• KDI Journal of Economic Policy
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• v.13 no.1
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• pp.3-33
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• 1991

Since the early 1980's, the Korean government has gradually been widening the Korean market to foreign consumer goods. This, combined with the increased purchasing power of the Korean consumers resulting from the continued economic growth of the country, has sparked a spectacular influx of foreign consumer goods into Korea, ranging from BMW's to chopsticks. Import of foreign consumer goods amounted to more than 6 billion dollars in 1989 and is continuing to grow at a rapid rate. The increased import of foreign consumer goods doubtlessly improved the overall welfare of the Korean consumers by providing them with a wider range of options to choose from, by lowering the prices of some of the consumer goods domestically produced, and also by forcing the producers of some Korean goods to face competition with better foreign goods, thus giving them an incentive to raise the quality of their products. However, it is agreed by most economists that this increase in general welfare has been much smaller than what they had expected at the outset. Consumer prices of most imported consumer goods are easily double the import price, and in some cases, more than treble the import prices. Further, there has not been a noticeable drop in the prices of domestically produced consumer goods. Much of the blame has been attributed to the distribution sector of Korea. The objective of this paper is to analyze the imported consumer goods distribution sector of Korea, focusing on the possible sources of the poor performance of that sector, and to make policy suggestions that could potentially increase the welfare. This paper differs from all the previous research by others on this subject in that it analyzes the imported consumer goods distribution sector of Korea as a vertical structure. The distribution sector of an imported consumer good is a vertical structure since it consists of an international market, an import stage, and domestic wholesale and retail markets, in that order vertically. Our study naturally includes the analysis of the vertical restraints as well as the analysis of the industrial organization of each horizontal stage in the vertical structure. Each horizontal component of the imported consumer goods distribution sector is basically a monopolistically competitive market differentiated by characteristics of goods and by the locations and the services of firms. Further, restrictive dealership and resale price maintenance are found to be widely in use. Our main findings are the follwing; First, most consumer goods are imported monopolistically or oligopolistically through restrictive dealership contracts between foreign producers and domestic importers. Such restrictive dealership gives importers market power in the domestic market and explains many of the large discrepancies betwen the consumer prices and the import prices of many goods. Korean anti - trust law does not cover the issues arising from the market power of an importer resulting from a restrictive dealership contract. Second, some major producers of Korean goods are also importers of foreign goods that are substitutes of their products. The import of substitutes by major domestic producers is anti - competitive because it tends to raise the prices of both domestic goods and foreign goods, and also because it reduces the incentive of the domestic producers to raise the quality of their products. Third, wholesalers and retailers widely use resale price maintenance as a price fixing mechanism, and while this is against the anti- trust law, it seldom gets noticed. Fourth, the high level of rents of real estate for commercial use works as an entry barrier to the distribution sector and results in reduced competition by the firms in that sector. Finally, there are information problems. Consumers have inferior information to firms about the quality of a foreign consumer good that they have not tried before. Such information asymmetry often enables firms to raise prices. In addition, information asymmetry between importers frequently delays the import of cheaper substitutes. In order to alleviate the problems indentified above, we suggest the following policy changes. The government should strengthen the anti - trust law and its enforcement to regulate restrictive import contracts, import of competing goods by major domestic producers, and RPM by wholesalers and retailers that is aimed at price fixing. In addition, the government should loosen its tight real estate policy to encourage investment in the distribution sector. Finally, we suggest that the import price revelation policy that has been in use for some items since 1990 be expanded to most imported consumer goods that are introduced for the first time to give consumer better information and be used only for the period of time needed to inform sufficient number of consumers.

• Journal of Korea Technology Innovation Society
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• v.10 no.1
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• pp.73-97
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• 2007

R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.

