• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.95-115
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• 2001

We propose classifying the venture firms into four types of knowledge management. For this purpose, we collected questionnaire data from 101 venture firms listed in KOSDAQ, and applied a unsupervised neural network algorithm SOM to obtain four clusters representing knowledge management types-High Tech Type, Organizational Knowledge Type, Information Technology Type, and Beginner Type. Based on the results, we conclude that the venture firms listed in KOSDAQ should first know its own knowledge management type, and then apply appropriate strategies to take advantage of the knowledge management impacts on the competitiveness.

• Knowledge Management Research
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• v.21 no.1
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• pp.151-173
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• 2020

The purpose of this study is to identify the antecedents that impact on the individual knowledge sharing based on motivational perspectives. Specifically, the authors investigate the roles of general self-efficacy and popularity on knowledge sharing drawn on costly signaling theory and trait activation theory. Data from 227 pairs of employees and coworkers working in companies located in South Korea supported the model. General self-efficacy was positively related to knowledge sharing and popularity was positively associated to knowledge sharing. Also, by taking an interactional approach, our study demonstrated the moderating effect of popularity on the relationship between general self-efficacy and knowledge sharing. The positive relationship between general self-efficacy and knowledge sharing is significant when popularity is low, but not significant when popularity is high. Our findings suggest that the various motivation types including intrinsic and extrinsic motivations for knowledge sharing of individuals exist simultaneously and these motivations have an interactive effect on knowledge sharing.

• The KIPS Transactions:PartD
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• v.15D no.5
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• pp.705-712
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• 2008

Recently, interests in the notion of PKMS(Process based on Knowledge Management System) utilizing BPMS(Business Process Management System) and KMS(Knowledge Management System) have been significantly increased. Specially, most public organizations require their own effective knowledge management strategies since public business service needs various knowledge types. Based on a comprehensive framework that reflects lifecycle requirements of KMS and BPMS, we propose an PKMS system architecture, which performs step-by-step knowledge-providing strategy in public organization. To propose a PKMS architecture, this paper first investigates inter-relationships between public business and various knowledge types, and classifies knowledge types into three groups and then we suggest knowledge management strategies considering priority order among knowledge groups. Based on the proposed knowledge management, a PKMS system architecture can combine the advantages of the KM and BPM paradigms. This paper presents the PKMS system applied to employment insurance business part in real environment and demonstrated the advantages via inter-relationships between KM and BPM requirements.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.272-275
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• 1992

A novel fault diagnosis method based on likelihood decomposition is proposed for linear stochastic systems described by autoregressive (AR) model. Assuming that at some time instant .tau. the fault of one of the following two types is occurs: innovation fault (actuator fault); and observation fault (sensor fault), the log-likelihood function is decomposed into two components based on the observations before and after .tau., respectively, Then, the type of the fault is determined by comparing the log-likelihoods corresponding two types of faults. Numerical examples demonstrate the usefulness of the proposed diagnosis method.

• Knowledge Management Research
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• v.8 no.1
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• pp.1-14
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• 2007

This paper is an exploratory study providing critical research issues in knowledge management strategy, process operations, and knowledge management system design and control in mass customization. The firms implementing mass customization provide good cases adopting recent changes in business environment including increased diversity and variability of customer needs, fast development of related technologies, and increase of the necessity of knowledge management. In this study, required knowledge management characteristics are investigated and future research issues are suggested for successful implementations of knowledge management. Research issues are extracted from the context of strategy, process, and information system for the purpose of practical adaptation and the types of mass customization are emphasized as a mediating element for fit and consistency between firms' corporate strategy and knowledge management characteristics.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.662-670
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• 1998

In order to overcome the problems with first generation expert systems at the symbol level, recently various knowledge level development techniques of second generation expert systems have been proposed. But, these techniques are conceptual modelling techniques. This paper modifies and complements these conceptual modelling techniques and proposes a Task Object Modelling (TOM) technique as a practical knowledge level expert system development technique. This paper defines a Task Object(TO) as a knowledge unit consisted of a goal, execution conditions, behaviour knowledge, and so on. And, we define a Task Object Diagram(TOD) to depict structual, dynamic, and functional aspects of TO easily. We also define Inference Types as basic units to describe behaviour knowledge of TOs. In order to utilize the proposed TOM technique as not a simple conceptual modelling technique but a practical second generalion expert system development technique, we implement a TOD editor, a TO editor, and TO processing algorithm based on the state of TOs. Also we implement a Inference Types Library, in which each inference type is corresponded to an IRE(Jntelligent Rules Element) method, to transform the defined inference types into IRE methods automatically.

