• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.211-229
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• 2004

The basis of cyber trading has been sufficiently developed with innovative advancement of Internet Technology and the tendency of stock market investment has changed from long-term investment, which estimates the value of enterprises, to short-term investment, which focuses on getting short-term stock trading margin. Hence, this research shows a Short-term Stock Price Forecasting System on Learning Agent System using DTA(Decision Tree Algorithm) ; it collects real-time information of interest and favorite issues using Agent Technology through the Internet, and forms a decision tree, and creates a Rule-Base Database. Through this procedure the Short-term Stock Price Forecasting System provides customers with the prediction of the fluctuation of stock prices for each issue in near future and a point of sales and purchases. A Human being has the limitation of analytic ability and so through taking a look into and analyzing the fluctuation of stock prices, the Agent enables man to trace out the external factors of fluctuation of stock market on real-time. Therefore, we can check out the ups and downs of several issues at the same time and figure out the relationship and interrelation among many issues using the Agent. The SPFA (Stock Price Forecasting System) has such basic four phases as Data Collection, Data Processing, Learning, and Forecasting and Feedback.

• IE interfaces
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• v.24 no.4
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• pp.408-419
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• 2011

R&D is a foundation for new business chance and productivity improvement leading to enormous expense and a long-term multi-step process. During the R&D process, decision-makers are confused due to the various future uncertainties that influence economic and technical success of the R&D projects. For these reasons, several decision-making models for R&D project investment have been suggested; they are based on traditional methods such as Discounted Cash Flow (DCF), Decision Tree Analysis (DTA) and Real Option Analysis (ROA) or some fusion forms of the traditional methods. However, almost of the models have constraints in practical use owing to limits on application, procedural complexity and incomplete reflection of the uncertainties. In this study, to make the constraints minimized, we propose a new model named Real Option Decision Tree Model which is a conceptual combination form of ROA and DTA. With this model, it is possible for the decision-makers to simulate the project value applying the uncertainties onto the decision making nodes.

• Journal of Family Resource Management and Policy Review
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• v.11 no.2
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• pp.1-19
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• 2007

The purpose of this study was to analyze the affecting factors on employed mens' retirement and reemployment decision making. The focus was on the process of employed mens' decision on retirement and their reemployment decision after retirement from present job. The major findings were as follows ; First, the employed men who had a retirement plan were having more household income, more household net asset, more savings and investment for elderly life, and more positive attitude toward retirement. Second, the major factors affecting on having retirement plan or not were employed mens' age, household income, expected income after retirement, savings and investment for elderly life, job, and attitude toward retirement. Third, the major affecting factors on expected retirement age were employed mens' age, health status, job security, and attitude toward retirement. Forth, the employed mens' reemployment decision was affected from their household income, expected income after retirement, pension ownership, and attitude toward retirement. From the findings, it can be concluded that the employed mens' age, economic status, and attitude toward retirement played a important role in the process of retirement and reemployment decision making.

• KDI Journal of Economic Policy
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• v.28 no.1
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• pp.117-144
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• 2006

This study is to analyze the existence of the real buffer effect that reflects the effect of beginning-of-period inventory stocks effect on the demand for fixed investment, and the financial buffer effect indicates the substitution effect between end-of-period inventory stock and the source of financing for fixed investment. I use panel data of 361 Korean listed non-financial firms during 1990-2003. After the crisis, it also observed whether the relationship between inventory stocks and fixed investment has altered or not. I review the theoretical connection between inventory stock and fixed investment through the paper by Bo(2004) and estimate the investment model by the method of GMM-SYS. The results show negative relation between end-of-period inventory stock and fixed investment in the whole period and each period classified, also it confirms that the relation between fixed investment and end-of-period investment is significantly negative. It can be interpreted through two aspects that firms not only use inventory stock as a buffer in response to unexpectedly high demand, but also utilize inventory stock as a source of financing for fixed investment. The results imply that firm's decision-making is much correlated with production-and-inventory stock adjustment, decision-making about fixed investment, and decision-making about financial affairs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.27
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• pp.113-119
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• 1993

The purpose of this study is to develop a analytic procedure of the alternatives for the FMS that consist of high-priced facilities. A procedure to analysis the alternatives are as follows. Stage one is procedure to appraise investment alternatives of FMS and devide factors into strategic, analytic, economic viewpoint and draw upon decision making matrix through normalization Stage two is appraise to normalized alternatives using TOPSIS model among multiple attributes decision making models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.855-861
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• 2017

Gordon & Loeb[1] suggested that the optimal level of investment decision of an enterprise is the point that the marginal benefit(MB) of information security investment is equal to the marginal cost(MC). However, many companies suffering from information security incidents are not aware of the fact that they are experiencing information security accidents and can not measure how much they are affected. In this paper, I propose a model of information security investment decision making under the incomplete information situation by modifying the Gordon & Loeb[1] model and compare the differences in investment level. Under the incomplete information situation the expected return from the information security investment tends to be lower than that of actual information security investment, and the level of investment is also less. This shows that if a third party such as the government gives accurate information such as the rate of incidents of information security accidents and the amount of damages, companies can expand their investment in information security.

