• Korean System Dynamics Review
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• v.13 no.1
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• pp.63-80
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• 2012

This paper is aiming at providing the systems thinking perspective on the collapse of the savings and loan banking system in Korea. Two causal loop diagrams are developed to conduct the analysis: The first is focusing on the structural problems included in the establishment of S&L banking in 1990s. The later is developed based on the project financing mechanism by controlling the credit standard required during the due diligence. The result of this study shows that the main cause of the collapse of the S&L banking is the structural problem connected to real estate market including the failure of regulation.

• International Commerce and Information Review
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• v.8 no.3
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• pp.99-119
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• 2006

The recent trend in the payment terms of international trade shows the gradual shift toward more diversified payment methods (from L/C to not L/C) in order to cope with the increasingly dynamic international transactions in a more flexible manner. The reasons behind this recent shift are as follows : first, the global trade market is breaking away from the traditional L/C methods based on letters of credit toward a not L/C methods. nother reason for the changing trade payment methods is the increasing volume of intra transactions between headquarters and their foreign subsidiaries based on collection payment methods. Having mentioned the above problems that impede the Korean export insurance system, some suggestions can be put forward through a comparative analysis with foreign export insurance system. First, inducing private investments is one way of strengthening financial health of the KEIC. The KEIC also needs to diversify its insurance coverage adapting to the changing international trade environments.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.11
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• pp.1542-1553
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• 2007

Recently, the growing of the aging population resulting from the medical and science development has made the elderly consumer as a new market. The purposes of this study were 1) to examine the purchase behavior of apparel products and hairdressing services of elderly consumers, 2) to investigate the purchase behavior in the apparel store and hairdressing shop on lifestyle types. Data were collected from 853 women in their 50s and 60s living in Busan. Data were analyzed by frequency analysis, descriptive analysis, factor analysis, Cronbach#s alpha, Chi-square analysis, cluster analysis, one-way ANOVA and Duncan test using SPSS WIN 12.0. The results of the study were as follows: First. when elderly consumers purchased apparel product, they were likely to use credit cards, to shop alone or with friends at a department store, and to use the store as information source. In their purchases of hairdressing services, they tended to visit the near shop for a permanent service bimonthly and to depend on their past experiences for hairdressing. Second, elderly consumers were classified by the lifestyle into the Active self-fidelitist, Economy family-oriented, and Passive-stagnant. The purchase behaviors in the apparel store and hairdressing shop were different among lifestyle types. Implications were suggested for the consumer behavior researchers and retailers of the elderly fashion market.

• Journal of Distribution Science
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• v.13 no.1
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• pp.83-91
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• 2015

Purpose - Despite the structural irrationality of multi-level transportation and the oil price rise, the domestic freight transportation market continues to grow, mirroring the rise in e-commerce and resultant increase in courier services and freight volumes. Several studies on courier services have been conducted. However, few studies or statistics have been published regarding regular freight services although they have played a role in the freight service market. The present study identifies the characteristics of regular freight service users to seek competitiveness enhancement measures specific to regular freight services. Research design, data, and methodology - IPA is a comparative analysis of the relative importance of and satisfaction with each attribute simultaneously. This study used IPA because it facilitates the process of analyzing importance and performance, deriving implications and a visual understanding of results. To enhance the competitiveness of regular freight services, this study surveyed its current users regarding the importance of the regular freight service factors. A total of 200 copies of a questionnaire were circulated and 190 copies were returned. In addition to demographics, respondents answered questions about the importance of and satisfaction with services on a 5-point Likert scale. Excluding 3 inappropriate copies, 187 out of 190 copies were analyzed. PASW Statistics 18 was used for statistical analysis. A total of 20 question items were selected for the service factors presented in the questionnaire based on the 1st pilot survey and previous studies. Results - According to the IPA performed to compare the importance of and satisfaction with service factors, both importance and satisfaction are high in the 1st quadrant, which involves the economic advantage of using regular freight services, quick arrival at destinations, weight freight handling, and less time constraints on freight receipt/dispatch. This area requires continuous management. Satisfaction is higher than importance in the 2nd quadrant, which involves the adequacy of freight, cost savings over ordinary courier services, notification on freight arrival, and freight tracking information. This area requires intensive investment and management. Satisfaction is lower than importance in the 3rd quadrant, involving the credit card payment system, courier delivery service, distance to freight handling sites, easy access to freight handling sites, and prompt problem solving. This area requires further intensive management. Both importance and satisfaction are low in the 4th quadrant, involving the availability of collection service, storage space at freight handling sites, kindness of collection/delivery staff, kindness of outlet staff, and easy delivery checks. This area is a set of variables should be excluded from priority control targets. Conclusions - Based on the IPA, service factors that need priority controls because of high importance and low satisfaction include the credit card payment system, delivery service, distance to freight handling sites, easy access to freight handling sites, and prompt problem solving. The findings need to be applied to future marketing strategies for regular freight services and for developing competitiveness enhancement programs.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.421-444
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• 2001

