• Journal of Digital Convergence
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• v.12 no.7
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• pp.315-325
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• 2014

This study is investigates decisive factors impacting business profits of regional medical centers by utilizing their environmental characteristics to provide useful basic data to seek for a method to establish financial soundness and profitability. The research objects are medical treatment record and management indicators of 31 regional medical centers for the past three years from 2010 through 2012. The method of analysis are ANOVA and Multiple Regression Analysis. The results revealed the debt and management ratio in the profit rate of total medical liabilities and net worth, current balance in the medical profit on medical revenue, and hospital bed turnover rate, emergency hospitalization rate, rate of labor cost, and rate of material cost in the business profits as the decisive factors. It is recommended to identify financial feedback and establish diversified management strategies through accurate management analysis to secure financial soundness and profitability in medical centers.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of Korean Academy of Nursing
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• v.22 no.4
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• pp.491-505
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• 1992

The purpose of this research was to understand the structure of the lived experience of parents of a child terminally ill with cancer The research question was “What is the structure of the experience of parents of a child terminally ill with cancer\ulcorner” The sample consisted of 17 parents of children admitted to the cancer units of two university hospitals in Seoul. The unstructured interviews were carried out from October 10, 1991 through January 10, 1992. They were audio-recorded and analysed using Van Kaam's method. Parents ascribed the cause of the cancer to the mother's emotional imbalance during pregnancy, the mother's stress, failure to observe religious rites, food, the parent's sin, misfortune and pollution. The theme clusters were tension, fear and depression experienced during pregnancy, stress that children suffer from abusive parents, failure to observe religious activites, bad luck, and sins committed during a previous life. When the child suffered a recurrence of cancer, the parents experienced negative emotions, nervousness, sorrow. depression and death. The theme clusters were feelings of despair, helplessness, regret, guilt, insecurity, emptyness and apathy. The long struggle with cancer resulted in the loss of economic security, loss of psychological and physical well being, and social withdrawal. The theme clusters were the economic burden of medical cost, giving up treatment, debt, limited medical insurance coverage and blood transfusion. The loss of psychological well being included stress, lack of support systems, inability to carry out responsibilities, lack of trust of the medical ten family breakdown, inappropriate expression of emotion and not disclosing the diagnosis to the child. Physically the parents suffered fatigue, insomnia, loss of appetite, loss of weight, dizzness, headache, psychosomatic symptoms, and increased consumption of liquor and cigarettes. Social withdrawal was manifested by taking time off from work to look after the child, decrease of outside social activities and feelings of isolation. Influences on family life were spousal conflicts, negative response of siblings, separation of the family members and economic hardship. The theme clusters were blaming a spouse for the cause of the illness and disagreements, maladjustment, lonliness, hostility and depression of siblings. The high price of medical care over the long period was a major factor influencing the life of the family. Positive experiences during the child's long illness were the strengthening of support systems and religious beliefs and financial help from social organizations. The support of one's spouse primarily helped to overcome the stress of the long illness. In addition, support was received from parents of other children with cancer and from nurses and religious leaders. The nurse, by providing empathetic support, should be a person with whom parents can express their feelings and share their experiences.

• Korean Journal of Construction Engineering and Management
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• v.12 no.3
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• pp.121-130
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• 2011

Real option values of early termination payment for selected BTO PPI projects are studied using binomial models. Two cases of early termination payments are considered; an option with the condition of private participants' default, and an option without the condition. Values vary depending upon parameter values such as revenues, costs, discount rates, debt ratio, and volatility of revenues. For selected projects, the option values without the default condition are estimated as 1%~7% of total project costs, whereas the option values with the default condition are estimated as 0%~1.89% of total project cost. When actual revenues differ from the forecasted revenues, apparently the option values deviate from the values based upon the forecasted revenues. When actual revenues fall short of the forecasted revenues, the option values increase by a large amount whereas the option values decrease by a small amount in the opposite case. This implies that the option values can be quite bigger than the values based upon the forecasted revenue especially when the revenue forecast uncertainty is large. This study is expected to play an important role in improving the early termination payment option policy of the government in PPI projects in Korea.

• Korean Journal of Construction Engineering and Management
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• v.11 no.1
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• pp.59-69
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• 2010

Although international construction market gradually takes a important position among the export industries, the previous studies about international construction entry strategy have just focussed on trend investigation or suggestion for revitalization. Moreover, in order to prepare the market uncertainty such as world financial crisis and to plan the long term strategy, specific strategy studies based on corporate level are required. Therefore, this study estimates the nine strategic index and four financial index of 31 companies that performed 1920 international projects from 1993 to 2007 and evaluate the performance as three periods by multi-regression analysis. Also, this study analyze dynamic correlation between these index and the performance considering times. this study verifies that market diversification, product diversification, localization and decrease of debt to asset ratio make a good effect on the international order as long term strategy and shows that collaborated entry with domestic corporations, alliance entry with host country's company, alliance entry with third country's company, portion of labor cost and portion of management expense differently make a influence on the performance as times. these results will be helpful for the construction companies to plan the international entry strategy reasonably and specifically.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.3870-3881
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• 2015

This study examined one of the contemporary issues on debate to identify any significant financial determinants on the cash holdings of the cheabol firms in the Korean domestic capital markets. Several important findings on the financial characteristics affecting the cash holdings were evidenced by utilizing various methodologies for statistical estimations. Financial or managerial implications with discussion were provided for the pronounced factors such as CASHFLOW, MVBV, REINVEST, and AGENCY. Assuming that the chaebol firms were overall subject to the financial constrains, they may increase or stockpile cash reserves as internal capital for future investment opportunities or repayment of existing debt, rather than external financing burdened by a high cost of capital. Given the on-going controversy on the optimal level of corporate cash holdings coupled with any foreseeable capital transfer among the associated nations through the investment vehicles such the FTAs (Free Trade Agreements) or TPP (Trans-Pacific Pacts), any empirical findings of the study may shed new light on identifying financial determinants which may significantly affect the level of cash holdings for the business conglomerates, the 'chaebol' firms, in the Korean capital markets.

