• Journal of the Korean Society for information Management
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• v.34 no.2
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• pp.7-26
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• 2017

There has been growing interest in the methods for measuring the credits of individual authors in multi-authored research papers in response to the increase of research collaboration. Having a good understanding for academic norms of individual discipline is essential to measure author credit effectively. However, many Korean universities do not consider different norms for determining the order of authors across disciplines. Rather, they tend to use a standardized method to assess the credits of authors in multi-authored papers. Therefore, this study presented some problems of applying a standardized method to measure author credits in multi-authored papers in economics. The findings of this study confirmed the frequent use of alphabetical author order in economics papers; however, many university guidelines for research evaluation do not take account the alphabetical authorship in measuring the credits of authors. The authors suggest the needs for (1) establishment of a clear definition for primary authors, (2) flexibility in assessment methods for author credit, and (3) empirical research on author credit.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1017-1028
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• 2011

When it is not easy to decide the credit scoring for some loan applicants, credit evaluation is postponded and reserve to ask a specialist for further evaluation of undecided applicants. This undecided inference is one of problems that happen to most statistical models including the biostatistics and sportal statistics as well as credit evaluation area. In this work, the undecided inference is regarded as a missing data mechanism under the assumption of MNAR, and use the bivariate probit model which is one of sample selection models. Two undecided inference methods are proposed: one is to make use of characteristic variables to represent the state for decided applicants, and the other is that more accurate and additional informations are collected and apply these new variables. With an illustrated example, misclassification error rates for undecided and overall applicants are obtainded and compared according to various characteristic variables, undecided intervals, and thresholds. It is found that misclassification error rates could be reduced when the undecided interval is increased and more accurate information is put to model, since more accurate situation of decided applications are reflected in the bivariate probit model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.1044-1051
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• 2002

This paper proposes a two-phase mathematical programming approach by considering classification gap to solve the proposed credit scoring problem so as to complement any theoretical shortcomings. Specifically, by using the linear programming (LP) approach, phase 1 is to make the associated decisions such as issuing grant of credit or denial of credit to applicants. or to seek any additional information before making the final decision. Phase 2 is to find a cut-off value, which minimizes any misclassification penalty (cost) to be incurred due to granting credit to 'bad' loan applicant or denying credit to 'good' loan applicant by using the mixed-integer programming (MIP) approach. This approach is expected to and appropriate classification scores and a cut-off value with respect to deviation and misclassification cost, respectively. Statistical discriminant analysis methods have been commonly considered to deal with classification problems for credit scoring. In recent years, much theoretical research has focused on the application of mathematical programming techniques to the discriminant problems. It has been reported that mathematical programming techniques could outperform statistical discriminant techniques in some applications, while mathematical programming techniques may suffer from some theoretical shortcomings. The performance of the proposed two-phase approach is evaluated in this paper with line data and loan applicants data, by comparing with three other approaches including Fisher's linear discriminant function, logistic regression and some other existing mathematical programming approaches, which are considered as the performance benchmarks. The evaluation results show that the proposed two-phase mathematical programming approach outperforms the aforementioned statistical approaches. In some cases, two-phase mathematical programming approach marginally outperforms both the statistical approaches and the other existing mathematical programming approaches.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.175-182
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• 2019

The purpose of this study is to test whether credit rating agencies highly evaluate the credit ratings of corporate bonds based upon management participation and ownership share by family governance in ownership structure forms. The samples of this study for empirical analysis were 1,449 non-financial companies listed on Korean Exchange from 2011 to 2016, over whose firm/year data this study conducted regression analysis. The results of empirical analysis in this study are as follows. First, family businesses had positive effects on the evaluation of corporate credit ratings. Second, if the ownership share of family businesses was higher, corporate credit ratings were higher. This result means that high ownership share in family businesses has very positive effects on the credit ratings of related businesses. It is meaningful that this study tested the effect that family businesses can alleviate agency problems and reduce information asymmetry. Furthermore, it is also academically meaningful that this study can contribute to future studies on the role of ownership structure.

