• Management & Information Systems Review
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• v.36 no.3
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• pp.203-217
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• 2017

This study aims to verify the effects of unrealized gain or loss, that is the fair value evaluation item of insurance company's assets and liabilities, to capital markets focusing on fair value evaluation of insurance company's liabilities, which is the core of IFRS 17 that will be implemented in 2021. For this purpose we carried out regression analysis to verify the effects of changed other comprehensive income(OCI) and accumulated OCI, published in quarterly financial statements of listed insurance companies, on stock price utilizing Ohlson(1995)'s extended test model. The results of the empirical analysis are as follows. First, changed OCI showed a significant negative(-) effects on stock price. Second, accumulated OCI revealed a significant positive(+) effects on stock price. Furthermore, extended test model classifying changed OCI and accumulated OCI in a basic model represented the highest $R^2$ number and public announcement policy of OCI, a kind of unrealized gain or loss item, implied that it could give positive impact on accounting information. But still the direction that unrealized gain or loss affects on firm value must be carefully reviewed and considered in the future via more detailed study by the user of information. Therefore this study is meaningful in that it can predict usefulness of information on insurance company's fair value evaluation via empirical test accompanied by introduction of newly established IFRS 17 and it also can suggest direction of information production suitable for capital market.

• International Area Studies Review
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• v.21 no.4
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• pp.247-268
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• 2017

This paper analyzes for companies of 2011~2014 the effects of corporate social responsibility on audit efficiency. Using KEJI Index and its individual components which is published by Citizens' Coalition for Economic Justice Institute, this paper analyzes their effects on audit efficiency of audit fees and audit hours. The results of analyses are as followings. First, corporate social responsibility(CSR) composite index did not show any significant relationship between audit fees and audit hours. However, for analyses of the effects of CSR individual components on audit efficiency, variable such as CSR fairness(CSR2), CSR social contribution(CSR3), CSR environmental protection activity(CSR5) have the negative effects on the audit fees and audit time. and CSR customer protection(CSR4), CSR employee satisfaction(CSR6) have the positive effects on the audit fees and audit time. Results suggest that independent auditors may reduce audit risks associated with possible misrepresentation of financial statements for companies with high scores of CSR fairness (CSR2), CSR social contribution(CSR3), and CSR environmental protection activity(CSR5). Also, financial statement auditors may perceive surge of discretionary expenses, and set audit risk high for companies with CSR customer protection(CSR4), and CSR employee satisfaction(CSR6). Together, KEJI Index and its individual components appear to have differential effects on audit efficiency.

• Journal of East Asia Management
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• v.4 no.1
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• pp.23-51
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• 2023

We investigate whether the association between management overconfident tone and the level of audit effort measured by audit fees and hours differs depending on the level of earnings management. Prior studies suggest that firms led by overconfident managers are likely to initiate risky investments, report low quality financial statements, and have material weaknesses in internal control system. These characteristics, combined together, result in higher audit risk. At the same time, auditors assess audit risk based on the quality of financial reporting, measured by level of earnings management. As a result, the assess audit risk is likely to reflect the combined effect of management overconfidence and the level of earnings management. In this paper, we investigate whether auditors differentiate the effects of real earnings management (REM) and accrual-based earnings management (AEM) when they assess the audit risk related management overconfident. Using the CEO's letter published in 2018, we measure the CEO's tone representing the degree of overconfidence (i.e., activity). Based on this measure, we find that the positive association between managerial overconfident tone and audit effort is more pronounced as the level of REM is higher. However, we find that the baseline association does not vary depending on the level of AEM. These results suggest that auditors consider the managerial overconfident severer when such characteristic accompany the higher level of REM, which can be outcome of aggressive business decisions possibly leading to the higher audit risks. We further find that these results are stronger for Big 4 auditors and continuing auditors. This paper contributes to the literature and practice as follows. First, we provide contextual evidence on how auditors reflect managerial characteristics in the audit process by documenting that auditors actively increase their audit efforts only when overconfident managerial characteristics are highly likely to lead to audit risk. This result suggests that auditors conduct external auditing considering both the efficiency and effectiveness of the audit process. Second, we suggest that auditors use information obtained from a wide range of sources to identify audit risks. Our results provide evidence of how the auditing standards, which do not provide detailed guidelines for audit risk assessment, are being applied in practice. Finally, our results also enhance the understanding of how audit fees are determined. Combined with the studies related to audit pricing, we provide the important reference for discussion between the auditor and the auditee about the audit fee that has created acute tension after the enforcement of the new External Audit Act.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.71-103
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• 2009

