• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.355-363
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• 2020

This study aims to investigate whether financial attitude links financial literacy to financial capability. To make sound financial decisions, one essentially requires a certain level of financial literacy - knowledge and skill in finance. Even more effective is when one's financial literacy could be developed into financial capability. The samples comprised 342 individuals from informal labor in the South of Thailand. The stratified multistage sampling technique was utilized to select the respondents, while the interview questionnaires were used to collect the data. By using SmartPLS 3.0, the data analysis included descriptive statistics and structural equation modeling (SEM). The result revealed that the one with the highest debt was Gen Y compared to Gen B and Gen X. Considering financial literacy, financial attitude, and financial capacity across generations, it was found that Gen Y had the highest average score in financial literacy and financial capacity, higher than that of Gen X and Gen B. The impact of financial literacy on financial capability through financial attitude, it was found that the impact on Gen B was higher than that of Gen X and Gen Y. With the right financial attitude, people of all generations would be equipped with a higher level of financial capability.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.167-172
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• 2020

The purpose of this study was to suggest implications that the level of sound financial management ability of university students could be raised, starting with the awareness that not only college students but also all financial consumers need high levels of financial management ability, such as knowledge and attitudes toward financial management, as economic conditions are in trouble in the aftermath of the ongoing Corona19. A survey was conducted on college students to achieve the purpose of the study. In relation to the research model set in this study based on the survey, financial management ability and financial self-efficacy as the independent variable, and financial management behavior as the dependent variable were selected to analyze the structural relationship according to the study model. The analysis shows that financial management ability had an effect on financial self-efficacy and financial management behavior. Based on these results, theoretical and policy implications were presented. Finally, the limitations of this study and future research directions were suggested.

• Korean Journal of Human Ecology
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• v.14 no.4
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• pp.613-629
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• 2005

This research analyzes household financial structures and ratios to understand factors of household utility. Its main themes are as following: First, what kinds financial structures are found at each level of income? Second, how are they different by the level of income? Third, what factors contribute to appropriate financial ratios? The themes are supported by the texts on financial ratios from both inside and outside of Korea and proved by the Korean Labor and Income Panel Survey, the fifth annual edition. The households are exempted that do not support the household principle record in the principle and household economy record. Accordingly, this survey is from a financial structure analysis of 3,762 households. The analysis utilizes SPSS Window (Version 10.0) program. The following are the results: First, the income level 4 and above, in which the increasing number indicates a higher level of income, are highly ranked on the income-expense level and the asset-debt rate. Also, level 4 has a strong financial structure, whereas level 1 does not. Apparently, the management of the household is complicated by debt redemption and a lower level of assets. Second, Ratio 1, Ratio 2, Ratio 4, and Ratio 5 are different by the level of income. Third, the level of income contributes to the appropriate financial ratio. The financial safety and prospective financial structure at each income level is an important variable. Households with a high income, in particular, have to balance their finances and capital, reducing liabilities and increasing the total assets. In other words, the family must hold assets to enhance efficiency according to the character and income level of the household. This research is a useful resource for such a decision-making as to improve household financial structure stability. Also, it can be adopted to evaluate financial products for specific households and be used for economic and social welfare planning to predict how households influence the nationwide economy.

• The Journal of Information Systems
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• v.18 no.4
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• pp.41-57
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• 2009

Although financial information is a great influence upon determining of the group which use them, detection of management fraud and earning manipulation is a difficult task using normal audit procedures and corporate credit evaluation processes, due to the shortage of knowledge concerning the characteristics of management fraud, and the limitation of time and cost. These limitations suggest the need of systemic process for !he effective risk of earning manipulation for credit evaluators, external auditors, financial analysts, and regulators. Moot researches on management fraud have examined how various characteristics of the company's management features affect the occurrence of corporate fraud. This study examines financial characteristics of companies engaged in fraudulent financial reporting and suggests a model and system for detecting GAAP violations to improve reliability of accounting information and transparency of their management. Since the detection of management fraud has limited proven theory, this study used the detecting method of outlier(upper, and lower bound) financial ratio, as a real-field application. The strength of outlier detecting method is its use of easiness and understandability. In the suggested model, 14 variables of the 7 useful variable categories among the 76 financial ratio variables are examined through the distribution analysis as possible indicators of fraudulent financial statements accounts. The developed model from these variables show a 80.82% of hit ratio for the holdout sample. This model was developed as a financial outlier detecting system for a financial institution. External auditors, financial analysts, regulators, and other users of financial statements might use this model to pre-screen potential earnings manipulators in the credit evaluation system. Especially, this model will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings and to improve the quality of financial statements.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.273-280
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• 2021

