• Korean Journal of Labor Studies
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• v.24 no.3
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• pp.143-178
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• 2018

This study is aimed at empirically examining the Korean unionists' solidarity using the survey of 476 full-time workers employed at the unionized workplace. It also questions the determinants affecting the unionist' willingness to be united with the contingent workers. The Korean unionism has faced the biggest challenge, that is, the crisis-in-worker solidarity. Although prior literature has noted the crisis in Korean unionism, it lacks a solid investigation of individual workers' perception of solidarity which may play a key role in building up worker-solidarity in the union movement. This study first examines the three sources of solidarity allowing for the historical and theoretical approach to the modern solidarity; economic interests, worker-identification and empathy, which provide an emprical framework for this study. The empirical evidences shows dynamic aspects as of how the full-timers perceive solidarity with the non-regular workers in the three terms of solidarity. First, full-time unionists share rare willingness to be united with contingent workers in terms of economic solidarity. In addition, the KCTU (Korean Confederation of Trade Unions) with social reformative orientation has little influence on increasing their member's orientation towards solidarity. Second, it is found that full-time unionists have more willingness to identify themselves with the non-regular workers as a member of the labor class. The KTCU is also positively associated with their member's will of identification with contingent workers. Third, the unionists, however, show little empathy toward non-regular workers, which is contrast to the willingness to worker identification. No causality is also found between the KTCU and their members' empathy for the others.

• The Korean Journal of Air & Space Law and Policy
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• v.33 no.2
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• pp.267-290
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• 2018

This paper reviews and criticizes the EU Case of C-452/13, Germanwings GmbH v. Ronny Henning. Under this case, Ronny Henning later sued Lufthansa's budget carrier Germanwings after it refused to pay him 250 euros compensation for a delay he said totalled more than three hours. Germanwings, however, maintained his flight had arrived only two hours and 58 minutes behind schedule. In those circumstances, the following question to the European Court of Justice (ECJ) for a preliminary ruling: What time is relevant for the term time of arrival used in Articles 2, 5 and 7 of Regulation [No 261/2004]: (a) the time that the aircraft lands on the runway (touchdown); (b) the time that the aircraft reaches its parking position and the parking brakes are engaged or the chocks have been applied (in-block time); (c) the time that the aircraft door is opened; (d) a time defined by the parties in the context of party autonomy? ECJ says that the situation of passengers on a flight does not change substantially when their aircraft touches down on the runway at the destination airport, when that aircraft reaches its parking position and the parking brakes are engaged or when the chocks are applied, as the passengers continue to be subject, in the enclosed space in which they are sitting, to various constraints. Therefore, it is only when the passengers are permitted to leave the aircraft and the order is given to that effect to open the doors of the aircraft that the passengers may in principle resume their normal activities without being subject to those constraints. ECJ rules that it is apparent that Articles 2, 5 and 7 of Regulation No 261/2004 must be interpreted as meaning that the concept of 'arrival time', which is used to determine the length of the delay to which passengers on a flight have been subject, corresponds to the time at which at least one of the doors of the aircraft is opened, the assumption being that, at that moment, the passengers are permitted to leave the aircraft.

• The Southeast Asian review
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• v.27 no.1
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• pp.163-191
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• 2017

This article aims to review the recent, especially focusing on the year of 2016, situations and prospects of the Vietnamese politics, economy, and international relations. Politically, Vietnam completed the election of members for the National Assembly and organized new leadership at the 12th National Congress of the Vietnamese Communist Party in 2016. One characteristic of the new leadership is that the politicians, especially the members of politburo, from the North continue to occupy the position of majority. The other one is that the new leadership promised to carry out the restructuring of economy toward industries producing higher value-added commodities even though Vietnam industries admittedly need to accelerate present industrialization and modernization as a developing country under the seemingly contradictory slogan of "the development of market economy for socialism." The declared goals of the new leadership in Vietnam are inevitable in a sense since the development of Vietnamese economy has been heavily dependent upon Foreign Direct Investment(FDI) taking advantage of Vietnamese cheap labor and simultaneously it is evident that its future is unsecure if it maintains status quo. In fact, the Vietnamese economy has impressively showed high growth rate by the help of foreign capitals since 1990s despite the repetitive recessions of global economy but its growth is not likely to be sustainable anymore if it will not reduce foreign dependency and social economic inequality in a long term. In a short run, global economic recession, the financial and monetary policies of global powers, and recent protectionism and uncertainty of trade agreements will be three crucial variables to affect Vietnamese economy. In terms of international relations, Vietnam is continuously expected to practise the policy of checks and balances among the powerful countries. Vietnam has seriously disputed with China on islands sovereignty in the South China Sea and attempted to maintain close relationship with other powerful countries including especially America. However, mainly due to the new protectionism by the regime of American president Donald Trump, the Vietnamese government also need to keep close relationship with China increasingly for both economic and diplomatic security. Under the circumstances, Vietnam is expected to maintain more practical and balanced international relations.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Korean Chemical Engineering Research
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• v.61 no.3
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• pp.378-387
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• 2023

