• Korean Management Science Review
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• v.22 no.1
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• pp.179-197
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• 2005

This study examines market acceptance for DMB service, one of the touted new business models in Korea's next-generation mobile communications service market, using adoption end diffusion of innovation as the theoretical framework. Market acceptance for DMB service was assessed by predicting the demand for the service using the Bass model, and the demand variability over time was then analyzed by integrating the innovation adoption model proposed by Rogers (2003). In our estimation of the Bass model, we derived the coefficient of innovation and coefficient of imitation, using actual diffusion data from the mobile telephone service market. The maximum number of subscribers was estimated based on the result of a survey on satellite DMB service. Furthermore, to test the difference in diffusion pattern between mobile phone service and satellite DMB service, we reorganized the demand data along the diffusion timeline according to Rogers' innovation adoption model, using the responses by survey subjects concerning their respective projected time of adoption. The comparison of the two demand prediction models revealed that diffusion for both took place forming a classical S-curve. Concerning variability in demand for DMB service, our findings, much in agreement with Rogers' view, indicated that demand was highly variable over time and depending on the adopter group. In distinguishing adopters into different groups by time of adoption of innovation, we found that income and lifestyle (opinion leadership, novelty seeking tendency and independent decision-making) were variables with measurable impact. Among the managerial variables, price of reception device, contents type, subscription fees were the variables resulting in statistically significant differences. This study, as an attempt to measure the market acceptance for satellite DMB service, a leading next-generation mobile communications service product, stands out from related studies in that it estimates the nature and level of acceptance for specific customer categories, using theories of innovation adoption and diffusion and based on the result of a survey conducted through one-to-one interviews. The authors of this paper believe that the theoretical framework elaborated in this study and its findings can be fruitfully reused in future attempts to predict demand for new mobile communications service products.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.457-466
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• 2013

Wind energy is rapidly becoming significant generating technologies in electricity markets. As probabilistic nature of wind energy creates many uncertainties in the short-term scheduling, additional actions for reliable market operation should be taken. This paper presents a novel approach to evaluate ramping capability requirement for changes in imbalance energy between day-ahead market and real-time market due to uncertainty of wind generation as well as system load. Dynamic ramp rate model has been applied for realistic solution in unit commitment problem, which is implemented in day-ahead market. Probabilistic optimal power flow has been used to verify ramping capability determined by the proposed method is reasonable in economic and reliable aspects. This approach was tested on six-bus system and IEEE 118-bus system with a wind farm. The results show that the proposed approach provides ramping capability information to meet both forecasted variability and desired confidence level of anticipated uncertainty.

• Environmental and Resource Economics Review
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• v.18 no.2
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• pp.311-344
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• 2009

The hypothesis that the common market equilibria for housing attributes are attained within distinctive submarkets was tested. Markets for housing attributes with greater supply flexibility, i.e., structural variables, were found to be closer to their common equilibria than markets with less supply flexibility, i.e., neighborhood and distance variables. In addition, submarkets with greater mobility were found to achieve common market equilibria for more housing attributes with greater supply flexibility, but not for housing attributes with lower degree of supply flexibility. Results suggest supply flexibility and occupier mobility are both necessary conditions for achieving common market equilibria for housing attributes.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.185-201
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• 2003

The business component for satisfying a variety of domain requirements should be developed to provide a variety. But, although components are developed by analyzing the variety of requirements when they are developed, developing components that satisfy all requirements is not easy since unexpected requirements occur as it is used components. For this reason, components are not provided as black boxes but as white boxes, and there by components are not modified in the interface only but the source codes are directly modified. Accordingly, a Time-To-Market by the use of components is not easy and a reusability of the components also decreases. This study proposes a customization technique that can be satisfied requirements of many different kinds of domains by analyzing variable spots of components. The initial variability of components is designed in the component development phase. and a customization technique is used to apply the variability. The variability can be redesigned during the development of application by using the components to which the variability is applied. Through this process, a variability of components evolves and a generality of the components can be improved. The proposing customization technique in this study can change the component to extend without changing the existing component when it is redesigned.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.47-63
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• 2019

