• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.187-204
• /
• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of Environmental Impact Assessment
• /
• v.4 no.3
• /
• pp.41-48
• /
• 1995

In former times the protection of our environment didn't play an important role due to the fact that emissions and effluents were not considered as serious impacts. However, opinions and scientific measurements meanwhile confirmed that the impacts are more serious than expected. Thus measures to protect our earth has to be taken into consideration. A part of these measures in the Environmental Impact Assessment (EIA). One of the most important parts of the EIA is the collection of basic datas and the following evaluation. Experience out of the daily business of Gerling Consulting Group shows that the content of the EIA has to be revised and enlarged in certain fields. The historical development demonstrated that in areas in which the population and the industrial activities reached high concentration there is a high necessity to develop strict environmental laws and regulations. Maximum values of the concentration of hazardous materials were fixed concerning the emission into and water. Companies not following these regulations were punished. The total amount of environmental offences increased rapidly during the last decade, at least in Germany. During this development the public consciousness concerning environmental affairs increased as well in the industrialized countries. But it could clearly be seen that the development in the field of environmental protection went into the wrong direction. The technologies to protect the environment became more and more sophisticated and terms as: "state of the art" guided more and more to lower emissions, Filtertechnologies and wastewater treatment for example reached a high technical level-but all these sophisticated technologies has one and the same characteristic: they were end-of-the pipe solutions. A second effect was that this kind of environmental protection costs a lot of money. High investments are necessary to reduce the dust emission by another ppm! Could this be the correct way? In Germany the discussion started that the environmental laws reduce the attractivity to invest or to enlarge existing investments within the country. Other countries seem to be not so strict with controlling the environmental laws which means it's simply cheaper to produce in Portugal or Greece. Everybody however knows that this is not the correct way and does not solve the environmental problems. Meanwhile the general picture changes a little bit and we think it changes into the correct direction "End-of-the-pipe" solutions are still necessary but this word received a real negative touch and nobody wants to be brought into connection with this word received a real negative touch and nobody wants to be brought into connection with this word especially in connection with environmental management and safety. Modern actual environmental management starts in a different way. Thoughts about emissions start in the very beginning of the production, they start with the design of the product and modification of traditional modes of production. Basis of these ideas are detailed analyses of products and processes. Due to the above mentioned facts that the public environmental consciousness changed dramatically a continous environmental improvement of each single production plant has to be guarantied. This question is already an important question of the EIA. But it was never really checked in a wholistic approach. Environmental risks have to be taken into considerations during the execution of an EIA. This means that the environmental risks have to be reduced down to a capable risk-level. Environmental risks have to be considered within the phase of planning, during the operation of a plant and after shut down. The experience shows that most of the environmental relevant accidents were and caused by human fault. Even in highly protected plants the human risk-factor can not be excluded during evaluation of the risk-potential. Thus the approach of an EIA has to regard technical evaluations as well as organizational thoughts and the human factor. An environmental risk is a threat to the environment. An analysis of the risk concerning the organizational and human aspect however never was properly executed during an EIA. A possible solution could be to use an instrument as the actual EMAS (Environmental Management System) of the EC for more accurate evaluation of the impact to the environment during an EIA. Organizations or investors could demonstrate by an approved EMAS or even by showing their installment of EMAS that not only the technical level of the planned investment meets the requested standards but as well the actual or planned management is able to reduce the environmental impact down to a bearable level.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.9 no.1
• /
• pp.119-132
• /
• 2014

