• Journal of Environmental Policy
• /
• v.10 no.1
• /
• pp.93-127
• /
• 2011

Investment on technology to obtain green energy is prevailing all over the world. The technology development project is more likely to involve multiple sub-projects, each of which is related to develop elementary technology when the project is larger and nation-wide. However, the methodologies identifying optimal combination of elementary technologies among the candidates have been very few. Hence, the purpose of this paper is to propose a novel methodology which provides an optimal combination of green energy technologies. To do so, to-be developed technologies are clustered with multiple categories. Among the technologies, based on Delphi method, the experts select a representative technology, which is indispensible to the green energy system and has the highest connectivity with other elementary technologies. Then the methodology selects an elementary technology from each technology category based on two metrics: Relatedness with representative technology and project risk. To show the feasibility of the proposed methodology, we applied the methodology to an actual windmill development project.

• Korean Journal of Construction Engineering and Management
• /
• v.6 no.2 s.24
• /
• pp.102-110
• /
• 2005

After the IMF bailout, the Environment of Domestic Construction Industry had changed dramatically. Before the IMF, Domestic Construction Firms are secured by the government regulations and some traditional practices. However, due to the following reasons: a decrease in public works, an increase in uncertainty of market prediction, the change of bid system, and increase in construction firms, recently the competition among construction firms has became keen. Under the serious competition, in order that medium-size construction firms survive in the construction market, it is need to establish the strategy that could increase productivity. In order to establish the strategy, firstly, construction firms should set up an appraisal standard of construction firms. Consequently, This study will introduce companies' objective appraisal in domestic construction market as well as basal data for setting-up strategy through adaptation industry structure analysis of business administration for strategic group analysis and a company which has lagged behind competitive power among the competitive companies can choose a target strategic group which should be pursued it in the future through being classified according to a group taken analogical strategy.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.3B
• /
• pp.159-164
• /
• 2008

For increasing productivity of domestic IT industry, government and local agencies have some plans to establish industrial clusters to provide local firms with testbed, R&D center, and cooperative research project. The most difficult problem in this process is to decide the location of them by resonable methodology. In this paper, the subject is to find what the factors to be considered in locating facilities and industrial clusters invested by government are and how to decide efficiently. First, we look over some cases of other countries, and then find assessment items for locating. Finally we analyze these items and assessment model by the analytic Hierachy Process(AHP) and make conclusion, As a conclusion, we find the result that there are some differences between the object of govenmental policy and needs of industry. 'The base infrastructure for telecommunications environment' is more important to be considered by the firms than 'The local benefit of the public'

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.9
• /
• pp.4587-4592
• /
• 2013

GPS is recognized the essential method to obtain the best result in the sphere of earth science that is setting of International Reference Frame, decision of the rotation coefficient about the earth rotation axis, detection of the crustal deformation, and observation of the diastrophism by high precision positioning except for navigation, geodetic survey and mapping. Therefore, in this study, it was attempted to build an expert service that enables non-experts to use high-precision GPS data processing. As a result, an Precise Point Positioning Solution that can maximize user convenience simply by entering the minimum required information for GPS data processing was developed, and the result of Precise Point Positioning Solution using GPS data provided by National Geographic Information Institute was compared with result of ITRF.

• Korean Chemical Engineering Research
• /
• v.54 no.3
• /
• pp.320-331
• /
• 2016

Linze-Donawitz gas (LDG) adjunctively produced in the steel mill contains over 60% of CO. Two processes that recover high purity CO from LDG were considered: COSORB and CO-Pressure swing adsorption (PSA). This study aimed to decide which one is more economically feasible than the other by techno-economic analysis (TEA). From the technical point of view of TEA, the process flow diagram (PFD) was constructed, the mass and energy balances were calculated, and the equipment type and size were determined in order to estimate the total capital investment (TCI) and the total production cost (TPC). From the economic point of view of TEA, economic performance such as return on investment (ROI) and payback period (PBP) was evaluated, and the sensitivity analysis was carried out to identify key factors influencing ROI and PBP. It was found that CO-PSA is more economically feasible due to higher ROI and lower PBP. The CO price highly influenced ROI and PBP.

• Korean Journal of Construction Engineering and Management
• /
• v.15 no.4
• /
• pp.58-67
• /
• 2014

The proportion of investment in national R&D projects in construction and transportation has been increasing continuously; in terms of the size of R&D projects, there are many medium- to large-sized projects of over KRW 10 billion. However, in spite of such continuous increase in R&D investments, there are many technologies developed but not commercialized, i.e., the quiescence of technology. Accordingly, it is necessary to link the R&D results to commercialization by expanding the scope of R&D projects. In this context, this study presented objective reference prices to be used in contracting/transacting technology and implementing commercialization strategy by conducting technology valuations against on-going research projects with earnings approach, and by estimating value of patented technology. Sum of free cash flow (business value) that can be generated during the life of the technology was estimated as KRW 512 million by reflecting a discount rate of 16.34% to convert it into the present value. In addition, the technology value was computed as KRW 227million by applying a technology factor of 44.39% to the above value. Based on the technology value estimated in this way, it is necessary to establish industrialization and commercialization strategy of the technology.