Petrochemical is an energy consuming industry that consumes about 30% of total industrial energy consumption and is a representative carbon dioxide (CO₂) emission source. Among them, the Naphtha Cracking Center (NCC), which produces ethylene, propylene, propane and mixed C4, consumes large amounts of energy and emits significant amounts of CO₂. For this reason, an integrated techno economic- environmental impact assessment aimed at reducing energy consumption and environmental impact factors is necessary to ensure efficiency in terms of economics and environment. This study aims to analyze the efficiency of the heat exchanger network used in the existing NCC base on the pinch analysis and select an improvement plan that can reduced energy consumption. In order to reduces the utility consumption in the process, an optimal heat exchanger network considering the high-temperature and low-temperature stream was derived, and the economic evaluation was conducted by considering the trade-off between the reduction in utility consumption and the increase in heat exchanger installation cost. In addition, an environmental impact assessment was conducted on the reduced CO₂ emission in consideration of the environmental aspect, and the economic environmental impact assessment used the payback period to recover the invested funds to come up with an energy saving plan that can be applied based on the actual process. As a result of considering the economic-environmental impact assessment, when the environmental impact assessment was not considered, it was 4.29 months, 3.21 months, and 3.39 months for each case, and when considering the environmental impact assessment, it was 4.24 months, 3.17 months, and 3.35 months for each case. These results appeared equally both when the environmental impact assessment was not include and when it was include. In addition, a sensitivity analysis was conducted for each case to determine how important factors affect the payback period. As a result of the sensitivity analysis, the cost of the heat exchanger was identified as a major factor influencing the overall cost.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• The Korean Journal of Air & Space Law and Policy
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• v.25 no.1
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• pp.97-158
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• 2010

The purpose of this paper is to research on the contents and improvement of national legislations relating to space development in Korea to make the sustainable progress of space development project in Korea. Korea has launched its first satellite KITST-1 in 1992. The National Space Committee has established "The Space Development Promotion Basic Plan" in 2007. The plan addressed the development of total 13 satellites by 2010 and the space launch vehicle by 2020, and the launch of moon exploration spaceship by 2021. Korea has built the space center at Oinarodo, Goheng Province in June 2009. In Korea the first small launch vehicle KSLV-1 was launched at the Naro Space Center in August 2009, and its second launch was made in June 2010. The United Nations has adopted five treaties relating to the development of outer space as follows : The Outer Space Treaty of 1967, the Rescue and Return Agreement of 1968, the Liability Convention of 1972, the Registration Convention of 1974, and the Moon Treaty of 1979. All five treaties has come into force. Korea has ratified the Outer Space Treaty, the Rescue and Return Agreement, the Liability Convention and the Registration Convention excepting the Moon Treaty. Most of development countries have enacted the national legislation relating to the development of our space as follows : The National Aeronautic and Space Act of 1958 and the Commercial Space Act of 1998 in the United States, Outer Space Act of 1986 in England, Establishment Act of National Space Center of 1961 in France, Canadian Space Agency Act of 1990 in Canada, Space Basic Act of 2008 in Japan, and Law on Space Activity of 1993 in Russia. There are currently three national legislations relating to space development in Korea as follows : Aerospace Industry Development Promotion Act of 1987, Outer Space Development Promotion Act of 2005, Outer Space Damage Compensation Act of 2008. The Ministry of Knowledge Economy of Korea has announced the Full Amendment Draft of Aerospace Industry Development Promotion Act in December 2009, and it's main contents are as follows : (1) Changing the title of Act into Aerospace Industry Promotion Act, (2) Newly regulating the definition of air flight test place, etc., (3) Establishment of aerospace industry basic plan, establishment of aerospace industry committee, (4) Project for promoting aerospace industry, (5) Exploration development, international joint development, (6) Cooperative research development, (7) Mutual benefit project, (8) Project for furthering basis of aerospace industry, (9) Activating cluster of aerospace industry, (10) Designation of air flight test place, etc., (11) Abolishing the designation and assistance of specific enterprise, (12) Abolishing the inspection of performance and quality. The Outer Space Development Promotion Act should be revised with regard to the following matters : (1) Overlapping problem in legal system between the Outer Space Development Promotion Act and the Aerospace industry Development promotion Act, (2) Distribution and adjustment problem of the national research development budget for space development between National Space Committee and National Science Technology Committee, (3) Consideration and preservation of environment in space development, (4) Taking the legal action and maintaining the legal system for policy and regulation relating to space development. The Outer Space Damage Compensation Act should be revised with regard to the following matters : (1) Definition of space damage and indirect damage, (2) Currency unit of limit of compensation liability, (3) Joint liability and compensation claim right of launching person of space object, (4) Establishment of Space Damage Compensation Council. In Korea, it will be possible to make a space tourism in 2013, and it is planned to introduce and operate a manned spaceship in 2013. Therefore, it is necessary to develop the policy relating to the promotion of commercial space transportation industry. Also it is necessary to make the proper maintenance of the current Aviation Law and space development-related laws and regulations for the promotion of space transportation industry in Korea.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Journal of the Korean Geographical Society
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• v.30 no.1
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• pp.35-56
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• 1995

