• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.289-291
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• 2000

In a competitive electricity power market, the price of electricity changes instantly, that of conventional market is predetermined and hardly changes. In such a new environment, customers' behaviors change instantly according to the changing electricity prices. If we develop a electricity load model that well describes the behavior of electricity consumers, we can utilize that model in forecasting the amount of future load, solving the load flow problem and finding the weak point of the system. In this paper new electricity model that considers the price of electricity and power factor of the load is presented. While conventional load model, which is demand function of electricity, uses the price of real and reactive power as the independent variable of the demand function. this new load model uses price of real power and penalty factor according to the power factor for the calculation of amount of electricity demand.

• 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 Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.822-831
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• 2008

This paper examines the theoretical and empirical technology diffusion processes to understand the Korean success in the internet access service markets. In order to do this, first, we propose an integrated demand diffusion model in terms of competition of inter-and intra-technologies and market structure as represented by the number of operators in the market. Second, by using the proposed model, we analyze the dynamic diffusion processes of Korean internet access services such as Narrow-band technology including Dial modem vs. Broad-band technology including ISDN, xDSL and Cable modem. The competition of inter-and intra-technologies as well as the extent of market competition has made a positive effect on the diffusion patterns of internet access demand. And also we propose, based on the proposed model and its empirical results, several implications for diffusion strategies and policies in the future of ICT market in Korea.

• Environmental and Resource Economics Review
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• v.17 no.2
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• pp.287-311
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• 2008

This paper is designed to examine how the global timber market impacted by climate change would affect global warming through the carbon flux of forests. For this purpose, we integrated the modified TSM 2000 and the extended TCM in order to simulate the projection of net carbon release of forests from 1995 to 2085. On the basis of the simulation results under normal demand growth scenario, we identified that the global timber market impacted by climate change ameliorates the atmospheric carbon about 3.60% of carbon dioxide concentration in 1990 over 90 years. This implies that the global timber market impacted by climate change has a negative feedback effect on global warming over 90 years. For sensitivity analysis, we performed these simulation procedure under high demand growth scenario and very high demand growth scenario.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.63-72
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• 2012

The Korean telecommunications market has been expanding swiftly, these days, to be saturated. In this environment, the upcoming mobile telecommunication market, where 4G service was introduced this year, is becoming more substitutive and competitive. Thus, the demand forecasting of 4G service is very difficult, while it is critical to market success. This paper adopts a multi-generation diffusion model to capture the diffusion and substitution patterns for two successive generation of technological services, i.e., 3G and 4G mobile telecommunications services. The three parameters, i.e., the coefficient of innovation, the coefficient of imitation, and the coefficient of market potential, used in the multi-generation diffusion model based on Norton and Bass[11] are obtained by inference from similar substitutive relations between older and newer telecommunication services to 3G and 4G services. The simulation results show that the Bass type multi-generation model can be successfully applied to the demand forecasting of newly introduced 4G mobile telecommunication service.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1232-1255
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• 2011

This paper proposes a model for demand forecasting that will require less effort in the process of utilizing the new product diffusion model while also allowing for more objective and timely application. Drawing upon the theoretical foundation provided by the hype cycle model and the consumer adoption model, this proposed model makes it possible to estimate the maximum market potential based solely on bibliometrics and the scale of the early market, thereby presenting a method for supplying the major parameters required for the Bass model. Upon analyzing the forecasting ability of this model by applying it to the case of the hybrid car market, the model was confirmed to be capable of successfully forecasting results similar in scale to the market potential deduced through various other objective sources of information, thus underscoring the potentials of utilizing this model. Moreover, even the hype cycle or the life cycle can be estimated through direct linkage with bibliometrics and the Bass model. In cases where the hype cycles of other models have been observed, the forecasting ability of this model was demonstrated through simple case studies. Since this proposed model yields a maximum market potential that can also be applied directly to other growth curve models, the model presented in the following paper provides new directions in the endeavor to forecast technology diffusion and identify promising technologies through bibliometrics.

• The Journal of Fisheries Business Administration
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• v.34 no.2
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• pp.131-139
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• 2003

The products of the quality certificated fisheries which are protected from environmental pollution, decomposition are hygienically safe and convenient for food. However, consumers have not yet understood the recognition of the system of quality certfication so far because of lack of demand on the quality certification fisheries. Above all, to put the system of the quality QC in place sucessfully, to understand the variation of consumer's inclination efficiently, the empirical study must be carried out by both consumer's take part in the market of the quality certificated fisheries products and how much the amount of consumption is in this market. The purpose of this study, under the preconditions where these have limited fisheries items in consumer's inclination survey, is to analyze the demand of QC though the Double Hurdle Model. Explanatory variables included were household characteristics such as housewives' age and education, her job, household income as well as their health perceptions and food purchase behaviors. Survey from 530 household was collected in Pusan City in 2003, of 502 were actually used for empirical analysis. The Double-hurdle framework proved to a better representation of the factors influencing the separate decision participation and consumption levels. According to the results of this study, whether or not, participating In the market of quality certicipating in the market of qualify certificated fisheries products is affected by how much experience and confidence these have got. housewives' having a job or not. Furthermore, the amount of consumption is mostly affected income. This value is attributed to the safety of QC fisheries products in comparison with regular fisheries. Findings suggest that the consumers put substantially high monetary value on safe food, such as high quality fisheries products. Therefore, first of all, legal and institutional systems should be clearly and strictly identified for the QC products.

• Perspectives in Nursing Science
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• v.13 no.2
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• pp.81-87
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• 2016

Purpose: The aim of this study is to review the nurse demand forecasting methods in empirical studies published during 1991~2014 and suggest ideas to improve the validity in nurse demand forecasting. Methods: Previous studies on nurse demand forecasting methodology were categorized into four groups: time series analysis, top-down approach of workforce requirement, bottom-up approach of workforce requirement, and labor market analysis. Major methodological properties of each group were summarized and compared. Results: Time series analysis and top-down approach were the most frequently used forecasting methodologies. Conclusion: To improve decision-making in nursing workforce planning, stakeholders should consider a variety of demand forecasting methods and appraise the validity of forecasting nurse demand.

• Korean Management Science Review
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• v.19 no.2
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• pp.125-137
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• 2002

The telecommunications market is expanding rapidly and becoming more substitutive. In this environment, demand forecasting is very difficult, yet important for both practitioners and researchers. in this paper, we adopt the modeling approach proposed dy Jun and Park ［6］. The basic premise is that demand patterns result from choice behavior, where customers choose a product to maximize their utility. We apply a choice-based substitutive diffusion model to the Korean mobile telecommunication service market where digital service has completely replaced analog service. In comparison with Bass-type multigeneration models. our model provides superior fitting and forecasting performance. The choice-based model is useful in that it enables the description of such complicated environments and provides the flexibility to include marketing mix variables such as price and advertising in the regression analysis.