• The Journal of Fisheries Business Administration
• /
• v.55 no.3
• /
• pp.1-13
• /
• 2024

The purpose of this study is to examine the determinants of management performance in the remaining offshore fishing industry after the resource management-oriented fisheries structure improvement policy by the fisheries vessel buy-back program and Total Allowable Catch (TAC). The results of the analysis of the determinants of management performance of offshore fishing can be summarized as follows. First, based on the management performance determinant model of offshore fishing, it is confirmed that the government's resource-managed fishing structure improvement policy, such as the fishing boat reduction project and the TAC policy, is improving the management performance of the resource-managed remaining fishing boat. Second, looking at the specific management performance determinants based on the management performance model of offshore fishing, the leverage ratio (TLTA), which is the total debt ratio, shows a statistically significant positive (+) relationship with management performance, which increases management performance directly proportional to the leverage ratio. The increase in the leverage ratio (total debt ratio) was expected to lead to a high interest cost burden, resulting in a reverse (-) financial leverage effect; however, rather a positive (+) financial leverage effect occurred with a high profit covering interest costs. The total catch (TCATCH) has a positive (+) relationship with management performance at a statistical significance level of less than 1%, indicating that an increase in catch is improving or increasing the management performance of fishing companies. The selling price (UPRICE) shows a positive (+) relationship with management performance at a very high statistical significance level of less than 1%, and it can be seen that high fishing prices are a major factor in improving or increasing the management performance of offshore fishing. On the other hand, fishing vessel tonnage (TON), fishing vessel horsepower (RHP), and operating days (WDAYS), which indicate have a statistically significant negative (-) relationship with management performance, which deviates from the existing fisheries common sense that the size of fishing vessel tonnage and fishing vessel horsepower and the increase in the number of operating days is proportional to management performance. As a result of the increase in fishing vessel tonnage, horsepower, and the number of operating days, it was confirmed that the higher the fishing cost, such as oil costs, is worsening the management performance of fishing companies. Participation in TAC has a statistically significant positive (+) value with management performance, indicating that the remaining offshore fishing companies participating in TAC are improving or increasing management performance compared to offshore fishing companies that do not. Third, there are conflicting results depending on the industry as a result of estimating the management performance determinants of offshore fishing by TAC participation, and TAC participation had a negative impact on management performance in anchovy boat seine and southern west sea bottom trawl in fishing industry while TAC participation had a positive impact on management performance in large stow nets on anchor in fishing industry.

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

• Proceedings of the Korea Database Society Conference
• /
• 1999.06a
• /
• pp.175-186
• /
• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• The Korean Journal of Financial Management
• /
• v.27 no.2
• /
• pp.1-33
• /
• 2010

This study explores if the higher initial returns and the poorer long-run performance observed in the IPOs markets are associated with the firms offered in the 'hot markets,' and then empirically examines the effect of optimistic investors' sentiment on this phenomenon, particularly in the aspects of both pricing mechanism and the opportunistic behavior of offering firms. We analyzed a total of 432 IPO firms for the years between 2001 and 2005. This analysis finds that the initial returns and long-run under-performances of 'IPOs in the hot market' are significantly higher than those of 'IPOs in the cold market.' This study also finds that the proxy variables for the optimistic investors' sentiment have a positive effect on the initial return and negative effect on the long-run performance. Finally, this research finds no difference of ownership structure, venture capital backed, and financial properties between hot market IPOs and cold market IPOs. R&D expenditure rate and financial qualities of IPOs are higher in the hot market than in the cold market. These results do not support the 'windows of opportunity' hypothesis that low quality firms take advantage of hot market condition for successful IPOs.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 1999.03a
• /
• pp.175-186
• /
• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• 한국노년학
• /
• v.37 no.3
• /
• pp.527-547
• /
• 2017

