• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1561-1570
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• 2015

Even though much investment to prevent or mitigate damage from information security breaches have been considered, researches on economically rational information security decision-making such as investment, management, etc. are not introduced in Korea. This study analyzes research themes and methodologies of articles presented at the Workshop on the Economics of Information Security (WEIS) for 2002 - 2014. Results of the study can suggest future research topics for researchers, and help make rational information security decision-making for practitioners.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.549-556
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• 2020

Real estate markets play an essential role in the economic development of both developed and developing countries. Investment decisions in private real estate demand the consideration of several qualitative and quantitative criteria. Especially in Vietnam, demand for housing, apartments are rising which has resulted because of the migration from rural to urban areas. This study aims to determine the influencing factors of the real estate purchasing behavior and then recommend a grey Multi-Criteria Decision Making (MCDM) support model to evaluate real estate alternatives based on a numerical example in Vietnam. A set of essential criteria are identified based on experts' opinion, and the proposed determinants are initial investment, maintenance cost, prestige location, distance to interesting places, parking lot, public transportation, property condition, total area size, number of rooms, and neighbors. The subjective weights were obtained by using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model, and the Grey Relational Analysis (GRA) technique is employed to prioritize and rank real estate alternatives. The results reveal that this approach can be useful to make purchasing decisions for many kinds of real estate property under uncertain business environments. These findings indicate that the presented hybrid model has advantages in granting flexibility to the preferences of decision makers.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.43-48
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• 2009

The purpose of the this paper is to make decision of the maintenance priority of power distribution system using Time-Varying Failure Rate(TVFR) with interruption cost. This paper emphasizes the practical use of the reliability indices and interruption cost. To make a decision of maintenance priority on power distribution system equipment, the quantification of the reliability level should be represented as a cost. In this paper, the TVFR of power distribution system equipment applied in this paper utilizes analytic method to use the historical data of KEPCO. From this result, the sensitivity analysis on TVFR of equipment was done for the priority, which represents that high priority of the equipment has more effect on system reliability, such as SAIDI or SAIFI, than other equipment. By this priority, the investment plan is established. In this result, customer interruption cost(CIC) could be extracted, and CIC is used as weighting factor to consider a importance of customer. After that, the result calculated the proposal method in this paper is compared with other priority method, such as lifetime, failure rate or only sensitivity.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.229-235
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• 2020

Investors aim to maximize the return rate for their own investment, utilizing various information as possible as they can access. However those investors, especially individual investors, have limitations of interpretation of the domain-specific information or even the acquisition of the information itself. Thus, individual investors tend to make decision affectively and frequently, which may cause a loss in returns. This study aims to analyze analysts' target price and to suggest the strategy that could maximize individual's return rate. Most previous literature revealed that the optimistic bias exists in the analysts' target price and it is also confirmed in this study. In this context, this study suggests the upper limit of target rate of returns and the optimal value named 'alpha(α)' which performs the adjustment of proposed target rate to maximize excess earning returns eventually. To achieve this goal, this study developed an optimization problem using linear programming. Specifically, when the analysts' proposed target rate exceeds 30%, it could be adjusted to the extent of 59% of its own target rate. As apply this strategy, the investors could achieve 1.2% of excess earning rate on average. The result of this study has significance in that the individual investors could utilize analysts' target price practically.

• Korea Trade Review
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• v.46 no.1
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• pp.169-187
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• 2021

This paper analyzes the feasibility of using machine learning and deep learning methods to forecast the income and employment using the strategic industries as well as investment, export, and exchange rates. The decision tree, artificial neural network, support vector machine, and deep learning models were used to forecast the income and employment in Busan. The following were the main findings of the comparison of their predictive abilities. First, the decision tree models predict the income and employment well. The forecasting values for the income and employment appeared somewhat differently according to the depth of decision trees and several conditions of strategic industries as well as investment, export, and exchange rates. Second, since the artificial neural network models show that the coefficients are somewhat low and RMSE are somewhat high, these models are not good forecasting the income and employment. Third, the support vector machine models show the high predictive power with the high coefficients of determination and low RMSE. Fourth, the deep neural network models show the higher predictive power with appropriate epochs and batch sizes. Thus, since the machine learning and deep learning models can predict the employment well, we need to adopt the machine learning and deep learning models to forecast the income and employment.

• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.137-159
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• 2001

This study provides a thorough methodology for IT Investment evaluation. A software tool to support the evaluation process was introduced along with a case study. The software supports the methodology that consists of 7 phases : Target analysis, ldentifying IT measures, Measuring IT impact, Assessing business value, Analyzing the decree of realization, Cost-benefit analysis, and Reporting. The case study showed that the software (CAFA) was a very useful tool supporting both decision-making and post-implementation reviews of IT investment.

• Information Systems Review
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• v.19 no.1
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• pp.185-202
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• 2017

Most studies based on production function theory have concluded that economic growth is a result of information technology (IT) capital use. However, some studies have indicated that economic growth is a determinant of IT investment. To determine if these results also hold at the industry level, we use the Granger causality test to analyze bidirectional causality with industry-level data for 1977~2007 from the United States. The results generally reveal that IT investment causes economic growth in many industries under the concept of Granger causality, that economic growth causes IT investment in some industries, and that IT investment is not associated with economic growth in some industries. In the country-level time-series data made by summing up the IT capital and gross output for each industry, the results do not show any causality between IT investment and economic growth. However, they show bi-directional causality between IT investment and economic growth in the panel data. These results may be a source of IT productivity paradox.

• IE interfaces
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• v.14 no.3
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• pp.310-317
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• 2001

The purpose of this study is to investigate and to develop a decision support system for supporting the outworn facility replacement analysis in shipbuilding. This paper also provides an information system which can be effectively applied to various criteria in decision making. The modelbase of decision support system uses the concepts of the analytic hierarchy process along with an appropriate scoring methods. The AHP represents an improvement over other well-known scoring approaches since the criteria weights of priorities established by the AHP are not based on arbitrary scales, but use a ratio scale for human judgements. The proposed methodology in this research enables the decision maker to evaluate the investment alternatives based on qualitative data and quantitative data in a systematic way.

• Journal of Korean Society for Quality Management
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• v.22 no.3
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• pp.66-84
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• 1994

The investment to advanced manufacturing techniques is essential to reinforcement of furture competitiveness. To make a decision for selecting an appropriate manufacturing facility is very important ; it is, however, rather difficult to get a precise evaluation through conventional cost analysis methods. The supreme decision-maker does not only take into consideration tangible cost attributes in decision-making ; he also takes into account such intangible attributes as strategic ones. This study combines Analytic Hierarchy Process and Simulation in order to graph the variations of weighted indices of alternatives for effective decision making when cost attributes are uncertain. A numerical example is illustrated to explain the basic mechanics of the proposed decision procedure.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.6
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• pp.119-130
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• 2019

Although a well-established line of research has addressed the funding decision, the activities of investee startups to receive funding have been overlooked because prior research has been conduced from investor's point of view. In addition, funding does not result from one off decisions but from decision process with many stages. Moreover, the emphasis placed on specific investment criteria varies by different stages during the process. Therefore, understanding the initial funding of startups requires to analyze the strategic behaviors of startups throughout the entire funding decision process from first meeting with investors to funding success. This study investigates the initial funding process of startups, and the analysis is based on a case study of LetinAR one of the successful startups founded by students in South Korea. This study investigates how early start-ups were able to receive funding from startup's point of view, and the analysis is based on a case study of LetinAR, an augmented reality(AR) startup using Pin mirror technology. By adding "legitimacy building" stage that had not been addressed previously, we divided funding process into four stages: 1) legitimacy building, 2) familiarization, 3) screening, and 4) bargaining phase. We did not only analyze major criteria, but also strategic activities of startup at each stage. This study makes a contribution by helping us understand complicated process of funding and the successful strategic behavior of investor backed startups.