The volatility of major crypto currencies was examined and they are diagnosed whether they have a systematic risk or not, by estimating market beta representing systematic risk using GARCH( Generalized Auto Regressive Conditional Heteroskedastieity) model. First, the empirical results showed that their prices are very volatile over time because of the existence of ARCH and GARCH effects. Second, in terms of efficiency, asymmetric GJR model was estimated to be the most appropriate model because the standard error of a market beta was less than that of the OLS model and GARCH model. Third, the estimated market beta of Bitcoin using GJR model was less than 1 at 0.8791, showing that there is no systematic risk. However, unlike OLS model, the market beta of Ethereum and Ripple was estimated at 1.0581 and 1.1222, showing that there is systematic risk. This result shows that bitcoin is less dangerous than Ripple and Ethereum, and ripple is the most dangerous of all three crypto currencies. Finally, the major cryptocurrency found that the negative impact caused greater variability than the positive impact, causing bad news to fluctuate more than good news, and therefore good news and bad news had a different effect on the variability.

• Korean Management Science Review
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• v.31 no.3
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• pp.1-12
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• 2014

This study suggests the two types DEA models such as DEA CCR model and Super Efficiency model to evaluate the value of a company and to apply them for the investments. 14 kinds of real data of companies such as EV/EBITDA, EPS growth rate, PCR, PER, dividend yield, PBR, stock price/net current asset, debt ratio, current ratio, ROE, operating margin, inventory turnover, accounts receivable turnover, and sales growth ratio were used as input variables of DEA models. 12 year data from December 30, 2000 up to December 30, 2012 were collected, and the data with negative, missing and 0 values were removed reflecting the characteristics of the DEA. In order to verify the effectiveness of the models, we compared the historical variability and rate of return of both models those of the market. Study results are as follows. First, two DEA models are more stable than market in terms of rate of return because the historical variability of both models are less than that of market. Second, Super Efficiency model is more stable than CCR model. Lastly, the cumulative rate of return of Super Efficiency model (434%) is greater than that of the CCR model (420%) and that of the market (269%).

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.1
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• pp.49-58
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• 2014

Variability factors of transship cargo in the container transportation market analysis short term factors. In the past, studies on the factor of variability in container cargo volume have focused on long term volume forecast and increase in investment and competitiveness from strategic perspectives. Unlike previous studies, this paper analyzes factors of variability in transshipment volume rapidly varying in short term and seeks measures. Since it was identified that transshipment volume depends on vessel operation cost and port volume in long term but effectively on special strategies launched by port authorities in short term, the port authority experienced rapid drop in volume should continue to observe strategies of competition ports and to make use of strategies seeking appropriate countermeasures.

• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.13-24
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• 2005

Software development by component integration is the mainstream for time-to-market and is the solution for overcoming the short lifecycle of software. Therefore, the effective techniques for component integration have been working. However, the systematic and practical technique has not been proposed. One of main issues for component integration is how to specify integration and the component architecture for operating the specification, in this paper, we propose a workflow variability design technique for component integration, This technique focuses on designing to a connection contract based on the component architecture. The connection contract is designed to use the provided interface of component and the architecture can assemble and customize components by the connection contract dynamically.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.539-549
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• 2006

Component-Based Development (CBD) has emerged as a new effective technology that reduces development cost and time-to-market by assembling reusable components in developing software. The degree of conformance to standards and common features in a domain largely determines the reusability of components. In addition, variability within commonality should also be modeled and customization mechanism for the variability should be designed into components. Enterprise JavaBeans (EJB) is considered a most suitable environment for implementing components. However. the reusability of EJB is limited because EJB does not have built-in variability design mechanisms. In this paper, we present efficient variability design techniques for implementing components in EJB. We propose a method to customize the variability of EJB-based components by applying three variability design mechanisms; selection, plug-in, and external profile. And we elaborate the suitable situations where each variability design mechanism can be applied, and conduct a technical comparison to other approaches available.