Financial behavior and financial well-being are two closely related aspects of an individual's financial decision making. This study attempts to investigate the extent to which financial behavior influences financial well-being in the Indian scenario. The data is collected using a structured questionnaire from a sample of 150 respondents. The study employs Financial Management Behaviour Scale (FMBS) (Dew & Xiao, 2012) to measure financial behavior. Factor analysis and multiple regression are performed to find the influence of financial behavior on financial well-being. The findings of the study suggest that except for credit commitment all the other behavioral factors like future security, savings and investments, credit indiscipline, and financial consciousness have a significant impact on the financial well-being of an individual in the Indian scenario. The regression coefficients of financial well-being are strongly determined by financial consciousness. The study is a contribution to the existing behavioral studies literature and the model used identifies the factors that influence the financial well-being in the Indian scenario. The study is conducted during the year 2020, so the results could have been influenced by the economic scenario of the period. The results of the study can be used by financial advisors to understand the financial well-being in the Indian scenario.

• 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.

• Journal of the Korea Institute of Building Construction
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• v.4 no.2
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• pp.137-142
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• 2004

There was the time of IMF(1998) that management condition of construction business had been the worst. After that time, structural regulation was completed and financial structure was returned to normalcy(2001). At that time, the aim of this paper is that fifteen construction business are researched for process of management condition and capital structure after they is selected as samples for three years, also failure of two-groups is predicted as statistics analysis and multiple discriminant analysis for them. In this paper, It is researched financial statement of business by the forecast experiment of failure and analyzed statistically possibility of failure and success for financial ratio. For them, the fifteen companies of failure and the fifteen companies what were not the failure, for listed company, and the fourteen variables are selected and they are analyzed statistically according to Logit Analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.670-673
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• 2020

Recent advances in artificial intelligence have allowed for easier sentiment analysis (e.g. positive or negative forecast) of documents such as a finance reports. In this paper, we investigate a method to apply text mining techniques to extract in the financial report using deep learning, and propose an accounting model for the effects of sentiment values in financial information. For sentiment analysis with keyword detection in the financial report, we suggest the input layer with extracted keywords, hidden layers by learned weights, and the output layer in terms of sentiment scores. Our approaches can help more effective strategy for potential investors as a professional guideline using sentiment values.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.57-73
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• 2015

While many previous studies investigated the effect of operations performance on financial performance, most studies considered only a few performance indicators and ignored the characteristics of industries. Therefore, this study intends to analyze the effect of operations performance on financial performance, by selecting a rather comprehensive operations performance indicators from firms' financial data. In doing so, we used operating efficiency and supply chain performance indicators for operations performance and a firm's profitability and future value indicators for financial performance. For the analysis, we collected 544 firms' operations and financial performance data belonging to eight key industries from the 'Forbes Global 2000'. We first analysed the differences in operations and financial performance among high, medium and low supply chain performance groups based on the quantitative criteria of Gartner's 'Supply Chain Top 25' ranking procedure. Then we analysed the effect of operations performance indicators on financial performance for both entire industry and individual industries, using multiple regression. Based on the results, we provided practical insights into key operations performance indicators to focus on and manage in order to improve financial performance.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.17-27
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• 2020

The research aims to investigate the impact levels of determinants on the conversion of financial statements from Vietnamese accounting standards (VAS) to International financial reporting standards (IFRS) in the multinational firms in Vietnam. The method of data collection was done through the survey and subjects are accountants in Multinational Firms doing business in Hanoi and ten neighboring provinces. After checking the information on the votes, there are 170 questionnaires with full information for data entry and analysis. We use Cronbach's Alpha, EFA analysis and run regression model to investigate the impact levels of each independent variable on dependent variable of the conversion of VAS financial statements to IFRS. The results show that five determinants including Economic, Politics, Law, Culture, and Conditions for implementation have positive relationships with the conversion of VAS financial statements to IFRS. In particular, Economic determinant is the most strongest. Based on the findings, some recommendations are given for improving the conversion of VAS financial statements to IFRS of multinational firms doing business in the context of Vietnam. The results are considered a useful reference for firms when making financial statements to transparently change the financial statement information and improve the quality of financial statement information.