• Information Systems Review
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• v.12 no.1
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• pp.107-130
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• 2010

Knowledge management strategy is considered a key determinant of successful knowledge management. However, theoretical and empirical researchers disagree on how knowledge management strategies improve firms' performance. The inconsistent results of prior studies may be attributed to the fact that complementary relationships among knowledge management strategies have not been adequately taken into consideration. While the previous literature has focused on investigating the impact of knowledge sourcing strategies on firms' performance one-at-a-time, in reality firms adopt several different knowledge management strategies together. By drawing on complementarity theory, this study revisits this research problem and develops three complementarity hypotheses. Surveys collected from 139 firms in Korea were analyzed to test the hypotheses by using super modularity function. The results confirmed complementary relationships between system- and person-oriented, and between internal- and external-oriented knowledge management strategies. Our results found no complementarity among the four different knowledge management strategies. This study sheds new light on knowledge management research by developing a new conceptual framework and using advanced analytical approaches to explore the relationship between knowledge management strategies and firms' performance. Implications for practice highlight that a successful knowledge management strategy requires a judicious combination of system- and person-oriented, or of internal- and external-oriented knowledge management strategies.

• Journal of Korea Port Economic Association
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• v.29 no.4
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• pp.201-222
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• 2013

The purpose of the present study is to analyze how and to what degree multinational companies organize and operate their supply chains in accordance with the strategic resource of knowledge in their multinational management, and what kind of influence knowledge oriented global supply chain management has on the management performance of multinational corporations. For this purpose, the current research proposed a measurement model to provide specific shape to the concept of knowledge oriented global supply chain management by adopting the knowledge creation process proposed by Nonaka (1994), and conducted an empirical analysis of what kind of impact the knowledge management system and the knowledge creation process of companies have on the performance of their global supply chain management. The result of the empirical analysis of 113 multinational companies verified the validity and reliability of the measurement model proposed in this study. In addition, the comparative study of the sampled companies by grouping them according to the level of knowledge orientation in global supply chain management indicated that the enterprises that effectively manage the knowledge created within the global supply chain presented overall superiority on the performance of global supply chain management.

• Knowledge Management Research
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• v.22 no.3
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• pp.75-89
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• 2021

A knowledge map should be able to support the referential navigation of knowledge inquiries, i.e., cross- and sequential searches and queries on content relevance-based associated knowledge. This study performs a user-oriented test to verify which type of knowledge map, hierarchical or networked, exhibits superior performance in supporting knowledge inquiries required for problem solving. Both the effectiveness identified by the correct answer rate and the efficiency identified by the number of completion time and reference documents have been revealed superior performance in the networked knowledge map. This study's result can underpin the basic steps to develop more user-friendly and reasonable knowledge services.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.54-61
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• 1999

Objective of the research is to put the vast and complex fault tracking knowledge of human experts in semiconductor production line into the knowledge base of computer system. We mined the fault tracking knowledge of domain experts(engineers of production line) for the construction of knowledge base of the expert system. Object oriented fact models which increase the extensibility and reusability have been built. The rules are designed to perform the fault diagnosis of the items in production device. We have exploited the evidence accumulation method to assign check priority in rules. The major contribution is in the overall design and implementation of the nile base and related facts of the expert system in object oriented paradigm for the application of the system in fault diagnosis in semiconductor production line.

• Women's Health Nursing
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• v.12 no.1
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• pp.47-52
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• 2006

Purpose: This study was undertaken to test effects of action oriented BSE education on knowledge, selfefficacy, and performance competence in nursing students. Methods: A non-equivalent pre-posttest of time serial quasi-experimental design was used to prevent diffusion of the experiment. Out of 53 nursing students selected by convenient sampling in the third grade at a nursing college, 27 students were randomly assigned to the control group and were first given a traditional lecture on BSE. For the experimental group of 26 students action oriented BSE education consisted of lectures, demonstrations with breast models, and BSE skill practice by micro teaching. Results: There was no significant difference in general and BSE-related characteristics between the two groups. Scores of the experimental group in knowledge, self-efficacy, and performance after the intervention were significantly higher than those of the control group. Conclusions: Results showed that action- oriented BSE education was effective in increasing knowledge, self-efficacy and performance competence in nursing students. Education for students should incorporate strategies reinforcing confidence by practicing actual BSE skills as well as acquiring knowledge of BSE, so that students can become competent and practical cancer prevention educators.

• ETRI Journal
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• v.20 no.2
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• pp.192-213
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• 1998

The current approaches in Object-Oriented Analysis have limitations on modeling complex real world systems because they require priori knowledge about objects and their interactions before applying them. This may be practical in small systems and systems with clear domain knowledge, but not in large real world systems with unclear domain knowledge. Our approach uses a stepwise refinement technique in a top-down manner to the Object-Oriented Analysis stage with the application of use cases. This approach is especially good for new areas where we do not know all the information in advance. We present the approach with an example of its application to the B-ISDN service modeling and distributed systems.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.99-104
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• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• The Journal of Information Systems
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• v.21 no.3
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• pp.45-70
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• 2012

Based on the usage levels of target costing systems(TCS) and information technology (IT) infrastructure, this study aims to develop a framework useful for classifying four types of knowledge management(KM) strategies in manufacturing firms: process-oriented, product-oriented, mixed and negative. We adopted a multi-methodological approach by mixing both qualitative and quantitative methods. Before developing a framework, through a case study of the H Motor Company in Korea, this paper investigated and showed the functions of TCS in the management of tacit knowledge. The results from the case study indicated that with the use of TCS, a firm can create, transfer, and share diverse kinds of tacit knowledge among employees for the facilitation of process innovation. We also empirically confirmed the four types of KM strategies, and demonstrated the characteristics(i.e., size, total sales, age, and knowledge intensity) of the organizations adopting each strategy.

• International Journal of Advanced Culture Technology
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• v.7 no.3
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• pp.158-165
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• 2019

Knowledge based system includes tools for constructing, testing, validating and refining the system along with user interfaces. An important issue in the design of a complete knowledge based system is the ability to produce explanations. Explanations are not just a series of rules involved in reasoning track. More detailed and explicit form of explanations is required not only for reliable reasoning but also for maintainability of the knowledge based system. This requires the explanation mechanisms to extend from knowledge oriented analysis to task oriented explanations. The explicit modeling of problem solving structures is suggested for explanation generation as well as for efficient and effective reasoning. Unlike other explanation scheme such as feedback explanation, the detailed, smaller and explicit representation of problem solving constructs can provide the system with capability of quality explanation. As a key step to development for explanation scheme, the problem solving methods are broken down into a finer grained problem solving primitives. The system records all the steps with problem solving primitives and knowledge involved in the reasoning. These are used to validate the conclusion of the consultation through explanations. The system provides user interfaces and uses specific templates for generating explanation text.