• Korean Journal of Construction Engineering and Management
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• v.12 no.3
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• pp.83-90
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• 2011

Although the CM(construction management) market in Korea has shown rapid growth, unlike other market sectors, there has been lack of a system by which the economy trend of the CM market can be analyzed. The objective of the paper is to analyse and identify key characteristics of the CM market as of the third quarter of 2010 by using the CMBSI(Construction Management Business Survey Index) which was proposed in the previous study. In the paper, the CMBSI is used as the main index along with other five supplementary indices. The use of the CMBSI can contribute to enhancing the understanding of CM market situation and prospect, and also to providing information for CM policy and regulations.

• Journal of Distribution Science
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• v.13 no.6
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• pp.35-44
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• 2015

Purpose - To accelerate economic cooperation, this study investigates trade structures of Korea and the United States and identifies trade discrepancies. Such discoveries can lead to increases in trade volume by improving policies, eventually uncovering ways for trade expansion. Research design, data, and methodology - The Index of trade intensity, from trade intensity theory, is used to analyze the trade decision factors. Even though specific factors should materialize in the analysis, realistically, concrete explanations are difficult as there are so many unsolved factors and diversifications. Results - First, the Index of A value/ B value positions Korean against the United States in terms of market share and Korea against world market share, which thereby reveals comparative market intensity. Second, Korea is taking comparative advantage of export specialization. Third, real comparative advantage indices are considerably improved since early 2000. Conclusions - This study uses quantitative measurements and trade intensity theory and trade specialization to come up with a comparative advantage index to see how inter-trade relations between Korea and the United States have changed over the past 10 years.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.2
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• pp.75-81
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• 2015

At the end of the 19th century, Edison's DC power system and Tesla's AC power system was debated in power market. Finally, AC system became the primary system of the power market because both step-up and step-down of voltage by using transformer and long-distance power transmission are easily possible. However, nowadays the power market takes some action for introducing DC system. Both domestic and foreign researchers are conducting the study on the DC system as well. Some researchers have conducted the studies on power quality and economic evaluation of the DC distribution system but DC distribution system is still controversial in terms of the effectiveness and reliability. In this paper, we calculate the reliability indices of the Low Voltage Direct Current(LVDC) distribution system considering arrangement of power electronics, layout of the distribution system, and distance between load points.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.806-807
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• 2007

Systematic studies on the dispatch scheduling algorithm and related constraints can enhance the effectiveness of electricity market operation. When System Operator (SO) establishes a dispatch schedule, the bid information should be preserved in the schedule as much as possible. In this paper, we introduce a new type of sensitivity factor called Line Outage Impact Factor (LOIF) to screen a transmission line causing the most severe outage when scheduling the dispatch. This screening can assure the stable system operation and make an efficient feedback between the SO and market participants. We propose a transmission line contingency constrained Pre-dispatch algorithm using sensitivity indices in a suitable Pre-dispatch scheduling. The proposed algorithm has been tested on sample system and the results show more secure operation against critical contingencies.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.308-314
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• 2013

Although global construction spending has experienced slow growth due to consecutive economic crises, global contractors have consistently attempted to expand their overseas market share, leading to more intense competition among contractors in the international construction market. In this market environment, owners, clients and financial institutions require reasonable and systematic criteria to effectively assess the business capabilities of international construction firms. However, the existing evaluation methods for construction firms rarely consider overseas-focused business capabilities. To address this problem, this study proposes a quantitative approach to assessing the overseas business capabilities of international construction firms. The limitations of existing approaches are reviewed, and the capabilities required to perform overseas businesses are analyzed through expert interviews. Finally, 18 evaluation indices are suggested in four categories: technology resources, project management, experience and performance, and sustainability. The relative weight of each index is determined according to the Analytical Hierarchy Process (AHP) method, and a preliminary investigation of 11 Korean construction firms is conducted. The proposed method is expected that it will provide the rational criteria for international owners, clients, and financial institutions for decision-making and for evaluating international contractors.

