• 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.211-232
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• 2014

Recently, there is a growing interest toward social commerce using SNS(Social Networking Service), and the size of its market is also expanding due to popularization of smart phones, tablet PCs and other smart devices. Accordingly, various studies have been attempted but it is shown that most of the previous studies have been conducted from perspectives of the users. The purpose of this study is to derive user-centered CSF(Critical Success Factor) of social commerce from the previous studies and analyze the CSF perception gap between social commerce service providers and users. The CSF perception gap between two groups shows that there is a difference between ideal images the service providers hope for and the actual image the service users have on social commerce companies. This study provides effective improvement directions for social commerce companies by presenting current business problems and its solution plans. For this, This study selected Korea's representative social commerce business Ticket Monster, which is dominant in sales and staff size together with its excellent funding power through M&A by stock exchange with the US social commerce business Living Social with Amazon.com as a shareholder in August, 2011, as a target group of social commerce service provider. we have gathered questionnaires from both service providers and the users from October 22, 2012 until October 31, 2012 to conduct an empirical analysis. We surveyed 160 service providers of Ticket Monster We also surveyed 160 social commerce users who have experienced in using Ticket Monster service. Out of 320 surveys, 20 questionaries which were unfit or undependable were discarded. Consequently the remaining 300(service provider 150, user 150)were used for this empirical study. The statistics were analyzed using SPSS 12.0. Implications of the empirical analysis result of this study are as follows: First of all, There are order differences in the importance of social commerce CSF between two groups. While service providers regard Price Economic as the most important CSF influencing purchasing intention, the users regard 'Trust' as the most important CSF influencing purchasing intention. This means that the service providers have to utilize the unique strong point of social commerce which make the customers be trusted rathe than just focusing on selling product at a discounted price. It means that service Providers need to enhance effective communication skills by using SNS and play a vital role as a trusted adviser who provides curation services and explains the value of products through information filtering. Also, they need to pay attention to preventing consumer damages from deceptive and false advertising. service providers have to create the detailed reward system in case of a consumer damages caused by above problems. It can make strong ties with customers. Second, both service providers and users tend to consider that social commerce CSF influencing purchasing intention are Price Economic, Utility, Trust, and Word of Mouth Effect. Accordingly, it can be learned that users are expecting the benefit from the aspect of prices and economy when using social commerce, and service providers should be able to suggest the individualized discount benefit through diverse methods using social network service. Looking into it from the aspect of usefulness, service providers are required to get users to be cognizant of time-saving, efficiency, and convenience when they are using social commerce. Therefore, it is necessary to increase the usefulness of social commerce through the introduction of a new management strategy, such as intensification of search engine of the Website, facilitation in payment through shopping basket, and package distribution. Trust, as mentioned before, is the most important variable in consumers' mind, so it should definitely be managed for sustainable management. If the trust in social commerce should fall due to consumers' damage case due to false and puffery advertising forgeries, it could have a negative influence on the image of the social commerce industry in general. Instead of advertising with famous celebrities and using a bombastic amount of money on marketing expenses, the social commerce industry should be able to use the word of mouth effect between users by making use of the social network service, the major marketing method of initial social commerce. The word of mouth effect occurring from consumers' spontaneous self-marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers; in this context, the word of mouth effect should be managed as the CSF of social commerce. Third, Trade safety was not derived as one of the CSF. Recently, with e-commerce like social commerce and Internet shopping increasing in a variety of methods, the importance of trade safety on the Internet also increases, but in this study result, trade safety wasn't evaluated as CSF of social commerce by both groups. This study judges that it's because both service provider groups and user group are perceiving that there is a reliable PG(Payment Gateway) which acts for e-payment of Internet transaction. Accordingly, it is understood that both two groups feel that social commerce can have a corporate identity by website and differentiation in products and services in sales, but don't feel a big difference by business in case of e-payment system. In other words, trade safety should be perceived as natural, basic universal service. Fourth, it's necessary that service providers should intensify the communication with users by making use of social network service which is the major marketing method of social commerce and should be able to use the word of mouth effect between users. The word of mouth effect occurring from consumers' spontaneous self- marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers. in this context, it is judged that the word of mouth effect should be managed as CSF of social commerce. In this paper, the characteristics of social commerce are limited as five independent variables, however, if an additional study is proceeded with more various independent variables, more in-depth study results will be derived. In addition, this research targets social commerce service providers and the users, however, in the consideration of the fact that social commerce is a two-sided market, drawing CSF through an analysis of perception gap between social commerce service providers and its advertisement clients would be worth to be dealt with in a follow-up study.

