• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.421-431
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• 2021

This study investigates the empirical linkages between ASEAN countries' institutional quality and financial inclusion using country data from 2008-2019. In this paper, six governance indicators from the World Governance index are used to measure the impact of institutions on financial inclusion. The PCA method's financial inclusion index is constructed from 3 indicators: penetration, access, and usage: penetration, access, and usage with six indices respectively as the number of ATMs per 1000 km², the number of bank branches per 1000 km², the number of ATMs per 100,000 people and the number of bank branches for 100,000 adults, the ratio of credit to private to GDP, and the ratio of deposit to private to GDP. Regression analysis with the Generalized Moments method shows the positive impact of institutions and other control variables like GDP per capita, inflation, bank concentration, and human development index on financial inclusion. Therefore, this study recommends that the government and policymakers in countries pursue the financial inclusion agenda to pay attention to the financial and economic indicators and institutional factors. This is because many savers, borrowers, and investors may not be protected when financial contracts are enforced or breaches occur in an environment where economic, legal, judicial, and political institutions are weak, such as in ASEAN countries.

• International Journal of Contents
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• v.10 no.4
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• pp.75-82
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• 2014

The purpose of this paper was to identify suitable variables for financial distress prediction models and to compare the accuracy of MDA and LA for early warning signals for wind energy companies in Korea. The research methods, discriminant analysis and logit analysis have been widely used. The data set consisted of 15 wind energy SMEs in KOSDAQ with financial statements in 2012 from KIS-Value. We found that five financial ratio variables were statistically significant and the accuracy of MDA was 86%, while that of LA is 100%. The importance of this study is that it demonstrates empirically that financial distress prediction models are applicable to the wind energy industry in Korea as an early warning signs of impending bankruptcy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.35-42
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• 2020

This study aims to investigate the relationship between the variables of Current Ratio (CR), Return-on-Equity (ROE), Return-on-Assets (ROA), Debt-to-Equity Ratio (DER), and Firm Size (FS) on Dividend Policy (DP) in real estate and property companies listed on the Indonesia Stock Exchange in the period 2016-2019, looking at nine real estate companies in Indonesia. The research methodology uses an explanatory analysis approach and linear regression. Based on the eligibility and homogeneity of the data, the number of sample companies selected was nine companies. The company's financial statement data derived from primary data obtained on the Indonesia Stock Exchange, such as current ratio (CR), return-on-equity (ROE), return-on-assets (ROA), debt-to-equity ratio (DER) and firm size and dividend policy variables. The data analysis procedure is first to transform financial data from the original ratio data into interval data and, then, transform it to ordinal data. Furthermore, the validity and reliability process are ignored because the data is primary. Finally, regression testing is part of the hypothesis testing stage. The results of this study showed that the CR, ROE, and firm size had no positive and significant effect on dividend policy. In contrast, DER and ROA have a positive and significant impact on dividend policy.

• The Korean Journal of Franchise Management
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• v.15 no.1
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• pp.61-78
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• 2024

Purpose: Dining out at restaurants was limited during the COVID-19 period. In order to confirm the impact of COVID-19 on the chicken market, this study selected three chicken companies, Kyochon, BBQ, and BHC, and conducted financial statement analysis and regression analysis. Research design and methodology: Each company's financial statements were divided into before and after COVID-19, and the rate of change and financial ratio for each item were calculated to see if there were any significant changes, and the impact of COVID-19 on each company's sales was identified through regression analysis. Result: As a result of the study, the increase in sales and assets of each company continued, and the influence of COVID-19 could be confirmed through regression analysis. It can be inferred that COVID-19 indeed affected the expansion of the chicken market. Conclusion: Therefore, it was confirmed through this study that COVID-19 had a significant effect on the growth of the chicken market. While individual chicken small business owners are grappling with declining sales per outlet, the decline of commercial areas, and a surge in closures, the broader chicken franchise industry is witnessing a surge in demand and business expansion prompted by the pandemic.

• Journal of Preventive Medicine and Public Health
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• v.19 no.2 s.20
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• pp.213-223
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• 1986

Ratio analysis allows a hospital to evaluate its own performance over time and to compare its performance with that of other hospitals. For this study, three types of ratio analysis were conducted based on some data on hospitals in Massachusetts. First, Key ratios influencing financial performance were identified using discriminant analysis. Second, the financial structures of the teaching and the non-teaching hospitals were compared using ratios and multiple comparison method. Third, the effects of the prospective reimbursement law of the state on financial performance were examined using ratios and paired t-test. The purpose of the law is to reduce hospital costs by setting the revenue ceiling prior to the effective budget year. The findings of this study were as follows: 1) When hospitals were divided into three groups, according to their operating income, only profitability ratios showed a consistent difference among the groups. 2) In the discriminant analysis, five ratios were selected: current ratio, operating margin, return on assets, fixed assets turnover, and inventory turnover. They are the key ratios to be monitored periodically for the purpose of evaluating the financial performance of hospitals. 3) When teaching hospitals were compared with non-teaching hospitals, acid ratio, days of cash on hand, and inventory turnover were statistically significant before the law went into effect, whereas only fixed assets turnover and inventory turnover were significant afterward. Contrary to previous studies, profitability ratios of teaching hospitals were higher than those of non-teaching hospitals, although the differences were not statistically significant. 4) When the ratios between the two periods (before and after the law) were compared, three profitability ratios (operating margin, return on assets, and return on equity) were significant for teaching hospitals, whereas three activity ratios (total assets turnover, fixed assets turnover, current assets turnover) were significant for non-teaching hospitals. Furthermore, while both total operating revenue and expenses were decreased, net operating income was increased, due to a greater decrease in total operating expenses. This shows that the law can indeed, simultaneously, achieve both a reduction in costs as well as an improvement in the financial situation of hospitals.