• Journal of Technology Innovation
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• v.25 no.3
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• pp.299-331
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• 2017

This research details firm knowledge search types based on the locus and features for Korean firms in the knowledge-based industry, and then analyzes differences in innovation performance according to the types from the view of a configurational approach. Existing research has mainly concentrated on establishing a relation between knowledge search and outcome variables. Consequently, firms have relatively insufficient understanding of how to systematize knowledge search. Hence, this research classifies knowledge search into four dimensions-external search breadth, external search depth, internal search breadth, and internal search depth-by the locus and features of search. Furthermore, the research draws actual types of knowledge search of firms and analyzes differences in innovation performance. The main result of the research is as follows. First, the research reasons out six clusters of firms which have a dissimilar knowledge search type. Each cluster shows differences while participating in every dimension of knowledge search or few dimensions. Second, as for innovation performance, each cluster shows different exploitative and exploratory innovation performance according to their knowledge search type. This research applies a configurational approach while existing research applied a reductionistic approach, thereby establishing the major contribution which enables us to study a phenomenon as it comes, not to analyze variables and relationships of variables. Lastly, the research suggests a future direction of research based on the result of this research.

• Communications of Mathematical Education
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• v.25 no.4
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• pp.693-734
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• 2011

The purpose of this research is to analyze the pedagogical content knowledge on the natural number concepts of Korean Elementary School Teachers. Shulman(1986b) had developed a tool in order to understand teachers' knowledge, as he defined three types of knowledge in teaching ; Subject Matter Knowledge, Curricular Knowledge, and Pedagogical Content Knowledge. Pang(2002) defined two types of elements including in the ways of teaching ; individual element, and sociocultural element. Two research questions are addressed; (1) What is the pedagogical content knowledge of Natural number Concepts for Korean Elementary School Teachers? ; (2) What factors are included in the pedagogical content knowledge of Natural number Concepts for Korean Elementary School Teachers? Findings reveal that (1) the Korean Elementary School Teachers had three types of the pedagogical content knowledge on the natural number concepts; (2) Teacher Factors were more included than Social-Cultural Factors in the pedagogical content knowledge on the natural number concepts of the Korean Elementary School Teachers. Further suggestions were made for future researches to include (1) a comparative study on teachers between ordinary teachers and those who majored mathematics education in the graduate school. (2) an analysis on the classroom activities about the natural number concepts.

• Knowledge Management Research
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• v.19 no.2
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• pp.187-203
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• 2018

The purpose of this study was to investigate the perception about AI assistants and the differences between two groups, workers(secretaries) and supervisors(bosses), using the Q-methodology which has an advantage in understanding the types of subjective perceptions. Through literature reviews and interviews, 34 Q-samples were extracted, and then Q-sorting was conducted by P-samples(20 workers and 15 supervisors). As a result of Q-sorting, the types and characteristics of AI assistants perceived by each P-sample were explained. The perception of the workers divided into five distinct types, and the perception of the supervisors was divided into three distinct types. The most crucial factors in distinguishing between workers and supervisors' perceptions depend on whether they are capable of performing certain tasks and whether they can replace existing secretarial jobs. This study, as the primary research on AI assistants, can help to redefine the work that can be replaced by AI and the work that only people can do, and thus to establish education, recruitment, and training plans.

• Knowledge Management Research
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• v.2 no.1
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• pp.25-44
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• 2001

There are two types of organizational knowledge in terms of its creation process: experiential and analytical knowledge. The experiential knowledge is created by repetitive experiences of an individual or team through task execution, while the analytical knowledge is acquired by analyzing accumulated data or information in the organization. The experiential knowledge often remains tacit or implicit in the organization because it is primarily acquired at an individual or team level. Therefore, the issue on the experiential knowledge is to share it actively within the organization. On the other hand, the analytical knowledge is explicit in its nature since it is extracted from data or information. Thus, it is important to guide a systematic creation of the analytical knowledge rather than encourage to share it. The current trend of "knowledge management" mainly focuses on the experiential knowledge - know-how, idea, case, etc - and neglects another important knowledge in the organization. i. e., analytical knowledge. This paper tries to shed a new light on the "knowledge management" arena by introducing rather new perspective in the concept of knowledge. The purpose of this study is to identify the factors affecting the analytical knowledge creation in the organization. We conducted an exploratory case study of three companies with a previously defined research framework and found some critical factors for the analytical knowledge creation. They are "organizational resource", "effectiveness of feedback process", "data source management", and "experimental mind set". Finally, we proposed research model and propositions regarding the analytical knowledge creation in the organization.