• International Area Studies Review
• /
• v.15 no.3
• /
• pp.471-491
• /
• 2011

This study is to analyze the determinants of inflow FDI with panel data of 12 provinces in western region of China for the period, 1990-2007, from the perspective of market-oriented FDI and production-efficiency-oriented FDI. The empirical findings are following. First, the empirical results prior to the start of western development program show that the GRDP, the intense of industrialization and university graduates per 10,000 residents have positive coefficient signs at the significant level, while wage level has a negative and significant value. Second the empirical results using the data after the launching of the western development program show that the GRDP, the intense of industrialization have positive relations with FDI, while openness in terms of the ratio of international trade to GRDP and the wage level have negative coefficients. Finally, this thesis finds that the empirical results for both periods are very similar, which suggest that the economic structure in western region has not changed significantly even though almost a decade passed since the western development program launched.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.123-139
• /
• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Korean small business review
• /
• v.31 no.2
• /
• pp.85-102
• /
• 2009

With the continued globalization of world markets, transfer pricing has become one of the dominant sources of controversy in international taxation. Transfer pricing is the process by which a multinational corporation calculates a price for goods and services that are transferred to affiliated entities. Consider a Korean electronic enterprise that buys supplies from its own subsidiary located in China. How much the Korean parent company pays its subsidiary will determine how much profit the Chinese unit reports in local taxes. If the parent company pays above normal market prices, it may appear to have a poor profit, even if the group as a whole shows a respectable profit margin. In this way, transfer prices impact the taxable income reported in each country in which the multinational enterprise operates. It's importance lies in that around 60% of international trade involves transactions between two related parts of multinationals, according to the OECD. Multinational enterprises (hereafter MEs) exert much effort into utilizing organizational advantages to make global investments. MEs wish to minimize their tax burden. So MEs spend a fortune on economists and accountants to justify transfer prices that suit their tax needs. On the contrary, local governments are not prepared to cope with MEs' powerful financial instruments. Tax authorities in each country wish to ensure that the tax base of any ME is divided fairly. Thus, both tax authorities and MEs have a vested interest in the way in which a transfer price is determined, and this is why MEs' international transfer prices are at the center of disputes concerned with taxation. Transfer pricing issues and practices are sometimes difficult to control for regulators because the tax administration does not have enough staffs with the knowledge and resources necessary to understand them. The authors examine transfer pricing practices to provide relevant resources useful in designing tax incentives and regulation schemes for policy makers. This study focuses on identifying the relevant business and environmental factors that could influence the international transfer pricing of MEs. In this perspective, we empirically investigate how the management perception of related variables influences their choice of international transfer pricing methods. We believe that this research is particularly useful in the design of tax policy. Because it can concentrate on a few selected factors in consideration of the limited budget of the tax administration with assistance of this research. Data is composed of questionnaire responses from foreign firms in Korea with investment balances exceeding one million dollars in the end of 2004. We mailed questionnaires to 861 managers in charge of the accounting departments of each company, resulting in 121 valid responses. Seventy six percent of the sample firms are classified as small and medium sized enterprises with assets below 100 billion Korean won. Reviewing transfer pricing methods, cost-based transfer pricing is most popular showing that 60 firms have adopted it. The market-based method is used by 31 firms, and 13 firms have reported the resale-pricing method. Regarding the nationalities of foreign investors, the Japanese and the Americans constitute most of the sample. Logistic regressions have been performed for statistical analysis. The dependent variable is binary in that whether the method of international transfer pricing is a market-based method or a cost-based method. This type of binary classification is founded on the belief that the market-based method is evaluated as the relatively objective way of pricing compared with the cost-based methods. Cost-based pricing is assumed to give mangers flexibility in transfer pricing decisions. Therefore, local regulatory agencies are thought to prefer market-based pricing over cost-based pricing. Independent variables are composed of eight factors such as corporate tax rate, tariffs, relations with local tax authorities, tax audit, equity ratios of local investors, volume of internal trade, sales volume, and product life cycle. The first four variables are included in the model because taxation lies in the center of transfer pricing disputes. So identifying the impact of these variables in Korean business environments is much needed. Equity ratio is included to represent the interest of local partners. Volume of internal trade was sometimes employed in previous research to check the pricing behavior of managers, so we have followed these footsteps in this paper. Product life cycle is used as a surrogate of competition in local markets. Control variables are firm size and nationality of foreign investors. Firm size is controlled using dummy variables in that whether or not the specific firm is small and medium sized. This is because some researchers report that big firms show different behaviors compared with small and medium sized firms in transfer pricing. The other control variable is also expressed in dummy variable showing if the entrepreneur is the American or not. That's because some prior studies conclude that the American management style is different in that they limit branch manger's freedom of decision. Reviewing the statistical results, we have found that managers prefer the cost-based method over the market-based method as the importance of corporate taxes and tariffs increase. This result means that managers need flexibility to lessen the tax burden when they feel taxes are important. They also prefer the cost-based method as the product life cycle matures, which means that they support subsidiaries in local market competition using cost-based transfer pricing. On the contrary, as the relationship with local tax authorities becomes more important, managers prefer the market-based method. That is because market-based pricing is a better way to maintain good relations with the tax officials. Other variables like tax audit, volume of internal transactions, sales volume, and local equity ratio have shown only insignificant influence. Additionally, we have replaced two tax variables(corporate taxes and tariffs) with the data showing top marginal tax rate and mean tariff rates of each country, and have performed another regression to find if we could get different results compared with the former one. As a consequence, we have found something different on the part of mean tariffs, that shows only an insignificant influence on the dependent variable. We guess that each company in the sample pays tariffs with a specific rate applied only for one's own company, which could be located far from mean tariff rates. Therefore we have concluded we need a more detailed data that shows the tariffs of each company if we want to check the role of this variable. Considering that the present paper has heavily relied on questionnaires, an effort to build a reliable data base is needed for enhancing the research reliability.

• Journal of Intelligence and Information Systems
• /
• v.16 no.3
• /
• pp.77-97
• /
• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.