• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1460-1470
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• 2015

This paper presents an approach to solve the long-term generation expansion planning problem of the restructured electricity industry using an agent-based environment. The proposed model simulates the generation investment decisions taken by a particular agent (i.e. a generating company) in a market environment taking into account its competitors’ strategic investment. The investment decision of a particular company is modeled taking into account that such company has imperfect foresight on the future system development hence electricity prices. The delay in the construction of new plants is also explicitly modeled, in order to compute accurately the yearly revenues of each agent. On top of a conventional energy market, several capacity incentive mechanisms including capacity payment and capacity market are simulated, so as to assess their impact on the investment promotion for generation expansion. Results provide insight on the investment cycles as well as dynamic system behavior of long-term generation expansion planning in a competitive electricity industry.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.181-187
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• 2012

This study inquires into what effect the tax burden of investors, for typical taxes related to real estate investment; acquisition tax, comprehensive real estate holding tax, and transfer income tax, might have on the real estate investment behaviors; the purpose of long-term investment. These real estate investment behaviors have been analyzed to see how much they affect investment performance such as realized compound yield. This study model, which considers the fact that the choice of investment behavior for the degree of tax burden of investors may lead to different results in real estate investment, is expected to be an effective decision-making tool for investment.

• Journal of Korea Trade
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• v.24 no.3
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• pp.55-72
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• 2020

Purpose - In this paper, we provide recommendations for Korea's long-term direction and strategic measures to attract inward foreign direct investment (FDI) in response to Japan's export regulations. In doing so, we analyze the current situation and characteristics of trade between Korea and Japan, focusing on the parts and materials industry, which is particularly affected by Japan's trade regulations. Design/methodology - Based on the analysis of five successful inward FDI cases (e.g. Toray, IGK, Delkor, GlobalWafers, DuPont) and statistic trend review in the parts and materials industry, we consider various factors pertaining to successful inward FDI in Korea and propose valuable investment attraction strategies. Findings - For a successful investment attraction strategy, we studied some statistical trends in the internal and external environments of the parts and materials industry and successful investment attraction cases in Korea. We have found that in order to increase the probability of success in attracting investment, we need a mid-to long-term strategy considering multiple factors such as "Production-oriented, Demand-linked, Global Value Chain (VGC) linked, and Policy-linked investment attraction." Originality/value - We suggest several specific measures and important strategic implications for the Korean government and firm's managers to attract inward FDI successfully.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.122-128
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• 2017

Korean government announced long-term railway safety investment plan for the safety improvement by 2020. But no research have been done about differential analysis on railroad safety investment and safety improvement. In this study, recent 10 year data on safety investments and accident data are analysed for the differential analysis. Three main safety investments are analysed on regard to accident rate and accident fatalities. Three safety measures include level crossing accident, platform fatalities, and track trespass fatalities. About 90% of railway accident fatalities are caused by these three kind of accidents. Differential analysis shows about 4 to 6 years delay after railroad safety investment and safety improvement. This result can be utilized for the decision making on safety measures and safety target. Which required long term approach.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.127-135
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• 2021

We analyze the information asymmetry in the capital market by examining the long-term performance by the insider's trading behavior in the companies that made investment announcements for the construction of the new office building. The results are summarized as follows. On average, the long-term abnormal returns on share prices of sample firms represent a significant positive value. The regression analysis confirmed that there is a statistically significant positive correlation between the factor of the change in equity of large shareholders and the long-term performance. On the other hand, negative correlation was observed between change in equity of small individual investors and long-term performance. These results mean that an insider can determine the authenticity of a manager's private intention. In other words, it supports that the insider is in a position of information superiority. In addition, it is expected to provide practical usefulness to investors in that the change in equity can be used as a predictor of long-term performance.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.19-34
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• 2008

IT investment is usually very costly and takes a long time to get the results out of investment. However, most of currently available evaluation methods for IT investment are based upon short-term effects, hence their results are not fully trustworthy. In addition, those methods commonly consider only financial aspects such as ROI. For more reliable evaluation, it is necessary to consider non-financial factors such as system utilization, customer satisfaction, public relations, and so on, as well as financial factors. In this research, we propose an evaluation method that can evaluate both financial and non-financial aspects on a long-term base. For this purpose, we employed the research results developed in System dynamics and Balanced scorecard. System dynamics is useful in analyzing long term behavior of a given system, and Balanced scorecard is useful for evaluating both financial and non-financial aspects. We demonstrated the usefulness of our method by applying it to the evaluation of RFID (Radio Frequency Identification) investment in a distribution and retail industry. From this application, we found that RFID investment may not be rewarding in the short term, but is sure to be returning the income relative to its investment in the long run.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.153-160
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• 2019

