• Review of Culture and Economy
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• v.21 no.2
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• pp.141-173
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• 2018

In this article, we explore how artistic fame is formed by analyzing antecedents of fame the extent to which the name of an actor or his/her work is positively known by his/her audiences among Korean handicraft artists. Drawing on prior literature on reputation and fame, we clarify the differences between the concept of reputation and the concept of fame and further distinguish three types of reputation among individual artists, depending on its sources expert reputation, market reputation, and peer reputation. We employ the mixed method in this study, in which we first conducted open-end interviews with three kinds of constituents (i.e., critics, market intermediaries, and artists) and then developed and tested the hypotheses derived from the insights we had obtained from the interviews. We further considered the impact of reputational work, defined as the level of effort devoted and activities performed by an artist him(her)self geared toward promoting his(her) work, on artistic fame. We find that there are large differences in factors associated with artistic fame between non elite and elite Korean handicraft artist groups, where elite status is captured by artists' educational background (i.e., Seoul National University and Hongik University, which are considered elite schools in accordance with prior research). Specifically, findings suggest that among non elite status artists, recognition by experts, or what we call expert reputation, acquired through national awards and invitations from prominent exhibitions as well as artists' own reputational work that incurs high cost, such as self-financed exhibition openings, were shown to be highly significant factors associated with artistic fame, which was measured as the number of media exposures related to her/his art work. By contrast, among elite status artists, peer reputation acquired through an artist's institutional affiliations and relatively low cost artists' own reputational work, such as self listing on a highly publicized magazine, were shown to be significant factors associated with fame. Taken together, this paper contributes to research on cultural industries and markets by highlighting the importance of understanding artistic fame not just as the outcome of her/his talent but as the social product that arises at the intersection of actors (artists) and her/his audiences in the social evaluation process.

• Journal of Nutrition and Health
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• v.52 no.4
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• pp.342-353
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• 2019

Purpose: The Dietary Reference Intakes for Koreans (KDRIs) suggest that the goal for the intake of sodium should be less than 2,000 mg, which is thought to be infeasible to achieve when eating the typical Korean diet. This study aimed to obtain the new intake goals for sodium with improved feasibility to achieve, and also to design optimized food intake patterns for Korean adults by performing linear programming. Methods: The data from a one day 24-hour dietary recall of the 2010 ~ 2014 Korea National Health and Nutrition Survey were used to quantify food items that Korean adults usually consumed. These food items were categorized into seven groups and 24 subgroups. The mean intakes and intake distributions of the food groups and the food subgroups were calculated for eight age (19 ~ 29, 30 ~ 49, 50 ~ 64, and over 65 years old) and gender (male and female) groups. A linear programming model was constructed to minimize the difference between the optimized intakes and the mean intakes of the food subgroups while meeting KDRIs for energy and 13 nutrients, and not exceeding the typical quantities of each of the food subgroups consumed by the respective age and gender groups. As an initial solution of the linear programming, the optimized intake of seasonings, including salt, was calculated as 0 g for all the age and gender groups when the sodium constraint was inserted not to exceed 2,000 mg. Therefore, the sodium constraint was progressively increased by 100 mg until the optimized intake of seasoning was obtained as the values closest to the $25^{th}$ percentile of the intake distribution of seasonings for the respective age and gender groups. Results: The optimized food intake patterns were mathematically obtained by performing linear programming when the sodium constraint values were 3,600 mg, 4,500 mg, 4,200 mg, 3,400 mg, 2,800 mg, 3,100 mg, 3,100 mg, and 2,500 mg for the eight age and gender groups. Conclusion: The optimized food intake patterns for Korean adults were designed by performing linear programming after increasing the sodium constraint values from 2,000 mg to 2500 ~ 4,500 mg according to the age and gender groups. The resulting patterns suggest that current diets should be modified to increase the intake of vegetables for all the groups, milk/dairy products for the female groups, and fruits for the female groups except for the females aged 50 ~ 64 years.