During the last two decades, Korea has achieved remarkable economic growth. In this process the nation has become urbanized and industrialized. But we have also encountered widening regional disparity, housing shortage of larger cities, transportation congestion, environmental pollution and many other problems. Rapid increasing urbanization and continuous migration toward Seoul since the late 1960s have been one of the major concerns of government. Government has sought ways to moderate the population increase in Seoul. The regulation which include new town development near Seoul and dispersion strategies of higher education and other administration and living facilities outside of Seoul havemade a great expansion of the spatial influence of Seoul city. Seoul metropolitan reaion has evolved as the most powerful center of political and economical spaces. Generally within a metropolitan region, there exists a growing mutual interdependence economically, as well as socially between a central city and its surrounding area. Seoul metropolitan region manifests itself not only as a coherent system of urbanized regions, but also as an integral part of the daily urban system. The surrounding Gyunggi province and Seoul city become closely linked both economically and functionally, constituting true functlonai urban system. This study is primarily undertaken with the purpose of delineation of the sphere of influence of Seoul city in 1990. At the time of 1985, Seoul metropolitan region was delineated according to the result of the study which was performed by Korea Research Institute for Human Settlements. Afterward, the rapid speed of metropolitanization process with dramatic increase in mobility through the provision of wider transportation system across the Capital region have evolved, resulting in the great expansion of the spatial influence of Seoul city. So this study examines the expanded area of Seoul metropolitan regin during the period of 1985-90. In order to delineate Seoul metropolitan region, the indices of urbanization and functional linkage are selected. Variables included in the measurement of the urbanization level are agricultural structure, population characteristics, manufacturing and service industries, and cultural aspects such as newspaper circulation, the ratio of car ownership and piped water supply. Variables included in the measurement of functional linkage are commuting, shopping pattern, centralized service such as medical facilities and trade of agricultural products. The standardization method and factor analysis are employed in making the delineation of Seoul metropolitan region. According to the result of this study, 2 cities, 8 Eups and 46 Myuns are included Seoul metropolitan region in 1990. If we compare this delineated area in 1990 to that of 1985, we can find the distinctive pattern of expanded axes according to the main transportation routes such as Seoul-Suweon, Seoul-Gwangju, Seoul-Incheon. In 199O, all the Gyunggi province, except a few Myuns located at the north and northwest part of Gyunggi province, are included in Seoul metropolitan region. Furthermore, this study attempts to the analysis of regional structure of Seoul metropolitan region according to the functional characteristics of each city and Gun. Variables included in this analysis are the new residential function, manufacturing function, service function, education and infermation function, public facility function and agricultural function. Factor analysis and cluster analysis are employed in making regionalization. Seoul metropolitan reaion is subdivided into four subregions which reflect different functional specialization. The first group is the specialized region of newly formed residential function. The second group is the specialized reaion of manufacturing function. The third group is the specialized region of service function. And the fourth group has little specialized in terms of manufacturing, service, and residential function. But this region has some potentiality of development when Seoul metropolitan region grow continuously. Seoul metropolitan region accounted for 43% of national population, despite 11.8% of national land size in 1990. Although Seoul metropolitan region enjoys important agglomeration economies, it also has huge social cost in the form of transportation congestion, housing shortage, rapid increase of land value, environment pollution, and etc. Efficient metropolitan plan making is a vital element in promoting Seoul's economic development and providing high quality living environment at low cost. In the light of the result of this study, the outer ring of Seoul metropolitan region, especially northeastern part, are underdeveloped compared to overdeveloped southwestern area. It is needed to develop the guidelines for the implement of the growth control and management plan, inducing more balanced development for whole Seoul metropolitan reaion.