• Korea Trade Review
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• v.46 no.2
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• pp.19-38
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• 2021

This study aims to analyze the foreign asset leverage effect on Korean oil & gas companies' foreign profits and to maintain the appropriate foreign asset volume for reducing exchange risk. For a long time, large Korean companies, including oil companies, overheld foreign currency liabilities. For this reason, most large companies have been burdened to hedge exchange risk and this excess limit holding deteriorated total profit and reduced foreign currency asset management efficiency. Our paper proceeds in presenting a three-stage analysis considering diversified exchange risk factors through estimation on transformation of foreign transactions a/c including annual trends of foreign asset and industry specifics. We also supplement incomplete the estimation method through a practical hedging case investigation. Our research parts are differentiated on the analyzing four periods considering period-specifics The FER value of the oil firms ranged from -0.3 to +2.3 over the entire period. The results of the FER Value are volatile and irregular; those results do not represent the industry standard comparative index. The Korean oil firms are over the credit limit without accurate prediction and finance high interest rate funds from foreign-owned banks on the basis on a biased relationship. Since the IMF crisis, liabilities of global firms have decreased. Above all, oil firms need to finance a minimum limit without opportunity losses on the demand forecast and prepare for uncertainty in the market. To reduce exchange risk from the over-the-limit position, we must consider factors that affect the corporate exchange risk on the entire business process, including the contract phase.

• Asia-Pacific Journal of Business
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• v.14 no.2
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• pp.63-84
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• 2023

Purpose - The purpose of this study is to examine the effect of CSR activities on innovation performance and to identify the mediating role of knowledge sharing and innovation behaviors between CSR activities and innovation performance. In addition, the purpose of this study is to verify the role of sequential mediating effect of knowledge sharing and innovation behavior between CSR activities and innovation performance. Design/methodology/approach - This study collected survey data from 293 organizational members working in Chinese companies. The exploratory factor analysis (EFA), confirmatory factor analysis (CFA), reliability analysis, correlation analysis and process macro were used in order to analyze the data. Findings - First, this study verified that CSR activities had a significant positive effect on knowledge sharing, innovation behavior, and innovation performance. Second, it was found that knowledge sharing had a significant positive effect on innovation behavior and innovation performance. Third, it was verified that innovation behavior had a significant positive effect on innovation performance. Fourth, knowledge sharing and innovation behavior had a sequential mediating effect in the relationship between CSR activities and innovation performance. Research implications or Originality - With the uncertainty of the environment and the intensification of competition among companies, more and more companies begin to pay attention to innovation. Different from existing studies, this study focuses on CSR activities, identifies the role of CSR activities, explores ways to guide innovation performance, and verifies the sequential mediating role of knowledge sharing and innovation behavior. Through this measure, the importance of knowledge sharing and innovative behavior among organizational members is emphasized, solutions to strengthen innovation are explored, and theoretical and practical implications are provided for companies.

• Geomechanics and Engineering
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• v.39 no.1
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• pp.1-11
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• 2024

Geotechnical parameter estimation is critical to the design, performance, safety, and cost and schedule management in Tunnel Boring Machine projects. Since these parameters vary within a certain range, relying on mean values for evaluation introduces significant risks to the project. Due to the non-homogeneous characteristics of geological formation, data may not exhibit a normal distribution and the presence of outliers might be deceptive. Therefore, the use of reliable analyses and simulation models is inevitable in the course of the data evaluation process. Advanced modeling techniques enable comprehensive analysis of the project data and allowing to model the uncertainty in geotechnical parameters. This study involves using Monte Carlo Simulation method to predict probabilistic distributions of field data, and therefore, establish a basis for designs and in turn to minimize project risks. In the study, 166 sets of geotechnical data Obtained from 35 boreholes including Standard Penetration Test, Limit Pressure, Liquid Limit, and Plastic Limit values, which are mostly utilized parameters in estimating project requirements, were used to estimate the geotechnical data distribution of the study field. In this context, firstly, the data was subjected to multi-parameter linear regression and variance analysis. Then, the obtained equations were implemented into a Monte Carlo Simulation, and probabilistic distributions of the geotechnical data of the field were simulated and corresponding to the 90% probability range, along with the minimum and maximum values at the 5% probability levels presented. Accordingly, while the average SPT N30 value is 42.86, but the highest occurrence rate is 50.81. For Net Limit Pressure, the average field data is 17.07 kg/cm², with the maximum occurrence between 9.6 kg/cm² and 13.7 kg/cm². Similarly, the average Plastic Limit value is 22.32, while the most probable value is 20.6. The average Liquid Limit value is 56.73, with the highest probability at 54.48, as indicated in the statistical data distribution. Understanding the percentage distribution of data likely to be encountered in the project allows for accurate forecasting of both high and low probability scenarios, offering a significant advantage, particularly in ordering TBM requirements.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.143-157
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• 2024