최근 데이터 마이닝 기법이 주목받고 있는 이유 중의 가장 큰 이유는 자사가 보유하고 있는 고객의 특성을 파악함으로써 기존의 고객을 효과적으로 유지·관리할 수 있도록 지원하기 때문이다. 특히 고객 보유율 5% 신장이 수익률 120% 증대를 가져오는 것으로 보고되고 있는 신용카드 업계에서는 신규고객을 확보하는 것 만큼 기존 고객을 유지·관리하는 것이 중요하다. 특히, 신용카드를 발급 받고 거의 사용하지 않은 고객이나 쉽게 이탈하는 고객을 판별하는 것은 신용카드사의 입장에서는 비용절감 차원에서 매우 중요하다. 그러나 아직까지 어떠한 속성을 보유하고 있는 고객이 쉽게 이탈하는지를 판별할 수 있는 연구는 거의 진행되지 않았다. 이에 본 인구에서는 데이터마이닝 기법 중 널리 알려진 인공신경망, 로지스틱 회귀분석, C5.0 방법을 이용하여 신용카드 시장에서의 고객현황에 대하여 분석하고자 한다. 이를 위하여 본 연구에서는 모 신용카드사의 최근 4년간 (97넌 3월 이후) 가입고객 및 이탈고객을 대상으로 실증분석을 실시하였다. 분석결과 신용카드 시장에서 카드를 지속적으로 보유하고 있는 고객과 이탈하는 고객을 구분하는 속성이 존재함을 발견하였고, 이를 바탕으로 신용카드사가 수립해야 할 마케팅 전략을 제시하였다.

• 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 Distribution Science
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• v.10 no.8
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• pp.25-34
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• 2012

