• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.510-521
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• 2020

Recently, transparency in accounting for medical institutions has been emphasized. However, due to the current system problems and structural limitations, there is a lack of diagnosis on the financial status of domestic hospitals. This study is based on the financial statements per 100 beds of 374 including domestic hospital level to tertiary hospital, and analyzed the Free Cash Flow(FCF) by hospital size from the perspective of Free Cash Flow Hypothesis. After deriving Operating Cash Flow(OCF) through the profit or loss statement of medical institutions, FCFs were analyzed through the prior and current financial statements and OCFs, and the correlation between financial variables was confirmed. According to the analysis, first, hospitals with 160 to 299 beds and 300 beds or more have relatively high FCFs. Second, certified tertiary hospitals, hospitals with less than 160 beds, and general hospitals have negative(-) FCFs. Thus, there's a need to narrow the FCF gap based on the size of the hospital, maintaining an appropriate level of FCF. This study is meaningful in that it was the first FCF analysis based on hospital size. This study is also expected to offer an informative resources in setting differentiated strategies according to the size of medical institutions when establishing new accounting policies in the future.

• Korea Journal of Hospital Management
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• v.26 no.2
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• pp.17-26
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• 2021

Purposes: This study aims to identify factors affecting dental university hospitals' profitability and understand recent their business condition. Methodology: Data from 2016 to 2019 was collected from financial statement, public open data in 8 dental university hospitals. For the study, multiple regression test with stepwise selection was applied. Findings: First of all, 9 out of 19 independent variables were selected by stepwise selection. As a result of multiple regression test with selected independent variables and the dependent variable(operating profit margin ratio), the factors affecting hospitals' profitability were the number of dental unit chair, hospital location, debt ratio, total capital turnover ratio, employment cost rate, material cost rate, management expense rate, the number of patient per a dentist. Practical Implication: To improve dental university hospitals' profitability, hospitals specifically analysis and manage their cost such as employment, material and management cost and seek effectiveness by managing the proper number of patient per a dentist.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.190-198
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• 2007

This study is to analysis the application statue of account and non-account information of the tax investigators, who are charging significant roles in the decision making process of the tax investigation and to verify whether work factors, regarding work performance, affect on the application of the taxation discretion. Following to verified results of the study, tax investigators apply the income statement most frequently and significantly consider the financial statement with annexed specification from the data to expedite an efficient tax investigation. In a selection of non-account information, work group preferentially considers the disorder of job performance. The analysis of primary factor embodies that the professionalism, regarding legal or institutional work performance, and the working environment intimately effect on the tax discretion application.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.597-606
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• 2015

Technology is one of important factors to start-up. Researchers or engineers have led to make start-up, and research based company is one type of technology-based start-up. Technology holding company has made to encourage start-up and support research based company. Research based company was introduced in 2005 according to the Korean related law. In 2014, the number of technology holding companies of university is up to 39, but technology holding company of research institute is only one called ETRI Holdings. ETRI Holdings is a technology holding company to promote technology commercialization that established by ETRI in 2010. This study analysed the financial statements of ETRI Holdings for 5 years, and grasped the status of ETRI Holdings and 15 invested companies, research based companies. According to analysis ETRI Holdings played a role as technology holding company that invested in research based company, but had no virtual circle model until now. Also improvement directions for the management of technology holding company is suggested in this paper based on the analysis of financial statement.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.90-97
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• 2016

Since Korean construction firms have steadily advanced into the international market, small and medium construction companies (SMCCs) have also advanced in such market. SMCCs's recent trend have clearly shown the changes of contract types from single subcontractor projects to multiple general contracting projects. However, among those multiple projects performed by SMCCs, 1 out of 3 projects were deficit projects that impact the overall pe rformance of the firm. To increase such performance, risk management for in international construction must be managed at the enterprise level for SMCCs. This research aims to create a multiple project management model for SMCCS that employs the concept of acceptable risk to assess the limit risk level for corporation to acceptable. Using the accumulated data from previous survey and International Construction Association of Korea (ICAK), integrated risk of each firm and their profitability of each project are analyzed. Through the analysis, each firm's acceptable risk level is derived. Through the two research steps, acceptable risk algorithm was developed based on corporate integrated risk and profit correlation. To prove the acceptable algorithm relevance, financial statement analysis of 3 corporation was derived that level of acceptable risk and financial statement were available. Through the approach, this research allows the firms to analyze the firm's capability and find projects that suits the firm's situation and capability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.115-124
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• 2022

