• The Southeast Asian review
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• v.27 no.1
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• pp.1-52
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• 2017

This study aims to compare the state building process focusing on the founding presidents of South Korea, which was a colony of the defeated state of World War II and the Philippines, the colony of the victorious state. To this end, it compares the lives of the presidents, mainly the founding president of Korea Syngman Rhee and Manuel Quezon who led the autonomy of the Philippines and established the Commonwealth government, in the contexts of the state building process of the two countries. In each country, the leaders had to address the core tasks for founding the states in common. Firstly, after the independence or the acquisition of state autonomy, both countries adopted a constitution based on the presidential system with the strong authority of the presidents influenced by the United States. Secondly, the two countries after the independence were operated on the basis of anti-communism at the forefront of the Cold War. In addition, they also carried out land reform to bring the peasants into the system for supporting anti-communism. Lastly, the two countries also faced the same issues of liquidating the Japanese colonial legacies. Therefore the study examines the establishment of the constitution, settlement of anti-communism line, the land reform issues, and liquidation of Japanese colonialism or occupation in each country. The Philippines attained 'constitutional independence' in 1935 and experienced political development faster than any other post-colonial country in Asia. However, except for the establishment of the constitution, the early leaders were not able to address the principal issues for state building. As land reform failed, landowners became economically and politically dominant. The Philippines, where the modern citizen class has not arisen suffered from the political and economic recession. In Korea, despite the Korean War and division of the country, the founding president Syngman Rhee attempted to solve the tasks. As a result, he was able to lay the track of liberal democracy against communism and also settled Japanese colonial legacy as much as it was allowed. In particular, through land reform, he has laid the basis for the nation-state and economic development and has set up the girders of Korean economy by adopting the market economy system. Although there are merits and demerits, compared with the leaders of other countries especially with the Philippines, it is no doubt that Syngman Rhee has played an essential role in establishing the state as a founding president.

• The Korean Journal of Franchise Management
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• v.2 no.2
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• pp.95-110
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• 2011

As global economic conditions are getting uneasy and polarization of our economy is intensified, the economic sentiment of small businesses is still low and unstable. The collapse of worldwide banking systems due to sub prime crisis in 2007 became the catalyst that shakes financial industries in each country in the world; the most sentiment people, small businesspersons, also have hard time facing survival way out, facing a great crisis. All organizing powers including manufactures, wholesales and retails are being gradually greater in mutual relations and dependence, and unstable factors about risks are also increasing. For exterior environmental and physical risk factors which cannot make small businesses survive themselves by developing ways out are eventually increasing, those who cannot cope with these factors face a great crisis. Although the government tries hard to overcome this situation conducting many ways, the effect does not continue. It is the real state that independent business markets including overall employment and establishing business have vicious cycle that they cannot be improved, due to increase of employment centered on short-term labors which lack durability in creation of employment and decline of household income. Recently, growth shows indication of slowdown because of multinational risk factors including financial crisis in each country in Europe, the death of Kim Jung-il, relationship with North Korea, and unstability of war situation in the Middle East Asia. Experts expect that growth rate will be about 4%, and independent business that ordinary people feel is still gloomy. It's reality that there is no adequate alternative for lack of jobs, unstable employment and a means of living after retirement. Also, the fact that large companies enter the market which is narrow and in the excessive competition should be an environmental factor that makes the situation worse. The business concept, a franchise, is the part we should think about whether it is the institutional solution that can guarantee independent businessmen stable life. Major companies are frightfully entering the market today, breaking the barrier to entry and shouting of a win-win with independent businesses. It's the small businesspersons who go through painful domestic recession, cannot predict the future and manage confusing and unstable independent business. It's very important to restore the domestic economy through wisely boosting consumption as soon as possible. It's also important to lead the situation by gathering powers of the government and related organizations, agonizing, suggesting solutions, and establishing accurate directions. The purpose of this study, therefore, is to suggest ways to strengthen competitiveness of small businesspersons by examining small business support policies which are currently implemented.

• Clinical and Experimental Pediatrics
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• v.51 no.7
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• pp.671-689
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• 2008

The economic recession of North Korea has been prolonged, the need for humanitarian assistance for the women and children of DPRK has been raised. In March 2006, South Korean government signed MOU with World Health Organization (WHO) to financially support "Improving Women's and Children's Health in DPRK (IWCH)" project. The assistance projects through UNICEF and the non-government organizations of South Korea were also followed. IWCH project consists of three parts; nutrition, disease management, children and maternity care. The first term (2006-2007) of the project leading by WHO was finished, and the second term (2008-2010) is just begun. The projects driven by NGOs have relatively been delayed due to difficulties in negotiating on project contents and places with North Korea. Recently, however, re-modeling processes of an obstetric/gynecology hospital and a children hospital in Nampo were started. Up to recently, South Korean government has played only a limited role in the humanitarian assistance for North Korea. IWCH project is, however, a full-scale initiative driven by government based on a systematic review of need and priorities. A significant amount of budget and relatively long term (five year) project compare to the previous short term and small size programs were expected to make more meaningful achievement. Despite these positive aspects, the project remains a list of unsolved problems a lack of mutual trust, a different decision making process between South and North Korea, a lack of conflict management process, and unpredictability and complexity of international politics. In spite of such kind of political uncertainty, the health care sector will be a leading area in the process of improving relationship between South and North Korea, particularly, humanitarian assistance for women and children will play a crucial role in the process. The successful implementation of IWCH project, therefore, will contribute to provide the reference model in developing the mutually constructive relationship between South and North

