• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.831-839
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• 2008

The steel industry is becoming more important around the world and the demand of steel is increasing. Korea is the 5th country of steel producing in the world and the attention in the steel industry is growing. The steel industry is one of the key industry in leading the economic growth in Korea. This study attempts to analyze by time-series the economic impacts of the steel industry using an inter-industry analysis Specifically, the study investigates production-inducing effect, value added inducing effect and employ-inducing effect of the steel industry based on demand-driven model and the study deals with supply shortage effect and sectoral price effect of the steel industry by using supply-driven model and Leontief price model.

• Journal of Korea Planning Association
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• v.53 no.6
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• pp.117-130
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• 2018

Heavy snow is a natural disaster that causes serious economic damage. Since snowfall has been increasing recently, there is a need for measures against heavy snowfall. In order to make a policy decision on heavy snowfall, it is necessary to estimate the precise amount of damage by heavy snowfall. The direct damage of the heavy snow is severe, however the indirect damage caused by the road congestion and the urban dysfunction is also serious. Therefore, it is necessary to estimate indirect damage of snowfall. The purpose of this study is to estimate the effects on the regional economy from the limitation in traffic logistics caused by heavy snow using the transport demand model and inoperability input-output Model. The result shows that the amount of production loss caused by the heavy snow is KRW 2,460 billion per year and if the period of snowfall removal is shortened by one day or two days, it could be reduced to KRW 1,219 or 2,787 billion in production loss.

• Journal of Korea Trade
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• v.26 no.1
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• pp.99-112
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• 2022

Purpose - This paper empirically investigates via a spatial lag model from the perspective of space economy to find the influencing factors of South Korea's OFDI along with 60 countries. Design/methodology - In the study of regional economic phenomena, we must first test the corresponding spatial correlation, and on this basis, complete the construction of the spatial model. For the target research object, after testing the spatial correlation, if there is spatial correlation, a spatial measurement model is needed. This paper uses the global Moran's I index for calculation. Based on the characteristics and research needs of the research object, this paper selects the spatial lag model to verify the existence of the spatial effect and factors affecting OFDI. Findings - Our results show that export scale, infrastructure, technology level, political stability, resource endowment, market size, distance and labor cost have a certain impact on Korea's OFDI, but at present the distance and market size factors are the most important influencing factors for South Korea's OFDI, The technical level and political stability have little effect on South Korea's OFDI, and are not main factors determining South Korea's OFDI. Originality/value - Through spatial measurement verification, it was found that the spatial effect has a significant impact on OFDI, along with more than 60 countries. On this basis, relevant suggestions are put forward, which have strong practical significance for South Korea's OFDI to achieve healthy and sustainable development.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.449-457
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• 2022

The Port of Busan is currently ranked as the seventh largest container port worldwide in terms of cargo throughput. However, port competition in the Far-East region is fierce. The growth rate of container throughput handled by the port of Busan has recently slowed down. In this study, we analyzed how economic conditions and multiple external shocks could influence cargo throughput and identified potential implications for port business. The aim of this study was to build a model to accurately forecast port throughput using the ARIMA model, which could incorporate external socio-economic shocks, and the VEC model considering causal variables having long-term effects on transshipment cargo. Findings of this study suggest that there are three main areas affecting container throughput in the port of Busan, namely the Russia-Ukraine war, the increased competition for transshipment cargo of Chinese ports, and the weaker growth rate of the Korean economy. Based on the forecast, in order for the Port of the Port of Busan to continue to grow as a logistics hub in Northeast-Asia, policy intervention is necessary to diversify the demand for transshipment cargo and maximize benefits of planned infrastructural investments.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.183-193
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• 2023

This paper proposes and examines the economic impact of infrastructure improvement on the San-En-Nanshin region in the Chubu area of Japan. We develop a single transportation computable general equilibrium (CGE) model for each subregion within the San-En-Nanshin region. The explicit modeling of the transportation infrastructure is defined based on interregional commuting flows and business trips, considering the spatial structure of the San-En-Nanshin economy. A CGE model is integrated with an interregional transportation network model to enhance the framework's potential for understanding the infrastructure's role in regional development. To evaluate the economic impact of transportation improvement, we analyze the interrelationship between travel time savings and regional output and income. The economic impact analysis under the CGE framework reveals how transportation facilities and systems affect firm and household behavior and therefore induce changes in the production and consumption of commodities and transportation services. The proposed theoretical model was tested by using data from the 2005 IO tables of each subregion and the 2006 transport flow dataset issued by the Ministry of Land, Infrastructure, Transport, and Tourism in Japan. As a result, the paper confirms the positive effect of transportation investment on the total output and income of the studied region. Specifically, we found that while economic benefits typically appear in urban areas, rural areas can still potentially benefit from transportation improvement projects.

