• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.107-110
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• 1996

Continuing advances in the formulation and solution of risk-sensitive control problems have reached a point at which this topic is becoming one of the more intriguing modern paradigms of feedback thought. Despite a prevailing atmosphere of close scrutiny of theoretical studies, the risk-sensitive body of knowledge is growing. Moreover, from the point of view of applications, the detailed properties of risk-sensitive design are only now beginning to be worked out. Accordingly, the time seems to be right for a survey of the historical underpinnings of the subject. This paper addresses the beginnings and the evolution, over the first quarter-century or so, and points out the close relationship of the topic with the notion of optimal cost cumulates, in particular the cost variance. It is to be expected that, in due course, some duality will appear between these notions and those in estimation and filtering. The purpose of this document is to help to lay a framework for that eventuality.

• Proceedings of the KSR Conference
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• 2001.05a
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• pp.44-51
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• 2001

To account for uncertainties involved in an economic analysis of project, sensitivity analysis are usually being done in Korea. Though useful for policy analysis, but it larks explicit consideration of probability of occurring certain events considered in the sensitivity analysis. Risk analysis otherwise can explicitly account for the probability of certain event which has dire impact on project viability, such as cost, discount rate, and size of benefit. This paper reports experience of applying risk analysis method for economic evaluation of railroad investment. Probability distribution of event has paramount impact on the risk analysis results, while not many prior researches dealt with these issues. Probability distribution of rolling stock cost and operating cost, in addition to those cost variables, are developed considering railway demand in this study. Case study results are reported. Issues in applying risk analysis are reported in addition to further research direction.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.285-286
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• 2021

These days, interior construction is performed to prevent the deterioration of old building finishings or to make distinctive designs. In case of interior construction, a construction cost is estimated through basic 2D drawings in the design step. Accordingly, an efficient construction plan and direction is established according to budget. In such a case, construction is dependent on 2D drawings. At that time, a risk can occur easily. This study is aimed at reducing the cost and risk of interior construction by implementing 3D drawings with the use of the visual data of 2D drawings. For accurate analysis, 2D drawings were completed, and then 3D interior construction modeling for various buildings was conducted with the 3D modeling software 3D Max. According to the 3D modeling, it reduced the cost and risk more than 2D drawings based design, and influenced the improvement in the understanding of orderers and workers.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.488-493
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• 2013

Accurate initial cost estimates are essential to effective management of construction projects where many decisions are made in the course of project management by referencing the estimates. In practice, the initial estimates are frequently derived from historical actual cost data, for which standard distribution-based techniques are widely applied in the construction industry to account for risk associated with the estimates. This approach assumes the same probability distribution of estimate errors for any selected estimates. This assumption, however, is not always satisfied. In order to account for the probabilistic nature of estimate errors, an alternative method for measuring the risk associated with a selected initial estimate is developed by applying the Bayesian probability approach. An application example include demonstrates how the method is implemented. A hypothesis test is conducted to reveal the robustness of the Bayesian probability model. The method is envisioned to effectively complement cost estimating methods that are currently in use by providing benefits as follows: (1) it effectively accounts for the probabilistic nature of errors in estimates; (2) it is easy to implement by using historical estimates and actual costs that are readily available in most construction companies; and (3) it minimizes subjective judgment by using quantitative data only.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.13-24
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• 2022

Construction projects are exposed to various types of risks, which tend to increase. The increasing risks call for contractors' more attentions to forecasting and dealing with these risks. One of the measures to deal with contractors' risks is to forecast or estimate risk cost and include it in the construction budget. Although various researches in relation to risk cost have been observed, little attention has been paid to general contractors' perceptions and current practices in estimating risk cost of construction budget. The objective of the study is to identify and discuss key characteristics and implications based on the survey and analysis of general contractors' perceptions and current practices in estimating risk cost of construction budget. The study shows that there is a gap between the perception and the practice of estimating risk cost, that is, high perception of the importance of risk cost and a relatively low level of practice. It suggests that historical cost data, guidelines and corporate-level standard procedures are required to improve the current practice in addition to sufficient time allocations for risk cost estimating. It discusses that there is a need for using sophisticated estimating techniques including bid data analytics despite a low level of the current adoption, and also proposes that research and development in the field of the sophisticated estimating techniques should be further implemented in order to increase their practicality.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.623-635
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• 2021

The purpose of this research is to examine the impact of information risk on the Cost of Equity (COE) and whether the risk of a stock price crash mediates the relation between information risk and COE. To test the dynamic nature of the proposed model, the two-step system GMM dynamic panel estimators are applied to all the non-financial firms listed on the Pakistan Stock Exchange (PSX) from 2007- 2018. The results of this study show that all three types of information risk, as well as the risk of the share price crash, increases the COE. The crash risk strengthens the impact of information risk on the COE. Moreover, these three information risks are correlated with each other and an increase in information quality reduces the effect of asymmetric information and improves the investor interpreting ability, while an increase in private information decreases the transparency. The finding is crucial for asset pricing, portfolio management, and information disclosure. This study contributes to the literature by providing novel findings on the impact of three different types of information risk, i.e. private information, quality of information, and transparency of information on the COE as well as whether crash risk mediates the relationship.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.85-99
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• 1995

Increasingly, risk analysis is becoming important ingredients in achieving the successful implementation and application in the area of the project management. The project management system is designed to manage or control the project resources on a given activity within time, cost and performance so called TPPM (Total Productive Project Management). In this research, a risk analysis model misproposed to identify potential problem areas, quantify the risks, and generated the chice of the action that can be taken to reduce the risk. In addition two analysis models are proposed : 1) risk factor model and 2) network simulation model using VERT (Venture Evaluation and Review Technique ). The objective of the remodels is to estimate the schedule, cost performance risks. These proposed quantitative models for project risk analysis are proving its value for the project managers who need to assess the risk of changes in cost, schedule, or performance. The proposed models will be used in the area of project selection, evaluation and the allocation of project resources.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1176-1182
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• 2009

Due to recession in real estate market, interest of risk analysis is increasing. Feasibility study in the first stage takes a great role in a project. There are not objectified tools which are able to cope with uncertainty of project, and feasibility study based on selected method of determinism does not include liquidity of weight risk. Also, shortage of consideration for subjective and atypical external factors causes inappropriate results. Therefore, this study proposes feasibility study model focused on risk factor influences in construction cost and sales cost. Considering effective level of cost based on objective risk factors and probable weight of risk by this model, real workers are able to bring correct and scientific decisions better than former method based on selective analysis of real estate development.

• Korean Journal of Construction Engineering and Management
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• v.1 no.1 s.1
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• pp.63-71
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• 2000

The paper considers two non-deterministic methods of analysing the risk exposure in a cost estimate The fist method(referred to as the 'conventional statistical' method) analyses cost data directly, to describe a probability distribution for total cost. The second method(referred to as the 'Monte Carlo simulation' method) interprets cost data directly, to generate a probability distribution for total costs from the descriptions of elemental cost distribution. The common practice of allowing for risk through an all-embracing contingency sum or percentage addition is challenged. Rather than excluding conventional, non-deterministic methods, they are here presented as possibly the only of effective foundation on which to risk management in cost estimating.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.147-156
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• 1997

This Study deals with the problem of determining a minimum cost sampling inspection plan for destructive testing by attribute. The linear cost model(LCM) is constructed under the assumption that unit cost, destructive testing cost, producer's risk cost, consumer's risk cost are given. For the solution from the LCM, we assumed the uniform distribution as a prior distribution.