• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.6
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• pp.857-872
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• 2014

This study investigates the effect of service ubiquity perceptions on consumers' responses to virtual stores such as benefit and risk perceptions, shopping value perceptions, and service usage intention. Data were collected via a self-administered online survey from nationwide consumer panels of an online marketing research firm. Questionnaire items were adopted from previous literature and developed by authors via pretesting to measure variables. The results revealed that virtual store service ubiquity affects consumer benefit perceptions as well as risk perceptions. All benefit perceptions (including time effectiveness, user control, and compatibility) had significant mediating effects between service ubiquity and hedonic/utilitarian shopping service value perceptions. The mediating effect of financial risk was significant only in the relationship between service ubiquity and utilitarian value perception. The findings offer retailers and marketers information in regards to consumers' perception of a virtual store usage, which can enhance service and product strategy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.877-884
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• 2020

The main aim of the present study is to investigate the factors that are considered affecting the adoption of Activity-Based Costing (ABC) in the autonomous public universities in Vietnam. A quantitative research was carried out. The data was collected through an online questionnaire survey between June 2020 and September 2020 addressed to the target respondents comprising 168 managers and accountants from 23 autonomous public universities in Vietnam, which participated in the resolution project No. 77/NQ-CP of the Vietnamese government on the pilot renovation of operational mechanisms of public tertiary education institutions during the period of four years, from 2014 to 2017. The findings resulted from hypothesis testing by a binary regression analysis based on the SPSS 20.0 software show that training, competition, support of top manager, and university size are the four main factors that positively affect the adoption of Activity-Based Costing (ABC) in studied universities. On the other hand, no statistically significant impact was found on two other variables, namely the variety of services provided and the usefulness of cost information factors. From the research results, discussions and policy recommendations have been presented to promote the adoption of Activity-Based Costing (ABC) in Vietnamese autonomous public universities in the coming time.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.145-175
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• 2005

In 2001, e-Credit guarantee system was introduced by the Korea Credit Guarantee Fund(KCGF) to extends the credit guarantee services for the purchasing amount on credit in the B2B e-Marketplace. It combines both the merits of bill of exchange and credit card and eliminates the uneasiness related to the unpaid accounts due to the non-facial e-Marketplace. The purpose of this paper is to empirically analyze both the causal relationship and influences among theoretical variables by the structural equation model(SEM). e-Credit guarantee system can be a good strategy for promoting B2R e-Marketplace. The level of application of e-Credit guarantee system is attributable to both the characteristics of B2B e-Marketplace and products. The cost reduction or saving in purchasing procedures, production and stockpiling will be possible through e-Credit guarantee system. The close linkage of financial institutions with the enterprises based on e-Credit guarantee system will further promote B2B e-Marketplace in Korea.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.65-71
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• 2017

This paper proposes a smart phone authentication method based on user's behavior and habit that is an authentication method against shoulder surfing attack and brute force attack. As smart phones evolve not only storage of personal data but also a key means of financial services, the importance of personal information security in smart phones is growing. When user authentication of smart phone, pattern authentication method is simple to use and memorize, but it is prone to leak and vulnerable to attack. Using the features of the smart phone pattern method of the user, the pressure applied when touching the touch pad with the finger, the size of the area touching the finger, and the time of completing the pattern are used as feature vectors and applied to user authentication security. First, a smart phone user models and stores three parameter values as prototypes for each section of the pattern. Then, when a new authentication request is made, the feature vector of the input pattern is obtained and compared with the stored model to decide whether to approve the access to the smart phone. The experimental results confirm that the proposed technique shows a robust authentication security using subjective data of smart phone user based on habits and behaviors.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.495-508
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• 2020

