• Journal of Information Technology Applications and Management
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• v.17 no.1
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• pp.11-33
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• 2010

The majority of graphs and visuals made publicly available by Thai listed companies tend to be disjointed and minimal. Only a little over fifty percent of the total 478 companies included graphic representations of their business operations and performance in the form of two or three dimensional spreadsheet based graphs in their annual reports, investor relations documents, websites and so on. For novice users, these visual representations are unlikely to give the big picture of what is the company's financial position and performance. Neither will they tell where the company stands in its own operating environment. The existing graphics and visuals, in very rare cases, can provide a sense of the company's future outlook. For boundary users such as audit committees whose duty is to promote good governance through transparency and disclosure, preliminary interview results show that there is some doubt as to whether the inclusion of big-picture visuals can really be of use to minority shareholders. These boundary users expect to see more insightful visuals beyond those produced by traditional spreadsheets which will enable them to learn to cope with the on-going turbulence in today's business environment more quickly. However, the debate is still going on as to where to draw the line between internal or external reporting visuals.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.91-105
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• 2019

The paper aims to combine balance sheet analysis at the firm level with the International Monetary Fund's public debt sustainability assessment framework to assess state-owned enterprises' (SOE) leverage as a contingent liability to the public sector. Based on company data and the interest coverage ratio as a measure of debt at risk, aggregate baseline scenarios are projected to gauge the magnitude of SOE debt as a contingency. SOE's financial and debt ratios are first bootstrapped to generate firm-level distributions and then averaged into a fan chart of the economy-wide SOE contingent liability. Applied to the People's Republic of China as an example, the study finds that by the end of 2015 SOE leverage had grown to a substantial liability. However arbitrary the assumptions underlying these projections, it would appear that even if authorities had to mop up as much as 20% of SOE debt at risk gone bad, this would have been manageable at roughly 2.7% of the gross domestic product in 2016 or 5.5% by 2021. This projection framework is fully amenable to alternative assumptions and settings, which makes it a useful analytical tool to monitor contingent liabilities from non-financial corporate debt that have been building in emerging and advanced economies alike.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.441-449
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• 2021

Bankruptcy is indicated by the inability of the company to meet its maturity obligations. The Covid-19 pandemic has had a terrible impact on the economy and businesses. The aim of this study to determine the effect of the ratios of activity, growth, leverage, and profitability in predicting bankruptcy projected by earnings per share (EPS). The sample of this research was non-banking financial sector companies listed on the Indonesia Stock Exchange in 2015-2019 and the purposive sampling technique was used. The data analysis method used was the logistic regression method to test the hypotheses. Company growth shows the company's ability to manage sales and generate high company profits, as such, the probability of the company experiencing bankruptcy will be lower. The results of this study showed that the debt to assets ratio (DAR), debt to equity ratio (DER), and return on assets (ROA) can predict bankruptcy. Meanwhile, this research found that the total assets turnover (TATO) ratio, sales growth, and net profit margin (NPM) cannot be used to predict bankruptcy.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.241-247
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• 2021

This study analyzed the changes in explanatory power of the modified Jones model(1995) for estimating the amount of accruals for Korean Stock Market listed companies from 1990 to 2019. We hypothesized that if the properties of financial variables used in the existing model change over time or change in discretionary ratios, the model's explanatory power will change. As the result of regression models, I found that the explanatory power of the modified Jones model(1995) gradually declined over time. The results may be derived from the increase in accruals itself and the changes in the distribution of variables contained in the model. The results of this research's chronological approach are expected to give important implications to both academic researchers and accounting information users.

• East Asian Economic Review
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• v.26 no.3
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• pp.179-204
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• 2022

This study examines the extent to which policy-based loans to SME exporters affect their export performance (the intensive margin of exports). We also investigate the heterogeneous export effects of policy-based loans that may depend on firm- and industry-specific characteristics, such as credit ratings, debt-to-assets ratios, firm size and age. To do so, we conduct a survey, of 1,000 Korean SMEs, that collect information on firm-level exports and policy-based loans. The main empirical findings strongly support that SMEs that receive policy-based loans tend to increase their export volumes. However, these loans' positive impact on exports are only valid for SME exporters with credit scores of 12 or greater (that is, SMEs that have difficulty accessing the external financial market). The estimation results with respect to SMEs' dependence on external financing imply that policy-based loans for SMEs in sectors that are heavily dependent on external finance are effective in that they are instrumental in increasing these firms' exports. These empirical findings emphasize the importance of the external financial market to SME exporters who face various up-front investments that are related to their exporting activities.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.53-58
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• 2023

With the fast development of artificial intelligence day by day, users are demanding explanations about the results of algorithms and want to know what parameters influence the results. In this paper, we propose a model for bankruptcy prediction with interpretability using the SHAP framework. SHAP (SHAPley Additive exPlanations) is framework that gives a visualized result that can be used for explanation and interpretation of machine learning models. As a result, we can describe which features are important for the result of our deep learning model. SHAP framework Force plot result gives us top features which are mainly reflecting overall model score. Even though Fully Connected Neural Networks are a "black box" model, Shapley values help us to alleviate the "black box" problem. FCNNs perform well with complex dataset with more than 60 financial ratios. Combined with SHAP framework, we create an effective model with understandable interpretation. Bankruptcy is a rare event, then we avoid imbalanced dataset problem with the help of SMOTE. SMOTE is one of the oversampling technique that resulting synthetic samples are generated for the minority class. It uses K-nearest neighbors algorithm for line connecting method in order to producing examples. We expect our model results assist financial analysts who are interested in forecasting bankruptcy prediction of companies in detail.