• Korea Trade Review
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• v.48 no.3
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• pp.89-106
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• 2023

This study is to investigate the problem of credit rating by Korea Trade Insurance Corporation(KSURE) which evaluates overseas buyers in a state of capital impairment as G-grade regardless of the cause of capital impairment. This study classifies capital impairment into two types: deficit-type capital impairment due to accumulated operating losses and surplus-type capital impairment due to shareholder return policies such as dividends and treasury stock buybacks. It is proposed to improve the credit evaluation method on companies with surplus capital impairment from a formal review to a substantive review. This study is expected to improve credit rating of KSURE on overseas buyers for better support of trade credit insurance for exporters.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.237-248
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• 2009

The probability of default on the credit evaluation study is represented as a linear combination of two distributions of default and non-default, and the distribution of the probability of default are generally known in most cases. Except the well-known Kolmogorov-Smirnov statistic for testing the identity of two distribution, Kuiper, Cramer-Von Mises, Anderson-Darling, and Watson test statistics are introduced in this work. Under the assumption that the population distribution is known, modified Cramer-Von Mises, Anderson-Darling, and Watson statistics are proposed. Based on score data generated from various probability density functions of the probability of default, the modified test statistics are discussed and compared.

• Asian Journal of Business Environment
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• v.8 no.1
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• pp.23-29
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• 2018

Purpose - The purpose of this research is to make a comparative assessment of People Credit Funds (PCFs) ranking in Vietnam between the Circular No. 42/2016/TT-NHNN dated December 20, 2016 with the Decision No. 14/2007/QD-NHNN dated 09/4/2007 issued by the Governor of the State Bank. Research design, data, and methodology - This study is mainly based on the Circular No. 42/2016/TT-NHNN dated December 20, 2016 and the Decision No. 14/2007/QD-NHNN dated 09/4/2007 issued by the Governor of the State Bank on PCFs ranking. Results - The study paper has shown positive changes in PCFs ranking in Vietnam in accordance with the Circular No. 42/2016/TT-NHNN, such as increasing Capital Adequacy Ratio (CAR), maintaining CAR, improving assets quality, developing indicators of governance, management and control capability. These changes have implications for the development and efficient performance of PCFs in Vietnam. Conclusions - The classification and evaluation of PCFs will contribute to its healthy development. These finding support PCFs to understand more about rating methodology, significance of rating system and the importance of improving their rating. PCFs in Vietnam desire to develop their business effectively, they need to understand exactly and comply fully with regulations related to their field of operations.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.751-756
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• 2024

The accuracy of the model and the explanation of the results are important factors that should be considered simultaneously Recently, applications of explainable artificial intelligence are increasing, and it is especially widely applied in the financial field where interpretation of results is important. In this paper, we compare the performance of open API credit evaluation data using various machine learning techniques. In addition, existing financial logic is verified through explainable artificial intelligence technologies, SHAP and LIME. Accordingly, it is expected to demonstrate the applicability of machine learning in the financial market.

• Journal of Korean Academy of Nursing Administration
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• v.12 no.3
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• pp.365-372
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• 2006

Purpose: OSCE, Objective Structured Clinical Examination, is a good way to evaluate clinical skills of nursing students. To do this, we need modules, evaluators, persons to run the examination, as well as models and standardized patients if necessary. Author coached nursing students to develop modules and ran the examination by themselves. Method: 24 third-year and 4 first-year students volunteered; third-year students developed 5 modules, and organized and ran the examination. First-year students played patient role. 60 2nd-year students participated as examinees. Modules were duplicated to finish examination in a given time. The relationship between OSCE score, conventional clinical evaluation score and credit of students was compared. Effect of module duplication on score was tested. And responses of examinees were collected. Results: There was no correlation between OSCE and conventional clinical evaluation score (r=0.07), and credit (r=0.27), And there was no difference of OSCE score between duplicated modules $(53.77{\pm}7.61$ vs $55.33\pm7.74).$ Response of examinees to OSCE was favorable. Examinee did not expressed resistance for the evaluation by OSCE developed and ran by students. Conclusion: Nursing students successfully developed and ran OSCE, which was accepted favorably by examinees. Student-developed OSCE may play a role in evaluation of clinical performance.

• Korean Journal of Comparative Education
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• v.28 no.4
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• pp.23-49
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• 2018

This study aims to consider the subject completion system based on high school credit system in State of California. To achieve research aims, this study analyzed a characteristics of curriculum of credit system in US, subject completion system based on high school credit system in State of California. Based on analysis results, this study search implications for implementing high school credit system in korea. For stable implement of High School Credit System, This study proposed that 'review of relevance of graduation requirement credit', 'effort in Metropolitan and Provincial office of education and School for establishing meaningful subject', 'taking follow-up action in accordance with setting of subject completion standard', 'qualitative improvement of student's subject selection', 'revitalization of career coaching for meaningful subject selection', 'setting of level on connectivity between high school curriculum and university entrance examination', 'a study on the in-depth follow-up about high school curriculum based credit system in foreign country'.