• Journal of the Korea Institute of Building Construction
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• v.24 no.2
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• pp.273-284
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• 2024

This study investigates the impact of international oil price fluctuations on overseas construction orders secured by domestic and foreign companies. The analysis employs statistical data spanning the past 20 years, encompassing international oil prices, overseas construction orders from domestic firms, and new overseas construction orders from the top 250 global construction companies. The correlation between these variables is assessed using correlation coefficients(R), determination coefficients(R²), and p-values. The results indicate a strong positive correlation between international oil prices and overseas construction orders. The correlation coefficient between domestic overseas construction orders and oil prices is found to be 0.8 or higher, signifying a significant influence. Similarly, a high correlation coefficient of 0.76 is observed between oil prices and new orders from leading global construction companies. Further analysis reveals a particularly strong correlation between oil prices and overseas construction orders in Asia and the Middle East, potentially due to the prevalence of oil-related projects in these regions. Additionally, a high correlation is observed between oil prices and orders for industrial facilities compared to architectural projects. This suggests an increase in plant construction volumes driven by fluctuations in oil prices. Based on these findings, the study proposes an entry strategy for navigating oil price volatility and maintaining competitiveness in the overseas construction market. Key recommendations include diversifying project locations and supplier bases; utilizing hedging techniques for exchange rate risk management, adapting to local infrastructure and market conditions, establishing local partnerships and securing skilled local labor, implementing technological innovations and digitization at construction sites to enhance productivity and cost reduction The insights gained from this study, coupled with the proposed overseas expansion strategies, offer valuable guidance for mitigating risks in the global construction market and fostering resilience in response to international oil price fluctuations. This approach is expected to strengthen the competitiveness of domestic and foreign construction firms seeking success in the international arena.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of the Korean Vacuum Society
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• v.16 no.3
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• pp.161-166
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• 2007

Photovoltaic (PV) technology permits the transformation of solar light directly into electricity. For the last five years, the photovoltaic sector has experienced one of the highest growth rates worldwide (over 30% in 2006) and for the next 20 years, the average production growth rate is estimated to be between 27% and 34% annually. Currently the cost of electricity produced using photovoltaic technology is above that for traditional energy sources, but this is expected to fall with technological progress and more efficient production processes. A large scale production of solar grade silicon material of high purity could supply the world demand at a reasonably lower cost. A shift from crystalline silicon to thin film is expected in the future. The technical limit for the conversion efficiency is about 30%. It is assumed that in 2030 thin films will have a major market share (90%) and the share of crystalline cells will have decreased to 10%. Our research at Sungkyunkwan University of South Korea is confined to crystalline silicon solar cell technology. We aim to develop a technology for low cost production of high efficiency silicon solar cell. We have successfully fabricated silicon solar cells of efficiency more than 16% starting with multicrystalline wafers and that of efficiency more than 17% on single crystalline wafers with screen printing metallization. The process of transformation from the first generation to second generation solar cell should be geared up with the entry of new approaches but still silicon seems to remain as the major material for solar cells for many years to come. Local barriers to the implementation of this technology may also keep continuing up to year 2010 and by that time the cost of the solar cell generated power is expected to be 60 cent per watt. Photovoltaic source could establish itself as a clean and sustainable energy alternate to the ever depleting and polluting non-renewable energy resource.

• Informatization Policy
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• v.23 no.4
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• pp.76-94
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• 2016

Recently in Korea, the importance of information security awareness has been receiving a growing attention. Attacks such as social engineering and ransomware are hard to be prevented because it cannot be solved by information security technology. Also, the profitability of information security industry has been decreasing for years. Therefore, many companies try to find a new growth-engine and an entry to the foreign market. The main purpose of this paper is to draw out some information security issues and to analyze them. Finally, this study identifies issues and suggests how to improve the situation in Korea. For this, topic modeling analysis has been used to find information security issues of each country. Moreover, the score of sentiment analysis has been used to compare them. The study is exploring and explaining what critical issues are and how to improve the situation based on the identified issues of the Korean information security industry. Also, this study is also demonstrating how text mining can be applied to the context of information security awareness. From a pragmatic perspective, the study has the implications for information security enterprises. This study is expected to provide a new and realistic method for analyzing domestic and foreign issues using the analysis of real data of the Twitter API.

