• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12A
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• pp.2025-2033
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• 1999

In this paper, we forecast launching time of the commercial IMT-2000 service as feb. 2001, according to expert’s opinion, and most of they forecast rapid evolution. And, we propose two different models according to two cases for competition power of price for IMT-2000 service subscriber demand forecasting. In this paper, we combine the expert’s opinion method with the growth curve model for demand forecasting for new products in order to reduce error of the demand forecasting that haven’t past references. The estimation of needed coefficients for each growth curve model is based on experts’ subjective opinions.

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

• Korean Journal of Social Welfare Studies
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• v.43 no.1
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• pp.389-411
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• 2012

A new era of research has focused on examining the growth of change in drinking problems among the elderly. Thus, the purpose of the present study was two fold: (1) to investigate trajectories of drinking problems(CAGE) among the Korean elderly(age$${\geq_-}65$$); and (2) to identify the predicting factors for the intercept and the slope of alcohol problems using multi-level growth curve model. Data come from three waves(1st wave(2006)~3rd wave(2008) of the Korea Welfare Panel(KWP) study. The results indicated that the levels of drinking problems decreased over time and that age, gender, marital status, religion, poverty, self-rated health, and social relationship satisfaction were associated with the baseline CAGE. Further analysis showed that social relationship satisfaction affected the declining slope of drinking problems over time. Specifically, among those who satisfied social relationship, there was a sharp decline of CAGE over time. Overall findings highlight the importance of developing and implementing effective alcohol prevention programs for the elderly in the community settings to mitigate the harmful effects of various psycho-social stressors. Especially, programs to maintain and form healthy social support network are suggested as critical interventions for prevention as well as recovery of alcohol problems in late life.

• The korean journal of orthodontics
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• v.37 no.1 s.120
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• pp.16-28
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• 2007

Objective: Evaluation of individual growth is important in orthodontics. The aim of this study was to develop a convenient software that can evaluate current growth status and predict further growth. Methods: Stature data of 2 to 20 year-old Koreans (4893 boys and 4987 girls) were extracted from a nationwide data. Age-sex-specific continuous functions describing percentile growth curves were constructed using natural cubic spline function (NCSF). Then, final stature prediction algorithm was developed and its validity was tested using longitudinal series of stature measurements on randomly selected 200 samples. Various accuracy measurements and analyses of errors between observed and predicted stature using NCSF growth curves were performed. Results: NCSF growth curves were shown to be excellent models in describing reference percentile stature growth curie over age. The prediction accuracy compared favorably with previous prediction models, even more accurate. The current prediction models gave more accurate results in girls than boys. Although the prediction accuracy was high, the error pattern of the validation data showed that in most cases, there were a lot of residuals with the same sign, suggestive of autocorrelation among them. Conclusion: More sophisticated growth prediction algorithm is warranted to enhance a more appropriate goodness of model fit for individual growth.

• Convergence Security Journal
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• v.12 no.3
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• pp.115-121
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• 2012

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, we predict the future failure time by using the curve regression analysis where the s-curve, growth, and Logistic model is used. The proposed prediction method analysis used failure time for the prediction of this model. Model selection using the coefficient of determination and the mean square error were presented for effective comparison.

• Environmental and Resource Economics Review
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• v.15 no.3
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• pp.405-423
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• 2006

This paper develops theoretical model between economic growth and pollution as follows: First, emissions are generated from final good production process and technology accumulation. Second, pollution is directly connected with increase in final good production or in consumption, Third, no pollution abatement activity would be undertaken. Fourth, reproducible factors associated with labor and capital input are used in production function. We also test the existence of nonlinear Dynamics between economic growth and pollution using an exponential smooth transition autoregressive model(ESTAR). We find the presence of nonlinear dynamics between economic growth and pollution with a time series data for Seoul. This result shows indirectly that an inverted U relationship between air pollution and economic growth exists.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.335-335
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• 2012