• Health Policy and Management
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• v.20 no.4
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• pp.114-125
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• 2010

Objectives : This study investigates the determinants of contingent workers' ratio in public health centers. Since the economic crisis in 1997, there have been many studies on contingent workers in Korea. But, previous studies have been not conducted focusing on public health center. Methods : This study used 253 public health centers, installed and operated since December 31, 2008. in Korea as units of analysis. To examine the determinants of contingent workers' ratio, this study uses Pearson correlation and multiple regression analysis. Results : The following appeared as significant variable affecting contingent workers' ratio in public health centers; degree of the local government's financial independence(p<0.001), rate of increase/decrease in ages 65 and over(p<0.001), rate of increase/decrease in basic livelihood security recipients(p<0.01) and rate of increase/decrease in registered disabled persons(p<0.01). In contrast, internal organizational environment characteristics related variables were not statistically significant. Conclusions : Contingent workers' ratio in public health center is significantly affected by financial vulnerability of the local government and increase in demand of health care services.

• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.43-51
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• 2013

The changes in business structure of domestic construction companies suggest that there is a close relationship between the volume of overseas project and a company's financial condition. Based on this assumption, this study conducts an empirical analysis on a relationship between overseas project and financial stability of a construction company. The ratio of liquidity and liability was used as liquidity index and stability index respectively. The analysis was based on quarterly time-series data between 2000 and 2010. Two models were constructed for the analysis: Model 1 was based on the liquidity ratio and the amount of domestic and overseas construction project; Model 2 was based on the debt ratio and the amount of domestic and overseas construction project. The analysis results showed that the increasing amount of overseas project facilitated short-term financing with greater liquidity, and yet it was not very effective in lowering the debt ratio. This suggests that the dramatic increase in overseas construction project, which is observed recently, is not entirely an optimistic sign.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.683-684
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• 2015

Project Financing (PF) is the long-term financing of infrastructure and industrial projects based upon the projected cash flows of the project rather than the balance sheets of its sponsors. However, the financial institution, the subject of financing in the case of PF in Korea, the lack of validation system of business, rather than to assess the feasibility of the project, requested a credit reinforcement to the construction company, the fact is Construction Company on loans of the employer is the guarantor or debt argument commitments accordingly. As a result, PF contingent liabilities, which are indirect debt, are triggered in the construction company, not included in the financial statements, along with the disclosure standards established according to 2009 PF contingent liabilities, and major can be a management item. In this study, PF contingent liabilities is of Pearson of the index and the PF debt ratio showing the main financial ratios and risk by classifying the credit rating and contractors Ranking of construction companies in order to analyze the impact on the financial condition of the company was performed correlation analyzes, through the Pearson correlation coefficient analysis indicated quantitative or negative relationship to derive the explicit indication.

• The Journal of Small Business Innovation
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• v.20 no.2
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• pp.35-50
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• 2017

The aims of this study is to analyze the effectiveness of firms financial status quo and the scale of financial support on SMEs overall performance. We have gathered the financial guarantee data from 1998 to 2013, provided by Korea Credit Guarantee Fund (KODIT), to analyze the effectiveness of Financial policy. To classify both financial status quo and scale of financial support, we utilized the following variables; Interest Coverage Ratio (ICR) and newly guaranteed amount ratio. To take the measurement of the overall performance, we employed profitability, growth ratio and activity index. To minimize the effect of repeated financial support (redundancy benefits), firms were selected based on the following criteria: firms that receive no financial support prior to implementing such policy over the last 3 years and no new financial support over the last 2 years. Results suggest that firms with higher ICR and large newly guaranteed amount influence on financial performance in terms of profitability index. Firms with lower ICR and large scale financial support showed a better performance compare to firms with small-scale financial support. Firms with large-scale financial support, irrespective of ICR inclined to have better performance to those of small-scale financial support in terms of growth index. For activity index, however, firms with large scale support led to higher performance in the short term. In turn, our analysis presents objective perspective with respect to the effectiveness of financial policy through credit guarantee on overall performance of SMEs. This study, therefore, implies that well-balanced SMEs supporting policy may lead to better directions.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.