• International Area Studies Review
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• v.22 no.3
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• pp.221-251
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• 2018

Two-tier wage systems mean the dual wage systems that the new wage system require the new future employees to get much lower wage level, compared to the level of wages for existing employees under the existing wage system. While it allows employers to benefit from low-cost advantages, the two-tier wage systems is definitely a type of wage discrimination by the collusion between management and trade unions in that it forces the new future employee to accept the low wages. Also it reflects extreme collectivism which old union members try to keep having their jobs and wages at the sacrifice of future members' wages. The two-tier wage systems had been introduced by airplane industry in 1980s and introduced again in Big Three auto companies in 2007. The purpose of this paper is to examine the history, contents, and details of two-tier wage system in the United States and to think of the possibility of recurrence of the systems in the context of Korean auto industry in the near future. The tentative findings from this paper implies that the two-tier wage systems will likely happen in Korean auto industry because the collusion between trade unions and management are found easily and the degree of extreme collectivism favored by the old permanent union members is seriously high. It is time for trade unions to go back to their original ideals and purposes and to revitalize solidarity among workers.

• Journal of the Korean Applied Science and Technology
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• v.36 no.2
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• pp.498-506
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• 2019

This study is based on a coating method that provides utilization value as a micronised powder for cosmetic raw materials using natural minerals buried in Bonghwa, Gyeongsangbuk-do in Korea. The mineral powder name is called Buseok, and chemical name is pumice powder. The results of a study on the efficacy of cosmetics are reported by the development of particulate powder to assess the performance of this powder. First of all, in order to coat the surface of this powder with oil, aluminum hydroxide was coated on the particulate surface and then coated with alkylsilan. In addition, it was coated with vegetable oil to prevent condensation of the powder and increase the dispersion in the oil phase. First; the particle size of pumice powder was from 10 to 50mm having porous holes on the surface of the particles. Second; The components of this powder contained $SiO_2$, $Al_2O_3$, $Fe_2O_3$, MgO, CaO, $K_2O_2$, $Na_2O$, $TiO_2$, $TiO_2$, MnO, $Cr_2O_3$, $V_2O_5$. Third: The particles of this powder have a planetary structure and are reddish-brown with porosity through SEM and TEM analysis. Fourth; the far-infrared radiation rate of this parabolic powder was $0.924{\mu}m$, and the radiative energy was $3.72{\times}102W/m^2$ and ${\mu}m$. In addition, the anion emission is 128 ION/cc, which shows that the coating remains unchanged. Based on these results, it is expected to be widely applied to basic cosmetics such as BB cream, cushion foundation, powderfect, and other color-coordinated cosmetics, sunblock cream, wash-off massage pack as an application of cosmetics. (Small and Medium Business Administration: S2601385)

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Management & Information Systems Review
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• v.38 no.2
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• pp.139-163
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• 2019

The purpose of this study is to identify the influence of the high performance and the work system recognized by the organizational members participating in the NCS enterprise utilization consulting on the organizational effectiveness and the influence of the organizational performance. In order to achieve the purpose of this study, the research hypotheses were verified by applying multiple regression analysis and co-integration regression analysis on the 145 usable results from using the statistical program of SPSS 24.0. The results of this study are as follows. First, hypothesis 1, the analysis of positive(+) influence on organizational effectiveness on the characteristics of the system (selection system, evaluation and compensation, education and training opportunity, member participation system, job stability) was adopted due to its' positive(+) and significant relationship. Second, hypothesis 2, an analysis that the organizational effectiveness would have a positive impact on organizational performance was adopted due to its' proven work. However, its' effectiveness will need verification. Third, regression analysis was conducted to confirm the role of the hypothesis 3, personnel management effectiveness, between the high performance and the work system (selection system, evaluation/compensation, education/training opportunity, member participation system, job stability). As a result, Hypothesis 3 showed that the selection system (H3-1), evaluation and compensation(H3-2), education and career opportunities(H3-3), member participation system(H3-4), job stability(H3-4) showed that organizational effectiveness has a moderating role in HR effectiveness. The main implication of this study is that the positive and working system recognized by the organizational members has positive affects on organizational effectiveness and organizational performance. In order to enhance the substantiality management system through improvement of organizational performance, a regular implementation plan on a high-performance working system along with education & training system to improve organizational effectiveness is required so that the members of the organization could form a consensus. Second, as a result of confirming the moderating effects of HR management effectiveness, the moderating role of HR management system and organization effectiveness was verified positive. Therefore, this study shows that the part that verifies both organizational effectiveness and organizational performance through high-performance working system and the part that confirmed the role of control between high-performance work system and organizational effectiveness are the biggest difference from the previous research.

