• Journal of KIEE
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• v.11 no.1
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• pp.51-54
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• 2001

In this paper, a MW-Mvar investment technique focused on minimizing the system loss is presented. An optimization technique, in which the system loss is defined as the objective function and the power flow equations as the constraints, is introduced to obtain the Lagrangian multipliers λP and λQ. The Lagrangian multipliers imply the variation of the system loss with respect to incremental bus power and are used as MW-Mvar investment indices for minimizing the system loss. ΔP MW and ΔQ Mvar are invested, step by step, by the priority of λP and λQ index given for each bus. Derivation of the index uses the information from normal power flow calculation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.7
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• pp.407-413
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• 2003

Before expanding of distribution automation application to distribution network, we must examine whether there are economical effect. Investment expense for distribution automation can be divided into facility investment expense, maintenance expense, communication expense, investment expense etc. Effect of distribution automation can classify by effect that can convert into money and effect that can not convert into money. Representative effect is outage time decrease effect, distribution line loss decrease effect, main transformer upload effect, distribution line upload effect, work environment improvement effect of lineman and so on. This paper studied economical effect and break-even Point for investment expense by using data that acquire in KEPCO's distribution network.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.2
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• pp.56-61
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• 2000

In the paper, the system loss sensitivity index that implies the incremental system loss with respect to the change of bus power is derived using optimization technique. The index λ reaches $\infty$ at critical loading point and can be applied to actual power systems for following purposes. 1) Evaluation of system voltage stability 2)Optimal investment of reactive power focused on minimizing system loss and maximizing system voltage stability 3)Optimal re-location of reactive power focused on minimizing system loss and maximizing system voltage stability 4)Optimal load shedding in case of severe system contingency focused on minimizing system loss and maximizing system voltage stability. Case studies for each application have proved their effectiveness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.50-56
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• 2017

The IRR (internal rate of return) is often used by investors for the evaluation of engineering projects. Unfortunately, it is widely known that it has serial flaws. Also, External rate of returns (ERRs) such as ARR (Average Rate of Return) or MIRR (MIRR, Modified Internal Rate of Return) do not differentiate between the real investment and the expenditure. The PRR (Productive rate of return) is faithful to the conception of the return on investment. The PRR uses the effective investment instead of the initial investment. In this paper, we examined two cases of the engineering project. the one is a traditional engineering project with financing activity, another is the project with R&D. Although the IRR has only one value, it overestimates or underestimate profitabilities of Engineering Projects. The ARR and the MARR assume that a returned cash reinvest other projects or assets instead of the project currently executing. Thus they are only one value of a project's profitability, unlike the IRR. But the ARR does not classify into the effective investment and non-investment expenditure. It only accepts an initial expenditure as for an investment. The MIRR also fails to classify into the investment and the expenditure. It has an error of making a loss down as the investment. The IRR works as efficiently as a NPW (Net Present Worth). It clearly expresses a rate of return in respect of an investment in an engineering project with a loan. And it shows its ability in an engineering project with a R&D investment.

• Korea Real Estate Review
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• v.27 no.1
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• pp.7-16
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• 2017

In this study, we examine whether there are prospect theory investment patterns for individual investors in the real estate market. We use the maximum potential profit rate and the maximum potential loss rate of individual investors as a research method and additionally analyze it using the Jeong and Park(2015) model. As a result of the analysis, it was found that the investment pattern according to the prospect theory and disposition effect for individual investors. And we find the difference between zoning areas. This difference in investment behavior is believed to be due to the purpose of the real estate and the existence of rent fee, which creates a difference in investment behavior depending on the purpose. The limitations of this study are the analysis measurement of potential profit and potential loss using the land price index like the study of jeong and Park(2015). This implies that a new property price index needs to be developed or a benchmark for real estate assets is needed for deeper study of real estate investment sentiment.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.44 no.10
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• pp.1290-1294
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• 1995