• The Journal of Small Business Innovation
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• v.19 no.2
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.

• Korean Journal of Environmental Agriculture
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• v.19 no.3
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• pp.194-200
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• 2000

The amount of swine wastewater reaches about $197,000m^3$ per day at live-stock houses in the whole country. A half of the swine wastewater resources are too small to be restricted legally. This untreated wastewater causes the eutrophication in the water bodies. In case of swine wastewater treatment, the solid-liquid separation must be performed because feces(solid phase) and urine(liquid phase) have large differences in nitrogen and phosphorus concentration. It is necessary to assess exactly the concentration of the pollutants in swine wastewater for planning the wastewater treatment facilities. A full-scale operation was carried out in K city and the plant is consists of conventional plant, the supplementary flocculation basin of chemical treatment process and $anaerobic{\cdot}aerobic$ basin for nitrogen removal. The improved full-scale swine wastewater treatment plant removed the $1,500{\sim}3,000mg/l$ of total-nitrogen(T-N) to 120mg/l of T-N and $131{\sim}156mg/l$ of total-phosphorus(T-P) to $0.15{\sim}1.00mg/l$ of T-N. Accordingly, as a results of operational improvement, the removal efficiencies of T-N and T-P were over $92{\sim}96%$, 99%, respectively. The continuous supply of organic carbon sources and the state of pH played important roles for the harmonious metabolism in anaerobic basin and the pH value of anaerobic basin maintained at about 9.0 for the period of the study.

• Journal of Environmental Impact Assessment
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• v.27 no.2
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• pp.124-138
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• 2018

This research was conducted to examine the availability of spatial data for assessing absorption rates of $CO_2$ in the forest of Ansan-si and evaluate the validity of methods that analyze $CO_2$ absorption. To statistically assess the $CO_2$ absorption rates per year, the 1:5,000 Digital Forest-Map (Lim5000) and Standard Carbon Removal of Major Forest Species (SCRMF) methods were employed. Furthermore, Land Cover Map (LCM) was also used to verify $CO_2$ absorption rate availability per year. Great variations in $CO_2$ absorption rates occurred before and after the year 2010. This was due to improvement in precision and accuracy of the Forest Basic Statistics (FBS) in 2010, which resulted in rapid increase in growing stock. Thus, calibration of data prior to 2010 is necessary, based on recent FBS standards. Previous studies that employed Lim5000 and FBS (2015, 2010) did not take into account the $CO_2$ absorption rates of different tree species, and the combination of SCRMF and Lim5000 resulted in $CO_2$ absorption of 42,369 ton. In contrast to the combination of SCRMF and Lim5000, LCM and SCRMF resulted in $CO_2$ absorption of 40,696 ton. Homoscedasticity tests for Lim5000 and LCM resulted in p-value <0.01, with a difference in $CO_2$ absorption of 1,673 ton. Given that $CO_2$ absorption in forests is an important factor that reduces greenhouse gas emissions, the findings of this study should provide fundamental information for supporting a wide range of decision-making processes for land use and management.

