• Informatization Policy
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• v.27 no.2
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• pp.20-39
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• 2020

This paper introduces the Cryptocurrency Market Potential Index (CMPI) in order to measure the potential of the blockchain-backed cryptocurrency. Adopting the Distributed Ledger Technology (DLT) system as a conceptual framework, the whole process from development to implementation and adoption of blockchain-backed cryptocurrency are examined. This paper selects 30 variables and employs factor analysis for multivariate analysis to produce the CMPI for a total of 213 countries. The results show that although cryptocurrency is decentralized, its development and usage might still be very centralized in Europe, North America, hotspots in the Asia-Pacific, Middle East, and CIS regions. This result also highlights how important development and implementation are before adoption so that consequent financial transactions can take place.

• Journal of Korea Foundry Society
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• v.42 no.2
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• pp.83-93
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• 2022

Throughout this research course, we have analyzed the financial situation of more than 2,700 companies using credit evaluation disclosures from 2017 to 2019. The population was gathered based on the certification of Ppuri companies and Ppuri Expertise companies through the Korea National Ppuri Industry Center, accompanied by the NICE credit evaluation index. For the first time in Korea, we wanted to look at growth, profitability, and stability through financial analysis of the Ppuri industry. Through an indepth analysis, we identified operating income (rate), net income (rate), asset size, and debt ratio, along with three years of Ppuri company workers and total sales fluctuations, and looked at the financial structure per capita. In addition, financial status per person was compared by dividing Ppuri companies into six groups by employee size. Groups were 10 or fewer people, 11 to 20 people, 21 to 50 people, 51 to 200 people, 201-300 people, and 300 or more people; single individual companies were excluded for research convenience. Overall, the financial situation of Ppuri companies was judged to be in a very bad downturn, and financial indicators deteriorated over the course of the three years of investigation. In particular, the smaller the number of employees, the greater the financial fluctuations were and the worse the situations were. Among Ppuri companies, the casting industry, which is the technical starting point for the value chain of the industry, was found to also be in a very bad state, with continued workforce declines, total assets and sales reductions at severe levels, and operating income (rate) and net income (rate) also very poor. This is why we need a suitable and feasible policy direction, something that is difficult but must be allowed to develop.

• Land and Housing Review
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• v.4 no.1
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• pp.43-54
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• 2013

This This paper investigates the variation of the factors to determinate housing price in Seoul metropolitan area after sub-prime financial crisis, in Korea, using a VAR model. The model includes housing price and housing rent (Jeonse) in Seoul metropolitan area from 1999 to 2011, and uses interest rate, real GDP, KOSPI, Producer Price Index and practices to impulse response and variance decomposition analysis to grasp the dynamic relation between a variable of macro economy and and a variable of housing price. Data is classified to 2 groups before and after the 3rd quater of 2008, when sub-prime crisis occurred; one is from the 1st quater of 1999 to the 3rd quater of 2008, and the other is from the 2nd quater of 1999 and the 4th quater of 2011. As a result, comparing before and after sub-prime crisis, housing price is more influenced by its own variation or Jeonse price's variation instead of interest rate and KOSPI. Both before and after sub-prime financial crisis, Jeonse price is also influenced by its own variation and housing price. While after sub-prime financial crisis, influences of Producer Price Index, KOSPI and interest rate were weakened, influence of real GDP is expanded. As housing price and housing rent are more influenced by real economy factors such as GDP, its own variation than before sub-prime financial crisis, the recent trend that the house prices is declined is difficult to be converted, considering domestic economic recession and uncertainty, continued by Europe financial crisis. In the future to activate the housing business, it ia necessary to promote purchasing power rather than relaxation of financial and supply regulation.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.405-413
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• 2015

The purpose of this study is to measure the level of competition in the degree of Regional Public Hospital that can provide a basis for establishing an effective management strategy and analysis of the financial performance. Investigation period of the Regional Public Hospital HHI(Herfindahl-Hirschman Index) over three years from 2010, which was unknown until 2012, index and management performance evaluation criteria, a total of 31 were selected as Regional Public Hospital surveyed. In the conclusions, it showed that the most concentrated market with high financial performance, a significant correlation between the degree of local competition and financial indicators showed. The Regional Public Hospital for trends according to the degree of competitive local medical market and therefore is required to establish policies and practices to ensure competitiveness and public interest in the region. The Regional Public Hospital in order to preempt the lead for the competitiveness of other institutions will be considered in the strategy, such as improving medical services and capital investment.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Asia-Pacific Journal of Business
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• v.14 no.2
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• pp.51-61
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• 2023

