• Knowledge Management Research
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• v.16 no.4
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• pp.169-190
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• 2015

The status of small and medium-sized enterprises has been changed into more independent business entities rather than simply subcontractor so that the utilization of specialized knowledge has been much more necessary for the survival in the market. However, small and medium-sized enterprises, it is difficult to sufficient investment in knowledge services due to limited resources relative to large enterprises and demand for knowledge services business of government support is growing. For this reason, it is important to measure accurately the demand for knowledge services of small and medium-sized enterprises in knowledge management for effective utilization of knowledge service. In this study, we analyzed previous studies on small and medium-sized enterprises knowledge services that can be utilized in a comprehensive way. As a result, we developed knowledge service needs assessment model based on five critical success factors for continual growth and 12 types of knowledge service. This model has been modified and supplemented through expert meeting using delphi research method and topic modeling analysis using secondary data. This study is attempted to appropriately measure necessary knowledge services for small and medium-sized enterprises so that generated the evaluation model of knowledge service demands, comprehensively dealing with core knowledge services for many kinds of business entities. It is expected that the developed model will be a useful tool to understand and evaluate knowledge services demands of enterprises.

• KDI Journal of Economic Policy
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• v.37 no.2
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• pp.1-21
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• 2015

The creation of S&T knowledge and development of S&T- based innovation has spread worldwide from traditionally advanced countries to traditionally developing countries, often under the direction of governments. Korea is an exemplar in this new locus. Korea's burst in Science and Technology during the last three decades has made Korea a substantive player in the global production of S&T knowledge and its application to business. Although Korea still trails the US and other top countries in the quality of research, it has leaped from its 1980s standing as bit player in the knowledge economy to being among the leaders in the early 21st Century. This paper shows that Korea's advance benefited from its active participation in the global market in higher education, in international research collaborations, and its close ties to the U.S. Korea's experience offers lessons for other countries who seek to advance by becoming knowledge economies. Korea proves that a developing country can gain comparative advantage in knowledge production and use; that government policy can stimulate such a development; and that openness to the world of higher education and research is the best way to move forward and overcome the middle income trap.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• The Journal of Information Systems
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• v.2
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• pp.127-140
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• 1993

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.181-186
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• 2023

The main purpose of the study is to analyze the features of state regulation of the labor market in a crisis. Structural shifts in the labor market are due to the transformation of public and economic relations in today's globalized world. Increasing competition, the development of the knowledge economy, information technology, changes in the content and forms of labor require updating the labor market regulation system. The research methodology implies the use of modern methods of analysis. The analysis of the features of state regulation of the labor market in crisis conditions is carried out.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.2
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• pp.1-10
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• 2015

This study examines the relationships between export intensity and knowledge search activities of Korea SME manufacturers. Using 2,145 firm data from the 2011 SME Technology Statistics Survey, we focused on the nonlinear relationships of export intensity and internal and external knowledge search activities. The results show that there are U-shaped relationships between export intensity and both of internal and external knowledge search activities. Local market-oriented or global market-oriented SMEs than the middle-level of exporters have more search activities both internally and externally. This study extends our understandings on the relationships between export intensity and knowledge search activities. There are some policy implications to develop supporting programs differing in knowledge search activities according to the acceleration of export or globalization of Korean SME manufacturers.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.17-40
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• 1994

The objectives of this paper are to apply fuzzy cognitive map (FCM)- related techniques to (1) extract causal knowledge from a specific problem-domain and (2) perform a series of causal analysis in complicated decision making area. We propose a set operation-based augmentation (SOBA) algorithm to combine multiple FCMs developed by multiple experts. Based on the SOBA knowledge acquisition algorithm, we can obtain a causal knowledge base fairly representing multiple experts' knowledge about a problem domain. The causal knowledge base built by SOBA algorithm can be described as a matrix form, guaranteeing mathematically compact operation compared with a production (if-then) knowledge base. We applied out method to stock market analysis problem whichis a typical of highly unstructured problems in OR/MS fields.

• Knowledge Management Research
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• v.11 no.4
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• pp.79-89
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• 2010

Companies always competing with rivals in global market ought to cope with various kinds of crises coming from substitutes, new technologies, changing consumer tastes, and government regulations, etc. In this sense, it is highly required that companies should always remain well-prepared for crisis management. Nevertheless, many companies still lack detailed and well-guided strategies about how to handle crisis. This study proposes a case study to propose an effective crisis management by using knowledge management. Cases analyzed by this study are concerned with Daewoo International Corporation (http://www.daewoo.com) and Decoline (http://www.decoline.co.kr) where crises have been successfully overcome by using effective knowledge management strategies, and company performance reached sustainable level.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.352-366
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• 2021

To decrease Europe's harmful emissions, the European Union aims to substantially increase its offshore wind energy capacity. To further develop offshore wind energy, investment in ever-larger construction vessels is necessary. However, this market is characterised by seemingly unpredictable growth of market demand, turbine capacity and distance from shore. Currently it is difficult to deal with such market uncertainty within the ship design process. This research aims to develop a method that is able to deal with market uncertainty in early ship design by increasing knowledge when design freedom is still high. The method uses uncertainty modelling prior to the requirement definition stage by performing global research into the market, and during the concept design stage by iteratively co-evolving the vessel design and business case in parallel. The method consists of three parts; simulating an expected market from data, modelling multiple vessel designs, and an uncertainty model that evaluates the performance of the vessels in the market. The case study into offshore wind foundation installation vessels showed that the method can provide valuable insight into the effect of ship parameters like main dimensions, crane size and ship speed on the performance in an uncertain market. These results were used to create a value robust design, which is capable of handling uncertainty without changes to the vessel. The developed method thus provides a way to deal with market uncertainty in the early ship design process.

• Knowledge Management Research
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• v.24 no.2
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• pp.211-240
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• 2023

The purpose of this study is to analyze empirically the effects of changes in policies of the construction industry on the entry and exit in the construction industry and to present the direction of changes in construction industry policies based on the analysis results. The purpose of this study is also to present by analyzing the factors influencing the increase and decrease of builders in the actual construction market. The results of the survey indicate that for general contractors in Daegu and Gyeongbuk, which are mostly small and medium-sized construction companies, the strengthening of registration standards (capital, technicians, etc.) has a significant impact on market entry and exit. However, on the other hand, many of the construction policies implemented to eliminate unqualified contractors in the construction market have had the effect of increasing the number of unqualified contractors. This suggests that construction policies in the construction cycle have not achieved their objectives.