• Knowledge Management Research
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• v.25 no.2
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• pp.69-94
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• 2024

With the development of cyberspace and its increasing interaction with our daily lives, cybercrime has been steadily increasing in recent years and has become more prominent as a serious social problem. Notably, the "four major malicious cybercrimes" - cyber fraud, cyber financial crime, cyber sexual violence, and cyber gambling - have drawn significant attention. In order to minimize the damage of cybercrime, it's crucial to delve into the specifics of each crime and develop targeted prevention and intervention strategies. Yet, most existing research relies on indirect data sources like statistics, victim testimonials, and public opinion. This study seeks to uncover the characteristics and factors of cybercrime by directly interviewing suspects involved in 'copyright infringement', 'gambling' related to illicit online content, and 'pornography crime'. Through coding analysis and text mining, the study aims to offer a more in-depth understanding of cybercrime dynamics. Furthermore, by suggesting preventative and remedial measures, the research aims to equip policymakers with vital information to reduce the repercussions of this escalating digital threat.

• KDI Journal of Economic Policy
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• v.12 no.3
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• pp.153-172
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• 1990

The present paper investigates the potential value of strategic antitrust policy in an oligopolistic international market. The market is characterized by a non-cooperative Cournot-Nash equilibrium and by asymmetry in costs among firms in the world market. The model is useful for two reasons. First, it is important in the context of policy-making to examine the conditions under which it may be beneficial to relax antitrust law to enhance competitiveness. Second, the explicit derivation of the level of cost-saving required for a gain in total domestic surplus provides an empirical rule for excluding industries that do not satisfy the requirements for a socially beneficial antitrust exemption. Results of the analysis include a criterion that tells how the cost-saving and concentration effects of a merger offset each other. The criterion is derived from fairly general assumptions on demand functions and is simple enough to be applied as a part of the merger guidelines. Another interesting policy implication of our analysis is that promoting mergers would not be a beneficial strategy in a net importing industry where cost-saving opportunities are thin. Cost-saving domestic mergers are more likely to increase national welfare in exporting industries. The best candidate industries for application of strategic antitrust policy are those with the following characteristics: (i) a large potential for efficiency enhancement; (ii) high market concentration at the world but not the domestic level; (iii) a high ratio of exports to imports. Recently, many policymakers and economists in Korea have also come to believe that the appropriate antitrust policy in an era of increased foreign competition may actually be to encourage rather than to prohibit domestic mergers. The Industry Development Act of 1986 and the proposed bill for Mergers and Conversions in the Financial Industry of 1990 reflect this changing perspective on antitrust policy. Antitrust laws may burden domestic firms in the sense that they have a more constrained strategy set. Expenditures to avoid antitrust attacks could also increase costs for domestic firms. But there is no clear evidence that the impact of antitrust policy is significant enough to harm the competitiveness of domestic firms. As a matter of fact, it is necessary for domestic financial institutions to become large in scale in this era of globalization. However, the absence of empirical evidence for efficiency enhancement from mergers suggests caution in the relaxation of antitrust standards.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Management & Information Systems Review
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• v.39 no.2
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• pp.39-60
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• 2020

Block chain technology is one of the core elements for realizing the 4^th industrial revolution, and many efforts have been made by government and companies to provide services based on block chain technology. In this study we analyzed the benefits of block chain technology for EVMS and designed EVMS block chain platform with increased data security and work efficiency for project management data, which are important assets in monitoring progress, foreseeing future events, and managing post-completion. We did the case studies on the benefits of block chain technology and then conducted the survey study on security, reliability, and efficiency of block chain technology, targeting 18 block chain experts and project developers. And then, we interviewed EVMS system operator on the compatibility between block chain technology and EVM Systems. The result of the case studies showed that block chain technology can be applied to financial, logistic, medical, and public services to simplify the insurance claim process and to improve reliability by distributing transaction data storage and applying security·encryption features. Also, our research on the characteristics and necessity of block chain technology in EVMS revealed the improvability of security, reliability, and efficiency of management and distribution of EVMS data. Finally, we designed a network model, a block structure, and a consensus algorithm model and combined them to construct a conceptual block chain model for EVM system. This study has the following contribution. First, we reviewed that the block chain technology is suitable for application in the defense sector and proposed a conceptual model. Second, the effect that can be obtained by applying block chain technology to EVMS was derived, and the possibility of improving the existing business process was derived.

