• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.208-209
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• 2022

This study aims to analyze the risk factors caused by object damage and third-party damage loss in actual bridge construction based on past insurance premium payment data from major domestic insurers for bridge construction projects, and develop a quantitative loss prediction model. For the development of quantitative bridge construction loss model, the dependent variable was selected as the loss ratio, and the independent variable adopted 1) Technical factors: superstructure type, foundation type, construction method, and bridge length 2) Natural hazards: flood anf Typhoon, 3) Project information: total construction duration, total cost and ranking. Among the selected independent variables, superstructure type, construction method, and project period were shown to affect the ratio of bridge construction losses, while superstructure, foundation, flood and ranking were shown to affect the ratio of the third-party losses.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.37-41
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• 2018

Process safety technology has developed from qualitative methods such as HAZOP (hazard and operability study) to semi-quantitative methods such as LOPA (layer of protection analysis), and quantitative methods are actively studied these days. Quantitative risk assessment (QRA) is often based on fault tree analysis (FTA). FTA is efficient, but difficult to apply when failure events are not independent of each other. This problem can be avoided using a Markov process (MP). MP requires definition of all possible states, and thus, generally, is more complicated than FTA. A method is proposed in this work that uses an MP model and a Weibull distribution model in order to construct a reliability model for multiple dependent failures. As a case study, a pressure safety valve (PSV) is considered, for which there are three kinds of failure, i.e. open failure, close failure, and gas tight failure. According to recently reported inspection results, open failure and close failure are dependent on each other. A reliability model for a PSV group is proposed in this work that is to reproduce these results. It is expected that the application of the proposed method can be expanded to QRA of various systems that have partially dependent multiple failure states.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1943-1947
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• 2016

Korea Electrical Safety Cooperation(KESCO) have provided the electrical safety speed-call service from 2007 year. Purpose of the service is to reduce discomfort of electricity use and to prevent electrical accident like as electrical fire and shock accident by providing emergency treatment service on fault of the residential electrical facilities notified in the specific house like as a lower-income group and a social welfare facility. But efficiency and economic evaluation of the electrical safety speed-call service is impossible because analysis on the quantitative effect of the service is difficult. This paper presents cost-benefit analysis method and result of the electrical safety speed-call service. The presented cost-benefit analysis method has a two-step process: the first step is to measure quantitative electrical fire prevention effect of the service by using electrical accident statistics and developing outcome analysis logic model of the service effect, and the second step is to analysis cost-benefit(B/C)of the service by calculating quantitative benefit analysis on the measured quantitative electrical fire prevention effect. The results showed that cost-benefit(B/C)of the electrical safety speed-call service is over 4 after 2010 year.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2895-2905
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• 2018

We present a mixed multiplicative quantitative randomized response model which added a unrelated quantitative attribute and forced answer to the multiplicative model suggested by Bar-Lev et al. (2004). We also try to set up theoretical grounds for estimating sensitive quantitative attribute according to circumstances whether or not the information for unrelated quantitative attribute is known. We also extend it into the stratified mixed multiplicative quantitative randomized response model for stratified population along with two allocation methods, proportional and optimum allocation. We can see that the various quantitative randomized response models such as Eichhorn-Hayre's model (1983), Bar-Lev et al.'s model (2004), Gjestvang-Singh's model (2007) and Lee's model (2016a), are one of the special occasions of the suggested model. Finally, We compare the efficiency of our suggested model with Bar-Lev et al.'s (2004) and see that the bigger the value of $C_z$, the more the efficiency of the suggested model is obtained.

• Korean System Dynamics Review
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• v.17 no.2
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• pp.33-56
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• 2016

In this paper, a system dynamics model for explaining the application, grant and maintenance of patents is provided. Existing literatures regarding the patent application system are mostly econometric approaches that consider only economic variables such as GDP and R&D. The model in this paper includes patent variables such as disputes as well as economic variables. Moreover, we show that the model can be used in not only a quantitative prediction but also policy experiment. The results of the policy experiment shows that strengthening protection of patents tend to increase the propensity to patent more than R&D investment.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.363-364
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• 2023

The tunnel construction projects is demanded more efficient risk management measures and loss forecasts to prepare for risk losses from an increase in the trend of tunnel construction. This study aims to analyze the risk factors that caused the loss of material in actual tunnel construction and to develop a quantified predictive loss model, based on the past loss record of tunnel construction projects.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.53-63
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• 2017

Managing the quantitative measurement of the data control activities in enterprise wide is important to secure management of data governance. However, research on data governance is limited to concept definitions and components, and data governance research on evaluation models is lacking. In this study, we developed a model of quantitative assessment for data governance including the assessment area, evaluation index and evaluation matrix. We also, proposed a method of developing the model of quantitative assessment for data governance. For this purpose, we used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a quantitative evaluation model for data governance at the early stage of the study. This paper can be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• East Asian Economic Review
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• v.22 no.4
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• pp.507-529
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• 2018

This paper evaluates the whole impact of quantitative easing on inflation in Korea implemented by the central banks in four major advanced economies, the U.S., Euro Area, U.K. and Japan. According to the analysis employing a VAR-X model with the security holdings of those central banks an exogenous variable, quantitative easing is estimated to exert downward pressures on inflation in Korea. Considering the impulse responses of Korean macroeconomic variables to a quantitative easing shock, the spillover effect is transmitted through exchange rate channel while trade channel turns out to be ineffective. In an additional analysis assessing the impact of each quantitative easing program of the central banks, only those of the Fed and European Central Bank are estimated to be significant. The empirical results prove to be robust even if using long-term interest rates as an alternative indicator of quantitative easing.

• Management Science and Financial Engineering
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• v.10 no.1
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• pp.25-41
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• 2004

There have been many studies to build a model that can help investors construct optimal portfolio. Most of the previous models, however, are based upon the path-breaking Markowitz model (1959) which is a quantitative model. One of the most important problems with that kind of quantitative model is that, in reality, most of the investors use not only quantitative, but also qualitative information when they select their optimal portfolio. Since collecting both types of information from the markets are time consuming and expensive, making a set of target assets smaller, without suffering heavy loss in the rate of return, would attract investors. To extract only desired assets among all available assets, we need knowledge that identifies investors' preference for the risk of the assets. This study suggests two-layer decision-making rules capable of identifying an investor's risk preference and an architecture applying them to a quantitative portfolio model based on risk and expected return. Our knowledge-based portfolio system is to build an investor's preference-oriented portfolio. The empirical tests using the data from Korean capital markets show the results that our model contributes significantly to the construction of a better portfolio in the perspective of an investor's benefit/cost ratio than that produced by the existing portfolio models.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1548-1552
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• 2009

In the construction industry, IT has been an alternative for the enhancement of productivity and technical advances through a paradigm shift. While it has been recognized that the IT system will have a substantial influence on the industry, a quantitative valuation has been very limited. This paper has chosen EVMS (Earned Value Management System), which supports the integrated management of cost and schedule by utilizing IT tools, and which is the largest trend in the construction IT industry in Korea, in order to suggest an analysis model for the valuation of IT. The CVM (Contingent Valuation Method) is used to quantitatively measure intangible value of IT application. Then, a valuation and analysis model were suggested for the quantitative valuation of the effect of IT adoption. In terms of willingness to pay for EVMS, the expected benefits from the adoption of EVMS were US$ 584.52 per man annually. This research should be helpful for construction companies evaluating their investment to Project Management Information System.