• Journal of Arbitration Studies
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• v.30 no.2
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• pp.165-184
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• 2020

In this study, the factors affecting opportunism in the relationship between suppliers and key accounts were analyzed from the viewpoint of transaction cost theory, market power theory, and relationship marketing theory. As a result of the hypothesis test, Hypothesis 1 stating that demand volatility will have a positive effect on opportunism and Hypothesis 2 that transaction-specific investment will have a positive effect on opportunism were also supported. In addition, Hypothesis 3 stating that channel power will have a positive effect on opportunism was also supported. Lastly, Hypothesis 4 stating that relational commitment will have a negative effect on opportunism was not supported, along with Hypothesis 5 stating that transaction satisfaction will have a negative effect on opportunism. The theoretical and practical implications of this study are as follows. This study has identified the antecedents of opportunism by comprehensively applying the transaction cost theory, market power theory, and relationship marketing theory. In addition, this study can identify what a company should manage specifically to lower opportunism by identifying the antecedents of opportunism. The limitations of this study and the directions for future studies are as follows. First, not all of the antecedents of opportunism of key accounts have been extensively investigated from the viewpoint of the transaction cost theory, market power theory, and relationship marketing theory. In the future, it is necessary to identify additional factors. Second, the study was conducted only in the supplier's viewpoint. In future studies, it is expected that more accurate research results can be obtained by simultaneously examining not only the supplier's point of view but also the buyer's point of view.

• Journal of Korea Port Economic Association
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• v.35 no.2
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• pp.61-76
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• 2019

The purpose of this study is to use the EGARCH model and Granger causality test to analyze how the change in the BDI affects the Korean stock price volatility. The main analysis results are summarized as follows. First, according to the results of the mean equation, the change in the BDI is significant in large-cap stocks, as well as in the manufacturing, service, and chemistry indexes, but not in others. This implies that the Korean stock market does not respond appropriately to the maritime market situation; further, the increase in demand for raw materials has not led to a real economic recovery. Second, in the result of the variance equation, the coefficient on the change in the BDI is negative(-), and the change in the BDI is significant for all size indexes. Particularly, the change in the BDI has a greater impact on the volatility of small-cap stocks than that of large-cap stocks. The results of the analysis of the sector indexes were statistically significant for the service, financial, construction, and electric and electronics industries, but not for the manufacturing and chemical industries. In particular, the changes in the BDI have the greatest impact on the construction industry. Third, according to the Granger causality test results, the change in the BDI leads the financial industry and construction industry. There is, however, no relationship between the BDI and the other indexes. This shows that change in the shipping freight index can be used to predict the volatility in the Korean stock market. This can help investors and policymakers make better decisions.

• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.631-638
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• 2015

Today, the demand for speech recognition systems in mobile environments is increasing rapidly. This paper proposes a novel method for Korean phoneme segmentation that is applicable to a phoneme based Korean speech recognition system. First, the input signal constitutes blocks of the same size. The proposed method is based on a volatility indicator calculated for each block of the input speech signal, and the bulk indicators calculated for each bulk in blocks, where a bulk is a set of adjacent samples that have the same sign as that of the primitive indicators for phoneme segmentation. The input signal vowels, voiced consonants, and voiceless consonants are sequentially recognized and the boundaries among phonemes are found using three devoted recognition algorithms that combine the two types of primitive indicators. The experimental results show that the proposed method can markedly reduce the error rate of the existing phoneme segmentation method.

• Asia-Pacific Journal of Business
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• v.13 no.2
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• pp.39-50
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• 2022

Purpose - The purpose of this study is to examine how Korea's macroeconomic factors, such as GDP, CPI, Export, Import, Unemployment rate and USD/KRW exchange rate, are affected by the oil price shocks. Design/methodology/approach - This study used monthly and quarterly time-series data of each variable for the period 1983 to 2022, consisting of two sub-periods, to employ Granger causality test and GARCH method in order to identify the role of the oil price movement in macroeconomic factors in Korea. Findings - Korea's currency rate to the US dollar is negatively correlated with the price change of crude oil while the GDP change is positively correlated with the price change of crude oil with strong relationship between Export and Import in particular. The exchange rate and GDP growth are believed to be not correlated with the oil price change for the pre-GFC period. According to the Granger causality test, the price change in crude oil has a causal impact on CPI, Export and Import while other factors are relatively slightly affected. Transmission effect from the oil price to Export is found and there also exists volatility spillover from oil price to economic variables under examination. Comparing two sub-periods, CPI and Export volatility responds negatively to shocks in the oil price for the pre-GFC period while volatility of CPI and Unemployment reacts positively to the oil price shocks for the post-GFC period. Research implications or Originality - The findings of this study could be helpful for both domestic and international investors to build their portfolio for the risk management since rising WTI price can be interpreted as a result of global economic growth and ensuing increase in the worldwide demand of the crude oil. Consequently, the national output is expected to increase and the currency is also expected to be strong in the long run.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.4
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• pp.17-24
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• 2016