• Journal of Arbitration Studies
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• v.17 no.2
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• pp.141-165
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• 2007

This study aims to make a contribution to the promotion of trade and economic development of South Korea, and, at the same time, call attention to the increasing trend of investment agreements concluded within Free Trade Agreements (FTA) by examining theoretically FTAs and dispute resolution and investigating systematically the conclusion procedure of agreements, and the system, institutions, and jurisdiction of dispute resolution, and presenting these findings to the government and investors involved. The most problematic aspect in the legal process of arbitration involving disputes over investment is that of arguments concerning the right of jurisdiction. When a dispute arises, even though an investor files for arbitration at an ICSID institution, the parties become involved in another energy-consuming argument even before proceeding to the hearing and decision of the original plan in cases in which the respondent of the dispute files an objection to the decision rights of the arbitral tribunal. As the main basis for this type of plea, the point of non-existence of jurisdiction is first raised where the applicable dispute does not fall under the range of investments defined in individual investment contracts or investment agreements such as a Bilateral Investment Treaty (BIT). To avoid an open-ended definition of investment for the range of investments, articles concerning investments in the FTA and NAFTA between Canada and the USA adopt the limited closed-list method. Article 96 of the FTA between Japan and Mexico applied the same abovementioned method of limited form of definition regarding range of investments and concluded BITs between member countries of APEC applied a similar method as well. Instead of employing the previously used inclusive definition, the BITs concluded between countries of Latin America and the USA are equipped with limited characteristics of an investment. Furthermore, to correspond with this necessary condition the three following requirements are needed : 1) fixed investment funding; 2) expected profits resulting from such investments; 3) and the existence of fixed risk bearing.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.229-242
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• 2012

Although many companies acknowledge the necessity of investment of information security, it is difficult to grasp a tangible effect and to calculate a scale of damage from the security incident. Consequently, companies are under the reality that it is not easy to make an investment decision for information security and to calculate the investment scale. For the investment decision making, although there are several traditional techniques of investment analysis, the investment of information security, comparing to other tangible assets, has limitations in using traditional techniques due to the highly uncertain investment effects. In this study, the traditional technique of investment analysis will be described, and the application method of analytic technique for Real Option, which is developed from the evaluation technique of highly uncertain financial futures and options, will be suggested.

• Asia pacific journal of information systems
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• v.9 no.4
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• pp.125-142
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• 1999

The increased investment in technological innovations makes the investigation of factors affecting technology adoption more interesting. Several perspectives have been proposed to explain the determinants of information technology adoption. While the traditional innovation diffusion research streams try to explain and predict adoption behavior with the adopter's perceptions about the characteristics of the innovation itself, critical mass theorists argue that adoption behavior as a collective action is based on what their business partners are doing and whether there exists enough critical mass to justify the investment. Drawing on theses two perspectives, this study investigates the decision criteria in the adoption of information technology as innovation and factors affecting the decision criteria. The survey results reveal that the adoption behavior is affected both by innovation characteristics and by critical mass's activity. Correlation analysis, t-test, and stepwise regression models also show that as the environmental uncertainty is getting higher, adoption decision is affected more by what others are doing, and that highly competitive organizations seem to play the role of critical mass.

• Korea Trade Review
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• v.46 no.2
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• pp.281-299
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• 2021

This paper analyzes the feasibility of using machine learning methods to forecast the employment. The machine learning methods, such as decision tree, artificial neural network, and ensemble models such as random forest and gradient boosting regression tree were used to forecast the employment in Busan regional economy. The following were the main findings of the comparison of their predictive abilities. First, the forecasting power of machine learning methods can predict the employment well. Second, the forecasting values for the employment by decision tree models appeared somewhat differently according to the depth of decision trees. Third, the predictive power of artificial neural network model, however, does not show the high predictive power. Fourth, the ensemble models such as random forest and gradient boosting regression tree model show the higher predictive power. Thus, since the machine learning method can accurately predict the employment, we need to improve the accuracy of forecasting employment with the use of machine learning methods.