• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.1-27
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• 2009

Since online knowledge networks usually consist of a larger, loosely knit, and geographically distributed group of "strangers" who may not know each other very well, members may not willingly share their knowledge with others. In order to address this challenge, this study looks Into the factors that are expected to affect knowledge sharing in an online knowledge network. For empirical validation, we choose "the global network of Korean scientists and engineers (KOSEN)" as one of the best practices of online knowledge networks. By using the archival, network, and survey data, we validate two models of knowledge sharing in sequence (i.e., knowledge contribution and knowledge utilization models) and then discuss the results. The findings of this study show that individuals not only contribute but also utilize knowledge in an online knowledge network when they are structurally embedded and perceive a strong reciprocity. In the network. In addition, taking pleasure in helping is found to positively affect knowledge contribution, whereas perceiving usefulness is found to Influence knowledge utilization. Contributions of this study and future research opportunities are also discussed.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.139-142
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• 2005

Recently research interest in Knowledge Management (KM) has grown rapidly. Companies regard intellectual capital as important asset and strive to deploy KM in an organization to gain a competitive edge. Many organizations currently engage in knowledge management in order to leverage knowledge both within their organization and externally to their shareholders and customers. Most of the previous research related to KM are dedicated to investigate the role of information technology in extracting, capturing, sharing, coverting organizational knowledge. Knowledge workers, however, are paid less attention though they are the key players in KM activities such as knowledge creation, dissemination, capture and conversion. We regard knowledge workers as a major component of KM and starting point of understanding organizational knowledge activities. Therefore we adopt a method to understand and analyze knowldge workers' social relationships. In this paper we investigate Social Network Analysis (SNA) as a tool for analyzing knowledge network. We introduce the basic concept of SNA and suggest a framework for implementing knowledge network by explaining how SNA can be used for analyzing knowledge network. We also propose a numerical method for identifying knowledge workers using SNA after classifying knowledge workers. The suggested method is expected to help understanding key knowledge players within an organization.

• Knowledge Management Research
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• v.16 no.2
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• pp.67-89
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• 2015

Improving productivity of knowledge workers is an important issue in the 21st century referred as knowledge-based society. The core key word is knowledge sharing among constituents of an organization. The purpose of this study is to combine the social network position factors with attitude and behavior factors, and develop an integrated research model for the knowledge sharing among members of an organization. This study adopted the integrated theoretical framework based on social capital, self-efficacy, transactive memory, and knowledge sharing. Surveys were conducted to 42 organizational members from a department in a leading IT outsourcing company to empirically test the proposed research model. In order to validate the proposed research model, social network analysis tool, UCINET, a structural equation modeling tool, SmartPLS, were utilized. The empirical result showed that, first of all, organizational members' familiarity network position had significant influence on knowledge self-efficacy and transactive memory capability. Second, knowledge self-efficacy and transactive memory capability affected knowledge sharing intention. Third, knowledge sharing intention also had an impact on the job performance. However, organizational members' expertise network position had no significant influence on knowledge self-efficacy and transactive memory capability. This finding reveals the importance of the emotional approach rather than the rational approach in knowledge management. The theoretical and practical implications on the research findings were discussed along with limitations.

• Knowledge Management Research
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• v.19 no.4
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• pp.19-37
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• 2018

Knowledge transfer among employees integrates individual knowledge scattered within a firm, thus increases organizational effectiveness. In particular, the role of knowledge broker, which enables knowledge sharing across multiple teams or subunits, is critical for the success of knowledge management. This study classified the types of knowledge broker that facilitates knowledge flows among team, and examined the influences of various intra- and inter-team social networks. Survey responses from 128 employees of four R&D teams were gathered and analyzed using partial least square structural equation modeling. The results of analysis showed that all types of inter-team networks(i.e., emotional closeness network, frequency of interaction network, and perceived expertise network) had significant influences on related knowledge brokerage behaviors. In case of intra-team networks, only the emotional closeness network showed significant influence. These results proved the necessity of managing various types of intra- and inter-team networks to encourage knowledge brokerage behaviors within a firm.