The purpose of this paper is to understand the underlying dynamics for the share market bubbles in China during the most recent decade. By using the behavioral finance theory and the Shanghai Composite index prices during the periods from 2005 to 2008 and from 2014 to 2015 as the study samples, we find that the large volatilities in the Chinese share market are closely related to information blockage, which impedes share prices to timely respond to economic conditions as well as external shocks and increases (decreases) the demand of shares when the supply is difficult to adjust. Although the Chinese government has introduced a series of programs designed to increase more reliable information to the public, the share market still tends to confront issues of information asymmetry. The potential reason is that the reforms did not change the long-stand situation in China, where individuals or groups related to government bureaucracy who play a dominant role in the society are given priority to gain access and obtain information that benefits. By identifying the main reasons for the large volatilities in the market, policy makers are given advice as to which areas they may need to focus on to improve future market performance.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.331-338
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• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.85-97
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• 2018

This paper investigates factors underlying a decrease in trading values in KOSPI 200 futures/options market on the basis of the current state of the markets. Among the factors that could affect trading values in KOSPI 200 derivatives market, we focus on the market activity of underlying assets as it has an impact on the trading of financial derivatives. Trading value and volatility are designated as market activity and the empirical results confirm that the market activity of the underlying assets is significant in explaining the decrease in trading values in KOSPI 200 futures/options market. To figure out fundamental reasons of the decrease in trading values in this market, we examine mitigation of home bias and decrease in leverage incentives as they are presumed to have influence on KOSPI 200 index market. As the global and local financial environment is time-varying, the degree of home bias and the leverage demand also changes. It implies that institutional change and/or policy effort to promote the trading of KOSPI 200 financial derivatives should be made taking into account the fact that considerable portion of the change in trading values in financial derivatives market depends on the state of the market.

• Korea Trade Review
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• v.47 no.2
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• pp.133-154
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• 2022

The Baltic Capesize Index (BCI), which is used as an indicator for marine transportation of steel raw materials, is one of the key economic indexes for managing the risk of loss due to rapid market fluctuations when steel companies establish business strategies and procuring plans for raw materials. Still, the conditions of supply and demand of steel raw materials has been extremely affected by volatility shocks from drastic events like the financial crisis such as the Lehman Brothers incident and changes in the external environment such as COVID-19. And, especially since the 2008 financial crisis, endeavors to predict the market conditions of the steel raw material is becoming more and more arduous for the deepening uncertainty and increased volatility of BCI, which has been used as a leading indicator of the real economy. This study investigates the correlation between the steel raw material market and the marine transportation market by estimating the spillover effect of information between markets. The vector error correction model (VECM) was used to analyze information transfer based on the correlation between the BCI and crude steel production, capesize fleet supply, raw material price, and cargo volume.

• Resources Recycling
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• v.22 no.5
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• pp.3-12
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• 2013

It is necessary to manage risk of metals which are has rigid supply structures and expected demand expansion, considering to industry structure and resource securing capacity of each country. Countries conducted various criticality analyses and selected mainly rare metals as critical materials(or Critical metals or Critical raw materials). This study examined cases of metals risk evaluation and management which are based on technology changes and imbalance supply-demand. EU and U.S.A evaluated risk on metals needed as supply expansion of renewable energy. Japan forecasted demand of rare metals needed in Japan's growth engine industry. U.K analyzed criticality of metals, considering environmental burden occurred from mining to refining. Critical materials has features such as weak price signal, inelastic supply structure, demand volatility in technology change.

• Korea Trade Review
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• v.47 no.1
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• pp.13-24
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• 2022

This study was conducted because the global economic downturn caused by COVID-19 caused a surge in logistics costs and it was no longer possible to predict logistics costs using existing methods. For this study, we made the assumption that economic indicators affect logistics cost. Chapter 2 examines the current status of the liner market and factors affecting logistics costs. Based on this, Chapter 3 collects independent and dependent variables to determine the analysis model. As the independent variable, economic indicators of major countries constituting the SCFI were selected, and the dependent variables were the SCFI Europe Index and the SCFI USA Index. In Chapter 4, a panel analysis was conducted based on this, and it was confirmed that major economic indicators had a negative (-) effect on SCFI. This is contrary to the existing research results, which can be attributed to the special situation caused by COVID-19 and the imbalance of demand and supply by region. The results of this study are meaningful in that they can predict long-term logistics cost volatility without analyzing supply and demand, and can be applied to other studies as well.