Considering the expenditure size of public institutions centering on public enterprises, about 28% of Korea's GDP in 2007, public institutions have significant influence on the Korean economy. However, still in the new government, there are voices of criticism about the need of constant reform on public enterprises due to their irresponsible management impeding national competitiveness. Especially, political controversy over appointment of executives such as CEOs of public enterprises has caused the distrust of the people. As one of various reform measures for public enterprises, this study analyzes the effect of internal governance structure of public enterprises on their managerial performance, since, regardless of privatization of public enterprises, improving the governance structure of public enterprises is a matter of great importance. There are only a few prior researches focusing on the governance structure and managerial performance of public enterprises compared to those of private enterprises. Most of prior researches studied the relationship between parachuting employment of CEO and managerial performance, and concluded that parachuting produces negative effect on managerial performance. However, different from the results of such researches, recent studies suggest that there is no relationship between employment type of CEOs and managerial performance in public enterprises. This study is distinguished from prior researches in view of following. First, prior researches focused on the relationship between employment type of public enterprises' CEOs and managerial performance. However, in addition to this, this study analyzes the relationship of internal auditors and managerial performance. Second, unlike prior researches studying the relationship between employment type of public corporations' CEOs and managerial performance with an emphasis on parachuting employment, this study researches impact of employment type as well as expertise of CEOs and internal auditors on managerial performance. Third, prior researchers mainly used non-financial indicators from various samples. However, this study eliminated subjectivity of researchers by analyzing public enterprises designated by the government and their financial statements, which were externally audited and inspected. In this study, regression analysis is applied in analyzing the relationship of independence and expertise of public enterprises' CEOs and internal auditors and managerial performance in the same year. Financial information from 2003 to 2007 of 24 public enterprises, which are designated by the government, and their personnel information from the board of directors are used as samples. Independence of CEOs is identified by dividing CEOs into persons from the same public enterprise and persons from other organization, and independence of internal auditors is determined by classifying them into two groups, people from academic field, economic world, and civic groups, and people from political community, government ministries, and military. Also, expertise of CEOs and internal auditors is divided into business expertise and financial expertise. As control variables, this study applied foundation year, asset size, government subsidies as a proportion to corporate earnings, and dummy variables by year. Analysis showed that there is significantly positive relationship between independence and financial expertise of internal auditors and managerial performance. In addition, although business expertise and financial expertise of CEOs were not statistically significant, they have positive relationship with managerial performance. However, unlike a general idea, independence of CEOs is not statistically significant, but it is negatively related to managerial performance. Contrary to general concerns, it seems that the impact of independence of public enterprises' CEOs on managerial performance has slightly decreased. Instead, it explains that expertise of public enterprises' CEOs and internal auditors plays more important role in managerial performance rather than their independence. Meanwhile, there are limitations in this study as follows. First, in contrast to private enterprises, public enterprises simultaneously pursue publicness and entrepreneurship. However, this study focuses on entrepreneurship, excluding considerations on publicness of public enterprises. Second, public enterprises in this study are limited to those in the central government. Accordingly, it should be carefully considered when the result of this study is applied to public enterprises in local governments. Finally, this study excludes factors related to transparency and democracy issues which are raised in appointment process of executives of public enterprises, as it may cause the issue of subjectivity of researchers.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Korean Academy of Nursing
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• v.26 no.1
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• pp.223-247
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• 1996

This study was done to provide information which would lead to nursing care of the elderly being more holistically through an understanding of the phenomena of powerlessness based on the lived experience of powerlessness by the elderly, the meaning the elderly give to such phenomena, and what essence of powerlessness is. The methodology used in this study was Max Van Manen's phenomenological method based on the philosophy of Merleu-Ponty and a concerted approach was realized through the 11 steps suggested in the Van Manen's method. Data collection was done from March 2, 1995 to December 30, 1995. The subjects for this study were four elderly persons who lived with their families and who were over 60 years of age. Data were collected about the lived experience of the elderly, this researcher's experience of powerlessness, the linguistic meaning of powerlessness, idioms of the word or a feeling of powerlessness, and descriptions of powerlessness in the elderly as they appeared in the literature, are works, and phenomenological literature. All data were used to provide insights into the phenomena of powerlessness. Data about the experience of powerlessness by the elderly were collected through open interviews, participation, and observation. In the analysis of the theme of this study, the aspects of the theme, powerlessness in the elderly were clarified, thereby abstracting and finding meaningful statements by the elderly about their feeling of powerlessness, and then those significant statements were expressed as linguistic transformations. The summarized findings from the study are as follows : 1. Five meanings of powerlessness in the elderly were defined. 〈weakness〉, 〈dependence〉, 〈frustration〉, 〈worthlessness〉 and 〈giving up〉. 2. 〈Weakness〉 means that the elderly experience, not only their aging but also, their becoming weak and the loss of physical function frequently caused by diseases. 〈Dependence〉 means that the elderly experience dependence without any influence from the surroundings and that elderly patients who are hospitalized lose their autonomy, follow entirely their doctor's prescriptions, use aid equipment and directions, and depend only on those things. 〈Frustration〉 means that the elderly experience the loss of their roles from the past, there by feeling that there is no work for them to do anymore and therefore feel unable to do anything. 〈Worthlessness〉 means that the elderly experience the feeling of losing their social roles from the past, having no financial ability, thereby being a burden to their children or the people around them, and therefore regarding themselves useless. 〈Giving up〉 means that the elderly experience the feeling of closeness to death in the final stage of their lifetime, lose hope to be healed from their disease, and recognize the incontrollability of their own body. 3. From a general view of the meaning of the theme the powerlessness in the elderly-the most essential meaning of the theme is the 〈sense of loss〉. For the elderly are experiencing a sense of loss in the situation of being elderly and therefore being often hospitalized. Brief definitions of the five phenomena could be 〈weakness〉 meaning the loss of physical strength, 〈dependence〉 the loss of mentality caused by disease and hospitalization, 〈frustration〉 and 〈worthlessness〉 the loss of social performance caused by the loss of social functions from the past, and lastly 〈giving up〉 the loss of the controllability of such situations of aging and suffering disease. In light of the discussion above, it is understandable that the hospitalized elderly experience powerlessness not only as it related to their diseases but also to their normal aging, and this related to other characteristics of being elderly means that the 〈sense of loss〉 is the very essence of their powerlessness. 4. While most cases are of the normal elderly experiencing powerlessness in relation to their social network, cases of elderly who are hospitalized are of those experiencing powerlessness in relation to the loss of their physical desire. 5. The findings discussed above can serve as guidelines for nurses who take care of the ill elderly who are hospitalized and that can provide cues to appropriate nursing service, recognizing that the subjective experience of the objective age of the elderly is so important. Nurses can provide highly qualitative nursing service, based on their deep understanding of the suffering of the elderly due to feelings of powerlessness.