Unlike the semi-public system of city buses, Seoul's townbus are operated on a private operating system, which is poor condition to the changes in the environment. Sales decreased due to a decrease in the number of passengers due to COVID-19 and a demand for conversion due to the advent of competitive transportation methods, and the financial support of Seoul Metropolitan Government is continuously increasing. In this study, to analyze the characteristics of townbus operated by a private operating system, the townbus sales and surplus companies were analyzed by what factors were affected. For the analysis data, townbus financial statements of Seoul in 2018 were used, and townbus sales and surplus companies were applied as dependent variables, and townbus operation system, satisfaction survey, humanities and social variables, and subway and public bicycle characteristics were applied as independent variables. As a result of the analysis, the sales is affected by operating hours per vehicle, in-vehicle safety, the number of households, the number of elderly people, and public bicycle variables, and surplus companies are affected by in-vehicle safety, reliability, and public bicycle variables. In particular, public bicycles, a competitive means of transportation, had an impact on industry sales, and the townbus business environment is expected to become more difficult as time goes by. The industry is seeking self-rescue measures, and Seoul is required to strengthen financial support so that townbus can operate stably.

• 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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.278-282
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• 2001

The discovery of tacit knowledge from domain experts is one of the most exciting challenges in today\`s knowledge management. The nature of decision knowledge in determining the quality a firm\`s short-term liquidity is full of abstraction, ambiguity, and incompleteness, and presents a typical tacit knowledge extraction problem. In dealing with knowledge discovery of this nature, we propose a scheme that integrates both knowledge elicitation and knowledge discovery in the knowledge engineering processes. The knowledge elicitation component applies the Verbal Protocol Analysis to establish industrial cases as the basic knowledge data set. The knowledge discovery component then applies fuzzy clustering to the data set to build a fuzzy knowledge based system, which consists of a set of fuzzy rules representing the decision knowledge, and membership functions of each decision factor for verifying linguistic expression in the rules. The experimental results confirm that the proposed scheme can effectively discover the expert\`s tacit knowledge, and works as a feedback mechanism for human experts to fine-tune the conversion processes of converting tacit knowledge into implicit knowledge.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.51
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• pp.263-283
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• 2011

There are two typical international rules in issuing guarantee for obligations of party which is responsible to provide some duties such as services, construction, plants, loan repayment, etc. The two internationally recognized rules are currently ISP98 and URDG758. ISP98 was firstly introduced in 1998 for American banks to issue standby letter of credit domestic and overseas for the area where UCP does not cover. URDG was introduced first in 1991 in the name of URDG458 but it has not been widely used and therefore new URDG named URDG758 came out in 2010 to accommodate more standard guarantee practice. At the face of these two prevailing international rules, the users are sometimes confused which rule would be more suitable for their individual transaction. This led us to conduct a comparative analysis on these two rules. Our study suggests that URDG758 is more adequate for construction, ship-building and plants-supply obligations whilst ISP98 is for financial obligations. Also attentions are required when issues such as counter guarantee, governing rule, presentation period, document examination period and default statement exist. This is because ISP98 and URDG758 have different view points.

• Management & Information Systems Review
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• v.37 no.2
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• pp.259-281
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• 2018

Advocates of mandatory IFRS adoption claim that IFRS increase financial statement comparability, which in turn leads to greater cross-border investment(Securities and Exchange Commision, 2008). The notion is that improved financial statement comparability reduces the information acquisition costs of global investors and thereby increase their investment in foreign firms. The purpose of this study is to examine this assertion by examining whether the K-IFRS adoption rusults in improved comparability that leads to increased investment by foreign investment. We also examined whether the relation between comparability and foreign investment has strengthen after adoption of K-IFRS. To achieve the purpose of our study, we measure Korean firms comparability using stock price model, stock return model and cash flow from operation model by Barth et al.(2012). We use both foreign ownership in the end of year and average during the year for dependent variables were to reduce bias. We test our hypothesis using 1,817 firm-year observation of KOSPI firms during the period of our analysis, 2011-2015. Consistent with our hypothesis, we find K-IFRS adoption results in a greater increase in foreign investment in firms with high comparability firms. This result indicate that the adoption of K-IFRS intends to achieve the international accounting convergence as stated in the roadmap and to reduce the Korea Discount.