• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.418-421
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• 2003

Most construction companies recognize the necessity of risk management. The practical application, however, is not easy because of the absence of systematic procedure for risk management and the difficulty in objectification of subjective risk factors. This study suggests a systematic procedure and a models. In the first place for those researches, this study analyzes the present condition of risk management in the construction industry. The developed model can be used as a risk management tool that enables evaluation of construction risk factors by quantified method, and it provides project managers with the methods to prevent risk and to deal with potential risk factors in the planning and construction phases. The results of this study could be used as references for related researches because this study attempts to develop a systematic tool for risk management including risk identification, risk analysis. risk action phases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.469-480
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• 2006

The results of the study include a computerized system and a systematic process model for risk management and analysis. This study analyzes the present status of risk management in the construction industry, and then suggests reasonable methods for improved risk management plans. This study defines risk management procedures as preparation, identification, analysis, response and management to manage potential risks in the construction project. The modules for computerizing in this system consist of planning, construction, application of WBS (Work Breakdown Structure) and RBS (Risk Breakdown Structure), and risk analysis. The methodology for analyzing construction risk uses fuzzy theory, and the scope of developed system is focused to the contractors. The risk management system suggested in this study operates on the Internet, for providing contractors with a useful risk management tool by online system, with web-based menus that is helpful for practical application.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.475-480
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• 2008

In BTL project, the operation cost covering upcoming 20 years is usually alloted more than construction cost although its plan is made in short time. Therefore, it is a key issue to forecast and to analyze operation risks in the process of making contract in order to successfully finish the BTL project and to ensure the profitability of business. However, only a few domestic professional management companies are capable to carry out funding and facility management. To manage the potential risks efficiently in BLT project, it's essential to prioritize the risk factors by means of considering economical risk level, non-economical risk level and occurrence frequency. Thus, this study suggests risk analysis model for improving efficiency of BTL project from operation company's perspective by means of survey. The suggested risk analysis model is expected to establish a risk management strategy which can improve the efficiency of management affairs in BTL project.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1333-1343
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• 2014

Hansen and Lund (2005) documented that a univariate GARCH(1,1) model is no worse than other sophisticated GARCH models in terms of prediction errors such as MSPE and MAE. Here, we extend Hansen and Lund (2005) by considering multivariate GARCH models and incorporating risk management measures such as VaR and fail percentage. Our Monte Carlo simulations study shows that multivariate GARCH(1,1) model also performs well compared to asymmetric GARCH models. However, we suggest that actual model selection should be done with care in light of risk management. It is applied to the realized volatilities of KOSPI, NASDAQ and HANG SENG index for recent 10 years.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.101-108
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• 2004

The results of the study include a computerized system and a systematic Process model for risk management and analysis. This study analyzes the present status of risk management in the construction industry, and then suggests reasonable methods for improved risk management plans. This study defines risk management procedures as preparation, identification, analysis, response and management to manage potential risks In the construction project. The modules for computerizing this system consist of planning, construction, application of WBS (Work Breakdown Structure) and RBS (Risk Breakdown Structure), and risk analysis. The method logy for analyzing construction risk uses fuzzy theory, and the scope of developed system is focused to the contractors. The risk management system suggested in this study operates on the Internet, for providing contractors with a useful risk management tool by online system, with web-based menus that is helpful for practical application.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.423-432
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• 2010

This study suggested CRMS (construction risk management system) which is a new risk analysis model after analyzing existing risk management process for to guarantee a successful performance at the construction planning and work phase. CRMS is risk management procedures in order that the contractor identify, analyze and administrate the risk during performing construction project. This model may give much help to quantify and be ready the right managing methods about identified risk by the contractor. Especially, the most important and difficult things of all risk management may be to identify risk in the project. This study make more focusing on the developing a procedure that can identify risk more easily in the construction project. The risk is divided into global risk and local risk of a project. Also, this study suggests methods which are using the RBS (risk breakdown structure) related with WBS. This result will be useful as basic materials for developing computerizing system for risk management.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.519-524
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• 2001

Recently, our construction market recognizes the necessity of risk management, however the application of practical system is still limited on the construction site because the methodology for analyzing and quantifying construction risk and for building actual risk factors is not easy. This study suggests a risk management method by fuzzy theory, which is using subjective knowledge of an expert and linguistic value, to analyze and Quantify risk. The result of study is expected to improve the accuracy of risk analysis because three factors, such as probability, impact and frequency, for estimating membership function are introduced to quantify each risk factor.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.539-544
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• 2007

Owing to diversification of social desire and increase of demand as economic growth, construction industry recently is trending toward diversification, complication, gigantism. It means that is changing to difficult environment as existing construction company operation. Specially, some big construction companies are promoting get down to construction business risk management skill & development. Enterprise risk management system, recognized to risk portfolio, is suggested. instead of individually risk management. This study indicates ERM basic model, considering construction risk character, for apply to ERM to field of construction . And it is including analysis of recognition level and reality about ERM in construction company.

• 방재와보험
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• s.150
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• pp.14-17
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• 2013

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.85-94
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• 2013

As the financial market becomes larger, the loss increases due to the failure of the credit risk managements from the poor management of the customer information or poor decision-making. Thus, the credit risk management also becomes more important and it is essential to develop a credit scoring model, which is a fundamental tool used to minimize the credit risk. Credit scoring models have been studied and developed only for binary target variables. In this paper, we consider other types of target variables such as ordinal multinomial data or longitudinal binary data and suggest credit scoring models. We then apply our developed models to real data and random data, and investigate their performance through Kolmogorov-Smirnov statistic.