• Management & Information Systems Review
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• v.29 no.4
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• pp.1-22
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• 2010

There have been arguments in Korea that fair value accounting system improves quality of accounting information through the asset revaluation. These arguments are based on the fact that investors prefer fair value to cost value information. Others argue that cost principles may offer more proper information to the investors because financial statements applied the cost principles are more objective and thus more reliable. Prior researches focused mainly on the motives of asset revaluation but I examined the effects of the tangible asset revaluation on the stock prices. The empirical findings indicate that : (1) the gains on the tangible asset revaluation are positively correlated with the stock prices; (2) the net book values applied the cost principles explain stock prices better than the net book values applied fair values. My findings suggest that the gains on the tangible asset revaluation constitute a part of the firms' values but the accounting informations measured fair value are not always useful to the investors in the capital market.

• Industry Promotion Research
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• v.5 no.4
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• pp.39-53
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• 2020

With the recent increase in the demand for corporate trust based on transparency in accounting, such as management disclosures and autonomous management disclosures for Social Innovative Enterprises, the duties of Social Innovative Enterprises on accounting and tax affairs have become important. This study looked at the effects of NCS accounting, audit and tax functions on the sustainability of Social Innovative Enterprises, which have not been studied. In particular, issues such as management disclosures and adequacy of financial statements depend on how ethically the accounting officer performs the work. Accordingly, we looked at the intermediation of accounting ethics held by the person in charge of accounting in relation to the sustainability of the NCS accounting, audit and taxation functions. The research subjects surveyed 500 people in charge of accounting at 50 social innovation companies, including social enterprises established in special cities and metropolitan cities such as Seoul and Busan, as well as social cooperatives. A path analysis was conducted with 372 valid questionnaires. As a result of the analysis, NCS accounting, audit and tax functions have a significant impact on both economic value and social value and environmental value, which are the sustainability elements of Social Innovative Enterprises. It was also found that NCS accounting, audit and tax affairs had a significant impact on accounting ethics, and accounting ethics had a significant impact on social and environmental values, excluding economic values. In addition, accounting ethics were found to have a mediated effect between NCS accounting, audit and taxation functions and the sustainability elements of Social Innovative Enterprises. In particular, the relationship between NCS accounting, audit and tax affairs and social value was found to be completely mediated.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.1
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• pp.25-31
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• 2017

The objective of this study is to find the failure factors of venture companies. We analyze 210 troubled venture companies, all of which have been under guarantee from the Korea Technology Finance Corporation over the last three years. Methods of analysis for failure factors are as follows. First, we categorize the failure factors into the four different types based on growth and profitability indicators in the financial statements of targeted venture companies. Then we analyzed the failure factors of the subject companies based on the troubled guarantee reports made by the Korea Technology Finance Corporation. If a venture company under its guarantee program falls into insolvency, the Korea Technology Finance Corporation make the troubled guarantee report to find out the failure factors and evaluate the recovery potentials. We identify 374 failure factors of venture companies through the analysis. The most prominent among them are deteriorating of business environments (79 factors) and decreasing or withdrawing orders from major suppliers (54 factors) due to bankruptcies or change in business plans. They are followed by slowing collection of accounts receivable (31 factors), dropping or frozen product price (24 factors) due to intensifying competition and escalating pressures from major suppliers, rising raw material costs both at home and abroad (21 factors). In addition, the nuclear power plant disaster in Japan, shut-down of the Kaesong Industrial Complex and subsequent lawsuits, delay in technology development projects, high cost-low efficiency management structure, etc., are also revealed as new factors causing trouble for venture companies.