• Knowledge Management Research
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• v.11 no.2
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• pp.37-56
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• 2010

Nowadays many companies expect to apply knowledge management mechanism for the explicit business performance improvement. Because peoples who employees are the understanding of knowledge contribution in the organization should try to achieve goal through the effective knowledge management activities. The purpose of this study is to examine the effect of major factors to support the performance of knowledge management in the company by using structural equation modeling. From the empirical result of this study with 485 leading corporation in Busan, we came to know that the infrastructure of knowledge management has influence on knowledge sharing and creating mechanism related to knowledge management activities. And, the knowledge management activities has positive influence on internal and external customer' satisfaction, and firm's social responsibility.

• 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.

• The Journal of Information Technology
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• v.9 no.4
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• pp.13-23
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• 2006

The primary purposes of this study are to explain the relationship between Knowledge Management System(KMS) and Web 2.0, and understand the knowledge management system that assists a company and its organization on the whole in adopting knowledge management. In order to that, the studies associated with knowledge management and Web 2.0 are examined. Recently, the Web 2.0 that makes the interpersonal communication, and it is for Blogshpere is formed for communication. As a result of the analysis of correlation with the factors in creation of knowledge, and knowledge sharing, there are some correlations to each other.

• Knowledge Management Research
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• v.12 no.4
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• pp.91-119
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• 2011

Compared to the industrial society, the knowledge-based economy of the 21st century has placed importance on intellectual capital as a sustainable competitive advantage of an organization. The ownership, creation, and interaction of intellectual capital is emerging as the main challenges of the management and, moreover, it might extend to the issue of intellectual capital management. This research found that the exploitation and sharing of knowledge was more efficient in a networked organization through a case study for A research institute, which attempted intellectual capital management domestically for the first time. The contribution of this exploratory research is to suggest new perspectives on the ownership of intangible asset, the evaluation of knowledge-based product, and the competitive advantage and complementarity of an organization in the knowledge-based economy. The limitation is that this research is just exploratory due to the inaccessibility of data. If the intellectual capital management would be more common, the diverse researches should be empirically carried out.

• World Technopolis Review
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• v.4 no.2
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• pp.79-86
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• 2015

Over the last two decades, interest increased with regard to how some research universities made direct impacts on surrounding regional economic activities and growth. Although the role of basic research for most research universities has remained strong, pressure has intensified to broaden its missions to include helping local and regional economic development efforts. Consequently, many research universities have evolved their basic scientific research mission from the production of scientific knowledge to the sharing and exchange of knowledge with local industries by actively engaging in local economic development (Uyarra 2010). Previous examination has shown that most research universities contribute to local and regional economic development by various functions they provide. They are as follows: Creation of Knowledge, Human-capital creation, Transfer of existing know-how, Technological innovation, Capital investment, Regional leadership, Knowledge infrastructure production and Influence in regional milieu (Drucker and Goldstein 2007). This paper will review the existing literature on the role of universities and its impacts on local regional economic growth and development. In addition, this paper will show how two major research universities (The University of Arizona and Arizona State University) have contributed to the growth of Arizona during last two decades. It is believed that the existence of these two research universities have been instrumental in making industries more diverse and highly attractive, particularly in the Phoenix Metropolitan Area.

• Journal of Information Technology Applications and Management
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• v.20 no.4
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• pp.165-189
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• 2013

The advance of the smart working environment came the expectation that it would innovate and revolutionize the way people work, particularly in a society where smart work is readily available for creating a collaborative and 'connected' business. One of the core infrastructure elements for making smart work a viable option is the smart work center, the promotion of which requires a new form of 'smart work center business model' that can satisfy the purposes of both public services and private businesses. This calls for collaboration between the public and private sectors. Recently a number of businesses have been making significant headway in the creation of a new environment for business support and collaboration by adopting a sharing economy business model in their offices. The so-called 'Coworking Space' is an advanced form of business environment in the emerging 'smart work' era, and comes with the benefits of reduced costs as a result of sharing office space and knowledge sharing through the use of human networks. This paper describes the framework of a 'smart work center business model based on the sharing economy' using a BMC (Business Model Canvas), with an understanding of the characteristics inherent to the smart work center and the sharing economy. It was on the basis of this framework that a smart work center model for business incubation and startup, a private smart work center model for childcare services, and a community marketplace model with a global network were developed.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.85-97
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• 2010

