• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.115-135
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• 2001

The objective of this paper is to develop a knowledge assets measurement model in Korea. There are relatively many researches on measuring knowledge assets of an organization. These previous researches, however, lack of comprehensive view of knowledge management and view of Korean organizational culture. We surveyed and analyzed previous researches, and found common factors to measure knowledge assets. We developed an updated version of knowledge assets index. The developed model has been validated for its fitness with real data of Korean companies. The result of this research can be used as a measurement tool for knowledge assets of public institutions as well as private companies.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• Knowledge Management Research
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• v.4 no.2
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• pp.35-53
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• 2003

In recent years, knowledge has emerged as a major source of competitive advantage due to the continuous development of information and communication technology, the acceleration of globalization, and the entry into knowledge-based society. Thus interests in knowledge management have been increased significantly. Nevertheless theoretical backgrounds of knowledge management are not actively discussed. Studies on the knowledge management of R&D groups initiating knowledge creation and sharing are not actively conducted either. This study, therfore, provides a research model of knowledge management to investigate relationships among resource and institutional characteristics, knowledge management activities, and knowledge management performance of R&D groups based on knowledge-based theories and institutionalization theories. This study further offers research propositions inherent in the model.

• Journal of Information Technology Applications and Management
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• v.17 no.4
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• pp.19-38
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• 2010

This paper investigates the effect of stress on knowledge creation. The goal stress of resource inadequacy and job stress had negative influences on knowledge creation. However, the cohesion and mastery climate of team had positive influence on knowledge creation. Therefore this paper verifies the moderate role of the cohesion and mastery climate of team on the relationship between stress and knowledge creation. The model developed was tested using data collected from knowledge based industry with 375 members in 69 teams in 12 different firms. A Hierarchical Linear Model (HLM) was used to test the hypotheses generated from the model. Results show that job stress had a negative influence on knowledge creation as we expected but the goal stress didn't. The mastery climate of team affected knowledge creation positively and moderated the relationship between the goal stress and knowledge creation. Furthermore, the team cohesion had a positive influence on knowledge creation. The study provided some implications that practitioners should consider the stress when they design jobs for team members and suggest them the way to manage their job stress when they work.

• Korean System Dynamics Review
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• v.11 no.1
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• pp.103-131
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• 2010

This paper aims to investigate a dynamic mechanism underlying the process of knowledge creation and growth with a focus on the 'knowledge-friendly culture' conceptually coined by Davenport and Prusak in 2000. To achieve this objective, key attributes of knowledge are first identified by exploring the generic characteristics and information and interpreting the definitions of knowledge, from which four modes of knowledge growth (Socialization, Externalization, Combination, Internalization) are delineated into a dynamic SECI model by identifying cultural attributes underlying each mode and modeling their casual relationships based on the systems thinking. Further, a series of sensitivity analysis through computer simulation were made to find how 'knowledge-friendly' cultural factors affect the knowledge growth. It is found that individual knowledge is most influenced by organization's cohesion whereas organizational knowledge is most affected by the openness of organization.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.65-70
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• 2005

This paper introduces an approach to multi-layered product knowledge model for collaborative engineering environment. The participants in collaborative engineering want to share and reason product knowledge through internet without any heterogeneity and ambiguity. However the previous knowledge models are limited in providing those aspects. In this paper, the collaborative engineering domain is analyzed and then the product knowledge is organized into four levels such as product context model, product specific model, product design model and product manufacturing model. The four levels are represented by first-order logic in layered fashion. The concepts and the instances of a formal ontology are used for recursive representation of the four levels. The instances of the concepts of an upper level like product context model are considered as the concepts of an adjacent lower level like product specific model, and this mechanism is applied to the other levels. These logic representations are integrated with the schema and the instances of a relational database. OWL representation of the four levels is defined through the integration of the logic representation and OWL primitives. The four product knowledge models have their major representation according to the characteristics of each model. This approach enables engineer to share product knowledge through internet without any ambiguity and utilize it as basis for additional reasoning.

• Knowledge Management Research
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• v.2 no.1
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• pp.65-81
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• 2001

The aim of this study is classify knowledge work style management for knowledge management. It is based on the knowledge creation model of Nonaka by subdividing types of knowledge workers. It was designed to create a model for application to the actual environment of management. Nonaka suggested the process of socialization, externalization, combination, internalization that the knowledge of a person creates new knowledge through the interaction of implicit knowledge and explicit knowledge. This research demonstrated that knowledge worker of 16 forms by applying SECI model to the main function and the subordinate functions again. This study aims at achieving a higher outcome by applying the ability of existing knowledge worker to subdivided expert field efficiently. Suggested styles of knowledge worker in this research are classified into craftsman style, pragmatic style, combination style, developed style knowledge worker who creates knowledge by selecting socialization as the function and again by selecting externalization combination, internalization as subordinate functions. And they were classified into creation style, insight style, strategy style according to practical application worker and function which is selecting externalization as the main function and socialization as the subordinate functions. They were classified into future style, innovation style, analysis style, judgement style knowledge worker who are selecting combination as the main function and experiment style, intuition style, research style, learning style worker who are selecting internalization as the main function. They suggested the characteristics and cases of each type.

• Journal for History of Mathematics
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• v.27 no.1
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• pp.47-57
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• 2014

This paper aims to evaluate works of Frege and G$\ddot{o}$del, who play the trigger role in development of logic, by Knowledge Change Model. It identifies where their positions are in the model respectively. For this purpose I suggest types of knowledge change and their criteria for the evaluation. Knowledge change are classified into five types according to the degree of its change: improvement, weak glorious revolution, glorious revolution, strong glorious revolution, and total revolution. Criteria to evaluate the change are its contents, influence, pervasive effects, and so forth. The Knowledge Change Model consists of the types and the criteria. I argue that in the model Frege belongs to the total revolution and G$\ddot{o}$del to the weak glorious revolution. If we accept that the revolution in logic initiated by Frege was completed by G$\ddot{o}$del, it is a natural conclusion.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.290-293
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• 2000

Knowledge discovery refers to the overall process of discovering useful knowledge from data. The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the DSS area. However, they rely on the strict assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the GPS algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.564-568
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• 2005

Recently, Knowledge Management (KM) has been applied to construction industry. Surprising, there is few studies that address the most fundamental problem in KM: people may prefer not to share their knowledge so as to preserve their intellectual or unique values in the organization. Without the premise of each individual's willingness to share knowledge, there will be no valuable input for the IT system and, thus, no knowledge management at all. This paper aims to model the behavioral dynamics of knowledge sharing and to design an incentive system that may facilitate knowledge sharing for construction companies. In this paper, a game-theory based model will be developed, and the framework for designing an incentive system will be proposed according to the model.