• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• 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 agricultural medicine and community health
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• v.24 no.2
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• pp.269-289
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• 1999

This study was conducted to examine the relationship among health concern, health practice and ADL of elderly staying at home in a rural community and their affecting factors. Data were collected through direct interviews made with 480 old people aged more than sixty-five from November 15, 1998 to December 20, 1998. Out of 189 male and 291 female, the high-level group that showed high health concern accounted for 44.4%, the medium-level group for 13.1%, and the low-level group for 42.5%, in the health practice, the high-level group accounted for 3.8%, the medium-level group for 18.8%, and the low-level group for 77.5%. In the self-rated health status, the high-level group accounted for 29.0%, the medium-level group for 31.0%, and the low-level group for 40.0%, and in the ADL, the high ADL group accounted for 91.5%, and the low-level ADL group for 8.5%. The result of the chi-square test showed that for male, there was a significant relation between the health concern and the health practice index score. In the relation between the health practice index score and the self-rated health status, there was significant positive relationship between health practice index and self-rated health status, and in the relation between the health practice Index score and the ADL, old people with higher health practices showed good ADL(but not significant). Old people with good ADL also showed good self-rated health status. In the multiple regression analysis where the health practice was used as a dependent variable, the health concern was added to the sociodemographic variables as an independent variables, a formula was formed for male old people only and ones with high concern in health showed good health practice. In the multiple logistic regression analysis where the sociodemographic variables to which the health practices was added were used as an independent variable and the ADL as a dependent variable, the ADL appeared to be not good if for male old people the living costs were born by their sons and daughters and as for female old people their ages increased, but it was good if old people had sources of health information such as hospitals or health centers. The self-rated health status was worse, for male old people, if they had short living costs or diseases and for female old people, if they had spouses, living costs born by their sons and daughters or diseases, but it was better, for male old people, if they had periodical gatherings or carried out health practices a lot, and for female old people, if they had sources of health information such as hospitals or health centers or carried out health practices a lot. In view of the results stated above, the higher the old people had health concern, the more they carried out health practices, and the more they carried out health practices, the better they had ADL and self-rated health status that served as the level of health. Further, the better ADL, the better self-rated health status.

• 한국노년학
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• v.40 no.4
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• pp.639-657
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• 2020

The purpose of this study is to analyze the effect of individual differences in recognition of retirement responsibility on financial preparedness for retirement and to examine moderating effect of income-level on the relationships between the two variables, using the 7th Korean Retirement and Income Study(KReIS). Two research methods, descriptive analysis and hierarchical multiple logistic regression(HMLR) analysis, have been conducted. The total number of sample was 3,869 subjects with an average age of 58.9 years and 55.3% males. The results show that only 35.8% of the respondents make financial plans for retirement, and 64.2% did not. Main findings are as follows. First, 65% of respondents take a responsibility for financial preparedness for retirement, compared to 37% in European countries. Second, people with responsibility for their own retirement are more likely to have a financial preparation for retirement than people who think others(family, society, government) have to take a responsibility for retirement instead of them. Third, there is a significant moderating effect of income-level on relationships between recognition of retirement responsibility and financial preparedness for retirement. As income level decreases, the moderating effect reduces the positive effect of recognition of retirement responsibility on financial preparedness for retirement and vice versa. Fourth, as income level increases and educational level is higher, the tendency to prepare financially for retirement is also increasing. Low-income and low-educated people are less likely to have a financial preparation for retirement than their counterparts. The findings suggest that it is necessary to design an effective incentive scheme for financial preparedness for retirement for low-income and low-educated people and to develop various policies and services to encourage them to prepare financially for retirement.