• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.407-419
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• 2011

This study explains the knowledge transfer process by exploring the significant factors affecting knowledge transfer within an organization from a socio-political perspective. Knowledge transfer occurs in various social contexts, within individuals and groups, and, thus, is closely linked to inter-organizational politics and social network in an organization. By conceptualizing knowledge as a socio-political process, this paper applies organizational politic theory and social network theory to knowledge management area. Here the paper shows that both organizational politics and social network such as in-group and out-group's tie strength have a significant effect on knowledge transfer. In addition, the study empirically verifies that knowledge management system has a moderating effect on the in-group's tie strength and knowledge transfer.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.4
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• pp.87-97
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• 2012

A knowledge map is a diagramed network among knowledge which is related with each other in terms of the referential navigation. To formally as well as structurely represent various contextual use of knowledge, the ontology technology has been recommended to be applied. This research proposes a methodology to build the ontology-based knowledge map promoting referential navigation between knowledge. To prove the validity of the proposed concepts, an ontology-based knowledge map is designed as an example, which demonstrates whether the designed knowledge network in the knowledge map is underpinned by the referential navigation between knowledge.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.247-267
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• 2011

The purpose of this study is to investigate knowledge structure of knowledge organization research area in Korea. The study employed content analysis and network analysis to analyze degree centrality, betweenness, and eigenvector as well as frequency of words. It also analyzes research articles published during the period of 2000-2001. The study can be summarized that the network of keywords of knowledge organization researches is compact and complicated. Cataloging and classification play important roles in the network, and metadata and ontology becomes focal areas in knowledge organization. On the other hand, networks of authorships and authors are broad and fragmented. Collaboration is not active enough.

• Knowledge Management Research
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• v.19 no.3
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• pp.47-61
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• 2018

A knowledge map, a taxonomy of knowledge repositories, must have capabilities supporting and enhancing knowledge user's activity to search and select proper knowledge for problem-solving. Conventional knowledge maps, however, have been hierarchically categorized, and could not support such activity that must coincide with the user's cognitive process for knowledge utilization. This paper, therefore, aims to verify and develop a methodology to build a networked knowledge map that can support user's activity to search and retrieve proper knowledge based on the referential navigation between content-relevant knowledge. This paper deploys keywords as the semantic information between knowledge, because they can represent the overall contents of a given document, and because they can play the role of semantic information on the link between related documents. By aggregating links between documents, a document network can be formulated: a keyword-based networked knowledge map can be finally built. Domain expert-based validation test was also conducted on a networked knowledge map of 50 research papers, which confirmed the performance of the proposed methodology to be outstanding with respect to the precision and recall.

• Knowledge Management Research
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• v.18 no.4
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• pp.287-306
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• 2017

This research focus on the effect of developers' participation structure in knowledge creation and knowledge sharing activities in open source software development projects. Based on preferential selection theory, hypotheses of relationship between a developers' concentration of knowledge creation/sharing activities and collaboration performance was derived. To verify the hypotheses, we use the Gini coefficient in the commit contribution of the developers (knowledge creation) and the centralization index in the repository issue network (knowledge sharing network). Using social network analysis, this paper calculates centralization index from developers in the issue boards in each repository based on data from 837 repositories in GitHub, a leading open source software development platform. As a result, instead of all developers creating and sharing knowledge equally, only a few of developers creating and sharing knowledge intensively further improve the performance of the open collaboration. In other words, a few developers predominantly providing commit and actively responding to issues raised from other developers enhance the project performance. The results of this study are expected to be used by developers who manage open source software project as a governance strategy, which could improve the performance of open collaboration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1442-1453
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• 2016

Now, there are prodigiously expanding worldwide economic networks in the information society, which require their social structural changes through technology innovations. This paper so tries to formally define a process-centered knowledge model to be used to analyze policy-making procedures on technology innovations. The eventual goal of the proposed knowledge model is to apply itself to analyze a topic network based upon composite keywords from a document written in a natural language format during the technology innovation procedures. Knowledge model is created to topic network that compositing driven keyword through text mining from natural language in document. And we show that the way of analyzing knowledge model and automatically generating feature keyword and relation properties into topic networks.

• Knowledge Management Research
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• v.12 no.2
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• pp.1-16
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• 2011

This study examined the influence of the antecedents of knowledge transfer from both the knowledge source's and recipient's perspectives using a social network survey. Prior research usually focused on either perspective of the knowledge source or recipient, thus could not include both. Analyzing the responses from 335 R&D employees of the five firms, the study showed that all antecedents of knowledge transfer - reward, reciprocity, subjective norm, and perceived behavioral control - are influential on knowledge transfer from the knowledge source's perspective. However, from the knowledge recipient's perspective, perceived behavioral control was influential on the quality of knowledge transfer and subjective norm was on the number of knowledge recipients. Expected reward and reciprocity did not show significant influence. This study proved that the necessity of considering both the knowledge source's and the recipient's perspectives when measuring knowledge transfer and the importance of intrinsic motivations, such as subjective norm and perceived behavioral control.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.1-8
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• 2017

Knowledge network is considered to be an important factor in securing regional economic performance and competitiveness. In addition, research institutes that are capable of absorbing knowledge tend to form a global knowledge network regardless of geographical factors, and those that are not, are heavily influenced by regional factors. In this study, we examined how much influence of geographical factors of knowledge network is influenced by lower knowledge absorptive capacity in Korea. As a result, it was shown that the higher institutes of knowledge absorption, the more international collaborative research is being carried out. In other words, a region where science and technology has developed means that regional factors are no longer important factors. The results of this study correspond with the discussion of the preceding theories. In addition, it is worthy of study in that the precedent study was carried out in the case study in Korea.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.107-115
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• 2013

Various networks can be observed in the world. Knowledge networks which are closely related with technology and research are especially important because these networks help us understand how knowledge is produced. Therefore, many studies regarding knowledge networks have been conducted. The assortativity coefficient represents the tendency of connections between nodes having a similar property as figures. The relevant characteristics of the assortativity coefficient help us understand how corresponding technologies have evolved in the keyword-based patent network which is considered to be a knowledge network. The relationships of keywords in a knowledge network where a node is depicted as a keyword show the structure of the technology development process. In this paper, we suggest two hypotheses basedon the previous research indicating that there exist core nodes in the keyword network and we conduct assortativity analysis to verify the hypotheses. First, the patents network based on the keyword represents disassortativity over time. Through our assortativity analysis, it is confirmed that the knowledge network shows disassortativity as the network evolves. Second, as the keyword-based patents network becomes disassortavie, clustering coefficients become lower. As the result of this hypothesis, weconfirm the clustering coefficient also becomes lower as the assortative coefficient of the network gets lower. Another interesting result concerning the second hypothesis is that, when the knowledge network is disassorativie, the tendency of decreasing of the clustering coefficient is much higher than when the network is assortative.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.109-118
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• 2012

This paper theoretically derives an algorithm to discover a new type of workflow-based knowledge from workflow models, which is termed workflow-based affiliation network knowledge. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict a series of workflow-based knowledge from workflow models and their execution histories. So, this paper proposes a knowledge discovery algorithm which is able to discover workflow-based affiliation networks that represent the association and participation relationships between activities and performers defined in ICN-based workflow models. In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to derive its corresponding workflow-based affiliation network knowledge.