• Management & Information Systems Review
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• v.31 no.3
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• pp.117-139
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• 2012

The purpose of this study is to examine of transparency and Corporate Social Responsibility(CSR) on financial performance and firm value. The empirical results are as follows: First, we finds that ROA showed significant effect of all transparency measures exception QAS measure and Tobin's Q showed significant effect of CITSA, SCTSA, SETR and SATSA. Second, 'Total-ROA' and 'ROA' models showed significant positive effects of lnCSR(TranD${\times}$lnCSR) and ROA, also 'Total-Tobin's Q' and 'Tobin's Q' model had same results. Consequently, this study results had that The firms with higher transparency and higher CSR exhibit better financial performance and firm value.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1293-1308
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• 2014

The cause of privacy extrusion in credit card company at 2014 is usage of the original data in test system. By Electronic banking supervision regulations of the Financial Supervisory Service and Information Security business best practices of Finance information technology (IT) sector, the data to identify the customer in the test system should be used to convert. Following this guidelines, Financial firms use converted customer identificaion data by loading in test system. However, there is some risks that may be introduced unintentionally by user mistake or lack of administrative or technical security in the process of testing. also control and risk management processes for those risks did not studied. These situations are conducive to increasing the compliance violation possibility of supervisory institution. So in this paper, we present and prove the process to eliminate the compliance violation possibility of supervisory institution by controlling and managing the unidentified conversion customer identification data and check the effectiveness of the process.

• Knowledge Management Research
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• v.22 no.1
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• pp.21-37
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• 2021

The purpose of this study is to explore financial investment knowledge related to multi-strategy, which is not generally shared. Through case studies, we will share it with the domestic hedge fund market. Since the era of full-fledged private equity hedge funds in Korea opens, many funds are created; however, reality is that there is a lack of diversity in strategies. Initially, it started with a simple stock long/short strategy, and various strategies such as mezzanine and alternative investments are in use but funds using multi-strategy are limited. This study aims to present an empirical application plan for hedge fund management strategies using a case study. It will specifically focus on process of achieving Absolute Return using the Multi Strategy technique actively used in securities firms' Prop Trading. With the results of this study, we intend to contribute to those fund managers and desired researchers who are utilizing multiple strategies in the hedge fund management to pursue Absolute Return and to help them strengthening their financial knowledge and competitiveness.

• The Korean Journal of Financial Management
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• v.27 no.1
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• pp.181-208
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• 2010

In July 2007, Korean government has passed "The Capital Market and Financial Investment Services Act" to further develop the capital markets and the Act was to become effective in February 2009. Using a large sample of Korean firms, we have examined (i) the effect of underwriting activities on the firm value (bond spread) comparing commercial bank and investment bank, and (ii) the determinants of the firm value changes following underwriting activities of bank. To test our goal, we collected a wide range of samples of data for bond issuing activities executed by Korean firms listed on the Korea Stock Exchange (KSE) between 2000 and 2003. Our paper is distinguished from previous studies on this subject in a way that we analyzed the effect of corporate bond underwriting activities with regard to commercial banking and investment banking. Initially, we set up a hypothesis that "Certification View" and "Conflict-of-interest View" are major driving forces behind cross-firm differences in performance following bond issuance. We find that, in general, underwriting by investment bank (securities company) brings a positive effect on the firm value (spread between bench mark rate and bond issuing rate). This result indicates that firm value has been negatively affected by the bank underwriting and provides the evidence for "Conflict-of-interest View" in Korea. Our studies have also revealed that any change in firm value following bond issuance is positively related with the firm size (total asset), operating performance, liquidity (cashflow), and equity ownership by foreign investors. Overall, our results support the view that bank underwriting activities can play an important role in determining firm value and financial strategies under "The Capital Market and Financial Investment Services Act" of 2007.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.31-57
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• 1991

