• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Korea Trade Review
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• v.42 no.4
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• pp.69-91
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• 2017

Since the global financial crisis, major countries have been executing policies related to two top-priority goals to create more jobs: revitalization of entrepreneur activity and the cultivation of small and medium-sized companies. In South Korea, the interest of policy makers is increasingly focusing on the role of SMEs that have a technological competitive edge in the realization of a "job-centered creative economy." Due to the nature of the field, the health and medical industry requires a particularly long time until the achievement of industrialization, Also, because of the complex distribution structure, it is essential for related government ministries and institutions to jointly devise strategies. A lack of policy supports for the industry has thus far resulted in its development being relegated for the most part of small and medium-sized companies, which consequently means low global competitiveness. Now is the time for the South Korean government to provide the revolutionary supported options and strategies. This study aims to propose a general policy direction and policy areas for the cultivation of Korea's small and medium-sized companies in the healthcare industry into global small giant companies through an exploration of the German case. It is crucial to first cultivate the international competitiveness of Korean small and medium-sized companies (as in the case of Germany) so that they can grow into global small giant companies. Another important task is the creation of an environment that expedites the qualitative growth of promising SMEs as well as technological development. After securing competitiveness in terms of both product quality and technology in the global health market, substantive policy supports will be necessary to cultivate global small giant companies that are export-based (e.g. job creation effect, sales value added).

• Korean Journal of Plant Tissue Culture
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• v.28 no.5
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• pp.289-296
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• 2001

The main objective of this topic is to establish strategies and to plan biotechnology researches which are related to the agricultural improvements especially focusing on the crop breeding in Korea. From 1960's to 1980's government policy had been emphasized to develope high yielding cultivars for the self sufficient supply of the staple food crops. As a result, considerable increase of rice production has been made with accumulating technology and man's powers. Recently genetically modified crops harboring useful characteristics have been developed using biotechnology and released in the developed countries. National research institutes and private companies have been developed biotechnology researches to establish competitive capabilities, however they have not been successfully used in commercialization. Therefore it is necessary to promote the practical. application by connecting molecular technology with conventional breeding. Proposed research projects are; (1) basic researches including plant genome studies, (2) developing new cultivars through gene transformation, (3) screening and producing antioxidants, secondary metabolite substances and edible vaccines. To set a government policy, both domestic and international research trends were reviewed and possibility of success based on the economic view point were discussed. The intellectual property and preservation of environment play a key role to decide the research priority. It is also necessary for us to make one step system for the distribution of research resources such as microorganisms, genes cloned, plant seeds and research informations for promoting research activities.

• Journal of Mushroom
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• v.1 no.1
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• pp.1-8
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• 2003

Mushroom cultivation in Korea was launched in the early 1960's. At that time Korean government started a program for increasing cultivation of button mushroom (Agaricus bisporus) and oak mushroom (Lentinula edodes) to export agricultural products and to increase farm income. National research institutes under Rural Development Administration, Korea Forest Service, etc. play a leading role in mushroom industry as follows : Development and spread of genetically superior commercial strains, good spawns, and cultivation techniques. Training and field advice to lead farmers for mass production of high quality mushrooms. Political support of facilities and establishments for mushroom cultivation. Several mushrooms including oak mushroom, button mushroom, oyster mushroom, winter mushroom, Ganoderma, P. eryngii, etc. have been popularized for their cultivation techniques and produced in large quantities in the farm. According to a recent statistics, mushrooms have been grown by about 20,000 farm households, in Korea and the gross production of fresh mushrooms is estimated about 170,000 M/T. The gross production of oyster mushroom is the highest followed by winter mushroom, oak mushroom and button mushroom. The gross amount of mushroom production stands over 700 billion won. Thus, mushroom industry goes to the most important cash crop to be produced yearly.

