• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.345-356
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• 2007

This study deals with an early detection problem of structural change in won/dollar exchange market. A CUSUM algorithm is developed to monitor relevant economic variables indicating structural change in won/dollar exchange market. We applied the CUSUM algorithm to examine whether or not it was possible to alarm the 1997 economic crisis of Korea in advance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.422-425
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• 2012

Korea's conventional iPhone users had to pay for their applications in dollars. However, Apple will have to consider implementing a payment system in Korean won. Apple has strongly insisted on using the payment system in dollars, but despite its relatively small sales proportion, it will turn to the Korean market that ranks 3rd in the world for its number of downloads. In other words, the Korean market has tremendous potential for growth. Thus, this study aimed to analyze the changes that will be experienced by Apple in the Korean market due to the implementation of the iPhone-based won payment system, price fluctuations due to the introduction of iTunes, as well as positive aspects and implications of Apple's market expansion in Korea when users make payments in Korean won.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.57-75
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• 2004

The knowledge management is increasingly an important strategic weapon for sustaining competitive advantage of firms. Firms are undertaking knowledge management initiatives and making significant investments. However, there is relatively little empirical support for the impact of knowledge management on performance of firms. Understanding of the impact of knowledge management, this paper explores how knowledge management strategy influences firms' market value. We examine this issue using event study methodology and evaluate the cumulative abnormal returns for knowledge management strategy announced by firms from 1998 to 2002. The results show that firms' announcements of knowledge management strategy are positively related with firms' market value. Specially, dynamic style-which emphasizes both (i) knowledge reusability through information technologies and (ii) knowledge sharing through informal discussions among employees-has higher performance. This outcome presents empirical support to argument that the emphasis on both tacit and explicit knowledge results in better market value.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.329-337
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• 2003

Stock market prediction is regarded as a challenging task of financial time-series prediction. There have been many studies using artificial neural networks in this area. Recently, support vector machines (SVMs) are regarded as promising methods for the prediction of financial time-series because they me a risk function consisting the empirical ewer and a regularized term which is derived from the structural risk minimization principle. In this study, I apply SVM to predicting the Korea Composite Stock Price Index (KOSPI). In addition, this study examines the feasibility of applying SVM in financial forecasting by comparing it with back-propagation neural networks and case-based reasoning. The experimental results show that SVM provides a promising alternative to stock market prediction.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.77-91
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• 2004

This research compares the use of accounting data versus market data in the prediction of bankruptcy. Comparison is made through neural networks so that prediction accuracy is model-independent. Results of this study indicate that both market and accounting data provide useful information on corporate bankruptcies. Interestingly, using market and accounting information together can achieve substantial gain in prediction accuracy.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.185-188
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• 2000

Dongdaemoon clothes market can make traditional commerce to improve problems which happen to traditional commerce and satisfy between customers and salers through combination among Electronic Commerce which is growing up in 21 centuries place innovation This thesis is focusing on suggesting strategies which practice to let Dongdaemoon clothes market customers and wholesalers, retailers to use Electronic Commerce as strategic skills by analyzing core successful factors for adopting Electronic Commerce in Dongdaemoon clothes market. Adopting Electronic Commerce in Dongdaemoon clothes market when the customer make a reservation and the salers provide the customer with discounting service, the customer was willing to but it. Internet service categories which affect customer's satisfaction are providing lots of product information. This thesis shows providing information made the customer to increase customers's satisfaction degree and buying intention. Also convenience of product research, and reliability in transaction process can enable the customer to increase transaction reliability. These factors are very important in Electronic Commerce. In addition, factors which show customer's suggestion and inconvenience by using best seller information and discounting service board when they buy some items in Dongdaemoon clothes market affect the customer satisfaction degree and satisfaction degree of providing information. However, this thesis is analyzed that reliability of transaction process doesn't affect all successful factors such as product quality, size, online payment system, price reliability.

• The Journal of Information Systems
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• v.29 no.3
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• pp.119-144
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• 2020

Purpose Real estate usually takes charge of the highest proportion of physical properties which individual, organizations, and government hold and instability of real estate market affects the economic condition seriously for each economic subject. Consequently, practices for predicting the real estate market have attention for various reasons, such as financial investment, administrative convenience, and wealth management. Additionally, development of machine learning algorithms and computing hardware enhances the expectation for more precise and useful prediction models in real estate market. Design/methodology/approach In response to the demand, this paper aims to provide a framework for forecasting the real estate market with machine learning algorithms. The framework consists of demonstrating the prediction efficiency of each machine learning algorithm, interpreting the interior feature effects of prediction model with a state-of-art algorithm, LIME(Local Interpretable Model-agnostic Explanation), and comparing the results in different cities. Findings This research could not only enhance the academic base for information system and real estate fields, but also resolve information asymmetry on real estate market among economic subjects. This research revealed that macroeconomic indicators, real estate-related indicators, and Google Trends search indexes can predict real-estate prices quite well.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.165-173
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• 2000

Some people think that the Internet is a tool of making the current market as a perfect competition market and that the business model of selling products or services is not attractive. But research of this issue propose that the Internet give us new challenge of business. The objective of this study is to analyze the properties of Internet and Internet business and to evolute the Internet business model of selling products or services and to suggest survival strategies in fierce competition circumstances.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.455-461
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• 2009

This paper proposes Direct Load Control(DLC) operation scheme using a bidding system and the methodology to value proper quantity decided by the DLC program, which is a kind of resources for stabilization of electricity market price during peak times by managing consumer electricity demand. Since DLC program in Korea is based on the contract with the customers participating in this program, it is difficult to anticipate voluntary participation. That is, incentive for participants in DLC program is insufficient. To cope with this point, it is necessary to develop a new market mechanism and market compatible operation scheme for DLC programs. DLC market mechanism is deemed to be equipped with iterative bidding system, independent operation from energy market, and interactive with bidding information on energy market. With this market mechanism, it is important to find the optimal operation point of DLC allowing for the factors of stabilizing the electricity market price and compensating DLC implementation. This paper focuses on the mathematical approaches for the bid-based DLC operation scheme and examines several scenarios for the following technical justifications: 1) stabilization of electricity market price during peak times, 2) elasticity of demand.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.778-780
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• 2005

Electric power industry throughout the world is restructured. The electric power industry has a characteristics of an oligopoly with an imperfect competition. In Korea rules, all information is not available. So the strategy under such incomplete information market differ firm those under complete information system in game theory. This paper presents a analysis technique if Korea ma rket model with incomplete information.