Understanding customer' lifestyles important for banks because it will guide in determining marketing policies, such as services, pricing, service delivery and promotion decisions. From the customer' lifestyle, banks will know what kind of customers' attitudes, interests and opinions, so they also will understand what the costumer' needs and what services needed by them. For Islamic banks, customers understanding are important because, nowadays, the competition of the banks is not only with other Islamic banks but also with the well-established conventional banks offering Islamic products or services The aims of this research paper are to describe what factors underline the customer's lifestyle of both Islamic and conventional bank, to segment the bank customers based on their lifestyles and investigate the profile of each segments, to compare the characteristics of the segments, and to identify marketing policies based on the characteristics. The population of the study is banking customers in Indonesia, in which the researchers have used judgment sampling as sample selection. There were 186 customers of Islamic banks and 244 customers of conventional bank as respondents in this study. Statistical methods employed were exploratory factor analysis and cluster analysis. The finding of the study shows that there are twelve factor underlining the customers' lifestyle, namely: factor of fashion conscious, internet usage, sports spectator, financial and technology optimism, price sensitivity, independent, compulsive housekeeper, new brand tryer community activities, opinion leader, credit usage, and homebody. In addition, for Islamic banking, there are two market segments, namely fashionable-independent and innovative-social segment. Based on the lifestyle characteristics, the first segment has higher level in factor of fashion conscious, homebody, independent, optimism and price conscious, which is therefore called fashionable-independent segment. On the other hand, the second cluster has higher level in factor of new brand tryer, community minded, sport spectator, credit user, internet usage, opinion leader, and compulsive housekeeper, which is therefore called the innovative-social segment. Furthermore, for conventional banking, there are also two segments, namely persuasive-optimistic and sensitive-independent segment. The first segment has higher level on some factors, namely: opinion leader, optimism, internet usage rate, credit usage level, sport spectator, and new brand tryer. On the other hand, the second cluster is characterized by higher level in factor of price conscious, confidence, community minded, homebody, fashion conscious, and compulsive housekeeper. Managerial implications for the management of Islamic banks could be identified in this study as follows. Firstly, the twelve lifestyle factors of this study could be an alternative view in observe Islamic banking customers. The domination of both the fashionable conscious and the internet usage factor show that the aspects are quite instrumental in perceiving the customer' lifestyles, in which reflects the importance of these two aspects to customers. Secondly, in serving their customers, Islamic banks need to understand the customer lifestyle, in which the lifestyle segments found in this study provide a guide of how their needs were reflected. Finally, by understanding the segments and the characteristics each segment of the conventional banks, Islamic banks could adjust their marketing strategies differently from the conventional banks.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.59-87
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• 2014

In MIS field, the researches on payment services are focused on adoption factors of payment service using behavior theories such as TRA(Theory of Reasoned Action), TAM(Technology Acceptance Model), and TPB (Theory of Planned Behavior). The previous researches presented various adoption factors according to types of payment service, nations, culture and so on even though adoption factors of identical payment service were presented differently by researchers. The payment service industry relatively has strong path dependency to the existing payment methods so that the research results on the identical payment service are different due to payment culture of nation. This paper aims to suggest a successful adoption factor of noble payment service regardless of nation's culture and characteristics of payment and prove it. In previous researches, common adoption factors of payment service are convenience, ease of use, security, convenience, speed etc. But real cases prove the fact that adoption factors that the previous researches present are not always critical to success to penetrate a market. For example, PayByPhone, NFC based parking payment service, successfully has penetrated to early market and grown. In contrast, Google Wallet service failed to be adopted to users despite NFC based payment method which provides convenience, security, ease of use. As shown in upper case, there remains an unexplained aspect. Therefore, the present research question emerged from the question: "What is the more essential and fundamental factor that should takes precedence over factors such as provides convenience, security, ease of use for successful penetration to market". With these cases, this paper analyzes four cases predicted on the following hypothesis and demonstrates it. "To successfully penetrate a market and sustainably grow, new payment service should find non-customer of the existing payment service and provide noble payment method so that they can use payment method". We give plausible explanations for the hypothesis using multiple case studies. Diners club, Danal, PayPal, Square were selected as a typical and successful cases in each category of payment service. The discussion on cases is primarily non-customer analysis that noble payment service targets on to find the most crucial factor in the early market, we does not attempt to consider factors for business growth. We clarified three-tier non-customer of the payment method that new payment service targets on and elaborated how new payment service satisfy them. In case of credit card, this payment service target first tier of non-customer who can't pay for because they don't have any cash temporarily but they have regular income. So credit card provides an opportunity which they can do economic activities by delaying the date of payment. In a result of wireless phone payment's case study, this service targets on second of non-customer who can't use online payment because they concern about security or have to take a complex process and learn how to use online payment method. Therefore, wireless phone payment provides very convenient payment method. Especially, it made group of young pay for a little money without a credit card. Case study result of PayPal, online payment service, shows that it targets on second tier of non-customer who reject to use online payment service because of concern about sensitive information leaks such as passwords and credit card details. Accordingly, PayPal service allows users to pay online without a provision of sensitive information. Final Square case result, Mobile POS -based payment service, also shows that it targets on second tier of non-customer who can't individually transact offline because of cash's shortness. Hence, Square provides dongle which function as POS by putting dongle in earphone terminal. As a result, four cases made non-customer their customer so that they could penetrate early market and had been extended their market share. Consequently, all cases supported the hypothesis and it is highly probable according to 'analytic generation' that case study methodology suggests. We present for judging the quality of research designs the following. Construct validity, internal validity, external validity, reliability are common to all social science methods, these have been summarized in numerous textbooks(Yin, 2014). In case study methodology, these also have served as a framework for assessing a large group of case studies (Gibbert, Ruigrok & Wicki, 2008). Construct validity is to identify correct operational measures for the concepts being studied. To satisfy construct validity, we use multiple sources of evidence such as the academic journals, magazine and articles etc. Internal validity is to seek to establish a causal relationship, whereby certain conditions are believed to lead to other conditions, as distinguished from spurious relationships. To satisfy internal validity, we do explanation building through four cases analysis. External validity is to define the domain to which a study's findings can be generalized. To satisfy this, replication logic in multiple case studies is used. Reliability is to demonstrate that the operations of a study -such as the data collection procedures- can be repeated, with the same results. To satisfy this, we use case study protocol. In Korea, the competition among stakeholders over mobile payment industry is intensifying. Not only main three Telecom Companies but also Smartphone companies and service provider like KakaoTalk announced that they would enter into mobile payment industry. Mobile payment industry is getting competitive. But it doesn't still have momentum effect notwithstanding positive presumptions that will grow very fast. Mobile payment services are categorized into various technology based payment service such as IC mobile card and Application payment service of cloud based, NFC, sound wave, BLE(Bluetooth Low Energy), Biometric recognition technology etc. Especially, mobile payment service is discontinuous innovations that users should change their behavior and noble infrastructure should be installed. These require users to learn how to use it and cause infra-installation cost to shopkeepers. Additionally, payment industry has the strong path dependency. In spite of these obstacles, mobile payment service which should provide dramatically improved value as a products and service of discontinuous innovations is focusing on convenience and security, convenience and so on. We suggest the following to success mobile payment service. First, non-customers of the existing payment service need to be identified. Second, needs of them should be taken. Then, noble payment service provides non-customer who can't pay by the previous payment method to payment method. In conclusion, mobile payment service can create new market and will result in extension of payment market.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.107-120
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• 2012