This study analyzed the failure prediction model of the firms listed on the KOSDAQ by considering whether there are embezzlement, malpractice and the largest shareholder changes or not. This study composed a total of 166 firms by using two-paired sampling method. For sample of failed firm, 83 manufacturing firms which delisted on KOSDAQ market for 4 years from 2009 to 2012 are selected. For sample of normal firm, 83 firms (with same item or same business as failed firm) that are listed on KOSDAQ market and perform normal business activities during the same period (from 2009 to 2012) are selected. This study selected 80 financial ratios for 5 years immediately preceding from delisting of sample firm above and conducted T-test to derive 19 of them which emerged for five consecutive years among significant variables and used forward selection to estimate logistic regression model. While the precedent studies only analyzed the data of three years immediately preceding the delisting, this study analyzes data of five years immediately preceding the delisting. This study is distinct from existing previous studies that it researches which significant financial characteristic influences the insolvency from the initial phase of insolvent firm with time lag and it also empirically analyzes the usefulness of data by building a firm's fail prediction model which considered embezzlement/malpractice and the largest shareholder changes as dummy variable(non-financial characteristics). The accuracy of classification of the prediction model with dummy variable appeared 95.2% in year T-1, 88.0% in year T-2, 81.3% in year T-3, 79.5% in year T-4, and 74.7% in year T-5. It increased as year of delisting approaches and showed generally higher the accuracy of classification than the results of existing previous studies. This study expects to reduce the damage of not only the firm but also investors, financial institutions and other stakeholders by finding the firm with high potential to fail in advance.

• Journal of the Economic Geographical Society of Korea
• /
• v.20 no.3
• /
• pp.329-352
• /
• 2017

Since the late 2000s Korean foreign direct investors in North Korea and China border regions have gone through the closure of outward processing trade(OPT) networks and changes in their location due to UN security council resolution and Korean independent sanctions against North Korea's nuclear and missile tests. However, the introduction of new Chinese OPT policy has led to the invigoration of domestic market-based OPT networks towards North Korea. The main aim of this paper is to identify the exceptional characteristics of Dandong in Liaoning province, a North Korea and China border region by analyzing OPT networks towards North Korea. Fundamentally the establishment of OPT networks towards North Korea is likely to be based on the utilization of a plenty of low wages in North Korea. The main reasons for this are fallen into two perspectives: geo-economics and geo-politics. The first perspective is geo-economics centering on the consolidation of economic exchange between North Korea and China, and North Korean economic development. For example, the introduction of Chinese OPT in border region has enabled Chinese local firms based on domestic market to access a plenty of low wage in North Korea in formal and institutional contexts. The second is geo-politics for the stability of North Korean regime based on the means of geo-economics. As the invigoration of domestic market-based OPT networks might make North Korea possible promoting foreign money earning, it enable North Korea to be sustainable as a buffering region between capitalist and socialist regime for China. It shows Chinese geo-strategic attempts to deal with the economic and regime stability of North Korean as a buffering state. In other words, OPT networks in North Korea should be concerned with the discourse practice of geo-economics and geo-politics which might lead to various and contingent spatial economies in border region. As a consequence, North Korea and China border regions could defined as a space in which is applicable to exceptional institutions and policies, and an exploitative space in which create surplus and rents by utilizing a plenty of low wages in North Korea through OPT networks.