• Korean Management Science Review
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• v.32 no.4
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• pp.81-96
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• 2015

This paper models knowledge diffusion on an inter-organizational network. Based on literatures related to knowledge diffusion, the model considers critical factors that affect diffusion behavior including nodal property, relational property, and environmental property. We examine the relationships among network structure, knowledge search, and diffusion performance. Through a massive simulation runs based on the agent-based model, we find that the average path length of a network decreases a firm's cumulative knowledge stock, whereas the clustering coefficient of a firm has no significant relationship with the firm's knowledge. We also find that there is an interaction effect of network structure and the range of knowledge search on knowledge diffusion. Specifically, in a network of a larger average path length (APL) the marginal effect of search conduct is significantly greater than in that of a smaller APL.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Knowledge Management Research
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• v.12 no.2
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• pp.69-80
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• 2011

This paper reports on a structural view of a knowledge network comprised of clubs and organisationsexpressly concerned with cultural activities in a regional Australian city. Social network analysis showed an uneven distribution of power, influence, and prominence in the network. The network structure consisted of two modules of vertices clustered around particular categories of creative arts and these modules were linked most frequently by several organisations acting as communication hubs and boundary spanners. The implications of the findings include 'network weaving' for improving the network structure and developing a systemic approach for exploring the structures of social action that form community-based knowledge networks.

• Knowledge Management Research
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• v.14 no.3
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• pp.87-100
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• 2013

As the external knowledge networks of firms have become more and more important to their product and service innovations, many global leading companies such as P & G, IBM, and Samsung Electronics have formulated and implemented their open innovation strategy. This study attempts to empirically analyze the effects of CEOs' supports for external knowledge networks, external knowledge network-oriented cultures and inter-organizational knowledge management systems as the major antecedents to external knowledge networks by using the data based on organizational members' perceptions about them. Based on 847 samples collected from employees in three companies in the medical, the construction and the IT service industries, this study performed a structural equation modeling (SEM) analysis about the effects of the antecedents to the external knowledge networks on product and service innovations through Partial Least Squares (PLS). The empirical findings of this study show that CEOs' supports for external knowledge network positively influence product and service innovations, partially mediated by external knowledge network-oriented cultures and inter-organizational knowledge management systems. And they also show that external knowledge network-oriented cultures and inter-organizational knowledge management systems have a positive effect on product and service innovations, respectively, partially mediated by external knowledge networks. With these new findings, academic and practical implications are discussed.

• Journal of Information Management
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• v.36 no.4
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• pp.199-215
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• 2005

Experts participating in the knowledge expert network externalize their implicit knowledge by providing information or writing reports. Almost all the members of the network share externalized knowledge and the network facilitate the dissemination and diffusion of knowledge. Individuals reproduce another implicit knowledge by internalizing shared knowledge through the network and re-created knowledge is externalized, establishing knowledge circulation. In this paper, we analyze the expert groups of the Global Network of Korean Scientists & Engineers(KOSEN, www.kosen21.org), the Korea's No. 1 science and engineering knowledge expert community, with the application of the theory of policy network proposed by Marsh & Rhodes. According to the principal standards of policy network classification such as the number of participants, interaction among participants, consistency, distribution of resources and dependency, we categorize the KOSEN expert groups as closed policy network and opened issue network, and divide closed policy network into core community and periphery community.

• Knowledge Management Research
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• v.13 no.4
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• pp.71-82
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• 2012

The purpose of this study is to investigate the effects of employees who attend graduate school on the expansion of the knowledge sharing network in their company. For this purpose, the researchers chose 10 worker-graduate students and 75 members of company 'A' that they belong to and 107 members of university 'B' that they belong to, 172 members in total. 10 overlapped employee-students were excluded. The results of this study are summarized as follow: First, the personal relations of the employee-students enhanced after they have entered the graduate school. The score for the question was 3.85 out of 5 points. Second, the employee-students played the role of the knowledge bridge between company's co-worker network and graduate school's classmate network. It was confirmed that the density of the company's network was higher than the density of the connected network of the company and the graduate school. The analysis result confirmed that the difference of the two groups was significant. This means that the company carried out exchange with more members and therefore gained various kinds of knowledge. Also, in all types of network, the structural hole of the company network was lower than that of the connected network of the company and graduate school. The ANOVA test using QAP procedure confirmed that the difference of two groups was significant (friendship network F=1.2856, p<0.05; information network F=1.278, p<0.05; and trust network F=1.23, p<0.05). It means that the company not only gained the newly acquired knowledge by the knowledge bridge of the employee-students, but also was able to share it more effectively with members. Third and lastly, the employee-students share various information related to the organization, duties and roles rest in the company throughout break time, working hours and direct inquiries. This means that the employee-students contributed to the innovation of knowledge sharing in the company by sharing knowledge that they gained from the graduate school within the company.