• Management & Information Systems Review
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• v.38 no.1
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• pp.201-223
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• 2019

The purpose of this study is to verify empirically the causal relationship between service quality, ease of use, customer satisfaction, and repurchase intention of mobile shopping mall. And this study is to investigate the ease of use and customer satisfaction mediating effect of between service quality and repurchase intention. Therefore, 323 university students in Jeonnam area were surveyed and the structural equation model was derived based on previous research. Service quality of mobile shopping mall make a significant effect on using easiness, purchasing satisfaction and repurchase intention. However, among service quality of mobile shopping mall, service scape like mobile interface and site design made a positive effect on purchasing satisfaction, but did not any effect on repurchase intention. In other words, service quality factors that make positive effects on customer's pleasant using and repurchase intention make a positive effect on repurchase intention when providing and using the service customer wants faithfully rather than external part of the site and mutually influencing attitude or behavior well. The implications suggested by this study are as follows. First, service quality of mobile shopping mall makes a significant effect on repurchase intention, so it's necessary to improve CS service system so as to treat customers' inquiries or inconveniences actively during mobile shopping and return and refund of defective products quickly and conveniently. And, in addition to the finally used factors in analysis process, benefits using customers' grade by number of purchases, such as various events, coupons, reserve, etc. and active contents marketing strategies providing more various pleasures and values of shopping are necessary. Second, satisfaction of mobile shopping mall makes a positive effect on repurchase intention, so visiting of site and repurchasing of product are continuously done as customers' satisfaction on shopping mall is increasing. Therefore, shopping mall site requires differentiation of contents, exact plan and practice of service, marketing, etc. so that customers can feel more satisfaction. This study is significant as it systematically analyzed concepts of components that service quality of mobile shopping mall makes an effect on using easiness, purchasing satisfaction, and repurchase intention, verified the relations, systematized it by theoretical structure, and widened the understanding of effects making an effect on repurchase intention.

• Korean Journal of Heritage: History & Science
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• v.53 no.4
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• pp.136-149
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• 2020

It is generally believed that Douglas Fir timber imported from North America is used in repair work for Korean wooden heritage sites due to an insufficient supply of extra-large sized Korean pine timber. Based on this understanding in the cultural heritage repair field, Cultural Heritage Repair Business Entities ("CHRBE") prefer North American Douglas Fir timber which is more easily acquired on the market than large Korean pine timber. However, if CHRBE use large quantities of foreign-origin wood in the heritage repair field, this presents the threat of negative domestic impacts on cultural heritage such as breaching the preservation principal and ultimately weakening material authenticity. Therefore, this study aims to investigate the current supply status of large Korean pine timber through examination of existing research, interviews with experts engaged in CHRBE, and timber mills. With this information, the authors seek to identify whether the market supply of large Korean pine timber is indeed insufficient or not. In addition to this, this paper identifies the reasons why large Korean pine timber is not widely used if such timber supply is actually sufficient. In order to propose suggestions regarding the issues above, the authors study the distribution channel for large Korean pine timber and the price spectrum of this timber through examination of price information from the public agencies under the Korea Forest Service, research papers from the Cultural Heritage Administration, and estimation documents from timber mills. This paper also identifies two main opinions about why Korean timber has not been commonly used in the Korean heritage repair field. The first opinion is that the supply of large Korean pine timber really is insufficient in Korea. However, the second opinion is that it is hardly used due to inappropriateness of the government's procurement and estimation system, despite the fact that the supply of the timbers on the market is actually sufficient. Through the aforementioned research, this paper comes to the conclusion that the second opinion has strong grounds in many aspects. In terms of suggestions, alternative routes are proposed to stimulate the use of large Korean pine timber via supply by the 'Korea Foundation for Traditional Architecture and Technology' and surveys of the price spectrum of the timber, etc.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.