Korean firms of all sizes, from virtually every industry, have used and are using the term "excessive competition" to describe the state of their industry and to call for government interventions. Moreover, the Korean government has frequently responded to such calls in various ways favorable to the firms, such as controlling entry, curbing capacity investments, or allowing collusion. Despite such interventions' impact on the overall efficiency on the Korean economy as well as on the wealth distribution among diverse groups of economic agents, the term "excessive competition", the basis for the interventions, has so far escaped rigorous scrutiny. The objective of this paper is to clarify the notion of "excessive competition" and "over-investment" which usually accompanies "excessive competition", and to examine the circumstances under which they might occur. We first survey the cases where the terms are most widely used and proceed to examine those cases to determine if competition is indeed excessive, and if so, what causes "excessive competition". Our main concern deals with the case in which the firms must make investment decisions that involve large sunk costs while facing uncertain demand. In order to analyze this case, we developed a two period model of capacity precommitment and the ensuing competition. In the first period, oligopolistic firms make capacity investments that are irreversible. Demand is uncertain in period 1 and only the distribution is known. Thus, firms must make investment decisions under uncertainty. In the second period, demand is realized, and the firms compete with quantity under realized demand and capacity constraints. In the above setting, we find that there is "no over-investment," en ante, and there is "no excessive competition," ex post. As measured by the information available in period 1, expected return from investment of a firm is non-negative, overall industry capacity does not exceed the socially optimal level, and competition in the second period yields an outcome that gives each operating firm a non-negative second period profit. Thus, neither "excessive competition" nor "over-investment" is possible. This result will generally hold true if there is no externality and if the industry is not a natural monopoly. We also extend this result by examining a model in which the government is an active participant in the game with a well defined preference. Analysis of this model shows that over-investment arises if the government cannot credibly precommit itself to non-intervention when ex post idle capacity occurs, due to socio-political reasons. Firms invest in capacities that exceed socially optimal levels in this case because they correctly expect that the government will find it optimal for itself to intervene once over-investment and ensuing financial problems for the firms occur. Such planned over-investment and ensuing government intervention are the generic problems under the current system. These problems are expected to be repeated in many industries in years to come, causing a significant loss of welfare in the long run. As a remedy to this problem, we recommend a non-intervention policy by the government which creates and utilizes uncertainty. Based upon an argument which is essentially the same as that of Kreps and Wilson in the context of a chain-store game, we show that maintaining a consistent non-intervention policy will deter a planned over-investment by firms in the long run. We believe that the results obtained in this paper has a direct bearing on the public policies relating to many industries including the petrochemical industry that is currently in the center of heated debates.

• Management & Information Systems Review
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• v.36 no.3
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• pp.151-165
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• 2017

This study investigates the effect of revenue recognition by percentage of completion method on financial analysts' earnings forecasting information in order industry. Specifically, we examines how the analysts' earnings forecast errors and biases differ according to whether or not to report the unbilled revenue account balance and the level of unbilled revenue account balance. The sample consists of 453 firm-years listed in Korea Stock Exchange during the period from 2010 to 2014 since the information on unbilled revenue accounts can be obtained after the adoption of K-IFRS. The results are as follows. First, we find that the firms with unbilled revenue account balances have lower analysts' earnings forecast accuracy than the firms who do not report unbilled revue account balances. In addition, we find that the accuracy of analysts' earnings forecasts decreases as the amount of unbilled revenue increases. Unbilled revenue account balances occur when the revenue recognition of the contractor is faster than the client. There is a possibility that managerial discretionary judgment and estimation may intervene when the contractor calculates the progress rate. The difference between the actual progress of the construction and the progress recognized by the company lowers the predictive value of financial statements. Our results suggest that the analysts' earnings forecasts may be more difficult for the firms that report unbilled revenue balances as applying the revenue recognition method based on the progress criteria. Second, we find that the firms reporting unbilled revenue account balances tend to have higher the optimistic biases in analysts' earnings forecast than the firms who do not report unbilled revenue account balances. And we find that the analysts' earnings forecast biases are increases as the amount of unbilled revenue increases. This study suggests an effort to reduce the arbitrary adjustment and estimation in the measurement of the progress as well as the introduction of the progress measurement method which can reflect the actual progress. Investors are encouraged to invest and analyze the characteristics of the order-based industry accounting standards. In addition, the results of this study empower the accounting transparency enhancement plan for order industry proposed by the policy authorities.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.146-173
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• 2014