Purpose - This paper aims to analyze the relationship and correlation between the stock markets of Korea, the US, China, and Japan before and after the outbreak of COVID-19. Design/methodology/approach - This study conducted an empirical analysis using the stock market data from January 2016 to June 2023 for the representative market indices of Korea, the US, China, and Japan. The analysis employed the VAR model, Granger causality test, impulse response function, and variance decomposition. Findings - Analyzing the relationships of these stock markets before and after the outbreak of COVID-19, we obtained the following results. (i) The influence of the U.S. stock market was found to be absolute regardless of the COVID-19 period, and the rise in the U.S. stock market led to rises in other stock markets. (ii) The Chinese stock market had a significant negative impact on the U.S., Korean, and Japanese stock markets before COVID-19, but this influence disappeared after COVID-19. This suggests that the Chinese market exhibited unique characteristics different from the global market after COVID-19. (iii) Analyzing the period excluding the first quarter of 2020, when global stock market volatility was extremely high due to the spread of COVID-19, we found that the results were very similar to the analysis including the first quarter of 2020. Therefore, it is difficult to argue that the increased uncertainty during this period distorted the relationships among the stock markets of these four countries. Research implications or Originality - We anticipate that these findings will offer valuable insights for both individual and institutional investors, aiding them in portfolio diversification and risk mitigation.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3700-3716
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• 2024

Owing to spatial effects and vortex flow, flow in research reactors that use plate-type fuels can be maldistributed to the parallel channels of the core, which significantly impacts the reactor safety. In this study, the core flow of an advanced research reactor was measured in a real-scale facility under various hydraulic conditions. For flow measurement, integrated pressure lines were embedded in the mockups of 22 fuel assemblies and six fission molybdenum assemblies. Each assembly mockup was individually calibrated to obtain the relationship between the pressure drop and flow rate. Real-scale facility, which implements the characteristics of the hydraulic conditions in research reactors, was then used to evaluate the assembly-to-assembly flow distribution under normal operating condition, a partially withdrawn condition for the follower fuel assemblies, no flow for the pool water management system, and 1:1.5 asymmetric inlet flow condition. As a parallel channel system, core flow distribution was analyzed with conventional header design approach. Taking into account the measuring uncertainty, the core flow was uniformly distributed within 5 % under all conditions. This was mainly because the core flow resistance was sufficiently high and the vortex flow was minimized by the perforated plate.

• Korean Security Journal
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• no.26
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• pp.121-144
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• 2011

The Framework Act on the Management of Disasters and Safety 2004(FAMDS) currently underpins Korean civil protection system, and under this FAMDS, Korean civil protection establishes a three-tiered government structure for dealing with crises and disasters: central government, provincial & metropolitan government, and local government tiers. In particular, the concept of Integrated Emergency Management(IEM) emphasizes that emergency response organizations should work and act together to respond to crises and disasters effectively, based on the coordination and cooperation model, not the command and control model. In tune with this trend, civil protection matters are, first, dealt with by local responders at the local level without direct involvement of central or federal government in the UK or USA. In other words, central government intervention is usually implemented in the UK and the USA, only when the scale or complexity of a civil protection issue is so vast, and thus requires a degree of central government coordination and support, resting on the severity and impact of the event. In contrast, it appears that civil protection mechanism in Korea has adopted a rigid centralized system within the command and control model, and for this reason, central government can easily interfere with regional or local command and control arrangements; there is a high level of central government decision-making remote from a local area. The principle of subsidiarity tends to be ignored. Under these circumstances, it is questionable whether such top-down arrangements of civil protection in Korea can manage uncertainty, unfamiliarity and unexpectedness in the age of Risk Society and Post-modern society, where interactive complexity is increasingly growing. In this context, the study argues that Korean civil protection system should move towards the decentralized model, based on coordination and cooperation between responding organizations, loosening the command and control structure, as with the UK or the USA emergency management arrangements. For this argument, the study basically explores mechanisms of civil protection arrangements in Korea under current legislation, and then finally attempts to make theoretical suggestions for the future of the Korean civil protection system.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.71-88
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• 2012