Internet communities are a typical space for knowledge creation and use on the Internet as people discuss their common interests within the internet communities. When we define 'Knowledge Communities' as internet communities that are related to knowledge creation and use, they are categorized into 4 different types such as 'Search Engine,' 'Open Communities,' 'Specialty Communities,' and 'Activity Communities.' Each type of knowledge community does not remain the same, for example. Rather, it changes with time and is also affected by the external business environment. Therefore, it is critical to develop processes for practical use of such changeable knowledge communities. Yet there is little research regarding a strategic framework for knowledge communities as a source of knowledge creation and use. The purposes of this study are (1) to find factors that can affect knowledge creation and use for each type of knowledge community and (2) to develop a strategic framework for practical use of the knowledge communities. Based on previous research, we found 7 factors that have considerable impacts on knowledge creation and use. They were 'Fitness,' 'Reliability,' 'Systemicity,' 'Richness,' 'Similarity,' 'Feedback,' and 'Understanding.' We created 30 different questions from each type of knowledge community. The questions included common sense, IT, business and hobbies, and were uniformly selected from various knowledge communities. Instead of using survey, we used these questions to ask users of the 4 representative web sites such as Google from Search Engine, NAVER Knowledge iN from Open Communities, SLRClub from Specialty Communities, and Wikipedia from Activity Communities. These 4 representative web sites were selected based on popularity (i.e., the 4 most popular sites in Korea). They were also among the 4 most frequently mentioned sitesin previous research. The answers of the 30 knowledge questions were collected and evaluated by the 11 IT experts who have been working for IT companies more than 3 years. When evaluating, the 11 experts used the above 7 knowledge factors as criteria. Using a stepwise linear regression for the evaluation of the 7 knowledge factors, we found that each factors affects differently knowledge creation and use for each type of knowledge community. The results of the stepwise linear regression analysis showed the relationship between 'Understanding' and other knowledge factors. The relationship was different regarding the type of knowledge community. The results indicated that 'Understanding' was significantly related to 'Reliability' at 'Search Engine type', to 'Fitness' at 'Open Community type', to 'Reliability' and 'Similarity' at 'Specialty Community type', and to 'Richness' and 'Similarity' at 'Activity Community type'. A strategic framework was created from the results of this study and such framework can be useful for knowledge communities that are not stable with time. For the success of knowledge community, the results of this study suggest that it is essential to ensure there are factors that can influence knowledge communities. It is also vital to reinforce each factor has its unique influence on related knowledge community. Thus, these changeable knowledge communities should be transformed into an adequate type with proper business strategies and objectives. They also should be progressed into a type that covers varioustypes of knowledge communities. For example, DCInside started from a small specialty community focusing on digital camera hardware and camerawork and then was transformed to an open community focusing on social issues through well-known photo galleries. NAVER started from a typical search engine and now covers an open community and a special community through additional web services such as NAVER knowledge iN, NAVER Cafe, and NAVER Blog. NAVER is currently competing withan activity community such as Wikipedia through the NAVER encyclopedia that provides similar services with NAVER encyclopedia's users as Wikipedia does. Finally, the results of this study provide meaningfully practical guidance for practitioners in that which type of knowledge community is most appropriate to the fluctuated business environment as knowledge community itself evolves with time.

• 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.

• The Journal of Information Systems
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• v.18 no.3
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• pp.135-154
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• 2009

As the knowledge is recognized as a core factor of organization's competitiveness and creation of value added, the importance of knowledge management is also increased. To achieve the successful knowledge management, it is important to establish strategy that consider essential purpose of knowledge management such as creating and sharing of knowledge resource, improving performance, and continuing organizational innovation within the organization and influence factor inside and outside of organization. Until now, however, the research for knowledge management strategy was mostly limited to the statistical analysis based on the unilinear causality model, and systematic access and analysis that consider interaction and feedback structure between factors. In this paper, we developed the novel decision-making framework for successful strategy establishment by applying the analytic network process(ANP). Specifically. we derive clusters and components to decide the interaction and feedback structure between the elements of knowledge management by literature studies. And we produced relative importance and preference of clusters, components and alternatives dealing with feedback structure through the survey of experts in the field or related one of knowledge management. In result of this study, we expect that it will help the knowledge officer to decide establishing knowledge management strategy.

• Asia pacific journal of information systems
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• v.10 no.4
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• pp.57-75
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• 2000

Most current literature on knowledge and technology transfer(Appropriability Model, Dissemination Model, and Knowledge Utilization Model), describe the process of transfer in details, but has limitation in terms of their application in contemporary high-tech industries since most studies have not provided plausible explanation on levels and factors affecting transfer of knowledge and/or technology. To overcome these limitations, the four levels of knowledge and technology transfer are suggested: Knowledge and Technology Creation(Level I), Sharing(Level II), Implementation(Level III), and Commercialization(Level IV). Comprehensive literature identifies sixteen variables affecting the process and results of knowledge and technology transfer. The survey results show four key factors in knowledge and technology transfer: Communication, Distance, Equivocality, and Motivation, Communication refers to the degree to which a medium is able to efficiently and accurately conveys task-relevant information and media while distance involves both physical and cultural proximity. Equivocality refers to the degree of concreteness of knowledge and technology to be transferred while motivation involves incentives for and the recognition of the importance of knowledge and technology transfer activities. Further analysis shows that there are four distinctive clusters and they show very contrasting characteristics in terms of four key factors. The careful mapping of the four clusters on the four key factors show very informative knowledge and technology transfer patterns, the Knowledge and Technology Transfer Grid. Finally, actions to increase communication interactivity and motivation, and to reduce cultural distance and equivocality are suggested.