• The Journal of Industrial Distribution & Business
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• v.8 no.4
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• pp.47-52
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• 2017

Purpose - This current study will investigate the average financial ratio of top and failed five-star hotels in the Jeju area. A total of 14 financial ratio variables are utilized. This study aims to; first, assess financial ratio of the first-class hotels in Jeju to establishing variables, second, develop distress prediction model for the first-class hotels in Jeju district by using logit analysis and third, evaluate distress prediction capacity for the first-class hotels in Jeju district by using logit analysis. Research design, data, and methodology - The sample was collected from year 2015 and 14 financial ratios of 12 first-class hotels in Jeju district. The results from the samples were analyzed by t-test, and the independent variables were chosen. This was an empirical study where the distress prediction model was evaluated by logit analysis. This current research has focused on critically analyzing and differentiating between the top and failed hotels in the Jeju area by utilizing the 14 financial ratio variables. Results - The verification result of the accuracy estimated by logit analysis has shown to indicate that the distress prediction model's distress prediction capacity was 83.3%. In order to extract the factors that differentiated the top hotels in the Jeju area from the failed hotels among the 14 chosen, the analysis of t-black was utilized by independent variables. Logit analysis was also used in this study. As a result, it was observed that 5 variables were statistically significant and are included in the logit analysis for discernment of top and failed hotels in the Jeju area. Conclusions - The distress prediction press' prediction capability was compared in this research analysis. The distress prediction press prediction capability was shown to range from 75-85% by logit analysis from a previous study. In this current research, the study's prediction capacity was shown to be 83.33%. It was considered a high number and was found to belong to the range of the previous study's prediction capacity range. From a practical perspective, the capacity of the assessment of the distress prediction model in the top and failed hotels in the Jeju area was considered to be a prominent factor in applications of future hotel appraisal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.699-711
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• 2011

This study is to perform several major analyses to find any differences in the leverage between the pre- and post-period of the currency crisis. Moreover, another aspect is to investigate a financial aspect which has received relatively little attention to the firms and/or industries in the emerging capital markets in comparison to those in the advanced markets. The purpose of this empirical study is to confirm whether or not, it is myth or reality that Korean business conglomerate, chaebol, firms with subsidized financing from government-owned domestic financial institutions in the pre-financial turmoil, may still maintain their higher leverage, even after the crisis. It was found that firms belonging to the chaebol in Korea maintained higher average book-value and market-value based debt ratios, relative to their counterparts not belonging to the chaebol across all of the tested models. There were positive relationships of IND3(=the chemical industry) and Ind5(=the construction industry) to the book-value leverage. This study identified that there were no differences in the explanatory variables included, between the tested models (that is, without and with including the present value of an operating lease) related to each debt ratio. Since the Korean government continue to improve the corporate governance of the domestic firms in terms of accounting transparency and corporate ownership, it would be more efficient, if utilizing this "new" ratio considering an operating lease as an effective measurement of the level of leverage. In terms of the capital structure, it may also be possible for foreign firms to utilize and benefit from the results obtained in this study when operating their new businesses in Korea, given the economic circumstances such as the ongoing progress of the Korea-America FTA or the Korea-China FTA.

• Journal of Navigation and Port Research
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• v.45 no.3
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• pp.173-180
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• 2021

Although accounting is one of the core fields of corporate management, few studies have reported accounting phenomena involving shipping companies. In addition, although financial reporting is very important to shipping companies that use several financial tools such as ship finance and financial lease, it is difficult to identify studies investigating shipping companies' financial reporting, especially their earnings management. The purpose of this study is to analyze accrual earnings management behavior of shipping companies. Companies with high debt ratios and net losses are known to have incentives for earnings management. Due to the nature of the industry, shipping companies have a high debt ratio and often report net losses. Accordingly, shipping companies are expected to engage in substantial earnings management. Based on the analysis of KOSP I companies listed on the Korea Exchange from 2001 to 2020, it was found that shipping companies are engaged in higher levels of earnings management than non-shipping companies. Discretionary accrual was used as a proxy variable for earnings management. Discretionary accrual was measured using the modified Jones model of Dechow et al. (1995) and the performance matched model of Kothari et al.(2005). In this study, significant results were derived by comparatively analyzing the earnings management practices, which is one of the major accounting behaviors of shipping and non-shipping companies. Stakeholders such as external auditors, investors, financial institutions, analysts, and government authorities need to be aware of the earnings management behavior of listed shipping companies during their external audit, financial analysis, and supervision. Finally, listed shipping companies must conduct stricter accounting based on accounting principles.

• Management & Information Systems Review
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• v.32 no.2
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• pp.21-46
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• 2013

The purpose of this paper is to find impacts of financial activities-financing and investment of Venture Firms during pre-listing periods on the firms' Venture Firm's listing(delisting). The several ratios financial variables relevant to the financing and investment were examined whether there are difference or not between two venture firms groups. The results of study can be summarized as follows. First, the firms of successful group have fewer numbers of equity financing and higher times of premium in issuing stocks than those of failed firms but there is no significant difference in the required time from startup to listing the KOSDAQ. Second, there is no significant difference in the ratio of capital increase in IPO between two groups but additional survey reveals that the successful firms financed equity in IPO by higher numbers of premium than failed firms, which can makes the major shareholder of the successful firms maintain high rayios share of stock. Third, the ratio of working capital investment of the successful firms is significantly higher than that of failed firms, on the other hand the failed firms' ratios of equipment and repayment investment are higher than those of successful firms. Finally, the ratio of R&D investment has no difference between two groups, this result is against the expectation, which is to be further analyzed.