• The Journal of Information Systems
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• v.14 no.1
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• pp.107-124
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• 2005

ERP systems are comprehensive sorfware packages that seek to integrate the complete range of lbusiness processes and functions in order to present a heuristic perspectives of a firm from a single information and information technlogy architecture. The ERP systems have delicate internal controls with built-in devices. It is known that the delicate internal controls help to enhance the accounting transparency. We empirically investigate the relationship between the ERP systems inplementations and an accounting transparency. In order to measure the accounting transparency differences, we compare the ERP systems implementation firms with firms which did not implement the ERP systems by 6 financial ratios (accruals, net profit margin, operation cash folo to sales, total debt to equity, accounts receivable changes, assets quality). Data are collecte from 135 firms implemented the ERP systems and 135 firms non-implemented the systems (the firms listed in the Korea Stock Exchange). We analyze financial statements from 270 firms for the period 2001-2003 to ezamine the 6 financial ratios differences. The results of 810 firms analyses over the 3-year period indicate that the ERP systems implementation firms show the statistically significant differences in the accrual ratio, the net profit margin ratio, operating cash flow to sales ratio, and total debt to equity ratio from the ERP systems non-implementation firms. But there is statistically no differences between the two groups for accounts receivable changes to sales ratio and assets quality.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.81-90
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• 2020

This study investigates the nexus between the level of Corporate Social Responsibility Disclosures (CSRD) and Risk of Bankruptcy of companies that are listing in the Stock Exchanges of Vietnam. To investigate that relationship, this study collected secondary data from annual audited financial statements from 2014 to 2018 of listing companies. Applying two different regression models with two dependent variables and six independent and control variables, we find out that Vietnamese firms with higher level of CSRD performance can rapidly reduce their risk of bankruptcy. This phenomenon happens in the current year and in the coming years in all firms in the research sample. This result may be that the disclosures of social responsibility information can bring financial and non-financial benefits to the firms. In addition, the results also point out that there is a difference in risk of bankruptcy between the group of companies, which discloses and the one which does not disclose corporate social responsibility on their annual reports. This might be from the effects of various factors such as business size, financial leverage, market to book ratio, return on assets, cash flow from operations, etc. Our research results can be applied to other firms in Vietnam and in other similar jurisdictions.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.31-40
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• 2020

This study investigates whether other comprehensive income (OCI) reported in the statement of comprehensive income (one of the main financial statements after the adoption of K-IFRS) predicts a firm's future performance. Using the quarterly data of Korean listed companies, we examine the association between OCI estimates and future earnings. First of all, we find that OCI is positively associated with earnings in both 1- and 2-quarter ahead, supporting the predictive value of OCI. When we break down OCI into its individual components, our results suggest that the net unrealized gains/losses on available-for-sale (AFS) investment securities are positively associated with future earnings, while the other components (e.g., net unrealized gains/losses on valuation of cash flow hedge derivatives) present insignificant results. In addition, we investigate whether the reliability in OCI estimates enhances the predictive value of OCI to predict future performance. We find that the predictive ability of OCI, in particular the net unrealized gains/losses on available-for-sale (AFS) investment securities, becomes more pronounced when firms are audited by the Big 4 audit firms. Overall, our study suggests that information content embedded in OCI can provide decision-useful information that is helpful for the prediction of future firm performance.

• Asia-Pacific Journal of Business
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• v.12 no.4
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• pp.253-270
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• 2021

Purpose - The main purpose of this study is to measure and evaluate the level of national liabilities that Korea's national finances can afford. Specifically, the concepts of national debt and national liability are clarified, and the appropriate level of national liabilities is measured in terms of short-term fiscal crisis, mid-to-long-term fiscal crisis, and GDP. Based on these measurements of fiscal crisis, this study would like to propose national fiscal management plans. Design/methodology/approach - In order to clearly recognize the difference between the national debt and the national liability, this study examines the data from 2013 to 2020. In addition, this study uses data from the national financial statements from 2013 to 2018 to measure the appropriate level of national liabilities in terms of fiscal crisis management. Findings - Short-term fiscal crises, measured by current ratios, will not occur. Nevertheless, in view of the cash flow compensation ratio, the short-term bankruptcy of the national finances of Korea depends on the re-borrowing of short-term borrowings and current and long-term borrowings. In addition, in order to manage the mid-to long-term financial crisis, it is necessary to pay attention to the liability growth rate rather than the liability size. Research implications or Originality - While previous studies focused on the appropriate level of national debt, this study was differentiated as a study focused on the level of national liability coverage. It is expected that the results of this study will be used to manage the national fiscal soundness.

• Korea Journal of Hospital Management
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• v.6 no.1
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• pp.1-17
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• 2001

According to the increase of the proportion of aged people, the medical demand for a senile chronic disease has been increased; therefore, aged people call for a geriatric hospital for special geriatric medical service. The main purpose of this study was to analyze the general characteristics and financial status of geriatric hospitals. For the study, a questionnaire was designed and sent to the geriatric hospitals to fill out the patient statistics, number of headcount by department, etc. to find out the stability, profitability, activity and so on financial statements of the hospitals were analyzed. The major findings of this study were as belows. 1. The ratio of the medical expenses to the revenue of the geriatric hospitals is much lower than acute care hospitals. But the probability of bankruptcy is higher due to the high ratio of the liabilities therefore it is required to stabilize the financial position by donating more money. 2. Government budget for the elderly people is not enough. To support the geriatric hospitals by going subsides, government should increase the budget. 3. Portion's of the patient of the geriatric hospitals are government support patient. Since the government doesn't pay the medical charges quickly, geriatric hospitals have a serious cash flow problem. Therefore, it is required that government is to prepay the bill. 4. Since geriatric hospitals treat elderly patient and most patients are government support patients, geriatric hospitals can be said to operate under the strict. 5. When we introduce the daily medical charge, the self-liability will be reduced on approximately 50% of current. This affection will bring a huge progressing financial structure to the medical profit of the geriatric hospital, and also patient family will feel less economical burden.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.33-58
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• 2004

This paper tests Van Home's hypothesis, a negative correlation between degrees of operating leverage(DOL) and financial leverage(DFL). For an empirical analysis, we extract information from financial statements of manufacturing companies listed in the Korea Stock Exchange. Data extend from 1980 to 2001. The DOL continued to increase until 1997, but decreased dramatically after the IMF financial crisis. However, the DOL has been at a higher level than companies of other countries such as USA and Japan. The DFL has been maintained at a much higher level, as expected. The empirical results indicate a positive correlation between the DOL and the DFL, which is inconsistent with the VanHorne's hypothesis. To further investigate, we divide the whole sample into subgroups according to such management elements as asset size, level of leverages, earnings and cash flow. The results for sub-samples are different from those of whole sample. This indicates we need to incorporate specific managerial factors in order to correctly explain financial decision processes.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.