• The Korean Journal of Financial Management
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• v.26 no.1
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• pp.95-125
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• 2009

This paper examines the disciplinary effect of deposits using the semiannual accounting data of mutual savings banks(henceforth 'MSBs') in Korea for the period of 2003 through 2007. I find overall strong evidence in favor of the existence of market discipline in the industry. MSBs with higher BIS ratio and lower NPL ratio turn out to have higher increase rate of deposits than MSBs with lower such ratios. The coefficient of NPL ratio becomes greater with time, suggesting that the effect is cumulative. It turns out that depositors respond more sensitively to NPL ratio than BIS ratio in a period of MSB failure. On the other hand, MSBs turn out to act very positively responding to the depositors' discipline. They increase BIS ratio or decrease NPL ratio following the previous decrease in deposits. Government authorities need to make more efforts to develop a suitable incentive system (e.g. penalties on a false disclosure) to improve the efficiency of disclosure by MSBs. Moreover, they need to acknowledge the importance of NPL ratio as a market disciplinary tool which has been becoming more important, especially in times of MSB failure.

• Journal of Nutrition and Health
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• v.48 no.6
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• pp.542-557
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• 2015

Purpose: The aim of this study is to develop an evaluation tool for operation of food safety and nutrition education projects for middle class elderly using the concept of the balanced score card. Methods: After the draft of the evaluation tool for the elderly training projects was completed, it was revised into the questionnaire and the validity of the indicators was tested by the Delphi group. The validity of the indicators was rated using a 5-point scale. The Delphi group consisted of 26 experts in the education sector, 16 government officials, and 24 professionals of the related area in communities. The first round test was conducted from July 9 to July 17, 2012, and 45 persons responded. The second round test was conducted from July 18 to July 25 and 32 persons responded. Results: The indicators, which were answered by more than 75 percent of the experts as 'agree' (4 points), 'strongly agree' (5 point) were included as the final indicators for the evaluation tool: 28 items out of 36 in outcome perspectives, 9 items out of 12 in process perspectives, and 17 out of 20 items in structure perspectives. The score was allocated as 50 points for outcome indicators, 20 points for process indicators, and 30 points for structure indicators. Conclusion: Completion of the evaluation tool is a prerequisite to determine whether the program is effectively implemented. The monitoring tool developed in the study could be applied for identification of the most optimal delivery path for the food safety and nutrition education program, for the spread of the food safety and nutrition education program for middle class elderly.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.155-164
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• 2024

This study proposes an unsupervised learning-based clustering model to estimate the ESG ratings of domestic public institutions. To achieve this, the optimal number of clusters was determined by comparing spectral clustering and k-means clustering. These results are guaranteed by calculating the Davies-Bouldin Index (DBI), a model performance index. The DBI values were 0.734 for spectral clustering and 1.715 for k-means clustering, indicating lower values showed better performance. Thus, the superiority of spectral clustering was confirmed. Furthermore, T-test and ANOVA were used to reveal statistically significant differences between ESG non-financial data, and correlation coefficients were used to confirm the relationships between ESG indicators. Based on these results, this study suggests the possibility of estimating the ESG performance ranking of each public institution without existing ESG ratings. This is achieved by calculating the optimal number of clusters, and then determining the sum of averages of the ESG data within each cluster. Therefore, the proposed model can be employed to evaluate the ESG ratings of various domestic public institutions, and it is expected to be useful in domestic sustainable management practice and performance management.

• Korean Journal of Agricultural Science
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• v.35 no.1
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• pp.85-100
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• 2008

The United States Department of Agriculture (USDA) funded collaborative project on The Economic Feasibility Analysis of Crop Cultivation Practice Project in Pirganj and Kurigram Districts in Bangladesh will started during 2008-2012, for 4 years with total project cost of US$ 571,270. The project will be implemented in 6 villages; has 1,097 hectares areas which is divided into 948 hectares of agricultural land, 52 hectares of forest land and 345 hectares of other land, covered 1,059 households equal to 5,305 persons in Pirganj and Kurigram districts The project has proposed to be implemented in joint collaboration by Bangladesh Agricultural Research Council (BARC), Bangladesh Agricultural Research Institute (BARI) and Rangpur Dinajpur Rural Service (RDRS) Bangladesh with full participation of the farmers' groups of respective project site. The specific objectives of the project are: (1) to estimate the productivity of paddy, wheat, maize, tobacco and sugarcane (2) to determine the cost of production and returns to the above mentioned crops (3) to study the interrelationship between inputs and output of the above mentioned crops and (4) to examine the resource utilization patterns at farm level. In this project analysis, the net incremental profit is US$33,028. The expected incremental project benefit and incremented production cost are estimated as US$ 219,959 and US$ 186,931 respectively. The financial decision making criteria would be followed in this crop cultivation practice project. After the project implementation, the expected project benefits are assumed to be continued for 15 years. The benefit cost ratio (B/C) of the project is estimated at 1.077 (table 11) when using discount rate of 10% as an opportunity cost of capital in Bangladesh. FIRR of project is estimated at 26.15% which is bigger than the opportunity cost by more than double. So this project is financially feasible and acceptable. Therefore, this project should be extended to other areas to increase the farm income and economic growth of marginal poor farmers in Bangladesh.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.2
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• pp.129-139
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• 2013