• Journal of Global Scholars of Marketing Science
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• v.12
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• pp.29-57
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• 2003

Customers of local monopolistic department store can switch their store more easily than ever due to the rapidly changing environment in distribution system represented by multi-store-strategy of large department stores, increase in discount store and growing non-store retailing system. Consequently, local department stores which enjoyed their business with little competition are forced to study and understand the customer switching behavior. This work is intended to understand the switching behavior characteristics of monopolistic local clepartrrent store users. For the end, previous researches are reviewed firstly, then characteristics of store-switching behavior of custorrers amid rapidly changing distribution environment are studied in view of the relations of dissatisfaction factor, switching barrier, switch intention and custorrer characteristics such as shopping orientation, variety-seeking behavior, degree of openess to competition and sociodemographics. Study shows that; 1) dissatisfaction factor is related to customer characteristics (shopping orientation and degree of openess to competition), 2) switching barrier recognition is related to customer characteristics (degree of openess to competition and sociodemographics) and dissatisfaction factor, 3) intention to switch to expected competitor is related to customer characteristics (shopping orientation, degree of openess to competition and sociodemographics) and switching barrier recognition. Accordingly, switch control strategy of the monopolistic local department store facing competitors' entry into market, must be made, specifically, in a way to understand customer characteristics and to make deliberate effort to reduce customer dissatisfaction.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.17-40
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• 2007

Most research on web site design has focused on technological factors, while visual aesthetic factors have been considered less important. In contrast, this study focuses on visual aesthetic factors in web site design. Findings of this study can be summarized as follows : (1) The result of SPSS-factor analysis shows that there are 3 distinct factors, 'classical aesthetics', 'expressive aesthetics', and 'usability' 'Classical aesthetics' and 'expressive aesthetics' can be described by visual aesthetic design, 'Visual aesthetic design' can be distinguished from 'usability'. This conceptual confusion relating to 'usability' and 'visual aesthetic design' can be clarified by these findings. (2) As a result of multiple regression analyses, 'classical aesthetics', 'expressive aesthetics', and 'usability' have a positive influence on 'interactivity' and 'web site evaluation'. This research clarifies the concepts of 'expectations' of Grier [18] and 'engagement' of Rosen and Purinton [33] as the 'interactivity' between users and web sites. Furthermore, this research suggests a valid model with high $R^2$(interactivity, 48% : web site evaluation, 68%). (3) Empirical tests show that the differences among users in 'entry point' are related to the characteristics of web sites and the personal characteristics of users. The differences among users in terms of 'scanning time' are closely related to the attitudes and evaluation tendencies of users with respect to web sites. These findings could contribute to the 'search phase' of the Faraday model [16], enabling it to be more precise and extensible. The managerial implication of this study is that customers' preferences regarding web site designs are differences, as their preferences are based on their individual characteristics. Therefore, marketing managers should consider promotional tools on web sites that are relevant to the target market. An optimal strategy for web design could be a carefully-selected combination of factors that are relevant to the 'interactivity' and 'evaluation' of web sites. Additionally, if marketing managers want to attract more favorable attitudes and more affirmative evaluations from users, web sites should be designed so that they are understood more quickly by users. finally, this study suggests that 'good design' for web sites depends on understanding how to attain the appropriate balance between 'classical aesthetics' and 'expressive aesthetics', based on the target customer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.168-175
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• 2020

Recently, there has been an increasing need to expand the supply of renewable energy as a solution to greenhouse gas emissions. Therefore, as a measure to promote domestic renewable energy investment and gradual expansion, this study analyzed the investment value of renewable energy projects utilizing the unoccupied spaces of public enterprise's facilities and presented a strategic decision-making framework to support efficient national land development and government measures. The NPV was estimated to be 286 million won if the expansion of the facility was not considered, but it is reasonable to postpone the expansion decision because the value of -130 million won was calculated if the expansion was considered. On the other hand, the real-option value was estimated to be 444 million won, taking SMP uncertainty, expansion, and abandonment options into account, and an additional value of 288 million won was calculated from an analysis of the expansion project using the existing NPV analysis.