The global warming is probably the most significant issue of concern all over the world and according to the report published by the Intergovernmental Panel on Climate Change (IPCC), the average temperature and extent of global warming around the globe have been on the rise and so have the uncertainty for the future. Such effects of global warming have adverse effects on basic foundation of the mankind in numerous ways and water resource is no exception. The researches on water resources assessment for climate change are significant enough to be used as the preliminary data for researches in other fields. In this research, a total of 124 peer-reviewed publications and 57 reports on the subject of research on climate change related to water resources, that has been carried out so far in Korea has been reviewed. The research on climate change in Korea (inclusive of the peer-reviewed articles and reports) has mainly focused on the future projection and assessment. In the fields of hydrometeorology tendency and projection, the analysis has been carried out with focus on surface water, flood, etc. for hydrological variables and precipitation, temperature, etc. for meteorological variables. This can be attributed to the large, seasonal deviation in the amount of rainfall and the difficulty of water resources management, which is why, the analysis and research have been carried out with focus on those variables such as precipitation, temperature, surface water, flood, etc. which are directly related to water resources. The future projection of water resources in Korea may differ from region to region; however, variables such as precipitation, temperature, surface water, etc. have shown a tendency for increase; especially, it has been shown that whereas the number of casualties due to flood or drought decreases, property damage has been shown to increase. Despite the fact that the intensity of rainfall, temperature, and discharge amount are anticipated to rise, appropriate measures to address such vulnerabilities in water resources or management of drainage area of future water resources have not been implemented as yet. Moreover, it has been found that the research results on climate change that have been carried out by different bodies in Korea diverge significantly, which goes to show that many inherent uncertainties exist in the various stage of researches. Regarding the strategy in response to climate change, the voluntary response by an individual or a corporate entity has been found to be inadequate owing to the low level of awareness by the citizens and the weak social infrastructure for responding to climate change. Further, legal or systematic measures such as the governmental campaign on the awareness of climate change or the policy to offer incentives for voluntary reduction of greenhouse gas emissions have been found to be insufficient. Lastly, there has been no case of any research whatsoever on the anticipated effects on the economy brought about by climate change, however, there are a few cases of on-going researches. In order to establish the strategy to prepare for and respond to the anticipated lack of water resources resulting from climate change, there is no doubt that a standardized analysis on the effects on the economy should be carried out first and foremost.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.37-45
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• 2008

It is expected that conditions of water resources will be changed in Korea in accordance with world wide climate change. In order to deal with this problem and find a way of minimizing the effect of future climate change, the usefulness of climate model simulation information is examined in this study. The objective of this study is to assess the applicability of GCM (General Circulation Model) information for Korean water resources management through uncertainty analysis. The methods are based on probabilistic measures of the effectiveness of GCM simulations of an indicator variable for discriminating high versus low regional observations of a target variable. The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. An estimator that accounts for climate model simulation and spatial association between the GCM data and observed data is used. Atmospheric general circulation model (AGCM) simulations done by ECMWF (European Centre for Medium-Range Weather Forecasts) with a resolution of $2^{\circ}{\times}2^{\circ}$, and METRI (Meteorological Research Institute, Korea) with resolutions of $2^{\circ}{\times}2^{\circ}$ and $4^{\circ}{\times}5^{\circ}$, were used for indicator variables, while observed mean areal precipitation (MAP) data, discharge data and mean areal temperature data on the seven major river basins in Korea were used for target variables. The results show that GCM simulations are useful in discriminating the high from the low of the observed precipitation, discharge, and temperature values. Temperature especially can be useful regardless of model and season.

• Management & Information Systems Review
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• v.29 no.4
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• pp.333-357
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• 2010

Purposes of this paper are to investigate whether managers' compensation is sticky as accounting performance(ROA) vary or not and explore further what factors influence the managers' compensation stickiness. To empirically study the stickiness of managers' compensation, we used the financial data from manufacturing firms lised in the Korea Stock Exchange(1,000 firm-year data for 4 years). The results are as follows : First, managers' compensation is sticky with respect to change in accounting performance. That is, the increase in managers' compensation as accounting performance increases is greater than the decrease in managers' compensation in respect to equivalent decrease in accounting performance. Second, the degree of managers' compensation stickiness increases when managers have influence and contribution to firm value. Specifically, the degree of stickiness is positively associated with investment opportunity set, intangible assets' value, uncertainty of firms' operating environment, complexity of organizational hierarchy. But firms' size reversely impacts on the degree of managers' compensation stickiness.