This study is conducted so as to understand actual condition of financial difficulties confronted by construction companies in the recession of real estate market which has been continued since the financial crisis started from USA in the second half of 2008, and provide fundamental data for the establishment of policy direction. Compared with this actual condition survey with a 2008 investigation, it seems that the practice of financial institutions or credit evaluation relating parts among sections, which were pointed as problems in such investigation, are resolved to some extent. It seems that there are many causes to aggravate financial conditions as pointed at this time and such causes are related to self-problems, which are inherent to the construction business, such as the smooth settlement of construction payment, the securement of new construction projects, the limitation according to the risk inherent to the construction business, and the industry vision, etc.

• Korea Real Estate Review
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• v.28 no.1
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• pp.65-77
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• 2018

This paper analyzes the redemption risk of renters by estimating the LTV and CoLTV with finance market big data (individual credit information) and housing market big data (actual housing transaction data). The analysis showed that when using LTV, the redemption risk was higher in the case of the monthly renter than of the chonsei renter. On the other hand, when using CoLTV, the chonsei renter had a higher redemption risk than the monthly renter. This implies that there is a need to activate a guarantee system, such as risk management using the CoLTV index and the chonsei deposit return guarantee because it is possible for renters to experience losses on their chonsei deposits due to the higher redemption risk. Another implication is that the risk manager should consider the individual characteristics of renters because of the different effects of the redemption risk stemming from the characteristics of the rental contract and the personal characteristics of the renters. CoLTV was just a concept until this study calculated it using housing big data and actual housing transaction information. It helps identify the redemption risk through the characteristics of renters and their contracts.