• The Journal of the Korean life insurance medical association
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• v.22
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• pp.139-169
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• 2003

국내 보험 산업은 경제발전에 따라 많은 성장을 이루어왔으나 단체보험은 보험 회사의 외부적 또는 내부적 환경으로 인해 활성화가 미흡한 상황이다. 개인보험시장의 포화, 해외시장에서 단체보험의 지속적인 성장, 사회보험 민영화 논의, 방카슈랑스와 보험시장의 개방 등 급격한 변화를 겪고 있는 보험영업환경을 고려한다면 향후 확대될 기업복지시장에서의 성공적 역할수행을 위해서는 단체보험 영업과 지원시스템의 보완이 시급한 과제라고 할 수 있다. 특히 언더라이팅 기법은 단체보험의 핵심역량이며 회사의 경쟁력 강화와 사차익 안정화를 위해서는 단체보험 인수기법의 선진화가 필수요건이다. 단체보험은 대수의 법칙, 수지상등의 원칙 등 보험의 기본원리라는 측면에서는 개인보험과 다른 점이 없지만 하나의 계약을 통해 집단의 피보험자에게 보장을 제공하기 때문에 가지게 되는 역선택 축소, 비용절감, 기업에 의한 1차선택 등 몇 가지 특성들은 인수기법에서의 차이를 필요로 한다. 하지만 국내의 단체보험 언더라이팅은 기본개념조차 제대로 정립되어 있지 못한 초기단계로 단체보험의 특성을 제대로 반영할 수 있는 위험평가를 위해서는 선진기법의 도입이 절실하다. 첫째, 자유보장한도(FREE COVER LIMIT)의 도입이다. 자유보장한도는 단체에 대한 위험과 피보험자 개인의 위험을 구분하는 기준으로 자유보장한도내의 피보험자에 대해서는 고지나 의적 검사를 요구하지 않고 개인별 언더라이팅을 하지 않으며 거절체나 표준하체이더라도 자유보장한도 금액까지는 나머지 정상 피보험자들과 동일한 보장을 제공하는 것을 말한다. 이는 피보험자별 위험을 중심으로 심사하고 있는 현재의 국내 단체보험 인수방법에서 발생되는 고객측 불만과 심사의 비효율성을 개선할 수 있는 방안이다. 둘째, 단체별 특성에 따른 보험요율 차등화이다 단체는 산업의 종류, 피보험자의 직무, 지역적 위치, 크기(피보험자수), 성별구성비 등 여러 가지 특성들을 가지고 있으며 이런 특성들은 보장급부에 따라 발생위험에 영향을 미칠 수 있다. 하지만 현재 나이와 성별에 따라서 피보험자별로 정해지는 요율체계만으로는 이런 위험들을 적절하게 반영하지 못하고 단체별 형평성에도 문제가 생긴다. 따라서 정확한 data 구축을 통해 단체 특성별로 어떤 보장에 어느 정도로 위험 발생에 영향을 미치는지를 분석하여 보험요율을 차등부과 할 수 있는 체계를 갖추어야 한다. 셋째, 경험을 활용한 보험료 산정기법이다. 이것은 개인보험과 구분되는 가장 큰 단체보험만의 특성이라 할 수 있는데 해당 단체의 과거 경험 data 즉 청구로 인한 지급금액을 토대로 당해 계약 보험료를 결정하는 방법이다. 이를 위해서는 과거 경험 data가 얼마나 신뢰할 수 있는 지의 정도(신뢰도)를 측정하는 것이 필요하다. 과학적이고 효율적인 단체보험 인수를 위해서 경험율의 활용은 반드시 이루어져야 할 선결과제이다. 넷째, 관련규정의 정비가 필요하다 단체보험의 특성을 갖기 위해서는 가입가능한 피보험자들의 자격규정(eligibility), 활동적근무 조건(actively at work)이 요구되어야 하며 참여비율(가입비율)과 보장수준의 구성방법에 대해서도 가이드라인 설정을 통해 역선택을 최소화 할 수 있는 제도적 보완이 마련되어야 한다. 이런 선진인수기법의 도입과 함께 단체보험 언더라이터의 필요역량을 개발하고 향상시키는 노력도 병행되어야만 종합금융화, 대형화가 진전되면서 대경쟁의 구도로 바뀌고 있는 국내 보험시장에서의 경쟁력 확보가 가능할 것이다.

