• Journal of Digital Convergence
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• v.18 no.2
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• pp.205-211
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• 2020

The method of predicting the future may be predicted by technical characteristics or technical performance. Therefore, technology prediction is used in the field of strategic research that can produce economic and social benefits. In this study, we predicted the future market through the study of how to predict the future with these technical characteristics. The future prediction method was studied through the prediction of the time when the market occupied according to the demand of special product. For forecasting market demand, we proposed the future forecasting model through comparison of representative quantitative analysis methods such as CAGR model, BASS model, Logistic model and Gompertz Growth Curve. This study combines Rogers' theory of innovation diffusion to predict when products will spread to the market. As a result of the research, we developed a methodology to predict when a particular product will mature in the future market through the spread of various factors for the special product to occupy the market. However, there are limitations in reducing errors in expert judgment to predict the market.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.81-96
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• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.44-48
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• 2015

Housing price is a key indicator of housing demand. Actual Transaction Price Index of Apartment (ATPIA) released by Korea Appraisal Board is useful to understand the current level of housing price, but it does not forecast future prices. Big data such as the frequency of internet search queries is more accessible and faster than ever. Forecasting future housing demand through big data will be very helpful in housing market. The objective of this study is to develop a forecasting model of ATPIA as a part of forecasting housing demand. For forecasting, a concept of time shift was applied in the model. As a result, the forecasting model with the time shift of 5 months shows the highest coefficient of determination, thus selected as the optimal model. The mean error rate is 2.95% which is a quite promising result.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.47-53
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• 2005

The efficiency of fabrication (fab) operation is one of the key factors in order for a semiconductor manufacturing company to stay competitive. Optimization of manpower and forecasting manpower needs in a modern fab is an essential part of the future strategic planing and a very important to the operational efficiency. As the semiconductor manufacturing technology has entered the 8-inch wafer era, the complexity of fab operation increases with the increase of wafer size. The wafer handling method has evolved from manual mode in 6-inch wafer fab to semi-automated or fully automated factory in 8-inch and 12-inch wafer fab. The distribution of manpower requirement in each specialty varied as the trend of fab operation goes for downsizing manpower with automation and outsourcing maintenance work. This paper is to study the specialty distribution of manpower from the requirement in a typical 6-inch, 8-inch to 12-inch wafer fab. The human resource planning in today’s fab operation shall consider many factors, which include the stability of technical talents. This empirical study mainly focuses on the human resource planning, the manpower distribution of specialty structure and the forecast model of internal demand/supply in current semiconductor manufacturing company. Considering the market fluctuation with the demand of varied products and the advance in process technology, the study is to design a headcount forecast model based on current manpower planning for direct labour (DL) and indirect labour (IDL) in Taiwan’s fab. The model can be used to forecast the future manpower requirement on each specialty for the strategic planning of human resource to serve the development of the industry.

• Korean Management Science Review
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• v.25 no.1
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• pp.29-41
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• 2008

In the mobile communication service market, this study represents an attempt to forecast the subscribers of the IMT-2000 service market using the questionnaire of experts which is the qualitative technique is used. In this study, by using the substitution model of next generations among products in order to analyze the IMT-2000 demand of service, a demand was predicted. And by estimating the market demand prospect in which it becomes the important factor of the IMT-2000 service diffusion according to each bandwidth frequency the politically necessary approaching direction about the frequency was presented. It will be able to become the important part to not only the business carrier but also the policy maker to examine a prospect toward the subscriber of the IMT-2000 service. As a result, the market demand was exposed to be most big when the SKT 800MHz, and the KTF 800(900)MHz were used as the additional frequency. And it was likely to reach to the IMT-2000 number of subscribers to about 35.750 thousand peoples in the future at 2015.

• Korean System Dynamics Review
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• v.7 no.2
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• pp.57-80
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• 2006

Nuclear technology made a great contribution to the national economy and society by localization of nuclear power plant design, and by stabilization of electricity price, etc. It is very important to conduct the retrospective analysis for the nuclear technology contribution to the national economy and society, but it is more important to conduct prospective analysis for the nuclear technology contribution. The term "technology value" is often used in the prospective analysis to value the result of technology development. There are various definitions of technology value, but generally it means the increment of future revenue or the reduction of future cost by technology development. These technology valuation methods are widely used in various fields (information technology or energy technology, etc). The main objective of this research is to develop valuation methodology that represents unique characteristics of nuclear power technology. The valuation methodology that incorporates market share changes of generation technologies was developed. The technology valuation model which consists of five modules (electricity demand forecast module, technology development module, market share module, electricity generation module, total cost module) to incorporate market share changes of generation technologies was developed. The nuclear power technology value assessed by this technology valuation model was 3 times more than the value assessed by the conventional method. So it was confirmed that it is very important to incorporates market share changes of generation technologies. The valuation results of nuclear power technology in this study can be used as policy data for ensuring the benefits of nuclear power R&D (Research and Development) investment.