Purpose - Since COVID-19, the government's expansion of liquidity to stimulate the economy has resulted in an increase in private debt and an increase in asset prices of such as real estate and stocks. The recent sharp rise of the US Federal fund rate and tapering by the Fed have led to a fast rise in domestic interest rates, putting a heavy burden on the Korean economy, where the level of household debt is very high. Excessive household debt might have negative effects on the economy, such as shrinking consumption, economic recession, and deepening economic inequality. Therefore, now more than ever, it is necessary to identify the causes of the increase in household debt. Design/methodology/approach - Main methodology is regression analysis. Dependent variable is household loans from depository institutions. Independent variables are consumer price index, unemployment rate, household loan interest rate, housing sales price index, and composite stock price index. The sample periods are from 2017 to May 2022, comprising 72 months of data. The comparative analysis period before and after COVID-19 is from January 2017 to December 2019 for the pre-COVID-19 period, and from Jan 2020 to December 2022 for the post-COVID-19 period. Findings - Looking at the results of the regression analysis for the entire period, it was found that increases in the consumer price index, unemployment rate, and household loan interest rates decrease household loans, while increases in the housing sales price index increase household loans. Research implications or Originality - Household loans of depository institutions are mainly made up of high-credit and high-income borrowers with good repayment ability, so the risk of the financial system is low. As household loans are closely linked to the real estate market, the risk of household loan defaults may increase if real estate prices fall sharply.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.105-113
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• 2016

This study analyzed and verified panel data based on CSMAR (China Stock Market & Accounting Research) DB from 2002 to 2014 in order to find out significant differences of conservative accounting before and after Chinese companies adopted international accounting standards. Financial changes in companies can occur at the point of change in accounting standards, and as the difference would affect conservative accounting, it is important to understand conservatism in financial transaction. In this study, earnings per share and price, return on equity, and debt ratio were measured. As a result of analysis, conservative accounting has increased after the introduction of accounting standards, and as the debt ratio was higher, the proportion of conservative accounting was higher. Thus, at a certain point of change in accounting standards, companies apply conservative accounting in order to improve reliability in an unstable future financial environment. Therefore, this study is expected not only to practically influence business practice in changes in GAAP rules but also to provide useful guidance for future studies.

• Korea Journal of Hospital Management
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• v.27 no.3
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• pp.26-38
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• 2022

Purposes: We analyzed the profitability determinants of regional public hospitals during the entire period between 2010 and 2020 and the period before and after COVID-19. We intended to provide fundamental data for developing publicness evaluation index and task of establishing and expanding regional public hospitals. Methodology: The financial and non-financial information of the regional public hospitals were used as the main analysis data; The financial data was established by the Center for Public Healthcare Policy of National Medical Center, and the non-financial data by the Health Insurance Review and Assessment Service. T-test and regression analysis were used. Findings: The results can be summarized in two. First, the main determinants of profitability of the regional public hospitals were appeared to be the total asset turnover rate and the labor cost rate. Second, during the COVID-19 pandemic in the regional public hospitals, the number of sickbeds, the number of isolation rooms, the total asset turnover rate and the labor cost rate appeared to be the factor worsening the profitability. Practical Implication: The results of this study suggests that the management of the regional public hospitals is not aiming for the profit making, but it performs the functions as the community healthcare safety net such as controlling infectious diseases.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.27-35
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• 2019

The paper examines the level of disclosure on Islamic banks' performance in the United Arab Emirates (UAE). The data was collected through content analysis of annual reports and financial statements of all fully-fledged Islamic banks working in the UAE over the period 2009 to 2013. Return on Assets is used as a proxy for the performance of Islamic banks while disclosure index is used as a proxy for Islamic banks' disclosure. Also, predetermined variables are used in the study like Size, Deposits, Non-Performing Investments and Capital to Risk Weighted Assets Ratio. Two-Stage Least-Square regression method is used to check the interdependence relationships between disclosure and performance of Islamic banks in the UAE. The results show a significant relationship between performance and disclosure in the UAE Islamic banks. Our regression results show that Islamic banks with higher levels of disclosure lead to higher operating performance. Furthermore, the performance has a great impact on the level of disclosure which means Islamic banks with high performance measures will disclose more information for investors and other institutions in order to reduce the cost of equity and increase their values in the market. This study is considered as a battery for further studies in the relationship between disclosure and financial performance of Islamic banks at a global level.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.113-124
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• 2021

The study investigates how financial markets respond to a shock to tone and semantic similarity of the Bank of Thailand press releases. The techniques in natural language processing are employed to quantify the tone and the semantic similarity of 69 press releases from 2010 to 2018. The corpus of the press releases is accessible to the general public. Stock market returns and bond yields are measured by logged return on SET50 and short-term and long-term government bonds, respectively. Data are daily from January 4, 2010, to August 8, 2019. The study uses the Structural Vector Auto Regressive model (SVAR) to analyze the effects of unanticipated and temporary shocks to the tone and the semantic similarity on bond yields and stock market returns. Impulse response functions are also constructed for the analysis. The results show that 1-month, 3-month, 6-month and 1-year bond yields significantly increase in response to a positive shock to the tone of press releases and 1-month, 3-month, 6-month, 1-year and 25-year bond yields significantly increase in response to a positive shock to the semantic similarity. Interestingly, stock market returns obtained from the SET50 index insignificantly respond to the shocks from the tone and the semantic similarity of the press releases.