• Journal of Korean Society of Environmental Engineers
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• v.35 no.12
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• pp.867-876
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• 2013

To promote the carbon emission trading scheme and reduce greenhouse gas (GHG) emission as following 'Korean GHG & Energy Target Management System', GHG emissions should be accurately determined in each industrial sector. For the estimation method of GHG emission from waste landfill, there are several error parameters, therefore we reviewed the estimation method and proposed a revised method. Methane generation from landfill must be calculated by the selected method based on methane recovery rate, 0.75. However, this methodology is not considered about uncertainty factor. So it is desirable that $CH_4$ generation is estimated using first order decay model and methane recovery should use field monitoring data. If not, $CH_4$ recovery could be applied from other study results; 0.60 of operational landfill with gas vent and flaring system, 0.65 of operational site with landfill gas recovery system, 0.90 of closed landfill with final cover. Other parameters such as degradable organic carbon (DOC) and fraction of DOC decompose ($DOC_f$) need to derive the default value from studies to reflect a Korean waste status. Proper application of MCF that is selected by operation and management of landfill requires more precise criteria.

• Environmental and Resource Economics Review
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• v.26 no.4
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• pp.577-612
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• 2017

In response to climate change, Korea is attempting to shift the paradigm of energy and climate change policies by introducing carbon pricing based on market mechanisms. While policy adoption is proceeding at a rapid pace, the introduction of carbon pricing has been faced with great opposition from industry. This study measures to what extent Korean companies understand and accept carbon pricing, using data from a questionnaire survey covering energy consuming companies in 2012, when discussions between the government and such companies about the introduction of a domestic emission trading system were active. It further identifies how preparations and practices for carbon and energy management of companies correlate with their policy understanding and acceptance. The analysis results show that the surveyed companies indicate moderate understanding of, as well as resistance to carbon pricing policies, while appreciating the economic incentives and accepting the mandatory regulations in this phase. Companies' understanding is more related to characteristics, i.e., sector, size, etc. than external pressures. This study found that the extent to which companies understand policy is the essential factor in their policy acceptance and related practices. In particular, understanding of carbon policy significantly influences their managerial practices and voluntary activities for carbon and energy practices. This study substantiates the correlation between the level of policy understanding of a company and its carbon and energy practices - something that all countries seeking to introduce carbon pricing in response to climate change should consider prior to policy actually being implemented; in other words, enhancing the understanding of major policy subjects of the new instrument is a key policy strategy that should be elaborated as it will lead to better performance of companies and smoother policy implementation.

• Korean Journal of Construction Engineering and Management
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• v.18 no.1
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• pp.74-82
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• 2017

It is known that energy usage from Korean Universities was growing rapidly in the early 2000s. But since 2011, the change was caused by GHG emissions regulation enforced by the government. The purpose of this research was to find the characteristics and trends of greenhouse gas emissions from major universities in Korea according to the each university's data and information. The result shows that GHG emissions from University have increased steadily prior to enforcement by 4-5% annually, but the rate of increase marked 0.5~1% in 2011~2013 is the season of emission regulation and the total amount of emissions decreased 3%~5% in 2014~2015 while preparing an emissions trading scheme. Therefore we can say that the enforcement of GHG reduction such as energy target management system makes a visible effect at least in the University sector that level of GHG emissions is from $75kg/m^2$ to $58Kg/m^2$ for seven years. Another result says that the size of research fund is the main factor that affects the amount of GHG emissions before 2011, but the size of building area has been a new factor influencing the GHG emission since 2013. Thus we suggest that the criteria for evaluating the level of GHG emission from University is suitable if it is based on the building area intensity.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.179-194
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• 2023