Extant studies have explained that firm's innovations including technological product and process innovations contribute to its competitive advantage and growth, thereby supporting competitiveness and growth of industry. These studies, however, have focused mainly on the role and effect of technological change that is primarily measured by the patent numbers and R&D intensity. Aside from these traditional streams, there has been growing interest on the impact by various dimensions of innovation including non-technological innovations. Apart from the discussions on the dimensions and scope of innovation, stages or processes of innovation also have been studied. Extant studies on innovation process model, however, has limited its interests in the structure of the transformation of knowledge. This study have established a comprehensive model embracing operational and financial performance to investigate the causal paths between innovation and firm performance. Using multi-level generalized linear model with path analysis, this study have found results as follows: First, the processes from innovative activities to innovation output and outcomes including operational and financial performance at firm level were verified. Secondly, the influence of innovation decreases gradually as the distance away from the direct outputs of the innovation increase in the direction of financial outcomes. Third, the effect of innovation on the sales growth rate is higher for small businesses than for medium-sized businesses. The effect of innovation on the profit rate, however, is significant only for medium-sized businesses. For large businesses, innovation has no positive significant impact on any financial performance at all. Fourth, Fourth, the appropriability of innovation has positive impacts on innovative performance, patent applications, and operational performance.

• Management & Information Systems Review
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• v.28 no.3
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• pp.161-189
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• 2009

The sub-prime crisis led to the collapse of US investment banks which were considered highly competitive during the Asian Financial Crisis. The event gave us a lesson on importance of the financial supervision. Additionally concerns rise over the fact that the role model of the Capital Market Law, created for the purpose of developing the capital market, is the US investment banks. This paper investigates if the prudential regulations, among them especially the capital regulation, are able to prevent the risk the arises from Korean financial firms operating investment bank business. The current capital requirement regulation, Net Capital Ratio(NCR), is not sufficient, because it's nature of being a ratio makes the NCR ineffective when assets and liabilities are concurrently rising. We also verified the internal model which measured the market risk, by comparing the US investment and Korean banks' diversification effect. The result of the test is that it is difficult to conclude the internal model has a critical defect. This paper's contribution is that it is not sufficient use only the capital regulation in supervising financial markets.

• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.297-311
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• 2011

This paper deals with a strategic investment decision model for improving investment profit in shipping industry. Despite the quantitative expansion of Korean shipping business, many shipping firms have suffered financial difficulties due to financial and operating risks that result from the characteristics of capital-intensive business as well as of volatility of shipping markets. As a result, managers in charge of making an investment decision, particularly in tramper business sector, are required to take both financial and operating risk factors into consideration. Put it differently, managers are strongly recommended to avoid these risks by ship asset play; buy-low and sell-high, which results in considerable capital gain and cost reduction. In addition, managers in shipping industry are also recommended to consider the ship chartering investment alternative when the freight markets show extreme volatility as the case of 2008 triggered by sub-prime mortgage financial crisis in USA. For example, the BDI suffered plunging down from 1000 in 2008 to 100 in 2010. Consequently, the 4th largest shipping company in Korea, DAEHAN Shipping Co., has collapsed primarily due to excessive tonnage expansion during the peak time of bulk market. In sum, the strategic investment decision model, suggested in this paper, is designed to include such factors as capital gain by asset play, timely chartering for alternative shipping service, and optimization of operating profit by tonnage adjustment in accordance with change in the shipping markets concerned.