• Journal of Gifted/Talented Education
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• v.21 no.1
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• pp.57-81
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• 2011

The purpose of this study was to explore the quality of life of musically talented students as measured by their external experiences (e.g., activities, companions) and internal experiences (e.g., flow, emotion). The participants in this study were 33 musically talented students (10 males, 23 females) aged 13 to 19. Study data were collected for 7 consecutive days using the Experience Sampling Method (ESM), which employs a cellular-phone as a signaling device. The results were as follows: First, in response to the 1625 random signals, musically talented students reported that 40.9% of their time was spent on productive activities. An additional 33.4% of time was used for maintenance activities and the rest of their time was spent on leisure/social activities. Also, musically talented students reported that 48.5% of their time was spent alone. When they were alone, they spent a lot of time engaging in productive activities (44.3%). Second, in order to measure the flow of their life, two methods were used. One used a 4-channel flow model (i.e. apathy, boredom, flow, anxiety) and the other used 8 dimensions and conditions of the flow experience (i.e. concentration, self-consciousness disappears, action and awareness merge, distorted sense of time, freedom from worry about failure, clear goals, immediate feedback, balance between challenges and skills). According to the former, when engaged in music-related activities, musically talented students usually reported flow (54.0%), while they felt apathy (41.3%) for daily routines activities. According to the latter method, musically talented students experienced flow for most productive activities, while they experienced flow least for maintenance activities. Emotional variables of ESF are comprised of 10 semantic scales (i.e. happy-sad, strong-weak, active-passive, sociablelonely, proud-ashamed, involved-detached, excited-bored, clear-confused, relaxed-worried, cooperative-competitive). Musically talented students reported experiencing the most positive emotion for social activities and experiencing the most negative emotion for maintenance activities. Results of this study assert that musically talented students had to trade off immediate enjoyment for developing their special gifts. They could not afford as much time for socializing with friends, and they had to spend more time alone compared to their peers without such gifts. Consequently, they were found to deprive themselves of the spontaneous good times that teenagers usually thrive on. They were helped in this respect by their autotelic personality traits, especially their strong need for achievement and endurance. The downside, however, is that the moment-to-moment quality of their moods suffered. The argument concerning musically talented students applies for all adolescents. The choices that talented students must make between immediate gratification and long-term development, and between solitude and companionship, are the same choices every young person must make, regardless of her or his level of talent. All of us have gifts that are potentially useful and worthy of being appreciated. But to develop these latent talents we must cultivate them, and this takes time and the investment of mental energy. The lifestyle that musically talented students develop can show us some of the choices all of us must make in order to cultivate our gifts.

• Journal of Distribution Science
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• v.12 no.6
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• pp.15-20
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• 2014

