• Journal of Digital Convergence
• /
• v.18 no.2
• /
• pp.205-211
• /
• 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 the Korea Academia-Industrial cooperation Society
• /
• v.10 no.10
• /
• pp.2923-2934
• /
• 2009

This paper presents study on technological forecasting of Next-Generation Display technology. Next-Generation Display technology is one of the emerging technologies lately. So databases on patent documents of this technology were analyzed first. And patent analysis was performed for finding out present technology trend. And the forecast for this technology was made by growth curves which were obtained from forecast models using patent documents. In previous study, Gompertz, Logistic, Bass were used for forecasting diffusion of demand in market. Gompertz, Logistic models which were often used for technological forecasting, too. So, two models were applied in this study. But Gompertz, Logistic models only consider internal effect of diffusion. And it is difficult to estimate maximum value of growth in two models. So, Bass model which considers both internal effect and external effect of diffusion was also applied. And maximum value of growth in Gompertz, Logistic models was estimated by Bass model.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10a
• /
• pp.508-510
• /
• 2003

주식 가격의 결정은 시장 내 수요와 공급에 의해서 결정되며, 가격 변동은 일정한 패턴으로 움직인다고 가정한다. 이러한 패턴을 찾아내어 주식가격의 변동을 예측하는 분석 방법을 기술적 분석이라 한다. 기술적 분석에서는 수요.공급의 변화에 의해 추세가 변동되고, 모든 형태의 주가모형은 반복하려는 경향을 보인다고 가정한다. 이러한 가정하에 본 논문에서는 한국주가지수 200의 과거지수와 거래량을 분석하고, 일정한 패턴을 이용하여 미래의 지수를 예측하는 방법을 연구하였다.

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

• International Area Studies Review
• /
• v.14 no.3
• /
• pp.35-60
• /
• 2010

In this paper, we develop a dynamic structural model based on a dynamic supergame and measure market power for the Dallas-Forth Worth fluid milk market in the U.S. In particular, we compare the conduct parameter estimates from a static model with that from the dynamic model and illustrate bias in the market-power measure in a static model. And we also analyze the cyclical behavior of firm conduct. We find that the conduct parameter in a static model underestimates true market power if firms' behaviors are posited by a dynamic oligopoly game. We also verify that firm conduct in the Dallas-Forth Worth fluid milk market is countercyclical against demand shocks and expected future cost shocks. Our results indicate that the firms' conduct in the Dallas-Forth Worth fluid milk market is consistent with what dynamic oligopoly models predict. This implies that the firms consider not only the contemporary reactions of the other firms' but also future market competition. Therefore, the measurement of market power requires the specification of fully dynamic pricing relationship.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2008.11a
• /
• pp.371-375
• /
• 2008

Nowadays, Korean Housing Market have been unstable because of the global economic fluctuation such as steady decline in the interest rate and the house price bubble. While Korean Government policy responses these state, rapidly changing policies led to deep confusion in the Korean Housing Market. In this situation, Analysis for housing market forecasting has been partial and fragmentary, therefore comprehensive solution and systematical approach is required to analyze the housing market including causal nexus between market determining factors. In an integrated point of view, applying the system dynamics modeling, the paper aims at proposing basic Korean housing market dynamics models based on Fundamental principles of housing market determined by supply and demand.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.557_558
• /
• 2009

본 논문은 제 4차 전력수급계획의 발전설비 건설 계획을 기준으로 2022년까지 SMP를 P-Pool 전산모형을 이용하여 전망하였다. 미래 SMP 전망에 가장 영향을 크게 미치는 변수인 전력수요, 연료가격, 공급설비용량을 각각 3개의 시나리오로 가정하고 시나리오별 SMP를 예측및 각 변수별 민감도를 분석하였다.

• Journal of Korean Society of Rural Planning
• /
• v.21 no.2
• /
• pp.91-102
• /
• 2015

한국은 2050년까지 주요 선진국 중에서 고령화가 가장 심각한 사회로 전환되게 될 것으로 예상된다. 기대여명의 증가와 저 출산은 고령화를 더욱 악화시키며, 이는 심각한 사회문제로 발전하게 될 것이다. 이와 같은 문제를 해결하기 위해 한국정부는 2008년에 도시지역에는 주택연금제도를 도입하였으며, 2011년에는 세계 최초로 농촌지역을 대상으로 농지연금제도를 도입하였다. 그렇지만 이와 같은 제도는 설계 당시부터 복지상품이라기 보다는 장기적으로 손실과 수익의 균형에 초점을 둔 금융상품으로 개발되어 실질적으로 노인들에게 크게 인기를 얻지 못하였다. 따라서 본 연구는 농지연금제도를 활성화시켜, 농촌노인들에게 보다 더 많은 혜택을 주기 위해 지역 토지시장을 감안하여 지역별 농지가격상승률을 예측하고 연금액을 산출하였다. 또, 지금까지 사용한 년 혹은 분기별 감정가 대신에 월별, 지역별 실거래 가격을 모형에 적용하여 지역토지시장, 고령화 수준 등 지역 여건에 부합하는 연금액을 산출하였다. 할인율자료도 가장 안정적인 3년 만기 국고채 수익률을 활용하여 미래농지가격을 예측하고, 이를 유동화하여 월 생활자금으로 지급되도록 하였다. 특히 농지규모가 가장 많고, 고령화 정도가 심각하여 농지연금의 잠재적 수요가 가장 높을 것으로 예상되는 경상북도와 전라남도를 사례지역으로 선정하고, 이를 전국평균과 비교하여 지역적인 차이도 함께 분석하였다. 이를 위해 농지가격 및 이자율 시계열 자료의 안정성을 검정하고, 장기농지가격을 예측하였다. 이를 활용하여 경북, 전남, 전국의 노인들의 월평균 지급액을 추정하였다. 분석결과 정책의 잠재적 수요가 가장 높은 두 지역이 가장 낮은 금액이 지급되는 것으로 추정되어 이는 또 다른 지역불균형을 초래할 수 있는 것으로 평가되었다.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.1-23
• /
• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Korea Technology Innovation Society
• /
• v.10 no.1
• /
• pp.73-97
• /
• 2007

R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.