• International Commerce and Information Review
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• v.18 no.3
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• pp.3-21
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• 2016

The thesis examines genealogical study of various aspects to overcome lots of problems which come by when we execute SWIFTNet TSU BPO. Practical implications regarding the innovation of electronic trade infrastructure are as follows. First, the shipping documents in the SWIFTNet TSU BPO are directly sent to an importer by an exporter after the baseline is confirmed. With this process itself, therefore, the bank cannot secure the account receivable. When initiating the SWIFTNet TSU BPO deal, it is needed to set regulations on the bank's account receivable security in the contract. Second, the SWIFTNet TSU BPO should also have an institutionally unified sharing platform with security, stability and convenience. It other words, it is needed to develop services which meet e-payment paradigm and international environments through continued analysis on market changes and flow. Third, the SWIFTNet TSU is useful in terms of promptness, reduction of risk in foreign exchange payment, cost reduction. Therefore, the SWIFT should be perfectly united and linked among the banks, importer and exporter to make the SWIFTNet TSU more convenient in countries around the world. Fourth, the SWIFT should be approached from the aspect of expansion of network and creation of a new business model through analysis on these problems with a worldwide perspective. At the same time, it is necessary to build a cooperative system to share information and promote comprehensive management for efficient operation.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.2
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• pp.173-188
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• 2016

This paper argues that the establishment of the Kaohsiung Export Processing Zone (KEPZ), the first EPZ in East Asia, is a compromise of cold-war geopolitical economy in the 1960s. The KEPZ is part of the liberalization policy advise of the US Aid agency which intended to push the KMT (Kuomintang) government to downsize the nationalized sectors and foster private enterprises and encourage foreign investments. However, the KMT state hesitated to embrace the advice wholeheartedly but was forced to implement selectively the policies. To meet the compromise between liberalization and control, the KMT government takes advantage of the KEPZ to grab the geoeconomic opportunities emerging from the new international division of labor in the 1960s without losing the geopolitical support from the US. The idea that zoning as a space of compromise would provide a subtle re-examination of the rise of the KEPZ which is conventionally explained by the functionalist arguments such as increase of employment opportunities, foreign investments and export by the far-sighted developmental state.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.167-178
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• 2021

The purpose of this study is to analyze the direct investment decision factors in the Kaesong Industrial Complex and Vietnam, and to contribute to the creation of domestic jobs and the revitalization of the inter-Korean economy. According to the analysis, most of the Kaesong Industrial Complex and Vietnamese investment companies are entering the complex for the purpose of utilizing cheap labor, cheap factory locations, sales/development of local markets, and bypass export production bases in third countries. This can be divided into production-efficient investors using differences in production price such as labor costs and market-oriented investors to sell and expand the local market, which seems to be consistent with global direct investment patterns such as Nike, Apple, and Amazon. However, even if the North Korea-U.S. denuclearization talks ease or lift sanctions, Vietnamese investors' willingness to invest in the North Korea has been most burdened by the possibility of closing special economic zones due to political risks. Last but not least, it is important to note that those willing to invest in North Korea are mostly smaller enterprises in textiles, sewing, footwear and leather industries-those that benefit from low-cost labor. Since their size is small, they need policy support in financing, especially in the early stages of their business. Even after they grow past the early stages, those without collateral would still need state guarantee letters to get financing. Thus, it is worth considering to use the Inter-Korean Cooperation Fund to compensate commercial banks for bad loan loss or for low-interest loans for smaller SMEs. The interviews with SMEs found that red-tape is one of the biggest difficulties they face. Thus, it is recommended that a one-stop service agency should be established to cover all processes and issues related to inter-Korean economic cooperation to eliminate redundancy and expediate government support for SMEs.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Nuclear industry
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• v.37 no.9
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• pp.58-90
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• 2017