Purpose - In general, researchers try to abide by the code of research ethics, but many of them are not fully aware of plagiarism, unintentionally committing the research misconduct when they write a research paper. This research aims to introduce researchers a clear and easy guideline at a conference, which helps researchers avoid accidental plagiarism by addressing the issue. This research is expected to contribute building a climate and encouraging creative research among scholars. Research design, data, methodology & Results - Plagiarism is considered a sort of research misconduct along with fabrication and falsification. It is defined as an improper usage of another author's ideas, language, process, or results without giving appropriate credit. Plagiarism has nothing to do with examining the truth or accessing value of research data, process, or results. Plagiarism is determined based on whether a research corresponds to widely-used research ethics, containing proper citations. Within academia, plagiarism goes beyond the legal boundary, encompassing any kind of intentional wrongful appropriation of a research, which was created by another researchers. In summary, the definition of plagiarism is to steal other people's creative idea, research model, hypotheses, methods, definition, variables, images, tables and graphs, and use them without reasonable attribution to their true sources. There are various types of plagiarism. Some people assort plagiarism into idea plagiarism, text plagiarism, mosaic plagiarism, and idea distortion. Others view that plagiarism includes uncredited usage of another person's work without appropriate citations, self-plagiarism (using a part of a researcher's own previous research without proper citations), duplicate publication (publishing a researcher's own previous work with a different title), unethical citation (using quoted parts of another person's research without proper citations as if the parts are being cited by the current author). When an author wants to cite a part that was previously drawn from another source the author is supposed to reveal that the part is re-cited. If it is hard to state all the sources the author is allowed to mention the original source only. Today, various disciplines are developing their own measures to address these plagiarism issues, especially duplicate publications, by requiring researchers to clearly reveal true sources when they refer to any other research. Conclusions - Research misconducts including plagiarism have broad and unclear boundaries which allow ambiguous definitions and diverse interpretations. It seems difficult for researchers to have clear understandings of ways to avoid plagiarism and how to cite other's works properly. However, if guidelines are developed to detect and avoid plagiarism considering characteristics of each discipline (For example, social science and natural sciences might be able to have different standards on plagiarism.) and shared among researchers they will likely have a consensus and understanding regarding the issue. Particularly, since duplicate publications has frequently appeared more than plagiarism, academic institutions will need to provide pre-warning and screening in evaluation processes in order to reduce mistakes of researchers and to prevent duplicate publications. What is critical for researchers is to clearly reveal the true sources based on the common citation rules and to only borrow necessary amounts of others' research.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.231-249
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• 2014

We define $21^{st}$ century as an amalgamation of globalization and localization, or Glocalization. Additionally, due to the increasing supply of smart phones and wide usage of social networking services, the ability to utilize such global and regional information has increased a coperation's competitiveness in its market, and even the business models have evolved from the conventional "production and distribution" to E-commerce, through which either a direct or a non-direct transaction is possible. My hypothesis is that the ability to adapt to this trend is possible through transfer of learning, and consequently, this will have an impact on company's performance. Thus, this thesis analyzes the mid- to the long-term impact of such ability and environmental factors on the performance and technology innovation of Korean companies in China. Ultimately, this study intends to engender a basic foundation for a corporation's management strategy in China. Finally this research focuses on those Korean companies in China only and on the proof of influential factors' impact on technological innovation and technological innovation's impact on those corporations' future performances. Section I is an abstract and section II, the case examines the uniqueness and current status of Korean companies in China identifies the concept and the definition of influential factors such as education-orientation, technological innovation, and performance, and then scrutinizes each factors through a closer look at their past researches. Section III explains the thesis model, the survey's method and target, the thesis, variable factors, the content, and the method of analysis. In section IV, the thesis is proved based on the outcome of the survey. The result in Section V highlights the high comprehension of technological innovation: both education-orientation and technological innovation prove to have a positive (+) correlation with the performance. The vision on education orientation proves to have a positive (+) influence on technological innovation. The vision on education-orientation and technological innovation prove to have a positive (+) influence individually on company's performance.

• KDI Journal of Economic Policy
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• v.12 no.2
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• pp.51-79
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• 1990