This paper is targeted on proposing ameliorating alternative to performance assessment method of GSEM through evaluating the current one, which is initiated by SMBA to induce fair competition among 5 GSEM across the country and accommodate the quality improvement of entrepreneurship education since 2005 after beginning the SMBA support, from the perspective of BSC(Balanced Scorecard) tool. Ultimately, it complements the policy defects of SMBA over GSEM, in particular, in the process of performance assessment and management. This paper carries out two studies as follow. First, throughout reviewing the previous studies relating to BSC applications to non-profit organization, it set out the direction of introducing BSC in assessing performance of GSEM in order to enhance its effectiveness. Second, it evaluate the rationality of performance assessing tools apllied to GSEM by SMBA on the basis of BSC application over non-profit organization, especially in education institution. Research results shows the following implications. First, the current evaluation system over GSEM is just merely assessment itself and not much contributions for the post performance management. Second, The annual evaluation just remains to check up whether the policy goals are met or not. Third, the current evaluation puts much emphasis just on financial inputs and hardware infra, not considering human resources and utilization of government policy and institution. Fourth, the policy goals are unilaterally focused on entrepreneurs. Fifth, the current evaluation systems do not contain any indexes relating to learning and growth perspectives for concerning sustainable and independent growing up. However, lack of empirical testing require this paper to need the further study in the future.

• Korean Business Review
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• v.11
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• pp.241-253
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• 1998

One form of the anomalies of stock price changes as reaction to earnings information is believed to be caused by the so-called earnings fixation, which is the overreaction of stock prices to earnings. According to the Sloan (1996) study, stock price changes are positively associated with earnings at the time of earnings releases, but the association becomes negative after that, as the early overreaction is corrected. However, the problem in his study is to use cash flows computed by adjusting earnings with appropriate income statement and balance sheet items. As Bahnson et al. (1996) show, these cash flows substantially deviate from SFAS No. 95 cash flows and the sample used in this study is found to be subject to this substantial measurement error. Therefore, the result of Sloan might be driven by this error and the reexamination of earnings fixation is warranted. The results are generally consistent with those in Sloan. First, earnings is positively associated with stock price changes at the time of earnings releases, but the association becomes negative after that. Second, cash flows show a weak association with stock price changes at the time of earnings releases, but the association become stronger thereafter. Third, when seperated from cash flows, accruals have an incremental explanation about stock price changes beyond that of cash flows, accruals have a negative association later on. This finding is consistent with stock price overreaction to accruals, even when more cleaner cash flow data are used.

• Journal of the military operations research society of Korea
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• v.37 no.1
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• pp.49-70
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• 2011

This paper re-evaluated the research on the accounting information's effectiveness in military construction contracts, questioning the former research results on the central army's construction contract that was under the Qualification Assessment System, especially concerning the relations between the accounting information and the bidding ratios as well as the relations between the bidding rates and the defect rates, which targeted between 1 to 10 billions civil engineering, construction, electricity, telecommunication, and environment work types. Unlike the previous results, the relationship between the accounting information and the bidding rates was shown to be considerably limited that the bidding ratio could not be identified through the accounting information, while it could discern the relations with the defect rates. Furthermore, the proven results did not support the hypothesis that the differences in bidding rates could affect the defect ratio. However, through the prediction model of bidding and defect ratios, we could identity the accounting variables that influenced the ratios. Additionally through the results regarding the non-financial indexes in the Pre-Qualification items, the weight on these indexes could be adjusted. In conclusion, the research results has given us new understanding of the problems in the Qualification Assessment System which accounts for the majority of the current military construction contracts and provide validity on the government's expanded implementation of the Lowest Price Award System.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.