• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.53-64
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• 2021

As the 5G service market is expected to grow rapidly, the development of high-power, high-efficiency power amplifiers for the 5G communication infrastructure is indispensable. Gallium nitride (GaN) is attracting great interest as a key device in power devices and integrated circuits due to its wide bandgap, high carrier concentration, high electron mobility, and high-power saturation characteristics. In this study, we investigate the technology trends of Ka-band GaN radio frequency (RF) power devices and integrated circuits for operation in the millimeter-wave band of recent 5G mobile communication services. We review the characteristics of GaN RF high electron mobility transistor (HEMT) devices to implement power amplifiers operating at frequencies around 28 GHz and compare the technology of foreign companies with the device characteristics currently developed by the Electronics and Telecommunication Research Institute (ETRI). In addition, the characteristics of Ka-band GaN monolithic microwave integrated circuit (MMIC) power amplifiers manufactured using various GaN HEMT device technologies are reviewed by comparing characteristics such as frequency band, output power, and output power density of integrated circuits. In addition, by comparing the performance of the power amplifier developed by ETRI, the current status and future direction of domestic GaN power devices and integrated circuit technology will be discussed.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.87-93
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• 2023

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.529-531
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• 2022

The 5th generation mobile communication (5G) is being commercialized by major domestic and foreign mobile telecommunication businesses and is spreading to general customers mainly on smart devices such as smartphones, wearables, and IoT. If 4G networks and 5G access equipment were utilized by introducing NSA(None-Stand Alone) technology when 5G was first introduced, recently, 5G convergence services are being realized by gradually expanding evolution to 5G standalone networks through SA (Stand Alone) technology. The purpose of this study is to study a design plan for implementing necessary service-oriented functions from the perspective of communication network users on the configuration of 5G SA equipment based on SBA(Service-based Architecture) mentioned in the 3GPP technical specification document. Through this research, it is expected that companies that need to enter the 5G market can easily access the 5G SA network to develop and supplement specialized 5G convergence services to improve product performance and quality.

• Korea Trade Review
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• v.41 no.5
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• pp.1-14
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• 2016

Consumers have been increasing their interests in firms' ethicality as well as in the features of the firms' products when they decide to purchase a certain product. Recently, fair trade is considered to be a type of ethical marketing in the business-to-consumer market. In this regard, the effects of fair trade-based marketing on firm performance have become the center of academic and managerial concerns. Despite this importance, few studies have investigated whether fair-trade is a source of competitive advantage or just a cost of doing business. The present research attempts to provide evidence of how fair trade-based marketing influences competitive advantage. Two experimental studies were conducted to explore consumers' purchase intention, which can be a proxy of competitive advantage, in a foreign product-consumption context. Drawing on the stakeholder theory, the first study was performed to examine the effects of fair trade marketing on consumers' purchase intention through a within-subjects design. In addition, building on the signal theory, the second study was executed to test the effects of a fair trade mark on consumers' purchase intention. The findings of the current research reveal that consumers prefer fair trade-based products to others and that when it comes to fair trade-certified products, consumers are more likely to purchase products with that certification than otherwise, even when those products are sold at higher costs than rival products. Interestingly, the results of this research present that there is a significant difference of consumers' purchase intention of a fair trade-based product between two different marketers. This implies that fair trade-based products should be differentially distributed and targeted at a certain type of consumers.

• Journal of the Korean Society of International Agriculture
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• v.31 no.1
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• pp.8-16
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• 2019

Alternatives for increasing the competitiveness of locally manufactured agricultural machinery in domestic and foreign markets has been proposed. This was done by analyzing the major agricultural machinery's price and market share as well as their performance and quality. In the Korean domestic market, the market share of Japanese agricultural machinery has been identified to be 14.5% for tractors, 31.1% for combine harvesters, and 35.8% for rice transplanters, and on track for further increase. Japanese manufacturers' domestic patent shares are 58.5% for tractors, 79.9% for combine harvesters, and 69.8% for rice transplanters, showing the dire need for Korean domestic firms to expand their technological rights. To strengthen the industrial competitiveness of agricultural machinery, therefore, researches that develop the fundamental and elemental technology to reduce the frequency of breakdown should be needed in the short term. To achieve this, it is imperative to establish technology roadmap, promote greater cooperation between academia and industry, and systematically increase research funding. In addition, as a long-term solution for enhancing the competitiveness, an establishment of Agricultural Equipment Technology Institute is strongly recommended to systematically support R&D for developing core technologies, particularly high-quality components that guarantee durability and quality.