• Journal of Venture Innovation
• /
• v.2 no.2
• /
• pp.95-115
• /
• 2019

In the context of today's business environment, not only is the nation or company's credit rating considered very important in our recent society, but it is also becoming important in international transactions. Likewise, at this point of time when the importance and reliability of credit evaluation are becoming important at home and abroad, this study analyzes financial ratios related to corporate profitability, safety, activity, financial growth, and profit growth to study the impact of financial indicators on enterprise value and corporate taxes on credit evaluation. To proceed with this, the financial ratio of 465 companies of KOSPI securities listed in 2017 was calculated and the impact of enterprise value and corporate taxes on credit evaluation was analyzed. Especially, this further study tried to derive a reliable and consistent conclusion by analyzing the financial data of KOSPI securities listed companies for eight years from 2011, which is the first year of K-IFRS introduction, to 2018. Research has shown that the significance levels among variables that show the profitability, safety, activity, financial growth, and profit growth of each financial ratio were significant at the 99% level, except for the profit growth. Validation of the research hypothesis found that while the profitability of KOSPI-listed companies significantly affects corporate value and income tax, indicators such as safety ratio and growth ratio do not significantly affect corporate value and income tax. Activity ratio resulted in significant effects on the value of enterprise value but not significant impacts on income taxes. In addition, it was found that the enterprise value has a significant effect on the company's credit and corporate income taxes, and that corporate income taxes also have a significant effect on the corporate credit evaluation, and this also shows that there is a mediating function of corporate tax. And as a result of further study, when looking at the financial ratio for eight years from 2011 to 2018, it was found that two variables, KARA and LTAX, are significant at a 1% significant level to KISC, whereas LEVE variables is not significant to KISC. The limitation of this study is that credit rating score and financial score cannot be said to be reliable indicators that investors in the capital market can normally obtain, compared to ranking criteria for corporate bonds or corporate bills directly related to capital procurement costs of enterprise. Above all, it is necessary to develop credit rating score and financial score reflecting financial indicators such as business cash flow or net assets market value and non-financial indicators such as industry growth potential or production efficiency.

• Journal of Venture Innovation
• /
• v.1 no.1
• /
• pp.83-98
• /
• 2018

This paper makes a theoretical approach to the differences between transaction tax and capital gains tax when the financial instruments are traded and imposed taxes in K-OTC market, a newly emerging off-board market. Since it is difficult to reduce risk to the level which investors would like to pursue - depending on the taxation methods of portfolio-composed financial instruments - when it comes to forming a synthetic bond to hedge risk, this paper also seeks for effective taxation methods to make this applicable. First of all, to thoroughly review the taxation balance of synthetic bonds, this paper analyzed the effects of the transaction tax and capital gains tax imposed upon synthetic bonds according to the changes in final stock price and strike price in K-OTC market, and analyzed after-tax profit differences among them depending on whether income tax deduction took place or not. As a result of the research upon the tax gap in transaction tax and capital gains tax according to the changes of final stock prices, it was shown that imposing transaction tax is more likely to be effective for some level of risk hedging with replicating portfolio considering taxation policies and financial markets, since the effect of the transaction tax has a much lower tax gap than that of capital gains tax. In addition, in relation to whether income tax deduction was permitted or not, it was proved that the effect of the transaction tax and the capital gains tax vary depending on the variation in the strike price. Above all, it was shown that if the strike price is lower than the stock price, the transaction tax will be less affected by the existence of income tax deduction than the capital gains tax, while both will be equally affected by the existence of income tax deduction if the strike price is higher than the stock price. Further study would be to demonstrate the validation of this in the K-OTC market with actual financial instruments and, also, to seek for a more systematic hedging method by using a ratio analysis approach to the calculation of the option transaction tax

• Journal of Venture Innovation
• /
• v.1 no.1
• /
• pp.49-65
• /
• 2018

For a long time the German economy was primarily defined by large corporations and thriving small and medium-sized enterprises. Since about 2005 a second strand has started to emerge and it is one which is becoming increasingly important and is creating jobs - start-ups in the digital sector. This start-up activity is taking an important role in Germany's economic development: Start-up companies spawn innovations and create jobs, thus promoting the concept of competition. In general "start-up" refers to digitally-driven companies that are not more than five years old. Germany's start-up policy consists of three main parts. First of all, Germany has the characteristics of technology-based start-ups. The Hartz reform since 2002 has shown its focus on technology-based start-ups. In particular, it is the most appropriate for a start-up company to take the role of a new technology company to respond to changes in the global industrial structure. Second, it is approaching from a long-term perspective. In this regard, the small business policy, including Germany's new business policy, is seen as a tradition that can be consistent and can make policy decisions based on the basics rather than following the times. Third, the government is implementing policies centered on demand. Germany's start-up policy is summarized as a technology-based policy and new job creation. The policy response is that the government seeks the best combination of policies by adapting them to the times from the broad trend of employment market policies. What is important here is that policies are made based on consumers, not suppliers, in the process of policy making and implementation. With the Digital Agenda 2020 the Federal government has likewise committed itself to preparing the digital economy for international competition and making Germany the "No. 1 digital growth country in Europe". Ever since 1998 the Federal Ministry for Economic Affairs and Energy (BMWi) has awarded the "EXIST" start-up scholarship to students and graduates. The Ministry also invests in the High Tech start-up fund. Together with Kreditanstalt für Wiederaufbau (KfW) and 18 other investors from the world of business the seed investor promotes young technology companies. Germany offers start-ups a good infrastructure and lots of funding opportunities. Berlin is regarded as Europe's start-up capital and also attracts lots of international young entrepreneurs.

