• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.153-173
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• 2007

The purpose of this study is to investigate the middle school students' allowance managing behaviors and consumer education by the educational subject in order to explore a desirable direction of consumer education for allowance management. Questionnaire survey was conducted with 468 middle school students in Gyeongnam. The major findings are as follows: First, as for recognition of consumer education, the consumer education from home was the highest, and then the from school and mass media followed in that order. Second, the average score of the students' allowance managing behavior was low. The fulfillment ability was relatively high compared to planning and evaluative ability. Third, as for overall allowance managing behaviors, the more promoted a students' level of consumer education from school and mass media, the more cultivated his/her allowance managing behaviors. As for allowance managing behaviors in accordance with sub-factors, students' planning and fulfillment abilities were more cultivated, the more promoted his/her level of consumer education from school and mass media. Students' evaluative ability was more cultivated, the more promoted his/her level of consumer education from school and mass media. Fourth, there were differences in educational contents the students wanted in accordance with the educational subjects of consumer education. The consumer education can be more practical when it is connected with home, school, and mass media, development of an educational program with such connection is necessary.

• The Korean Journal of Financial Management
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• v.21 no.2
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• pp.27-63
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• 2004

Since the 1980s, many multinational corporations have been issuing stocks on foreign stock exchanges, not only to enhance their investor base and liquidity, but also to diversify risks. The phenomenon has also been intensified by the rapid financial globalization and securitization trends. The main purpose of this study is to look into the long-run performance of MNCs' cross-listings of stocks on foreign stock exchanges. We use the event study and cross-sectional regression methods. We obtained some interesting empirical results about the long-run effect of cross-listings. First before the listing data the effect of cross-listing is to increase the underlying stock Vice in the local market. It may be caused by expectation of lower risk and cost of capital. However, after the listing data the stock price has been declining, even if it is not significant. Second, we examine the difference in the long-run cross-listing effect, which may be caused by the listing direction. When listing is made from a less developed market to a more developed market, the effect is better than that in the reverse direction. Furthermore, the effect is worse, when the listing company's home country is the U.S. Third, there is a negative relation between CARs and underlying stock liquidity in the local market, So it implies that a firm, whose underlying stocks are very liquid in the local market should carefully value cross-listing based upon the cost and benefit analysis. Last, but not the least we find that the long-un cross-listing effect is better, when a listing firm's ROE is higher.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.191-211
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• 2022

As the value of highly sustainable companies increases, ESG(Environmental, Social, and Governance) has emerged as the biggest topic of discussion for companies around the world. In addition, as domestically, more research is being done on ESG in line with global trends, it is necessary to examine ESG research trends. Accordingly, ESG academic papers that have been published for the past 10 years were collected for each year, and frequency analysis was conducted using text mining techniques regarding key themes and thesis titles. This paper analyzed the number of selected publications by year and the cumulated number of studies through bibliometric analysis. The findings suggested that the number of ESG papers is increasing each year and that academic interest in ESG-related issues continues to abound. Next, according to the results of frequency analysis of the keywords and titles of the research papers, the words- "ESG", "company", "society", "responsibility", "management", "investment", and "sustainability"- were extracted. This analysis identified the research fields and keywords that have been relevant to ESG in the past 10 years. As a result of comparing the major ESG issues presented in recent overseas studies and the common factors of the ESG key keywords presented in this study, it was confirmed that the environment is the focus of recent studies compared to previous studies. Third, it was found that the data used by domestic ESG studies mainly include the KEJI index, the KRX index, and the KCGS ESG evaluation index. After identifying the main research subjects of ESG papers, research found that 8 out of 152 domestic ESG studies were focused on SMEs. Through this study, it was possible to confirm the ESG research trend and increase in research, and future researchers divided the research topics and research keywords and presented basic data for selecting more diverse research topics. Based on both, the arguments of previous ESG studies conducted on SMEs and the results of this study, there is a lack of studies on guidelines for ESG practice and their application to SMEs, and more ESG research regarding SMEs will need to be conducted in the future.