Economic integration is an indispensable trend in all countries. However, besides the advantages that economic integration brings, there are also disadvantages, such as competition between businesses among states in export activities. Vietnam is a developing country with many advantages, especially, the seafood exporting industry. However, with competitive pressure as well as strategic constraints, Vietnamese seafood exporters still face many difficulties. Therefore, the case study of the Kien Giang province of Vietnam is used to analyze the factors affecting the competitiveness of seafood exporting enterprises. The study applied quantitative research methods with a survey of 350 seafood exporting enterprises in Kien Giang province to achieve the research objectives. The research results identified eleven key factors affecting the competitiveness of seafood exporting enterprises, including (1) vision and strategy of leader; (2) human resources management capability; (3) organization capability; (4) customer-responsive marketing capability; (5) relationship management capability; (6) technical capability; (7) competitors reaction capability; (8) business environment adoption capability; (9) financial capability; (10) products and services innovation capability; and (11) branding management. The research results provided the basis to propose some managerial implications to improve the competitiveness of exporting enterprises in the context of the global economic integration.

• Informatization Policy
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• v.24 no.2
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• pp.20-42
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• 2017

In this paper, we focus on classification of security threats and definitions of security requirements for Internet banking service. Threats are classified based on the past and potential incidents, based upon which we will be able to propose security requirements. In order to identify security threats, the structure of the Internet banking service is classified into three sections - the financial institutions, the network, and the user-terminal - and we defined arising threats for each section. We focused the analysis especially on the user-terminal section, which is relatively vulnerable, causing difficulties in securing stability of the service as a whole. The analyzed security threats are expected to serve the foundation for safe configuration of various Internet banking services.

• World Technopolis Review
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• v.5 no.2
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• pp.108-118
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• 2016

There are very few studies on governance structure for the collaboration between HEIs and science and technology parks until today. Major activities between science parks and HEIs are R&D activities, collaborative researches, technology transfer, space provision for BIs and Technology BIs in the science parks, provision of technical, legal and financial services for start-ups and venture firms. Governance structure for the collaboration of high education institutes with science and technology parks is the handling of complexity and management of dynamic flows of collaboration between two groups. Three models on the governance structure for the collaboration are suggested in this study. The first model is a governance structure that links R&D system such as universities, public research institutes and private research institutes with industrial production cluster such as a group of companies and industrial parks. The second model is a governance structure that has four layers of hierarchy. This hierarchical governance model is composed of four levels of organizations such as central government, three actors, one center for collaboration and many individual research performers. The third model is a governance structure that networks all the stakeholders horizontally. Under this structure, governance is conducted by the network members with no separate and unique governance entity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.6
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• pp.1017-1022
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• 2007

In this paper, we try to analyze the likelihood of exercising the power of market dominance by certain generators in future power industry of Korea. Firstly, we estimated installed generation capacity and sales volume of electricity in Korea, based on 'The 3rd Long Term Power Plan' which was announced in December 2006. Secondly, we calculated HHI, an index showing the degree of concentration of an industry, and RSI, an index showing how adequate the supply of goods or services of an industry is, using Fast-Forward. Thirdly, assuming a major generator employs the strategy of withholding a part of its available capacity at a peak time, we simulated hypothetical movement of SMP over a certain period of time, which is compared with that obtained without assuming such strategy to generate Lerner Index. an index showing the degree of market power of a monopoly. Regulators, home and abroad, have not given much interest in analyzing the effect of market dominance that is likely to be exercised by certain players in the future. That said, this paper provides insight into developing methodologies of analyzing and mitigating such effect by proposing the above indices to gauge it. In addition, this paper also shows the potential impact of employing capacity withholding strategy on the financial account of a dominant generator.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.21 no.4
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• pp.193-203
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• 2010

This study investigates successful overseas cases and projects of digital archiving of historical materials in order to develop continuous digital archiving strategies in this rapidly changing digital information environment. The analysis is based on the information life cycle perspective of collection, preservation, access and use of digital archives as well as the concept of digital curation. Through the analysis, the study proposes nation-wide digital archiving policies, long-term preservation and standardization strategies for continuous services, and collaborative financial support strategies between institutions and countries for successful digital archiving and continuous improvement.