• Journal of Distribution Science
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• v.10 no.11
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• pp.31-37
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• 2012

Purpose - This study was conducted under the assumption that brand A, a store of company Z of Pangyo, with a new store at Pangyo station is targeting the Bundang-gu area of the newly developed city of Seongnam. Research design, data, methodology - As a result of demand forecasting using geometric series models, an extrapolation of past trends provided the coefficient estimates, without utilizing regression analysis on a constant increase in children's wear, for which the population size and estimated parameter were required. Results - Demand forecasting on the basis of past trends indicates the likelihood that sales of discount stores in the Bundang area, where brand A currently has a presence, would fetch a higher estimated value than that of the average discount store in the country during 2015. If past trends persist, future sales of operational stores are likely to increase. Conclusions - In evaluating location using the simple weighting model, Seohyun Lotte Mart obtained a high rating amongst new stores in Pangyo, on the basis of accessibility, demand class, and existing stores. Therefore, when opening a new counter at a relevant store, a positive effect can be predicted.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.139-145
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• 1996

A forecast on the past output data sets of small bar steels is very important information to make a decision on the future production quantities. In many cases, however, it has been mainly determined by experience (or rule of thumb). In this paper, past basic data sets of each small bar steels are statistically analyzed by some graphical and statistical forecasting methods. This work is mainly done by SAS. Among various quantitative forecasting methods in SAS, STEPAR forecasting method was best performed to the above data sets. By the method, the future production quantities of each small bar steels are forecasted. As a result of this statistical analysis, 95% confidence intervals for future forecast quantities are very wide. To improve this problem, a suitable systematic database system, integrated management system of demand-production-inventory and integrated computer system should be required.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.113-123
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• 2011

Recently, the global warming problem has arised around world, many nations has set up a various regulations for decreasing $CO_2$. In particular, $CO_2$ emissions reduction effect is very powerful in transport part, so there is a rising interest about development of green car, or electric vehicle in auto industry. For this reason, it is important to make a strategy for charging infra and forcast electric power demand, but it hasn't introduced about demand forecasting electric vehicle. Thus, this paper presents a demand forecasting for electric vehicles using choice based multigeneration diffusion model. In this paper, it estimates innovation coefficient, immitation coefficient in Bass model by using hybrid car market data and forecast electric vehicle market by year using potential demand market through SP(Stated Preference) experiment. Also, It facilitates more accurate demand forecasting electric vehicle market refelcting multigeneration diffusion model in accordance with attribute progress in development of electric vehicle. Through demand forecasting methodology in this paper, it can be utilized power supply and building a charging infra in the future.

• Korean System Dynamics Review
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• v.2 no.2
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• pp.25-40
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• 2001

This paper describes the forecast of power plant construction in a competitive korean electricity market. In Korea, KEPCO (Korea Electric Power Corporation, fully controlled by government) was responsible for from the production of the electricity to the sale of electricity to customer. However, the generation part is separated from KEPCO and six generation companies were established for whole sale competition from April 1st, 2001. The generation companies consist of five fossil power companies and one nuclear power company in Korea at present time. Fossil power companies are scheduled to be sold to private companies including foreign investors. Nuclear power company is owned and controlled by government. The competition in generation market will start from 2003. ISO (Independence System Operator will purchase the electricity from the power exchange market. The market price is determined by the SMP(System Marginal Price) which is decided by the balance between demand and supply of electricity in power exchange market. Under this uncertain circumstance, the energy policy planners such as government are interested to the construction of the power plant in the future. These interests are accelerated due to the recent shortage of electricity supply in California. In the competitive market, investors are no longer interested in the investment for the capital intensive, long lead time generating technologies such as nuclear and coal plants. Large unclear and coal plants were no longer the top choices. Instead, investors in the competitive market are interested in smaller, more efficient, cheaper, cleaner technologies such as CCGT(Combined Cycle Gas Turbine). Electricity is treated as commodity in the competitive market. The investors behavior in the commodity market shows that the new investment decision is made when the market price exceeds the sum of capital cost and variable cost of the new facility and the existing facility utilization depends on the marginal cost of the facility. This investors behavior can be applied to the new investments for the power plant. Under these postulations, there is the potential for power plant construction to appear in waves causing alternating periods of over and under supply of electricity like commodity production or real estate production. A computer model was developed to sturdy the possibility that construction will appear in waves of boom and bust in Korean electricity market. This model was constructed using System Dynamics method pioneered by Forrester(MIT, 1961) and explained in recent text by Sternman (Business Dynamics, MIT, 2000) and the recent work by Andrew Ford(Energy Policy, 1999). This model was designed based on the Energy Policy results(Ford, 1999) with parameters for loads and resources in Korea. This Korea Market Model was developed and tested in a small scale project to demonstrate the usefulness of the System Dynamics approach. Korea electricity market is isolated and not allowed to import electricity from outsides. In this model, the base load such as unclear and large coal power plant are assumed to be user specified investment and only CCGT is selected for new investment by investors in the market. This model may be used to learn if government investment in new unclear plants could compensate for the unstable actions of private developers. This model can be used to test the policy focused on the role of unclear investments over time. This model also can be used to test whether the future power plant construction can meet the government targets for the mix of generating resources and to test whether to maintain stable price in the spot market.