• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.241-250
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• 2020

This study examines the relationship between the attributes of board structure and the likelihood of financial distress for the non-financial sector of an emerging market characterized by concentrated ownership and family-controlled business. The present study utilized panel logistic regression to estimate the relationship between board structure attributes and the likelihood of financial distress. We used Altman Z-Score as a proxy for firm financial distress, as this tool measures the financial distress inversely. The study finds a significant relationship between board size and the likelihood of financial distress. The results show that a one-unit increase in board size would decrease the probability of financial distress by 3.4%. Further, we observe that a greater level of board independence is associated with a lower likelihood of financial distress. A one-unit increase in board independence would decrease the probability of financial distress by 20.4%. We also find a significant positive impact of leverage on the likelihood of financial distress. The present study contributes to the body of literature on board structure attributes and likelihood of financial distress in emerging markets, like Pakistan. Furthermore, the findings would be beneficial for corporate policymakers and investors in formulating corporate financial strategy and predicting business failure.

• Journal of Distribution Science
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• v.20 no.10
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• pp.61-66
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• 2022

Purpose: Predicting the financial distress distribution of an enterprise is important to warn enterprises about their future. Predicting the possibility of financial distress helps companies have action plans to avoid the possibility of bankruptcy. In this study, the author conducted a forecast of the financial distress distribution of enterprises. Research design, data and methodology: The forecasting method is based on Logit and Discriminant analysis models. The data was collected from companies listed on Vietnam Stock Exchange from 2012 to 2020. In which there are both companies suffer from financial distress and non-financial distress. Results: The forecast analysis results show that the Logistic model has better predictability than the Discriminant analysis model. At the same time, the results also indicate three main factors affecting the financial distress of enterprises at all three research stages: (1) Liquidity, (2) Interest payment, and (3) firm size. In addition, at each stage, the impact of factors on financial distress differs. Conclusions: From the results of this study, the author also made several recommendations to help companies better control company operations to avoid falling into financial distress. Adjustments to current assets, debt, and company expansion considerations are the most important factors for companies.

• Journal of Families and Better Life
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• v.28 no.5
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• pp.113-129
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• 2010

This study explored the level and general propensity of the economic distress and the financial management behavior of household financial managers and analyzes the effects of economic distress and the sub dimensions to financial management behaviors. The research results can be summarized as follows. 1. The overall level of economic distress of household financial managers was middle-levels and the financial management behavior were slightly higher than mid-point. 2. Regarding the household variables on the economic distress of household financial managers, education levels and occupations of husbands, monthly income, financial knowledge were the variables that had a significant negative effect on the economic distress. That is, higher education levels of husbands, husbands with management-level/professional-level career, higher monthly income, and higher level of financial knowledge generated lower economic distress. 3. Regarding the household variables and the economic distress on the financial management behavior, monthly income, and financial knowledge were the variables that had a significant positive effect on the financial management behavior. On the contrary, income-asset distress was negative variable. Thus, higher monthly income, higher level of financial knowledge, and lower level of economic distress generated higher financial management behavior. Statistically significant differences were detected in financial management behavior sub dimensions. From this research, it could be concluded that the main variables affecting the level of financial management behaviors are income-asset distresses and financial knowledge.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.4
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• pp.1621-1625
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• 2015

Background: Financial distress due to the cost of cancer treatments is prevalent among cancer patients. Identifying the level of financial distress and its affecting factors has an important role in providing supportive services. Accordingly, the aims of this study were to determine these parameters among Iranian cancer patients. Materials and Methods: This descriptive-correlational study was undertaken among 262 cancer patients admitted to both private and public hospitals in East Azerbaijan province, Iran. The financial distress/financial well being scale was used to determine financial distress. The data were analyzed using SPSS software using descriptive and inferential statistics (multiple linear regression). Results: Among the 262 cancer patients, 57.3% were male and their mean age was 47.0 years. The mean score for financial distress was 4.12 (2.01). The final regression model demonstrated that the independent variables (predictors) of income less than living expenses, income equal to living expenses, having an employed spouse in governmental job and living with parents, with regression coefficients of -1.029, -0.515, 0.198, and 0.096, respectively, were predictors of financial distress among cancer patients. These variables accounted for 50% of changes in variance of financial distress. Conclusions: Iranian cancer patients have moderate to high levels of financial distress. Considering policies for managing direct and indirect costs of cancer treatments must be followed.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.373-381
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• 2021