ASEAN is emerging as the next-generation market following BRICs. Korea is also an important economic cooperation partner as a second trading partner and third target for overseas investment. ASEAN is attracting attention as an attractive business place for many companies as a future investment area in the future. Therefore, the Korean government is strongly promoting a "New Southern Policy(NSP)" to develop cooperative relations with ASEAN. As ASEAN has recently emerged as a central area for shipping and logistics development, development cooperation and support for the shipping and logistics sector in the ASEAN region of neighboring countries are also active in entering the new southern region and the government is supporting it. In order to enter these countries, it is necessary to accurately understand the investment attraction system, strategy, and market for entering the business in other countries. Among the various methods of entering the overseas market, it is essential to understand the business selection and establishment method suitable for localization strategies such as foreign direct investment and establishment of foreign corporations. In order to understand the Overseas Investment Act and the Corporate Establishment Act of shipping and logistics-related companies who want to enter marine ASEAN countries, we will study the overseas investment method and the establishment method according to the type of company.

• Information Systems Review
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• v.22 no.1
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• pp.59-72
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• 2020

Artificial Intelligence is establishing itself as a familiar tool from an intractable concept. In this trend, financial sector is also looking to improve the problem of existing system which includes Fraud Detection System (FDS). It is being difficult to detect sophisticated cyber financial fraud using original rule-based FDS. This is because diversification of payment environment and increasing number of electronic financial transactions has been emerged. In order to overcome present FDS, this paper suggests 3 types of artificial intelligence models, Generative Adversarial Network (GAN), Deep Neural Network (DNN), and Convolutional Neural Network (CNN). GAN proves how data imbalance problem can be developed while DNN and CNN show how abnormal financial trading patterns can be precisely detected. In conclusion, among the experiments on this paper, WGAN has the highest improvement effects on data imbalance problem. DNN model reflects more effects on fraud classification comparatively.

• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.169-190
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• 2023

Uzbekistan, one of the top five cotton-producing countries in the world, primarily focuses its textile and fashion industry on raw cotton exports and the sewing industry. For Uzbekistan to achieve high added value, it is essential for the textile and fashion industry, which is currently at the CMT(cut, make, and trim) stage, to upgrade to OEM (original equipment manufacturing), ODM (original design manufacturing), and OBM (original brand manufacturing). South Korea recognizes Uzbekistan as a potential manufacturing base and trading partner and has invested Official Development Assistance (ODA) funds for the development of Uzbekistan's textiles and apparel sector. This study aims to evaluate Uzbekistan's fashion higher education in the context of global competitiveness and measure the need and prospects for education ODA from the Korean government in this field. Comprehensive investigations, including surveys of academics, industry experts, and government officials, in-depth interviews, and focus group interviews, were conducted to understand Uzbekistan's current fashion education environment. According to the research results, despite the textile and fashion sectors playing a pivotal role in the Uzbek economy, there is room for improvement in the curricula and teaching and learning methods of the fashion higher education programs. This study holds significance as foundational data for establishing education ODA strategies.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.109-130
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• 2022

The Vietnamese government has proposed contract farming through a new type of cooperative as an institutional innovation which aims to restructure the agricultural sector. However, policy changes often impact farmers, who bear the primary effects of the transition process. Understanding households' strategies for land use and livelihood is crucial for policymaking in the agricultural development field. This study was conducted in the rural Binh Dao commune in Central Vietnam. We analyzed household members' labor force changes and their livelihood behaviors after their participation in a contract farming scheme using qualitative analysis methods combined with geographic information system (GIS) support, based on secondary data and in-depth interviews of 190 farmers. Simultaneously, we created a digital map of the cooperative's production area to investigate changes in land use and production activities. The findings show that contract farming shaped the vertical coordination of the value chain from the farmers to the cooperative and agricultural product trading companies. Subsequently, it encouraged land use and labor efficiency due to mechanical support. In addition, it also increased productivity and protected farmers from market risks. However, despite its positive effects on agricultural productivity in this case, the contract farming scheme could not achieve the restructuring of the rural labor force toward non-agricultural sectors. Ironically, farmers in the Binh Dao commune tended to increase cultivable land during the agricultural restructuring program, rather than switching their labor forces to non-agricultural sectors. The lack of stable non-farming job opportunities in rural Vietnam results in challenges to the efficiency of agricultural restructuring programs. Consequently, farmers in the Binh Dao commune are still smallholder farmers, depending on the family labor force.