In this paper, a new voltage collapse proximity index (VCPI) based on system apparent power loss sensitivity is proposed. The newly proposed index .lambda.$^{Sloss}$ reaches -.inf. at system voltage collapse point and can be represented by .root..lambda.$^{Ploss}$$^{2}$+.lambda.$^{Qloss}$$^{2}$ where .lambda.$^{Ploss}$ and .lambda.$^{Qloss}$ are the VCPI based on the system active and reactive power loss sensitivity respectively. These indices can be used for the system VAR investment. .DELTA.Q [VAR] is invested, step by step, by the priority of the VCPI index given for each bus. The indices use information from normal power flow equations and their Jacobians. Computation time for deriving .lambda.$^{Sloss}$ is almost same as that for power flow calculation. Two case studies prove the effectiveness of the .lambda.$^{Sloss}$ index and the VAR investment algorithm proposed.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.635-645
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• 2020

This research was conducted to achieve several objectives and focus research was based on financial behavior theory and prospect theory as grounded theory e.g., investigate the financial decision-making behavior between financial and real assets investment, and confirm the relationship existing between herding behavior and overconfidence factors to the level of loss and regret aversion, and financial literacy into real assets investment decisions. The study used 220 real estate auction respondents as investor samples at the State Assets and Auction Service Office Makassar, South Sulawesi, Indonesia. Data was collected through the use of a questionnaire consisting of 23 questions to measure the variables. Moreover, the research data passed through several feasibility tests like the inner and outer modeling by Partial Least Square - Structural equation model (PLS-SEM) while the hypotheses formulated were also tested to determine the magnitude of the variable relationship. Through the use of the direct and intervening test, loss and regret aversion variables have a positive and significant effect while financial literacy variables have no significant effect. There is a slight difference in the decision-making process for real assets and financial assets investors. Investment decision making behavior in the financial assets sector requires less complicated decisions compared to the decisions related to real assets investments.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1231-1240
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• 2021

A shift in perspective from standard finance to behavioral finance has taken place in the past two decades that explains how cognition and emotions are associated with financial decision making. This study aims to investigate the influence of various psychological factors on investment decision-making. The psychological factors that are investigated are differentiated into two aspects, cognitive and emotional aspects. From the cognitive aspect, we examine the influence of anchoring, representativeness, loss aversion, overconfidence, and optimism biases on investor decisions. Meanwhile, from the emotional aspect, the influence of herding behavior on investment decisions is analyzed. A quantitative approach is used based on a survey method and a snowball sampling that result in 165 questionnaires from individual investors in Yogyakarta. Further, we use the One-Sample t-test in testing all hypotheses. The research findings show that all of the variables, anchoring bias, representativeness bias, loss aversion bias, overconfidence bias, optimism bias, and herding behavior have a significant effect on investment decisions. This result emphasizes the influence of behavioral factors on investor's decisions. It contributes to the existing literature in understanding the dynamics of investor's behaviors and enhance the ability of investors in making more informed decision by reducing all potential biases.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.147-165
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• 2009

This study proposes a certain measure or investment strategy for decision making associated with seismic retrofitting. This strategy reduces the risk of a large-scale malfunction such as water supply loss under seismic risks. The authors developed a stochastic value index that will be used in the overall evaluation of social benefit, income gain, life cycle costs and failure compensation associated with existing lifeline systems damaged by an earthquake during the remaining service period. Optimal seismic disaster prevention investment of deteriorated lifeline systems is discussed. Finally, the present study provides a performance-based design method for seismic retrofitting strategies of existing lifelines which are carried out using the target probabilities of value loss and structural failure.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.27-43
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• 2011

This article explores economic models that show the optimal level of information security investment in the presence of interdependent security risks, Using particular functional forms, the analysis shows that the relationship between the levels of security vulnerability and the levels of optimal security investments is affected by externalities caused by agents' correlated security risks. This article further illustrates that, compared to security investments in the situation of independent security risks, in order to maximize the expected benefits from security investments, an agent should invest a larger fraction of the expected loss from a security breach in the case of negative externalities, while an agent should spend a smaller fraction of the expected loss in the case of negative externalities.