• ETRI Journal
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• v.45 no.4
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• pp.636-649
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• 2023

Renewable energy generation cannot be consistently predicted or controlled. Therefore, it is currently not widely used in the electricity market, which requires dependable production. In this study, reliability- and variance-based controls of energy storage strategies are proposed to utilize renewable energy as a steady contributor to the electricity market. For reliability-based control, photovoltaic (PV) generation is assumed to be registered in the power generation plan. PV generation yields a reliable output using energy storage units to compensate for PV prediction errors. We also propose a runtime state-ofcharge management method for sustainable operations. With variance-based controls, changes in rapid power generation are limited through ramp rate control. This study introduces new reliability and variance indices as indicators for evaluating these strategies. The reliability index quantifies the degree to which the actual generation realizes the plan, and the variance index quantifies the degree of power change. The two strategies are verified based on simulations and experiments. The reliability index improved by 3.1 times on average over 21 days at a real power plant.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1035-1045
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• 2010

Products and/or services should be objectively verified in terms of the technological and use-conditional considerations before entering a market. Every organization or company tries to find the better procedure and method for checking the core needs of customers based on their experience in the market and looks for continuous ways to evaluate the power of products and services(PoP). They also prefer the overall evaluation of indices that could reflect various customer needs, rather than a separate evaluation index for each characteristic of the product or service. S. Ko (2008) proposes a Multi-characteristics Sigma Level(MSL) that can simultaneously evaluate many characteristics of a product or service. In this research, using MSL and a new Blue Ocean Index(BOI), an application of NPS, mobile phone field test is considered from a practical and statistical point of view.

• Korea Real Estate Review
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• v.27 no.3
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• pp.71-86
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• 2017

The purpose of this study was to apply the deep running method to real estate price index predicting and to compare it with the time series analysis method to test the possibility of its application to real estate market forecasting. Various real estate price indices were predicted using the DNN (deep neural networks) and LSTM (long short term memory networks) models, both of which draw on the deep learning method, and the ARIMA (autoregressive integrated moving average) model, which is based on the time seies analysis method. The results of the study showed the following. First, the predictive power of the deep learning method is superior to that of the time series analysis method. Second, among the deep learning models, the predictability of the DNN model is slightly superior to that of the LSTM model. Third, the deep learning method and the ARIMA model are the least reliable tools for predicting the housing sales prices index among the real estate price indices. Drawing on the deep learning method, it is hoped that this study will help enhance the accuracy in predicting the real estate market dynamics.

• Knowledge Management Research
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• v.22 no.4
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• pp.87-101
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• 2021

ESG Investment is emerging as a trend and common sense in the financial market. ESG Investment is an investment method that simultaneously pursue social sustainability and investment returns from a long-term perspective by reflecting non-financial factors such as environment, society and governance in addition to corporate financial performance in investment decisions. This study checked how the characteristics of ESG investment have been changed after Covid-19. Afterwards, it was confirmed that Covid-19 actually acted as a negative factor in the securities market by applying VAR model. At the same time, it was demonstrated that ESG indices of the US and Korea outperformed their benchmark in terms of return and risk during the pandemic regime. The result of this study hints that the importance of ESG investment will be unchanged after Covid-19. At the same time, it suggests that managers should avoid passive ESG management and engage in strategic ESG management based on knowledge management.

• Korea Trade Review
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• v.48 no.1
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• pp.127-163
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• 2023

The objective of this study is to investigate the volatility spillover effects among BDI, CCFI and SCFI. This paper will divide the empirical analysis section into two periods to analyze and compare the differences in volatility spillover effect between shipping freight indices before and after the outbreak of COVID-19 separately. First, in order to compare the mean spillover impact and index lead-lag correlations in BDI and CCFI indices, along with BDI and SCFI indices before and after COVID-19, the co-integration analysis and the test of Granger causality built on the VAR model were utilized. Second, the impulse response and variance decomposition are employed in this work to investigate how the shipping freight index responds to shocks experienced by itself and other freight indices in a short period. Before the COVID-19 epidemic, the results demonstrated that the BDI freight index is the Granger cause of the variable CCFI freight index. But the BDI and CCFI freight indices have no apparent lead-lag relationships after COVID-19, and this empirical result echoes the cointegration test result. After the COVID-19 epidemic, the SCFI index leads the BDI index. This study employs the VAR-BEKK-GARCH joint model to explore the volatility spillover results between dry bulk and container transport markets before and after COVID-19. The empirical results demonstrate that after COVID-19, fluctuations in the BDI index still affect the CCFI index in the maritime market. However, there is no proof of a volatility spillover relationship between the BDI and SCFI after the COVID-19 epidemic. This study will provide an insight into the volatility relationship among BDI, CCFI and SCFI before and after the the COVID-19 epidemic occurred.