• Korean Business Review
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• v.17
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• pp.153-183
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• 2004

The Gaisong Merchants can be regarded to playa pioneering role to activate the Korea's trade with foreign countries. In the early period of Yi-Dynasty, the Gaisong Merchants focused on personal trade, but in the middle period of Yi-Dynasty, they entered to the realm of governmental trade. Furthermore, their business activities widened to various forms of trades, for example, smuggling. Utilizing accumulated capital, Gaisong merchants expanded their trading activities to their neighboring countries such as Japan and China. In recent times, it is necessary for modem Korean companies to diversify risks through the establishment of corporations for production, marketing and R&D abroad or through joint venture, M&A and strategic alliance with foreign companies in order to reduce the risks originated from volatile economic and political situations. In this study, we utilize tools of comparative study to compare Gaisong Merchants' foreign trade strategies with those of modem companies such as AMOREPACIFIC, HANILCEMENT and SHINDORICO. The purpose of the paper is to test the hypothesis that modem Korean companies grew up by following the cases of Gaisong Merchants' business activities. We summarize our main findings as follows. First, both Gaisong Merchants and modem Korean companies have common functional core capability in the field of marketing, manufacturing technology, R&D, and human resources development. Second, both Gaisong Merchants and modem Korean companies have common organizational core capability. Third, both Gaisong Merchants and modem Korean companies have common infrastructures such as planning, finance, accounting and MIS. It constitutes the infrastructure of Korea's foreign trade sector. Fourth, both Gaisong Merchants and modem companies have common organizational culture in the field of management policy and philosophy. Actually, those factors are evaluated to be driving forces of Koera's success in foreign trade. In conclusion, the business activities of Gaisong Merchants who represented the peculiarity of Korean business spirit are partially inherited to current Korean business management. The value system and behavior pattern of modern Korean companies is succeeded from the spirit of Gaisong Merchants and it playa major role to specify the identity of Korean business administration.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.277-307
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• 2016

Since 2011, DCF(Discounted Cash Flow) method has been used initiatively for valuating R&D technology assets in the agricultural food industry and recently technology valuation based on royalties comparison among technology transfer transactions has been also carried out in parallel when evaluating the technology assets such as new seed development technologies. Since the DCF method which has been known until now has many input variables to be estimated, sophisticated estimation has been demanded at the time of technology valuation. In addition, considering more similar trading cases when applying sales transaction comparison or industry norm method based on information of technology transfer royalty, it is an important issue that should be taken into account in the same way in the Agri-Food industry. The main input variables used for technology valuation in the Agri-Food industry are life cycle of technology asset, the financial information related to the Agri-Food industry, discount rate, and technology contribution rate. The latest infrastructure building and data updating related to technology valuation has been carried out on a regular basis in the evaluation organization of the Agri-Food segment. This study verifies the key variables that give the most important impact on the results for the existing technology valuation in the Agri-Food industry and clarifies the difference between the existing valuation result and the outcome by referring the support information that is derived through the latest input information applied in DCF method. In addition, while presenting the scheme to complement fragment information which the latest input data just influence result of technology valuation, we tried to perform comparative analysis between the existing valuation results and the evaluated outcome after the latest of reference data for making a decision the input values to be estimated in DCF. To perform these analyzes, it was first selected the representative cases evaluated past in the Agri-Food industry, applied a sensitivity analysis for input variables based on these selected cases, and then executed a simulation analysis utilizing the key input variables derived from sensitivity analysis. The results of this study is to provide the information which there are the need for modernization of the data related to the input variables that are utilized during valuating technology assets in the Agri-Food sector and for building the infrastructure of the key input variables in DCF. Therefore it is expected to provide more fruitful information about the results of valuation.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.