• Korean Security Journal
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• no.22
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• pp.113-144
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• 2010

Bioterrorism is becoming more attractive to terrorist groups owing to the dramatic increase in the utility and lethality of biological weapons in line with today's cutting-edge biological science and technology. The Republic of Korea is facing both internal and external terrorist threats, as well as the possible biological warfare by North Korea. Therefore, it is essential to establish an effective bioterrorism response system in the ROK. In order to come up with the adequate response system for the ROK, an in-depth study has been conducted on the current bioterrorism response system of the U.S. whose preparedness is considered relatively adamant. As a result, the following facts have been found: (1)the legislation with regard to bioterrorism has been established or amended according to the current situation in the U.S., (2)the counter terrorism activities have been integrated with the Department of the Homeland Security as the central agency in order to maximize the national CT capacity, (3)Specific procedures and instructions to cope with bioterrorism have been made into manuals so as to enhance the working-level response capabilities. Next, the analysis on the ROK's bioterrorism response system has been performed in various categories, including the legislation system, task role distribution, cooperative relations, and resource application. It turned out that the ROK's legislation basis is relatively weak and it lacks the apparatus to integrate the bioterrorism response activities on the national level. The shortage of the adequate response facilities and resources, as well as the poor management of manpower have also emerged as problems that hinder the effective CT implementations. Through an analytical and comparative study of the U.S. and the ROK systems, this paper presents several ways to ameliorate improve the current system in the ROK as follows: (1)establish the anti-terrorism law, which would be the basic legal basis for the bioterrorism-related matters; and make revisions to the disaster-related legislation, relevant to bioterrorism response activities, (2)establish an integrated body that has a powerful authority to coordinate the relevant CT agencies; and converge the decentralized functions to maximize the overall response capacity, (3)install the laboratories with a high biosafety level and secure enough of the strategic medical stock-pile, (4)enhance the ability of the inexperienced response personnel by providing with a manual that has detailed instructions.

• Journal of Korean Society of Forest Science
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• v.97 no.6
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• pp.605-610
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• 2008

This study was carried out to investigate the short-term (3 years) effect of thinning on aboveground carbon storage for 34-year-old (site 1) and 45-year-old (site 2) Korean pine (Pinus koraiensis Siebold et Zuccarini) plantations with different diameter class and site quality located in Gwangneung experimental forest. Thinning was manually carried out in consideration of basal area in 2004 (site 1 : 30% and 60% of basal area removed and site 2 : 60% of basal area removed). In 2004 and 2007, DBH and tree height were measured to analyze the changes in carbon storage after thinning. In the sites of 60% of basal area removed, although the mean DBH of site 1 was higher than that of site 2, mean annual carbon storage increment in site 2 ($6.5Mg\;C\;ha^{-1}yr^{-1}$) was about 3 times higher than that in site 1 ($2.3Mg\;C\;ha^{-1}yr^{-1}$). The reason for this result was probably due to higher stem density and site quality in site 2 compared to site 1. In site 2, mean annual carbon storage increment in thinned plot ($6.5Mg\;C\;ha^{-1}yr^{-1}$) was about 1.3 times higher than that in control ($5.2Mg\;C\;ha^{-1}yr^{-1}$). The results suggest that the stem density and site quality may be much more related to the aboveground carbon storage compared to diameter class. In addition, it is needed to consider these two factors for determining whether thinning is a feasible management alternative for the increase in aboveground carbon sequestration.

• Korean Journal of Agricultural Science
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• v.20 no.1
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• pp.25-33
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• 1993

This study was conducted to obtain necessary informations for improving of wildlife rearing management. The data was gathered by surveying with questionaire. One hundred and eighty farmers which was 60 of deer and pheasant, 30 of wild boar and fox rearing farmers respectively were investigated during the summer in 1992. The results of this study are as follows : 1. Most of managers considered their rearing as a side job but agriculture was appointed as a main job from most of them except wild boar managers. 2. The major cost items were breeding stock and feeding which occupied over than half. 3. The yearly profit was the highest in deer(25.5%) but the lowest in wild boar(10.3%). 4. The break-even point was the highest in wild boar(24 mil. won) but the lowest in pheasant(7.3 mil. won). 5. The optimum sales scale for a year was deer(11 heads), Pheasant(1,027 heads), Wild boar(69 heads) and Fox (102 heads).