Research on technical efficiency, an important dimension of market performance, had received little attention until recently by most industrial organization empiricists, the reason being that traditional microeconomic theory simply assumed away any form of inefficiency in production. Recently, however, an increasing number of research efforts have been conducted to answer questions such as: To what extent do technical ineffciencies exist in the production activities of firms and plants? What are the factors accounting for the level of inefficiency found and those explaining the interindustry difference in technical inefficiency? Are there any significant international differences in the levels of technical efficiency and, if so, how can we reconcile these results with the observed pattern of international trade, etc? As the first in a series of studies on the technical efficiency of Korea's manufacturing industries, this paper attempts to answer some of these questions. Since the estimation of technical efficiency requires the use of plant-level data for each of the five-digit KSIC industries available from the Census of Manufactures, one may consture the findings of this paper as empirical evidence of technical efficiency in Korea's manufacturing industries at the most disaggregated level. We start by clarifying the relationship among the various concepts of efficiency-allocative effciency, factor-price efficiency, technical efficiency, Leibenstein's X-efficiency, and scale efficiency. It then becomes clear that unless certain ceteris paribus assumptions are satisfied, our estimates of technical inefficiency are in fact related to factor price inefficiency as well. The empirical model employed is, what is called, a stochastic frontier production function which divides the stochastic term into two different components-one with a symmetric distribution for pure white noise and the other for technical inefficiency with an asymmetric distribution. A translog production function is assumed for the functional relationship between inputs and output, and was estimated by the corrected ordinary least squares method. The second and third sample moments of the regression residuals are then used to yield estimates of four different types of measures for technical (in) efficiency. The entire range of manufacturing industries can be divided into two groups, depending on whether or not the distribution of estimated regression residuals allows a successful estimation of technical efficiency. The regression equation employing value added as the dependent variable gives a greater number of "successful" industries than the one using gross output. The correlation among estimates of the different measures of efficiency appears to be high, while the estimates of efficiency based on different regression equations seem almost uncorrelated. Thus, in the subsequent analysis of the determinants of interindustry variations in technical efficiency, the choice of the regression equation in the previous stage will affect the outcome significantly.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.439-450
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• 2015

This study objects to find characteristics in chemical tanker markets and to determine optimal chemical tanker size using a total shipping cost in main trading route of asia chemical tankers .Precedent studies of determination of the optimal ship size and case studies about chemical tankers was carried out and tried to introduce a cost model which is applicable to chemical tanker. This study is dependant on numerical analysis and involves scenario analysis to minimize sensitivity of results. This analysis shows as follows. First, 12,000DWT tanker is an optimal size on the 'Far East-Middle East' services, 9,000DWT tanker is a most competitive on the 'Far East-South East Asia' services and 3,000DWT tanker is a most economic size on the 'Inner Far East' services at average market situation. Second, the bigger size of chemical tanker, the more competitive advantage the tanker will obtain when bunker fuel prices rise. Small size ship gets more competitive during bunker prices down. Third, market fluctuation of time charter rate for chemical tanker is less than 20% against its average time charter hire which means less volatile. And tanker's competitiveness per each size is remained mostly same when time charterer rates rise at same proportion. Fourth, bigger size chemical tankers have cost advantages when tanker's quantity of each part cargo increase. And small-sized tanks are more competitive when part cargo scales decrease. For the last, ship's port stay strongly influences on the determination of the optical tanker size. When vessel has shorter port stay, bigger-sized tanker will be more competitive and even can be competitive if applies in short voyage as well.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.1-14
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• 2023

The objective of the study was to examine the associations of dietary carbohydrate and fat intake with the prevalence of metabolic syndrome in Korean women. A cross-sectional study was employed based on data from the Korea National Health and Nutrition Examination (2007-2016). A total of 22,850 women aged 19 to 69 years were studied after excluding responses from pregnant or lactating women and those with missing metabolic values. Dietary intake data were collected with a 24-hour recall method. Dietary carbohydrate and fat intakes were divided into quintiles. After controlling for confounding variables, a multivariable logistic regression and general linear model were used. The findings indicated that HDL cholesterol levels were lower (p for trend<0.01), while triglyceride levels (p for trend=0.04), waist circumference (p for trend<0.01), and systolic blood pressure (p for trend<0.01) were higher among participants in the highest quintile of carbohydrate intake compared to those in the lowest quintile. Participants in the highest quintile of fat intake had lower waist circumference (p for trend=0.02), triglyceride level (p for trend<0.01), and systolic blood pressure (p for trend<0.01), while higher HDL cholesterol level (p for trend<0.01) compared to those in the lowest fat intake quintile. Metabolic syndrome was more likely to be present in the highest quintile of carbohydrates intake than in the lowest quintile (5^th quintile vs. 1^st quintile, OR: 1.32; 95% CI: 1.11 to 1.57). However, metabolic syndrome was less likely to be present in the highest quintile of fat intake than in the lowest quintile (5^th quintile vs. 1^st quintile, OR: 0.73; 95% CI: 0.61 to 0.86). This study revealed that high dietary carbohydrate intake and low dietary fat intake were associated with metabolic syndrome in Korean women.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.57-75
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• 2021