'공포의 값비싼 대가(The High Cost of Fear)'는 공개된 자료 중 동료 평가를 마친 최신의 자료와 간단한 계산 방법을 통해 한국의 탈원전 정책이 가져올 경제적, 환경적 영향을 분석한 보고서이다. 우리는 탈원전 정책이 다음과 같은 영향을 미칠 것으로 예측한다. ${\cdot}$천연가스 구매에만 최소 매년 100억 달러의 비용이 들 것이다. 이는 한국 평균임금인 연소득 29,125달러를 받는 일자리 343,000개에 해당하는 금액이다. ${\cdot}$비용의 대부분은 연료 수입에 사용될 것이며, 한국의 무역 수지가 악화될 것이다. ${\cdot}$한국의 부족한 재생에너지 자원을 고려할 때, 상당한 양의 화석 연료를 추가로 사용하게 될 것이다. ${\cdot}$LNG 발전소가 석탄 발전소를 대체하지 못하고 원자력발전소를 대체하면서 대기 오염으로 인한 조기 사망자 수가 증가할 것이다. ${\cdot}$한국의 전도유망한 원전 수출 산업이 아예 붕괴되거나 큰 타격을 입을 것이다. ${\cdot}$평균적 미국 자동차의 연간 주행거리를 기준으로 150만대에서 270만대의 미국 자동차가 배출하는 배기가스의 양만큼 연간 탄소 배출이 증가할 것이고, 한국은 파리기후협정에서 약속한 탄소 배출 감축 목표를 달성할 수 없게 된다. 본 보고서는 현재 계획된 탈원전 정책의 역사적 사회적 배경을 분석하여 다음과 같은 결론을 도출하였다. ${\cdot}$'그린피스(Greenpeace)', '지구의 친구들(Friends for the Earth)' 등 막대한 자금 지원을 받는 해외 환경단체들은 탈원전 거짓 정보의 근원이며, 이들은 저렴하고 풍부한 에너지라는 개념을 반대한다. ${\cdot}$후쿠시마 원전 사고와 그 여파의 주된 원인은 일본 원자력산업계의 오만과 원자력에 대한 과장된 집단 공포이다. ${\cdot}$반핵 진영의 논리에는 산업계와 정부에 대한 불신과 원자력, 방사선에 대한 몰이해가 반영되어 있다. ${\cdot}$반핵 진영은 후쿠시마 사고를 2014년 한수원 납품 비리 사태의 심각성을 과장하는 데 사용하고 있다. 2014년의 비리 사태는 한국 원자력 규제기관의 독립성을 증명했으며, 2016년의 경주 지진은 2011년 후쿠시마에서 쓰나미와 노심 용융을 초래한 동일본 대지진의 1/350,000의 크기밖에 되지 않는다. 본 보고서는 한국과 타국가의 반핵 운동이 주는 교훈을 다음과 같이 정리하였다. ${\cdot}$어떠한 국가도 에너지 자원 최빈국인 프랑스나 한국 같은 국가조차도 탈원전 '전쟁'에서 자유롭지 않으며, 이는 전 세계적으로 원자력산업이 쇠퇴하는 원인이다. ${\cdot}$원자력산업계, 정부, IAEA 등은 한국과 세계 여러 국가에서- 문화적, 제도적, 재정적 원인으로 원자력산업의 보호와 확대라는 목표를 달성할 수 없다. ${\cdot}$원자력산업을 구하기 위해서는 새로운 비전과 새로운 제도, 그리고 새로운 리더십이 필요하다. ${\cdot}$원자력의 근원적이고 혁신적인 비전 원자력 인본주의(atomic humanism)에 대한 재조명이 필요하다. ${\cdot}$원자력을 지키고 대중과 소통하기 위해 과학 연구단체, 대학교, 사단법인, NGO 등의 새로운 기관들을 후원해야 한다. ${\cdot}$공포를 조장하는 반원전 세력에 맞서 공포를 극복해야 하고, 대중의 공포를 극복해왔던 다른 기술들의 사례에서 교훈을 얻어야 한다.

• The Journal of Small Business Innovation
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• v.19 no.3
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• pp.1-16
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• 2016

Korean government had used public 'credit guarantee schemes' (CGS) as a counter-cyclical measure. However, it is still controversial about the effectiveness of policy financing on the SMEs. Criticism on policy financing involves the argument that supporting enterprises hampers competition and innovation of SMEs by increasing their dependence on the government and delays the exit of marginal firms. In this paper, we investigate how to effectively build up the rationale of running public CGSs. At the same time, we propose the ways to coexist of public credit guarantee and market-based private finance system for SMEs. First, CGS, as a counter-cyclical function, must coexist with the private financial system by compensating the market failure caused by pro-cyclical behavior of the private financial market. Second, CGS has the comparative advantages, compared to both the interest rate policy of the central bank and fiscal policy of the government. The credit guarantee is the symptomatic treatment that could revitalize the economy shortly by providing liquidity. Also, knowing that CGS is provided based on the leverage ratio defined by outstanding guarantee divided by capital fund, public 'credit guarantee' (CG) has an advantage that is free from the risk of government deficit. Third, the reason for existence of the CGS should be founded in supporting services for SMEs, available only in a public sector that is difficult to expect from private banks. In this regard, it is desirable to strengthen the publicness of credit guarantee over the support for start-ups, growing companies, the improvement of productivity, increase of exports, a long-term investment in facilities, the employment-creating businesses, and innovative enterprises.