기후변화에 의한 미래 수문량 전망에 대한 연구는 전지구 모델 결과를 바탕으로 이루어진다. 현재 전지구 모델의 모의 결과 생산된 강우 자료는 기상청에서 제공되며, 제공된 자료는 기상청 관측 지점에 국한되어 있다. 어떤 유역의 확률홍수량 전망은 유역내 강우 지점의 확률강우량을 강우-유출 모형인 HEC-1에 입력하여 추정할 수 있다. 한강 유역과 같은 대유역의 확률홍수량을 구하기 위해서는 유역내 기상청 관측 지점만으로는 지점수가 부족하기 때문에 국토해양부나 수자원공사 관할의 지점 자료를 활용한다. 하지만 이러한 대유역의 미래 확률홍수량을 전망하고자 하는 경우에 제공되는 전지구 모델 결과가 기상청 지점에 국한되어 있어 다른 지점의 확률강우량을 산정하는 데 어려움이 있다. 본 연구에서는 이러한 문제를 보완하기 위해 지역빈도해석을 이용하여 미래 전망 자료가 없는 지점들의 확률강우량을 추정하였다. 지역빈도해석을 수행하기 위해서는 관측 자료가 있는 유역내 지점들의 특성치(site characteristics)를 바탕으로 지역을 구분하고, Hosking and Wallis(1997)가 제안한 이질성 척도(heterogeneity measure)를 근거로 구분된 지역의 수문학적 동질성 여부를 검토하며, 각 지역에 대한 성장곡선(growth curve)를 추정한다. 지역별로 추정된 성장곡선에 지점의 연최대값 평균을 곱하면 그 지점의 확률강우량을 추정할 수 있다. 따라서 미래 기간의 지역별 성장곡선과 지점의 연최대값 평균을 전망할 수 있으면, 미래 기간의 지점별 확률강우량을 산정할 수 있고, 이를 바탕으로 확률홍수량도 전망할 수 있다. 이를 위해 본 연구에서는 전지구 모델에서 모의된 강우 자료를 바탕으로 미래 기간의 성장곡선을 추정하고, 과거 대비 미래 기간의 지속기간별 연최대값 평균의 비율을 산정하여 모의 자료가 없는 지점에 적용함으로써 미래 기간의 연최대값 평균을 산정하였으며, 이를 바탕으로 미래 기간의 확률강우량을 산정하도록 하였다. 이 기법의 신뢰도를 검증하기 위해 관측 자료를 두 기간으로 구분하여, 이 기법을 적용하여 추정한 확률강우량과 관측 자료로부터 산정한 확률강우량을 비교하였다.

• Journal of Environmental Policy
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• v.10 no.4
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• pp.3-37
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• 2011

This paper investigates the existence of the environmental Kuznets curve (EKC) for carbon dioxide $CO_2$ emissions and its causal relationships with economic growth and openness by using time series data (1971-2006) from China (an emerging market), Korea (a newly industrialized country), and Japan (a developed country). The sample countries span a whole range of development stages from industrialized to newly industrialized and emerging market economies. The environmental consequences according to openness and economic growth do not show uniform results across the countries. Depending on the national characteristics, the estimated EKC show different temporal patterns. China shows an N-shaped curve while Japan has a U-shaped curve. Such dissimilarities are also found in the relationship between $CO_2$ emissions and openness. In the case of Korea, and Japan it represents an inverted U-shaped curve while China shows a U-shaped curve. We also analyze the dynamic relationships between the variables by adopting a vector auto regression or vector error correction model. These models through the impulse response functions allow for analysis of the causal variable's influence on the dynamic response of emission variables, and it adopts a variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the causal variables over time. Results show evidence of large heterogeneity among the countries and variables impacts.

• Journal of Technology Innovation
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• v.28 no.1
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• pp.1-30
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• 2020

The government has implemented policies to increase university technology commercialization while supporting university research over time. This paper adopts the neo-institutional theory and examines the effect of change in the government research funds that universities have received overtime on the change in their technology commercialization performance. It also investigates a location (Seoul metro or others) effect on the relationships. Using latent growth curve modeling (LGM), which is widely used for time-varying analysis, this study longitudinally analyzes 138 universities in South Korea over the past nine years from 2009 to 2017. The results indicate that the growth in the annual government research funds that universities attain affects the growth in the economic value of technology transfers. In addition, the relationship is stronger for universities in Seoul metropolitan areas than those in other areas. The relationships are intact with one-year lagging effects. The findings help understand the effectiveness of government R&D policies for promoting technology commercialization.

• Environmental and Resource Economics Review
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• v.12 no.3
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• pp.515-529
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• 2003

This theoretical model makes three contributions to the study on economic growth and environment. First, emissions are generated during final goods production and technology accumulation. Second, this paper assumes that pollution is directly increasing with increase in final goods output or in consumption. Third, we use reproducible factors associated with labor and capital input in production function and assume constant return to scale in reproducible factors. From growth rate condition we derived, increases in reproducible factors, increases in productivity of either the abatment or technology sector, and decrease in social discount rate would increase the sustainable growth rate. In empirical test, the environmental degradation did not effect the economic growth rate though other factors satisfied the growth rate condition equation. However, through the reinterpretation of this result, we found indirectly the fact of that an inverted U relationship between air pollution and economic growth rate would exist in 20 OECD countries using a panel data for the period of 1986~1995.