KHNP's shared growth activities are based on such public good. Reflecting the characteristics of a comprehensive energy company, a high-tech plant company, and a leading company for shared growth, it presents strategies to link performance indicators with its partners and implements various measures. Key tasks include maintaining the nuclear power plant ecosystem, improving management conditions for partner companies, strengthening future capabilities of the nuclear power plant industry, and supporting a virtuous cycle of regional development. This is made by reflecting the specificity of nuclear power generation as much as possible, and is designed to reflect the spirit of shared growth through win-win and cooperation in order to solve the challenges of the times while considering the characteristics as much as possible as possible. KHNP's shared growth activities can be said to be the practice of the spirit of the times(Zeitgeist). The spirit of the times given to us now is that companies should strive for sustainable growth as social air. KHNP has been striving to establish a creative and leading shared growth ecosystem. In particular, considering the positions of partners, it has been promoting continuous system improvement to establish a fair trade culture and deregulation. In addition, it has continuously discovered and implemented new customized support projects that are effective for partner companies and local communities. To this end, efforts have been made for shared growth through organic collaboration with partners and stakeholders. As detailed tasks, it also presents fostering new markets and new industries, maintaining supply chains, and emergency support for COVID-19 to maintain the nuclear power plant ecosystem. This reflects the social public good after the recent COVID-19 incident. In order to improve the management conditions of partner companies, productivity improvement, human resources enhancement, and customized funding are being implemented as detailed tasks. This is a plan to practice win-win growth with partner companies emphasized by corporate social responsibility (CSR) and ISO 26000 while being faithful to the main job. Until now, ESG management has focused on the environmental field to cope with the catastrophe of climate change. According to KHNP is presenting a public enterprise-type model in the environmental field. In order to strengthen the future capabilities of the nuclear power plant industry as a state-of-the-art energy company, it has set tasks to attract investment from partner companies, localization and new technologies R&D, and commercialization of innovative technologies. This is an effort to develop advanced nuclear power plant technology as a concrete practical measure of eco-friendly development. Meanwhile, the EU is preparing a social taxonomy to focus on the social sector, another important axis in ESG management, following the Green Taxonomy, a classification system in the environmental sector. KHNP includes enhancing local vitality, increasing income for the underprivileged, and overcoming the COVID-19 crisis as part of its shared growth activities, which is a representative social taxonomy field. The draft social taxonomy being promoted by the EU was announced in July, and the contents promoted by KHNP are consistent with this, leading the practice of social taxonomy

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.89-97
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• 2010

