criteria and finally analyzed the keyword network among them. Moreover, this study scrutinized knowledge hiding trends by comparing the conceptual model for knowledge hiding based on literature review and the network structure based on keyword network analysis. As results, first, the network centrality degree, knowledge sharing, creativity, and performance was higher than others in Degree, Betweenness, Closeness centrality. Second, this study analyzed ego networks about psychological ownership and individual emotion theoretically associated with knowledge hiding and explored the relationship between variables through comparing with the conceptual model for knowledge hiding. Finally, the study suggested theoretical and practical implications and provided the limitations and suggestions for future research based on study findings.

• The Journal of Information Systems
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• v.20 no.1
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• pp.1-20
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• 2011

This study investigated the factors that facilitate knowledge creation of team with the aspect of knowledge management. We considered two characteristics which are team members' psychological characteristics (achievement needs and conflict emotion) and knowledge network characteristics among team members (internal cohesion and external bridging) and verified the relationship between these characteristics and team performance. Furthermore, we examined whether these characteristics have a different effect on team performance according to the mastery climate. This study performed a survey targeting team members in knowledge based firms and 376 final surveys to be used as a sample in this study. The result showed that team members' psychological characteristics and knowledge network characteristics among Team members have an influence on team performance significantly. In addition, the master climate moderated the relationship between team members' psychological characteristics and team performance.

• International Journal of Knowledge Content Development & Technology
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• v.8 no.4
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• pp.75-98
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• 2018

In this study, the network analysis of researchers, institutions, and research principal agent was conducted to understand structure characteristics of international cooperation research project implemented from 1997 to 2018. The network of researchers and institutions were decentralized structure. On the other hands, the network of research principal agent was centralized structure. The Soul National University is the leading organization of international cooperation research project. In terms of research principal agent, corporation is the leading principal agent. In additions, the results of the network centroid analysis of the researchers and institutions were correlated with the research funds. As a result, it was confirmed that the network centroid of research organization was linearly related to research funds.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.877-893
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• 2022

With the development of deep learning, face inpainting has been significantly enhanced in the past few years. Although image inpainting framework integrated with generative adversarial network or attention mechanism enhanced the semantic understanding among facial components, the issues of reconstruction on corrupted regions are still worthy to explore, such as blurred edge structure, excessive smoothness, unreasonable semantic understanding and visual artifacts, etc. To address these issues, we propose a Learnable Structure Knowledge of Fusion Network (LSK-FNet), which learns a prior knowledge by edge generation network for image inpainting. The architecture involves two steps: Firstly, structure information obtained by edge generation network is used as the prior knowledge for face inpainting network. Secondly, both the generated prior knowledge and the incomplete image are fed into the face inpainting network together to get the fusion information. To improve the accuracy of inpainting, both of gated convolution and region normalization are applied in our proposed model. We evaluate our LSK-FNet qualitatively and quantitatively on the CelebA-HQ dataset. The experimental results demonstrate that the edge structure and details of facial images can be improved by using LSK-FNet. Our model surpasses the compared models on L1, PSNR and SSIM metrics. When the masked region is less than 20%, L1 loss reduce by more than 4.3%.

• Knowledge Management Research
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• v.13 no.3
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• pp.1-16
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• 2012

Nowadays, many first-time Internet users start off heavily using SNSs (Social Network Sites), such as Cyworld, Facebook, and Twitter. The reason for the growth of SNS use is closely related to the various services of gaming, playing, using entertainment items, sharing knowledge etc., provided by the SNS; technically, the most important of the services provided would be the behavior of sharing knowledge among people connected and networked in the site. In sum, we assume that the users may communicate well with each other and pay attention to building a close social network using the abovementioned activities. However, researchers have just begun to focus on the issues explaining why Internet users rush into SNSs and enjoy their time there. Therefore, we investigated the reasons for posting and sharing knowledge voluntarily on the SNS and how others respond to the posted knowledge and are actually affected by the behavior. We applied social identity theory and social capital theory in this study to find which network externalities in SNSs may affect online identity-based attachment and cause them to produce a knowledge sharing generation. We found that people's online identity in SNSs is closely related to and influences knowledge sharing. This empirical study resulted in the importance of social relations in SNSs, which leads to sharing knowledge.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1598-1605
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• 2021

Recently, convolutional neural networks (CNNs) have been widely used with excellent performance in various computer vision fields, including super-resolution (SR). However, CNN is computationally intensive and requires a lot of memory, making it difficult to apply to limited hardware resources such as mobile or Internet of Things devices. To solve these limitations, network lightening studies have been actively conducted to reduce the depth or size of pre-trained deep CNN models while maintaining their performance as much as possible. This paper aims to lighten the SR CNN model, SRGAN, using the knowledge distillation among network lightening technologies; thus, it proposes four techniques with different methods of transferring the knowledge of the teacher network to the student network and presents experiments to compare and analyze the performance of each technique. In our experimental results, it was confirmed through quantitative and qualitative evaluation indicators that student networks with knowledge transfer performed better than those without knowledge transfer, and among the four knowledge transfer techniques, the technique of conducting adversarial learning after transferring knowledge from the teacher generator to the student generator showed the best performance.

• Knowledge Management Research
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• v.12 no.5
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• pp.25-40
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• 2011

Today, Internet users start off using heavily SNS(Social Network Site) such like, Facebook, Twitter. The reason of the growth of using SNS would be closely related to the various services of gaming, playing, entertainment items, sharing information etc., provided by the SNS, technically, the most important one out of the services provided would be behaving of sharing knowledge among people who connected and networked in the site. In sum, we assume that the users may communicate well each other and pay attention to build closely a social network using that kind of activities. However, nevertheless the new trends of communications and sharing knowledge become popular, researchers have just began the research issues in explaining why Internet user rush into SNS and enjoy the time in there. Therefore, we investigate on the reasons of posting knowledge voluntarily in the SNS and how others response to the posted information and actually affected by the behavior. We appled personal relation and social identity theory for this study, which personal relation in SNS may affect on social identity and make them produce knowledge generation. We found that social identity and involvement in SNS is closely related and influence knowledge creation and generation. This empirical study resulted in the importance of social relations in SNS, which leads to a sharing knowledge.