• KDI Journal of Economic Policy
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• v.42 no.4
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• pp.117-138
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• 2020

Few studies have specifically focused on the uncertainty of demand forecasting despite the fact that uncertainty is the one of greatest risks for governments and private partners in PPP projects. This study presents a methodology for finding robust contract conditions considering uncertainty in travel demand forecasting in a PPP project. Through a case study of an urban railway PPP project in Korea, this study uncovered the risk of excessive government payments to private partners due to the uncertainty in contracted forecast ridership levels. The results allow the suggestion that robust contract conditions could reduce the expected total level of government payments and lower user fees while maintaining profitability of the project. This study offers a framework that assists contract negotiators and gives them more information regarding financial risks and vulnerabilities and helps them to quantify the likelihood of these vulnerabilities coming into play during PPP projects.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.165-178
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• 2016

Container port nowadays becomes one of the most vital link of the transportation chain, plays an important role in trading with other countries. Therefore, evaluating the operational efficiency of container ports to reflect their status and to reveal their position in this competitive environment is very important for port development. Although there have been lots of methods used to measure efficiency in the past, the DEA (Data Envelopment Analysis) model is still the most commonly applied approach. However, the data used in the model sometimes is complex and uncertain to handle using the basic DEA model. In this paper, we applied an uncertainty theory to create an uncertainty DEA model (UDEA), which can solve the limitation of the traditional one. This study mainly focuses on measuring efficiency of 41 container ports by applying proposed an UDEA model. The results show that among 41 container ports, only six container ports are regarded to have efficient operation through the clustering, meanwhile others have technical and scale inefficiencies. We found out that an UDEA model is better to analysis efficiency than existing DEA model.

• Journal of Korean Academy of Nursing
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• v.31 no.2
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• pp.244-256
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• 2001

The purpose of this study was to investigate the effects of coping mechanisms on uncertainty and depression. The subjects were 71 cancer patients selected from Junbook National University Hospital, and the data collection period was from June 21 to October 19 of 2000. Uncertainty was measured by using Mishel's Uncertainty Scale, problem- focused coping, and emotional-focused coping. The data was collected by a questionnaire developed by Lee (1984), and then depression measured by using Beck's depression scale. program by Pearson Correlation Coefficients, and Path analysis. The results were as follows : 1. The mean uncertainty score was 59.17, the mean problem-focused coping score was 48.78, the mean emotional-focused coping score was 42.52. 2. The mean depression score was 15.77. 3. Uncertainty in illness was significantly related to depression (p=0.003) and emotional-focused coping (p=0.028), but uncertainty was not associated with coping mechanisms. 4. When analyzed multiple regression between uncertainty, problem-focused coping, emotional- focused coping, and depression, more specifically emotional-focused coping showed a stronger association with depression than problem-focused coping. 5. Depression was highly correlated with economic status (p=0.015), educational background (p=0.005), duration of disease (p=0.045). 6. Problem-focused coping and emotional-focused coping appeared to function as moderators instead mediators on the relation between uncertainty and depression. In addition, as a whole, uncertainty showed a significant moderating effect on depression, while problem-focused coping did on depression. Finally, limitation of present findings were discussed and implications for future studies are suggested.

• Korean Management Science Review
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• v.33 no.3
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• pp.105-117
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• 2016

In this paper, we present empirical testing result to examine the validity of inbound supply and outbound demand risk factors in the sense of early predicting the firm's bankruptcy risk level. The risk factors are drawn from industry uncertainty attributes categorized as uncertainties of input market (inbound supply), and product market (outbound demand). On the basis of input-output table, industry level inbound and outbound sectors are identified to formalize supply chain structures, relevant inbound and outbound uncertainty attributes and corresponding risk factors. Subsequently, publicly available macro-economic indicators are used to appropriately quantify these risk factors. Total 68 industry level bankruptcy risk forecasting results are presented with the average R-square scores of between 53.4% and 37.1% with varying time lag. The findings offers useful insights to incorporate supply chain risk to the body of firm's bankruptcy risk level prediction literature.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.267-273
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• 2011

Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment in transport infrastructure has been active. However investment in transport infrastructure has more risks than others' due to uncertainty both in traffic volume and in construction cost. In the current appraisal procedure of deciding transportation infrastructure investment, instead of risk management, the sensitivity analysis considering only the changes of benefit, cost and social discount rate which are main factor affecting economic feasibility is carried out. Therefore the uncertainty of various factors affecting demand, cost and benefit are not considered in feasibility study. In this study the problems in current investment appraisal system were reviewed. Using Delphi technique the major factors which have high uncertainty in feasibility study were surveyed and then improvement plan was suggested in the respective of classic 4 step demand forecasting method. The range estimation technique was also mentioned to deal with the uncertainty of the future.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.43-51
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• 2018

We study the impact of economic policy uncertainty (EPU) of Asian four countries such as Korea, Japan, Hong Kong, and China on housing market returns in Korea. Also, we document the relationship between the EPU index of those four countries and the housing market including macroeconomic indicators in Korea. The EPU index of those four countries has significantly a negative effect on the housing purchase price index, housing lease price index in Korea. The EPU index in Korea and Japan has significantly a negative effect on the CPI. The EPU index in only Japan has significantly a negative effect on the PPI. The EPU index in Hong Kong and Korea has significantly a negative effect but the EPU index in China significantly has a positive effect on the stock price index in construction industry. The EPU index in only Korea has significantly a negative effect the stock price index in banking industry. This study shows the EPU index of the Korea has the negative relationships on the housing market economy rather than other countries by VECM. And this study has an important evidence of the spillover of several macroeconomic indicators in Korea for the EPU index of the Asian four countries.

• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.357-360
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• 2007

Any investment analysis has to deal with the uncertainty that arises over the course of operating the invested project. When it comes to an wind power, such analysis gets even more complicated, as the wind resource or the current is inherently unstable and unpredictable. Different from predecessors in the field of analyzing wind power economics, this paper proposes a stochastic methodology of analyzing the economic efficiency of an investment in wind power to explicitly address those uncertainties or risks. A probability distribution is assigned to each variable to generate a probability distribution of the economic value of an investment through a Monte-Carlo simulation

• Korean System Dynamics Review
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• v.11 no.3
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• pp.61-86
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• 2010

This research analyzed on the future energy society of Korea in 2030 using system thinking approach. Key uncertainty factors determining the future energy society were analyzed in a multi disciplinary view point such as politics, economy, society, ecology and technology. Three causal loop diagrams for the future energy system in Korea and related policy leverages were shown as well. 'Global economic trends', 'change of industrial structure' and 'energy price' were identified as key uncertainty factors determining the Korean energy future. Three causal loop diagrams named as 'rate of energy self－sufficiency and alternative energy production', 'economic activity and energy demand' and 'Excavation of new growth engines' were developed. We integrated those causal loop diagrams into one to understand the entire energy system of the future, proposed three strategic scenarios(optimistic, pessimistic and most likely) and discussed implications and limits of this research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.167-177
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• 2000

The problem of system reliability is very important issue in the nuclear power plant, because the failure of its system brings about extravagant economic loss, environment destruction, and quality loss. This paper therefore proposes a normalized scoring model by the qualitative factors order to evaluate the robust reliability of nuclear power plants under uncertainty. Especially, the qualitative factors including risk, functional, human error, and quality function factors for the robust justification has been also introduced. Finally, the analytical reliability and safety assessment model developed in this paper can be used in the real nuclear power plant.

• Environmental and Resource Economics Review
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• v.25 no.3
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• pp.403-419
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• 2016

Cap-and-trade policies that allow firms to trade emission allowances are designed to reduce emissions at least cost and are shown to be efficient when there is no uncertainty over emissions. This paper examines how uncertainty in emissions affects firms' decisions about permit purchase and abatement. The results show that whether firms abate more under uncertainty compared to a case with no uncertainty depends on the expected penalty cost and marginal abatement cost. If the expected marginal penalty cost is greater than the marginal abatement cost, the firm will choose to reduce emissions and abate more under uncertainty. When the expected marginal penalty is greater than the marginal cost of abatement, increases in uncertainty result in reduced emissions. This paper also examines whether the order of abatement and permit trading and the realization of uncertainty affect firms' decisions. The results show that total expected emissions are the same regardless of the order of moves.