• Korea Trade Review
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• v.42 no.2
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• pp.145-174
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• 2017

Recently, due to the worsening global economic recession, Korea which is a small, export-oriented economy has decreased exports and the domestic economy also continues to stagnate. Therefore, for continued growth of our economy through export growth, we need to analyze the validity of export support system such as export insurance and prepare ways to expand exports. This study is to investigate the effects of Export Insurance on the exports of SMEs as well as LEs. For this purpose, this study conducted Time Series Analysis using data such as export, export insurance acquisition, export price index, exchange rate, and coincident composite index(CCI). First, as a result of the Granger Causality Test, the exports of LEs has found to have a causal relationship with the CCI, and CCI is to have a causal relationship with the short-term export insurance record. Second, the results of VAR analysis show that the export insurance acquisition result and the export price index have a positive effect on the exports of LEs, while the short - term export insurance has a negative effect on the exports of LEs. Third, as a result of variance decomposition, the export of LEs has much more influenced for mid to long term by the short-term export insurance acquisition compared to SMEs. Fourth, short-term export insurance has a positive effect on exports of SMEs. In order to activate short-term export insurance against SMEs, it is necessary to expand support for SMEs by local governments. This study aims to suggest policy implications for establishing effective export insurance policy by analyzing the effects of export insurance on the export of SMEs as well as LEs. It is necessary to carry out a time series analysis on the export results according to the insurance acquisition results by industry to measure the export support effect of export insurance more precisely.

• Journal of Distribution Research
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• v.17 no.4
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• pp.55-80
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• 2012

I. Introduction Developing the relationships between companies is very important issue to ensure a competitive advantage in today's business environment (Bleeke & Ernst 1991; Mohr & Spekman 1994; Powell 1990). Partnerships between companies are based on having same goals, pursuing mutual understanding, and having a professional level of interdependence. By having such a partnerships and cooperative efforts between companies, they will achieve efficiency and effectiveness of their business (Mohr and Spekman, 1994). However, it is difficult to expect these ideal results only in the B2B corporate transaction. According to agency theory which is the well-accepted theory in various fields of business strategy, organization, and marketing, the two independent companies have fundamentally different corporate purposes. Also there is a higher chance of developing opportunism and conflict due to natures of human(organization), such as self-interest, bounded rationality, risk aversion, and environment factor as imbalance of information (Eisenhardt 1989). That is, especially partnerships between principal(or buyer) and agent(or supplier) of companies within supply chain, the business contract itself will not provide competitive advantage. But managing partnership between companies is the key to success. Therefore, managing partnership between manufacturer and supplier, and finding causes of conflict are essential to improve B2B performance. In conclusion, based on prior researches and Agency theory, this study will clarify how business hazards cause conflicts on supply chain and then identify how developed conflicts have been managed by two control mechanisms. II. Research model III. Method In order to validate our research model, this study gathered questionnaires from small and medium sized enterprises(SMEs). In Korea, SMEs mean the firms whose employee is under 300 and capital is under 8 billion won(about 7.2 million dollar). We asked the manufacturer's perception about the relationship with the biggest supplier, and our key informants are denied to a person responsible for buying(ex)CEO, executives, managers of purchasing department, and so on). In detail, we contact by telephone to our initial sample(about 1,200 firms) and introduce our research motivation and send our questionnaires by e-mail, mail, and direct survey. Finally we received 361 data and eliminate 32 inappropriate questionnaires. We use 329 manufactures' data on analysis. The purpose of this study is to identify the anticipant role of business hazard (environmental dynamism, asset specificity) and investigate the moderating effect of control mechanism(formal control, social control) on conflict-performance relationship. To find out moderating effect of control methods, we need to compare the regression weight between low versus. high group(about level of exercised control methods). Therefore we choose the structural equation modeling method that is proper to do multi-group analysis. The data analysis is performed by AMOS 17.0 software, and model fits are good statically (CMIN/DF=1.982, p<.000, CFI=.936, IFI=.937, RMSEA=.056). IV. Result V. Discussion Results show that the higher environmental dynamism and asset specificity(on particular supplier) buyer(manufacturer) has, the more B2B conflict exists. And this conflict affect relationship quality and financial outcomes negatively. In addition, social control and formal control could weaken the negative effect of conflict on relationship quality significantly. However, unlikely to assure conflict resolution effect of control mechanisms on relationship quality, financial outcomes are changed by neither social control nor formal control. We could explain this results with the characteristics of our sample, SMEs(Small and Medium sized Enterprises). Financial outcomes of these SMEs(manufacturer or principal) are affected by their customer(usually major company) more easily than their supplier(or agent). And, in recent few years, most of companies have suffered from financial problems because of global economic recession. It means that it is hard to evaluate the contribution of supplier(agent). Therefore we also support the suggestion of Gladstein(1984), Poppo & Zenger(2002) that relational performance variable can capture the focal outcomes of relationship(exchange) better than financial performance variable. This study has some implications that it tests the sources of conflict and investigates the effect of resolution methods of B2B conflict empirically. And, especially, it finds out the significant moderating effect of formal control which past B2B management studies have ignored in Korea.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.