This study researches the effects of common features on a no-choice option with respect to regulatory focus theory. The primary interest is in three factors and their interrelationship: common features, no-choice option, and regulatory focus. Prior studies have compiled vast body of research in these areas. First, the "common features effect" has been observed bymany noted marketing researchers. Tversky (1972) proposed the seminal theory, the EBA model: elimination by aspect. According to this theory, consumers are prone to focus only on unique features during comparison processing, thereby dismissing any common features as redundant information. Recently, however, more provocative ideas have attacked the EBA model by asserting that common features really do affect consumer judgment. Chernev (1997) first reported that adding common features mitigates the choice gap because of the increasing perception of similarity among alternatives. Later, however, Chernev (2001) published a critically developed study against his prior perspective with the proposition that common features may be a cognitive load to consumers, and thus consumers are possible that they are prone to prefer the heuristic processing to the systematic processing. This tends to bring one question to the forefront: Do "common features" affect consumer choice? If so, what are the concrete effects? This study tries to answer the question with respect to the "no-choice" option and regulatory focus. Second, some researchers hold that the no-choice option is another best alternative of consumers, who are likely to avoid having to choose in the context of knotty trade-off settings or mental conflicts. Hope for the future also may increase the no-choice option in the context of optimism or the expectancy of a more satisfactory alternative appearing later. Other issues reported in this domain are time pressure, consumer confidence, and alternative numbers (Dhar and Nowlis 1999; Lin and Wu 2005; Zakay and Tsal 1993). This study casts the no-choice option in yet another perspective: the interactive effects between common features and regulatory focus. Third, "regulatory focus theory" is a very popular theme in recent marketing research. It suggests that consumers have two focal goals facing each other: promotion vs. prevention. A promotion focus deals with the concepts of hope, inspiration, achievement, or gain, whereas prevention focus involves duty, responsibility, safety, or loss-aversion. Thus, while consumers with a promotion focus tend to take risks for gain, the same does not hold true for a prevention focus. Regulatory focus theory predicts consumers' emotions, creativity, attitudes, memory, performance, and judgment, as documented in a vast field of marketing and psychology articles. The perspective of the current study in exploring consumer choice and common features is a somewhat creative viewpoint in the area of regulatory focus. These reviews inspire this study of the interaction possibility between regulatory focus and common features with a no-choice option. Specifically, adding common features rather than omitting them may increase the no-choice option ratio in the choice setting only to prevention-focused consumers, but vice versa to promotion-focused consumers. The reasoning is that when prevention-focused consumers come in contact with common features, they may perceive higher similarity among the alternatives. This conflict among similar options would increase the no-choice ratio. Promotion-focused consumers, however, are possible that they perceive common features as a cue of confirmation bias. And thus their confirmation processing would make their prior preference more robust, then the no-choice ratio may shrink. This logic is verified in two experiments. The first is a $2{\times}2$ between-subject design (whether common features or not X regulatory focus) using a digital cameras as the relevant stimulus-a product very familiar to young subjects. Specifically, the regulatory focus variable is median split through a measure of eleven items. Common features included zoom, weight, memory, and battery, whereas the other two attributes (pixel and price) were unique features. Results supported our hypothesis that adding common features enhanced the no-choice ratio only to prevention-focus consumers, not to those with a promotion focus. These results confirm our hypothesis - the interactive effects between a regulatory focus and the common features. Prior research had suggested that including common features had a effect on consumer choice, but this study shows that common features affect choice by consumer segmentation. The second experiment was used to replicate the results of the first experiment. This experimental study is equal to the prior except only two - priming manipulation and another stimulus. For the promotion focus condition, subjects had to write an essay using words such as profit, inspiration, pleasure, achievement, development, hedonic, change, pursuit, etc. For prevention, however, they had to use the words persistence, safety, protection, aversion, loss, responsibility, stability etc. The room for rent had common features (sunshine, facility, ventilation) and unique features (distance time and building state). These attributes implied various levels and valence for replication of the prior experiment. Our hypothesis was supported repeatedly in the results, and the interaction effects were significant between regulatory focus and common features. Thus, these studies showed the dual effects of common features on consumer choice for a no-choice option. Adding common features may enhance or mitigate no-choice, contradictory as it may sound. Under a prevention focus, adding common features is likely to enhance the no-choice ratio because of increasing mental conflict; under the promotion focus, it is prone to shrink the ratio perhaps because of a "confirmation bias." The research has practical and theoretical implications for marketers, who may need to consider common features carefully in a practical display context according to consumer segmentation (i.e., promotion vs. prevention focus.) Theoretically, the results suggest some meaningful moderator variable between common features and no-choice in that the effect on no-choice option is partly dependent on a regulatory focus. This variable corresponds not only to a chronic perspective but also a situational perspective in our hypothesis domain. Finally, in light of some shortcomings in the research, such as overlooked attribute importance, low ratio of no-choice, or the external validity issue, we hope it influences future studies to explore the little-known world of the "no-choice option."

• 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.