The purpose of this study is to investigate how depression, death anxiety, and social support can exert influence on the psychological well-being of elderly living alone through a parameter of resilience. A survey was conducted involving 988 elderly over the age of 65 living alone in the Daejeon metropolitan area and Chungcheongnam-do and the data were analyzed using structure equation model. The results were as follows. First, in the measurement of variables according to demographic characteristics, depression showed significant differences depending on gender, level of education, health, and financial condition, while death anxiety differed depending on gender, and level of education. Social support was significantly different by gender, age, level of education, region, health, and financial condition. The level of resilience was significantly different by gender, age, level of education, health, and financial condition. Psychological well-being varied according to gender, level of education, health, and financial condition. Second, the effects of depression, death anxiety and social support on psychological well-being were examined. It was found that depression had a negative influence and social support had a positive impact while death anxiety showed no influence. Third, with regard to the effects of depression, death anxiety, social support on resilience, depression was found having negative influence, whereas social support having positive influence. Forth, psychological well-being was positively affected by resilience. Also, through the mediated pathway of resilience, their psychological well-being seemed to totally improve when the negative factors were reduced and the positive ones promoted. This study may have some significance in reference to examine the factors affecting the psychological well-being of elderly living alone and to develop social welfare service programs and policies in the field.

• The Journal of Society for e-Business Studies
• /
• v.26 no.4
• /
• pp.119-131
• /
• 2021

With the boom of platform businesses, digital transformation has become the most important topic for businesses. Digital transformation has now become the most urgent strategy for survival, from a strategy considered as an option to choose in the past. Many companies are desperately seeking the ways to be digitally transformed. Even though there have been many studies on digital transformation, most of them are on strategic and conceptual model levels based on simple case analyses. In this study, we analyze the benefits of data integration and network effects from it, based on platform business model at the core of digital transformation. The change based on platform can be categorized into the internal one for the integration of data and better decision making, and the external one for the expansion of the businesses and better prediction of consumer behaviors through the integration of external data sets by the platform business model based enterprises. While the progress for digital transformation is not mature enough yet, financial industry is one of the most promising industries for the change and realization of the aim of it with its relatively much more advanced IT infrastructure. Many companies are making various efforts for the integration of external data, and if the good results can be accomplished, financial industry will contribute to the advancement of digital transformation in other industries as well. For "My Data" project by Korean government, we suggest the data structure and transaction of data (of Korea) should be advanced and established more quickly.

• Journal of the Economic Geographical Society of Korea
• /
• v.17 no.2
• /
• pp.280-295
• /
• 2014

This paper analyzes the topological structure of housing market networks with an application of minimal spanning tree method into apartment sales markets in the Capital Region over the period 2003.7-2014.3. The characteristics of topological network structure gained from this application to some extent share with those found in equity markets, although there are some differences in their intensities and degrees, involving a hierarchical structure in networks, an existence of communities or modules in networks, a contagious diffusion of log-return rate across nodes over time, an existence of correlation breakdown due to the time-dependent structure of networks and so on. These findings could be partially attributed to the facts that apartments as a quasi-financial asset have been strongly overwhelmed by speculative motives over the period investigated and they can be regarded as a housing commodity with the highest level of liquidity in Korea.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.5
• /
• pp.61-72
• /
• 2020

The purpose of this study is to investigate the determinants of the capital structure of firms operating in a developing economy, Pakistan. The quantile regression method is applied on a sample of 183 non-financial companies listed on the Pakistan Stock Exchange during the period of 2008-2017. Specifically, the empirical analysis focuses on changes in the coefficients of the determinants according to the leverage ratio quantiles of the examined listed firms. The findings show that the capital structure of Pakistan listed firms differs between firms in different quantiles of leverage. These differences are significant with the sign of explanatory variables changes with the level of leverage. The research result found tangibility, profitability and age to be positively related to leverage among listed firms in Pakistan. However, size, liquidity and non-debt tax shield (NDTS) are negatively related to leverage. A firm's growth and risk are found to be insignificant predictors of capital structure in Pakistan listed firms. Moreover, the study also found a significant impact of industry characteristic on leverage. The findings of this study indicate that an individual firm's finance policy needs to be responsive to the firm's characteristics and should match with the different borrowing requirements of listed firms.

• Journal of Digital Convergence
• /
• v.15 no.12
• /
• pp.233-238
• /
• 2017

Although numerous theoretical and empirical studies on the capital structure have been performed, the studies on the capital structure of the high potential enterprises have not been worked. This paper performed empirical analyses for the first time to find out the determinants of capital structure of the high potential enterprises of Korea using the financial data of the manufacturing high potential enterprises listed on the Korea Exchange and KOSDAQ during 2010~2016. The results of regression analyses with debt ratio as dependent variable and profitability, firm size, asset tangibility and non-debt tax shield as independent variables show that the coefficients were relatively significant. The variables of the profitability and the tangibility were found to have positive relationship with the debt ratio. The non-debt tax shield were found to have in general positive relation with the leverage.