• Journal of Distribution Research
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• v.6 no.2
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• pp.1-17
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• 2002

The recent dot-com craze has been one of the main causes that accelerated the growth of internet-related companies in diversity as well as in size. Meanwhile, the domestic market of supplies and equipment for internet businesses has been dominated by major foreign companies. To regain their market positions, the domestic manufacturers had to find the way to build up their competitive advantages, such as meeting their customers needs and reducing overall costs. In this study, one domestic PC server manufacturer, which competes fiercely with foreign manufacturers for the top place, has been chosen as a model to evaluate its current supply chain and to find an area that can be improved for a better performance. System Dynamics is used throughout the study. The central concept to system dynamics is understanding how all the objects in a system interact with one another. It focuses on feedback and secondary effects to think through how a strategy might or might not work, depending on how organizational changes are received, and what kinds of consequences emerge. Then, computerized models were built for simulations, each with different conditions, and, finally, the results were evaluated based on some criteria which are considered to be important and meaningful. The inefficiency that exists in the supply chain was proved to be a thirty-day long purchasing order leadtime, and it was expected that more effective supply chain could be formed if the leadtme were reduced to 14 days or 7 days. The results of simulations showed that the overall expected costs in supply chain was the least with the purchasing leadtime being 7 days. The lower average number of parts held as inventory, along with the reduced lost sales, acted as the factor reducing the expected overall costs. Although there was a slight increase in the average number of final products held as inventory and the total ordering cost, the benefits from lower parts inventory and reduced lost sales were large enough to justify the overall cost reduction.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.19-34
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• 2021

The government budget for promoting startup have been skyrocketed as catching up with increasing demands for high-tech startup by disruptive innovation resulted from rapid technology change. However, major trend of startup have still fallen on self-employed type of startup due to the lack of expertise and fund in spite of desperate government policy efforts. In reality, the access to high-tech startup has been very limited and too high huddle to would-be entrepreneur. This paper implement empirical analysis on the effects of entrepreneur competency and satisfaction level to government support, considering these as the KSF for the growth and success of high-tech startup, to the performance of the company. In particular, it focus on defining unique characteristics of high-tech startup through differential proving by the backgrounds of entrepreneur such as major, R&D experience, patent possession, CTO possession. This research carry out survey to 217 entrepreneurs in high-tech company in Daejon and Daegue at R&D Special Innopolis Zone. Research results are as follow. First, entrepreneurial achievement competencies, conceptualization competencies, network competencies and market recognition competencies positively affect the financial and non-financial performance and organizational and technical competencies, while organizational and technological competencies only positively impact on non-financial performance. Second, the satisfaction level of government support showed a positive moderating effect on entrepreneurial achievement competencies and financial performance, while no significant effect in other competencies. Third, positive differential effect by the technological background of entrepreneur such as Major, R&D experience, patent possession, CTO possession) have been confirmed. This paper deliver several significant implications and contributions, First, it propose classified and systematized entrepreneur competency through the domestic and foreign literature reviews. Second, it proves the need for the wider spread of team based startup culture rather then sole startup. Third, it also proves the important role of technological background of entrepreneur among the characteristics of high-tech startup.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.463-474
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• 2016

As IT environment has changed, paths of information security in financial environment which is based on IT have become more diverse and damage caused by information leakage has been more serious. Among security incidents, personal information leakage incident is liable to give the greatest damage. Personal information leakage incident is more serious than any other types of information leakage incidents in that it may lead to secondary damage. The purpose of this study is to find how much personal information leakage incident influences corporate value by analyzing 21 cases of personal information leakage incident for the last 15 years 1,899 listing firm through case research method and inferring investors' response of to personal information leakage incident surveying a change in transaction before and after personal information leakage incident. This study made a quantitative analysis of what influence personal information leakage incident has on outcome of investment by types of investors by classifying types of investors into foreign investors, private investors and institutional investors. This study is significant in that it helps improve awareness of importance of personal information security by providing data that personal information leakage incident can have a significant influence on outcome of investment as well as corporate value in Korea stock market.