• The Korean Journal of Financial Studies
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• v.3 no.1
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• pp.233-265
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• 1996

We examine the impact of public and private information on price movements using the thirty DJIA stocks and twenty-one NASDAQ stocks. We find that the standard deviation of daily returns on information days (dividend announcement, earnings announcement, insider purchase, or insider sale) is much higher than on no-information days. Both public information matters at the NYSE, probably due to masked identification of insiders. Earnings announcement has the greatest impact for both DJIA and NASDAQ stocks, and there is some evidence of positive impact of insider asle on return volatility of NASDAQ stocks. There has been considerable debate, e.g., French and Roll (1986), over whether market volatility is due to public information or private information-the latter gathered through costly search and only revealed through trading. Public information is composed of (1) marketwide public information such as regularly scheduled federal economic announcements (e.g., employment, GNP, leading indicators) and (2) company-specific public information such as dividend and earnings announcements. Policy makers and corporate insiders have a better access to marketwide private information (e.g., a new monetary policy decision made in the Federal Reserve Board meeting) and company-specific private information, respectively, compated to the general public. Ederington and Lee (1993) show that marketwide public information accounts for most of the observed volatility patterns in interest rate and foreign exchange futures markets. Company-specific public information is explored by Patell and Wolfson (1984) and Jennings and Starks (1985). They show that dividend and earnings announcements induce higher than normal volatility in equity prices. Kyle (1985), Admati and Pfleiderer (1988), Barclay, Litzenberger and Warner (1990), Foster and Viswanathan (1990), Back (1992), and Barclay and Warner (1993) show that the private information help by informed traders and revealed through trading influences market volatility. Cornell and Sirri (1992)' and Meulbroek (1992) investigate the actual insider trading activities in a tender offer case and the prosecuted illegal trading cased, respectively. This paper examines the aggregate and individual impact of marketwide information, company-specific public information, and company-specific private information on equity prices. Specifically, we use the thirty common stocks in the Dow Jones Industrial Average (DJIA) and twenty one National Association of Securities Dealers Automated Quotations (NASDAQ) common stocks to examine how their prices react to information. Marketwide information (public and private) is estimated by the movement in the Standard and Poors (S & P) 500 Index price for the DJIA stocks and the movement in the NASDAQ Composite Index price for the NASDAQ stocks. Divedend and earnings announcements are used as a subset of company-specific public information. The trading activity of corporate insiders (major corporate officers, members of the board of directors, and owners of at least 10 percent of any equity class) with an access to private information can be cannot legally trade on private information. Therefore, most insider transactions are not necessarily based on private information. Nevertheless, we hypothesize that market participants observe how insiders trade in order to infer any information that they cannot possess because insiders tend to buy (sell) when they have good (bad) information about their company. For example, Damodaran and Liu (1993) show that insiders of real estate investment trusts buy (sell) after they receive favorable (unfavorable) appraisal news before the information in these appraisals is released to the public. Price discovery in a competitive multiple-dealership market (NASDAQ) would be different from that in a monopolistic specialist system (NYSE). Consequently, we hypothesize that NASDAQ stocks are affected more by private information (or more precisely, insider trading) than the DJIA stocks. In the next section, we describe our choices of the fifty-one stocks and the public and private information set. We also discuss institutional differences between the NYSE and the NASDAQ market. In Section II, we examine the implications of public and private information for the volatility of daily returns of each stock. In Section III, we turn to the question of the relative importance of individual elements of our information set. Further analysis of the five DJIA stocks and the four NASDAQ stocks that are most sensitive to earnings announcements is given in Section IV, and our results are summarized in Section V.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.