• Clean Technology
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• v.28 no.2
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• pp.138-146
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• 2022

Electricity has become a factor that dramatically affects the market economy. The day-ahead system marginal price determines electricity prices, and system marginal price forecasting is critical in maintaining energy management systems. There have been several studies using mathematics and machine learning models to forecast the system marginal price, but few studies have been conducted to develop, compare, and analyze various machine learning and deep learning models based on a data-driven framework. Therefore, in this study, different machine learning algorithms (i.e., autoregressive-based models such as the autoregressive integrated moving average model) and deep learning networks (i.e., recurrent neural network-based models such as the long short-term memory and gated recurrent unit model) are considered and integrated evaluation metrics including a forecasting test and information criteria are proposed to discern the optimal forecasting model. A case study of South Korea using long-term time-series system marginal price data from 2016 to 2021 was applied to the developed framework. The results of the study indicate that the autoregressive integrated moving average model (R-squared score: 0.97) and the gated recurrent unit model (R-squared score: 0.94) are appropriate for system marginal price forecasting. This study is expected to contribute significantly to energy management systems and the suggested framework can be explicitly applied for renewable energy networks.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.3
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• pp.1-9
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• 2005

In this paper, an operation algorithm and a performance simulator are developed for a 42-volt ISG vehiclewhich consists of 5 kW ISG, 2500cc IC engine, torque converter and 4 speed automatic transmission. Modularapproach using MATLAB Simulink is used to construct a dynamic model of the vehicle powertrain which is obtainedfrom each component such as engine, battery, ISG, torque converter, etc.. An operation strategy for a 42-volt ISG vehicle including the function such as engine idle stop and regenerative braking is proposed. Performance simulator is developed based on the dynamic models of the powertrain. It is found from the simulation results that fuel economy can be improved as much as 6 percent for FTP75 driving cycle mostly owing to the engine idle stop.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.693-702
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• 2020

The present study aims to investigate the impact of tourism growth on human development in Indian economy. For this purpose, the study uses annual data from 1980 to 2018 and utilizes two proxies for tourism growth - tourism receipt and tourist arrivals - and uses human development index calculated by UNDP. The study uses control variables such as government expenditure and trade openness. The study employs auto regressive distributed lag (ARDL) approach to investigate the cointegrating relationship among the variables in the model. Further, the study also explores the causal nexus between tourism sector and human development by using the Toda-Yamamoto Granger non-causality test. The result of ARDL bounds test reveals the existence of cointegrating relationship between human development indicators, government expenditure, trade openness, and tourism sector growth. The cointegating coefficient confirms a positive and significant relationship between tourism sector growth and human development in India. The causality result suggests that economic growth and tourism have a positive impact while trade openness has a negative impact on human development in India. The major findings of this study suggest that tourism plays an important role in the socio-economic development of Indian economy in recent years and the country must develop this sector to achieve sustainable development.

• Journal of Global Scholars of Marketing Science
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• v.9
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• pp.175-188
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• 2002

The objectives of this study are to develop and test a research model specifying the relationship between brand loyalty and sales of rice brands and to provide insight on establishing a marketing strategy for rice brands in South Korea. Results indicate that the information source a consumer relies upon is related to brand loyalty in the rice category. Second, consumers who are highly involved with the product category tend to be more brand loyal. Third, demographic of purchasing behavior are positively related to rice brand loyalty. Fourth, demographic characteristics can partially explain differences in rice brand loyalty. Finally, rice brand loyalty was positively related to consumer satisfaction.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.678-681
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• 2008

After rapid economy growth, Korean economy and Korean enterprises are aware of the importance on Mutual Cooperation. However, Korean society is not ready to proceed Mutual Cooperation and there are no theoretical model yet. Therefore, this study will suggest the theoretical basis for Mutual Cooperation, though identifying the most commonly used factors of three reliable sources: Mutual Cooperaton Manual(Ministry of Construction and Transportation 2006), selected distinguishing Mutual Cooperation Cases by Ministry of Construction and Transportation and Mutual Cooperaton Manual of other leading fields. through this study, it is expected to find reliable factors to evaluate Mutual Cooperations between General Contractor and Specialty Contractor.