• The Korean Journal of Financial Management
• /
• v.23 no.2
• /
• pp.109-141
• /
• 2006

The central factor in the pecking order theory of financial structure is the asymmetric distribution of information between managers and less-informed outside investors. Myers and Majluf (1984) show that this asymmetry leads managers to prefer internal funds to external funds. Funds are raised through equity issues only after the capacity to issue debt has been exhausted. In contrast, according to static tradeoff theory, an optimum financial structure exists by the tradeoff between tax saving by debt and bankruptcy costs. This study examines the recent changes of Korean firms' financial structure and financing behavior and the determinants of financial structure. The sample of firms comes from the period of $1996{\sim}2004$, and the number of firms is 32,003. The major findings are as follows. First, in contrast with previous studies using US firms as sample, Korean firms have been using debt financing as their major financing instrument. Especially, the firms in the fund deficit situation relies much more on $long{\sim}term$ and $short{\sim}term$ debts rather than on equity issues. Second, as is the case with previous studies using US firms sample indicates, the financing deficit variable can not explain perfectly the net debt issue. However, compared with net equity issue variable, net debt issue variable is more closely related to the financing deficit variable. Third, when financing deficit variable is added to the current list of explanatory variables of financial structure determinants model, it has a significant and positive explanatory power. In addition, the coefficients of determinants are much improved. Thus, it is concluded that although pecking order theory is not perfect, it appears to be more useful compared to static tradeoff theory, at least in explaining the recent financing behavior of Korean manufacturing firms.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.12 no.1
• /
• pp.1-13
• /
• 2017

The purpose of this study is to find out which factors determine the success of start-up in the initial market and what are the most important determinants. For the empirical analysis, the questionnaire related to the analysis of success factors for start-up success was designed according to the quantitative analysis (AHP technique). First, we selected 8 representative success factors for successful start-up in the initial market. In order to determine the degree of priority among these factors, we surveyed 12 entrepreneurs who are interested in entrepreneurship, universities, research institutes, and public officials. As a result of the empirical analysis, 51% of the funds in the tier 1 were ranked as the top priority to determine success factors. Followed by research and development (32.5%), management (8.7%) and marketing (7.8%). In particular, when each of the four items is calculated as 100 according to the result of the tier 1, and the tier 2 is converted, the foreign investment is analyzed as 43.7%. It was followed by 15.14% of R & D facilities, 14.07% of ideas, 8.7% of managerial ability, 7.29% of domestic investment, 5.85% of buyer feedback, 3.3% of development strategy and 1.95% of marketing strategy. Among the eight success factors, overseas investment items showed the closest preference to half, and it was the most important variable that determines the success or failure of market entry. The implication of this study is that many start-ups in Korea expect to receive investment and support from overseas accelerators. This means that overseas investment itself has been recognized as a start-up that makes services and products that can be used in the global market. A high preference for attracting foreign investment is due to the fact that the amount of investment is larger than that of Korea and that it can flexibly cope with the pressure on the performance compared to domestic investors. In this study, it was meaningful that we could confirm this fact through questionnaires of start-up experts. In future research, we need to find a viable alternative through studying how to provide start-up to foreign direct investment at the national level.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.25-41
• /
• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.