This study aims to investigate the impact of financial distress on the cash holding of non-financial companies in Indonesia as the largest emerging economy among ASEAN countries. Furthermore, the sub-sample business group to be investigated were divided into two, groups namely affiliated and non-affiliated groups. This was carried out to ascertain the difference in the impact of financial distress on cash holding between both groups. Sample collection was based on all firms listed on the Indonesian Stock Exchange (IDX) during 2008-2017, comprising 137 firms. The results showed that using the two-step system Generalized Method of Moments (GMM), the coefficients for financial distress (Z-Score) indices were positive and significant for all models. Therefore, the higher the Z-Score value, the lower the company's financial distress and vice versa. This implies that the lower the company's financial distress, the lower the cash holding. Furthermore, a positive and significant impact of the Z-Score on cash holding for non-affiliated groups was discovered. This implies that there are differences in the amount of cash holding between affiliated and non-affiliated groups. This result indicates that non-affiliated groups hold more cash during financial distress. However, these results had cash policy implications, particularly for non-affiliated groups.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2257-2261
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• 2015

Background: Return to work after treatment completion is important for both cancer survivors and society. Financial distress is one of the factors that may influence the return to work in cancer survivors. However, this relationship has not been well investigated. This study aimed to determine the rate of return to work and its relation to financial distress among Iranian cancer survivors. Materials and Methods: This descriptive-correlational study was undertaken among 165 cancer survivors who completed their initial treatments and had no signs of active cancer. The Return to Work questionnaire and Financial Distress/Financial Well-Being Scale were used for data collection. Data were analyzed using SPSS statistical software. Results: After initial treatments, 120 cancer survivors (72%) had returned to work, of which 50 patients (42%) had returned to full-time work and 70 (58%) reduced their work hours and returned to part-time work. Cancer survivors also reported high levels of financial distress. In addition, the financial distress was lower among patients who had returned completely to work, in comparison to patients who had quit working for cancer-related reasons (p= 0.001) or returned to work as part-time workers (p=0.001). Conclusions: The findings showed that a high percent of Iranian cancer survivors had not returned to their jobs or considerably reduced working hours after treatment completion. Accordingly, due to high levels of financial distress experienced by participants and its relation to return to work, designing rehabilitation programs to facilitate cancer survivor return to work should be considered.

• Journal of the Korean Home Economics Association
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• v.42 no.5
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• pp.161-174
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• 2004

Using a sample size of 643 college students, this study examined the level of financial stress and financial problems of college students and investigated the factors related to stresses and problems. A majority of the students had experienced financial stress that interfered their study. Among the financial problems, spending problems were the most problematic. The results of the study indicated that financial knowledge and practice were important determinants of students' financial stress and problems. Some of the demographic variables, such as family income, were also important in predicting the students' spending problems. It was suggested that good financial practices of expenditure and maintenance of those practices were important to reduce or prevent financial problems and distress. Financial educators and parents should provide their support in helping students handle their finances responsively.

• Proceedings of the Fisheries Business Administration Society of Korea Conference
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• 2007.12a
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• pp.167-184
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• 2007

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut-down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t-test is used to identify the differences in financial variables between the distressed group and the non-distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990$\sim$1993), period 2(1994$\sim$1997), period 3(1998$\sim$2002). The final model built from whole sample appled each three sub-samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub-sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• The Journal of Fisheries Business Administration
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• v.39 no.2
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• pp.61-79
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• 2008

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut - down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t - test is used to identify the differences in financial variables between the distressed group and the non - distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990 - 1993), period 2(1994 - 1997), period 3(1998 - 2002). The final model built from whole sample appled each three sub - samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub - sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• 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.