• Management & Information Systems Review
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• v.36 no.3
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• pp.167-184
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• 2017

In this study, we investigated the effect of offline banking trust on smart banking trust. As influencing factors of smart banking trust, this study compared offline banking trust, smart banking's system quality, and information quality. For the empirical study, 186 questionnaire data were collected from smart banking users and the data were analyzed using Smart-PLS 2.0. As results, it was verified that there is trust transfer in FinTech service, by the significant effect of offline banking trust on smart banking trust. And it was proved that the effect of offline banking trust on smart banking trust is lower than that of smart banking itself. The contribution of this study can be seen in both academic and industrial aspects. First, it is the contribution of the academic aspect. Previous studies on banking were focused on either offline banking or smart banking. But this study, focus on the relationship between offline banking and online banking, proved that offline banking trust affects smart banking trust. Next, it is the industrial contribution. This study showed that offline banking characteristics of traditional commercial banks affect the trust of emerging smart banking service. This means that the emerging FinTech companies are not advantageous in the competition of trust building compared to traditional commercial banks. Unlike traditional commercial banks, the emerging FinTech is innovating the convenience of customers by arming them with new technologies such as mobile Internet, social network, cloud technology, and big data. However, these FinTech strengths alone can not guarantee sufficient trust needed for financial transactions, because banking customers do not change a habit or an inertia that they already have during using traditional banks. Therefore, emerging FinTech companies should strive to create destructive value that reflects the connection with various Internet services and the strength of online interaction such as social services, which have an advantage over customer contacts. And emerging FinTech companies should strive to build service trust, focused on young people with low resistance to new services.

• Korean Journal of Social Welfare
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• v.53
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• pp.285-310
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• 2003

As National Pension Scheme for all nation complete in 1999 through expanding application in cities, the public pension including Public Occupational Pension became main axis of old-age income maintenance. After 4years since then, now, it is only half of total National Pension insured persons who have been qualified to receive pension through participate and contribution. The other half of National Pension insured is left the excluded from public pension. This paper is intended to identify scale and characteristics of the excluded from public pension and to analysis its cause, and to explore policy measures for solving the excluded's problem. for current recipients over 60 years old generation, the its excluded's scale is no less than 86% of the old over 60 years. The probability of getting in the excluded is high in case of old elderly and female for current elderly generation. For future recipients 18-59 years working generation, the its excluded's scale is no less than 61% of the 18-59 years total population. The probability of getting in the excluded is high in case of 18-29 years and female for current working generation. As logistic regression analysis determinant factor of paying or not pension contribution for future recipients, it appear that probability of getting in the excluded for current working generation is high in case of younger old, lower education attainment, irregular employee, working at agriculture forestry fishery sector, construction sector, wholesale retail trade restaurants hotels sector, financial institution and insurance real estate renting and leasing sector in comparison with manufacturing sector, occpaying at elementary occupation, professionals technicians and associate professionals, sale and service workers, plant machine operators and assemblers, legislators senior officials and managers in comparison with clerks. The Policy measures for the current recipient old generation have need to reinforce supplemental role of Senior's pension(non-contribution pension) until maturing of public pension, because of no having chance of public pension participants for them. And the Policy measures for the future recipient working generation have need to restructure social security fundamentally corresponding with social-economic change as labour market and family structure etc. The pension system has need to change from one earner one pension to one citizen one pension with citizenship rights. At this point, public pension have need to manage with combining insurance's contribution principle and citizenship principle financing by taxes. Then public pension will become substantially universal social network for old-age income maintenance and we can find real solution for the excluded from.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.1
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• pp.161-198
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• 2014