This paper analyzes the impact of investment tendency of foreign investor on accounting conservatism. We use the sample of 1,527 firm-year Korea listed companies belonging to non-financial corporate sector during 2014-2016. The results of empirical analyses show that investment horizons of foreign investors has a positive relevance with accounting conservatism. This result indicates that the firm have a long-term foreign investors has a good quality of accounting earning than the firm have a short-term foreign investors. This study that verified the relevance between investment tendency of foreign investor and accounting conservatism is expected to provide useful information by suggesting the need for more incentive for the long-term foreign investors. And we expect a follow-up study focused on the discriminative effect of investment tendency of foreign investor on accounting policy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.21-31
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• 2020

This study investigates the dynamic effects of economic development, international cooperation, electricity consumption, and political risk on the escalation of CO₂ emission in Vietnam. We adopted autoregressive distributed lag model and Granger causality method to examine the interaction between CO₂ and various economic and political factors, including foreign direct investment, trade openness, economic growth, manufacture, electricity consumption, and political risk in Vietnam since the economic revolution in 1986. The findings reflect opposite influence between these factors and the level of CO₂ in the intermediate and long-term durations. Accordingly, foreign direct investment and CO₂ emission have a bidirectional relationship, in which foreign direct investment accelerates short-term CO₂ emission, but reduces it in the long run through an interactive mechanism. Moreover, economic development increases the volume of CO₂ emission in both short and long run. There was also evidence that political risk has a negative effect on the environment. Overall, the findings confirm lasting negative environmental effects of economic growth, trade liberalization, and increased electricity consumption. These factors, with Granger causality, mutually affect the escalation of CO₂ in Vietnam. In order to control the level of CO₂, more efforts are required to improve administrative transparency, attract high-quality foreign investment, and decouple the environment from economic development.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.289-294
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• 2020

The study of environmental pollution plays an important role in controlling emissions in the production activities of FDI enterprises as well as export goods. Vietnam is a country with a large proportion of FDI contribution and high export value. Therefore, there should be studies to assess the actual effects of FDI and the openness of the economy (trade) on the environment. Therefore, the authors conduct research on the role of FDI and trade on environmental quality in Vietnam. With data collected from 1990 to 2018 (from the period of Vietnam's economy opening up) through the ARDL (Autoregressive Distributed Lag) model, the results show that FDI has a positive impact on CO2 emissions in the short term but has no impact on the long-term (In this study, CO2 is considered to represent environmental quality). The trade has a positive impact on CO2 emissions in both the short term and long term. The results of the study show the actual shortcomings of FDI as well as production activities in the export enterprises in Vietnam. From the results of this research, the author also provides the causes and remedies to control of CO2 emissions from two activities of foreign direct investment and trade.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.105-111
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• 2023

Recently, research on prediction algorithms using deep learning has been actively conducted. In addition, algorithmic trading (auto-trading) based on predictive power of artificial intelligence is also becoming one of the main investment methods in stock trading field, building its own history. Since the possibility of human error is blocked at source and traded mechanically according to the conditions, it is likely to be more profitable than humans in the long run. In particular, for the virtual currency market at least for now, unlike stocks, it is not possible to evaluate the intrinsic value of each cryptocurrencies. So it is far effective to approach them with technical analysis and cryptocurrency market might be the field that the performance of algorithmic trading can be maximized. Currently, the most commonly used artificial intelligence method for financial time series data analysis and forecasting is Long short-term memory(LSTM). However, even t4he LSTM also has deficiencies which constrain its widespread use. Therefore, many improvements are needed in the design of forecasting and investment algorithms in order to increase its utilization in actual investment situations. Meanwhile, Prophet, an artificial intelligence algorithm developed by Facebook (META) in 2017, is used to predict stock and cryptocurrency prices with high prediction accuracy. In particular, it is evaluated that Prophet predicts the price of virtual currencies better than that of stocks. In this study, we aim to show Prophet's virtual currency price prediction accuracy is higher than existing deep learning-based time series prediction method. In addition, we execute mock investment with Prophet predicted value. Evaluating the final value at the end of the investment, most of tested coins exceeded the initial investment recording a positive profit. In future research, we continue to test other coins to determine whether there is a significant difference in the predictive power by coin and therefore can establish investment strategies.