• Journal of Distribution Science
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• v.12 no.8
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• pp.113-121
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• 2014

Purpose - Recently, the number of corporations that practice environmental and social responsibility, besides engaging in traditional profit-seeking activities, has been growing steadily, as interest in Corporate Social Responsibility (CSR) is increasing. Recent research on CSR practices has identified the relationship between CSR activities and corporate value as one of the main issues in this respect. Considering that donations constitute a large proportion of a company's charitable activities, we considered the extent of donation expenses as a charitable activity in order to mitigate sample selection bias. Specifically, we analyzed the impact of donation expenses on firm value, while investigating if this impact varied in response to the level of corporate governance of firms. Research design, data, and methodology - We used non-financial firms listed on the Korean Stock Exchange, having their fiscal year end in December, and the sample period was 2006-2013. For the dependent variable, Tobin's q was used as the corporate value, and for the independent variable, donations were measured as the donation-expense-to-sales ratio. Corporate governance scores, as rated by the Korea Corporate Governance Service, were used to measure corporate governance levels because they consider the overall aspects of governance, including ownership structure, the board of directors, and the audit mechanism of individual companies. To examine the impact of donations on a company in relation to the level of corporate governance, we estimated regression models using the interaction terms of the governance dummy and donation variables. Then, we further estimated the regression models of two sub-samples that were classified according to the level of corporate governance. Similar to previous studies, the study uses variables that affect firm value, such as R&D expenditure, advertising expenses, EBITDA, debt-to-equity ratio, sales growth, company age, and company size as control variables. Results - The empirical results show that firm value significantly increased in response to an increase in donation expenses. Upon including the interaction terms of governance level dummy variables and donations, the coefficients of the interaction terms show significant positive values, while those of donation variables show significant negative values. In the strong governance sub-sample, the relationship between the donation expenses and corporate value was statistically positive (+) and significant. However, in the weak governance sub-sample, the relationship between the donation expenses and corporate value was statistically insignificant and negative (-). Conclusions - The empirical results suggest that donation expenses are significantly linked to an enhanced corporate value if firms have a good corporate governance structure. However, if the corporate governance structure is weak, the same relationship is not necessarily observed. The results of this study show that if a firm has high corporate governance, CSR practices enhance the company's reputation such that it has a positive (+) relationship with corporate value. If a firm has weak corporate governance, on the other hand, CSR practices are recognized as an agency cost and do not increase corporate value.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.1-12
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• 2024

This study investigates what decisions have an impact on bank performance. A panel regression analysis was conducted using data from the financial statements of banks located in the United States from 2013 to 2022, and the effects of explanatory variables were examined through hierarchical panel regression analysis divided into financial decision-making and management decision-making. In addition, by analyzing performance separately from the creditor and shareholder perspectives (hereinafter referred to as overall) and from the shareholder perspective alone, it suggests which elements should be utilized and how to improve performance from each perspective. When a panel regression analysis was performed using only liquidity and stability, dependency on deposits and the interest coverage ratio had a statistically significant impact from the perspective of overall performance, and the debt ratio also had a statistically significant impact from the perspective of shareholder performance. When adding non-technical factors, only the labor cost ratio among non-technical factors was found to be statistically significant from the overall performance perspective, and although the non-technical factors were not statistically significant from the shareholder performance perspective, the cash ratio was found to have a statistically significant impact. Lastly, when adding technical innovation elements, the intangible asset ratio was not statistically significant from the overall performance perspective, but was significant from the shareholder performance perspective. The significance and implications of this study are that there are differences in factors that can affect the performance of overall or shareholder and that various decision-making factors can affect a bank's performance.

• Information Systems Review
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• v.20 no.4
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• pp.79-96
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• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.193-208
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• 2020

In this study, we investigate the effects of technology innovation investments and employment on credit ratings of very small start-up businesses using the data period of 2009 till 2015 test two hypotheses: asymmetric information hypothesis or competence hypothesis. We use financial and non-financial data of 51,903 observations of 12,028 small businesses from a database of a commercial bank and fixed effects panel models and two-stage instrumental variable models. We find that in the short-run small size startups show lower credit ratings than non-startups, and that both technology innovation activities and employment capability improve their credit ratings. In the long-run, technology innovation investments do not improve their credit ratings of later years while employment capability improve their credit ratings of the subsequent year. In addition, the age of startups improves their credit ratings of the current year and until the subsequent two years while employee productivity, fixed ratio and ROA positively affect their credit ratings for up to three years. However, short-term and overall debt ratios, cost of borrowings and firm-size negatively affect their credit ratings for up to three years. The results of the study on credit ratings suggest that credit rating agencies seem to consider both technology innovation activities and employment capability in the credit ratings of small start-ups as 'competence factors' rather than 'asymmetric information factors' with inefficiency and cost burdens. The results also suggest that we must find ways to reflect properly the severe asymmetric information of the early-stage start-ups, and technology innovation activities and employment capability in the credit rating formula.