The idea of creating an International Space Exploitation Agency (tentative title: hereinafter referred to ISEA) is only my academic and theoretical opinion. It is necessary for us to establish ISEA as an international organization for the efficient and rapid exploitation of natural resources in the moon and other celestial bodies. The creation of ISEA as a new international organization is based on the Article 11, 5 and Article 18 of the 1979 Moon Agreement. In order to create it as a preliminary procedure, it needs to make the Draft for the Convention on the Establishment an ISEA among the space-faring countries. The main contents of this paper is composed of (1) introduction, (2) joint exploitation of the natural resources (Heliumn-3, etc.) in the moon and ISEA, (3) activities for the exploitation of moon and other celestial bodies by the space-faring powers, (4) legal problems and Solution for the exploitation and mining rights of the natural resources in the moon, mars and celestial bodies, (5) procedure of creating an ISEA, (6) the principal points that need to be included in the draft for the ISEA convention, (7) conclusion. The creation of an ISEA would lead to a strengthening of the cooperation among the States deemed essential by the global community towards joint undertakings in space and would act as a catalyst for the efforts on the exploitation of the natural resources moon, mars, Venus, Mercury and other celestial bodies and allow resources, technology, manpower and finances to be centrally managed in an independent fashion to the benefit of the space-faring countries. It is desirable and necessary for us to create ISEA in order to promote cooperation in the field of space policy, law, science technology and industry etc. among the space-faring countries. The creation of the ISEA will be promoted the international cooperation among the space-faring countries in exploration and exploitations of the natural resources in the moon, Mars, Venus, Mercury and other celestial bodies. Finally, it should be noted that the political drive will be necessary not only to set up the organization ISEA, but also study a subsequent measures. It is also necessary for us to create the ISEA in order to develop the space industry, to strengthen friendly relations and to promote research cooperation among the space-faring countries based on the new ideology and creative ideas. If the heads (president or prime minister) of the space super-powers including the UNCOPUOS will be agreed to establish ISEA at a summit conference, 1 believe that it is possible to establish an ISEA in the near future.

• Korean Journal of Labor Studies
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• v.24 no.2
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• pp.95-136
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• 2018

As the number of precariats grows, their poor labor rights and working conditions are becoming issues of major concern all over the world but how to represent their interests is still controversial. Basically, the union is the institutional mechanism for representing the labor rights. However, it is difficult for workplaceand enterprise-based unions to fully represent the labor rights of precarious workers. Recently, so-called community unions have emerged in the United States, the United Kingdom, and Japan as independent organizations representing the rights of non-standard workers. Community unions refer to labor unions which organize precarious workers across firms at the regional level. They are known to be suitable for covering the unemployed, job seekers, indirect employment workers, short-term contract workers, and small-firm workers. In South Korea, since the financial crisis in 1997, a dramatic increase in the number of precariats leads to emergence of new types of trade unions such as the Youth Community Union, the Arbeit Workers' Union, the Artist Social Union and the Korea Musician's Union. They have engaged in various activities to guarantee the labor rights of precariats. Recently, researchers have also tried to identify defining characteristics of these new forms of unionism. To expand research on trade unionism in South Korea, this study compares two different types of community unions: the Youth Community Union and the Arbeit Workers' Union. We believe that this attempt can contribute to the research on the alternative labor movement. For this purpose, this study starts with theoretical discussions on community unions, and compares the Youth Community Union with the Arbeit Workers' Union based on the five characteristics of community unionism: membership and organization structure, the recognition struggle, the type or scope of interest, solidarity with other civic organizations, and the repertoire of resistance strategies. Based on this comparative analysis, this study seeks to foresee the possibility of how community unionism will develop in South Korean in the future.

• 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.