• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.147-159
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• 2011

In this paper the demand and supply of labor are forecasted over the next 10 years for customized nurturing human resource focused on Manufacturing Industry in Chung-Nam Province. Despite that the industrial structure is rapidly changing, industrial labors are nurturing on the basis of past industrial structure. This research is conducted for reducing mismatched labors throughout forecasting human resources until 2020. As a practical approach, the BLS Methodology is partially utilized. And the previous researches and official statistics data are reviewed. In conclusion, this study presents that more human resources on Manufacturing Industry than other Industries will be needed in Chung-Nam province. In details, it shows that there will be required more Industrial labors for strategic industries for examples, Audio and Video related industry, and Car related industry which is propelling by overall local government. In additions, policy implications are developed by analyzing current status and forecasting the labor demand and supply in the Chung-Nam Manufacturing sector.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.2
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• pp.187-196
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• 2006

Forecasting the long-term water demand is important in the plan of water supply system because the location and capacity of water facilities are decided according to it. To forecast the long-term water demand, the existing method based on lpcd and population has been usually used. But, these days the trend among the variation of water demand has been disappeared, so expressing other variation of it is needed to forecast correct water demand. To accomplish it, we introduced the System Dynamics method to consider total connections of water demand factor. Firstly, the factors connected with water demand were divided into three sectors(water demand, industry, and population sectors), and the connections of factors were set with multiple regression model. And it was compared to existing method. The results are as followings. The correlation efficients are 0.330 in existing model and 0.960 in SD model and MAE are 3.96% in existing model and 1.68% in SD model. So, it is proved that SD model is superior to the existing model. To forecast the long-term water demand, scenarios were made with variations of employment condition, economic condition and consumer price indexes and forecasted water demands in 2012. After all scenarios were performed, the results showed that it was not needed to increase the water supply ability in Seoul.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.110-117
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• 2015

Spare part management is very important to products that have large number of parts and long lifecycle such as automobile and aircraft. Supply chain must support immediate procurement for repair. However, it is not easy to handle spare parts efficiently due to huge stock keeping units. Qualified forecasting is the basis for the supply chain to achieve the goal. In this paper, we propose an agent based modeling approach that can deal with various factors simultaneously without mathematical modeling. Simulation results show that the proposed method is reasonable to describe demand generation process, and consequently, to forecast demand of spare parts in long-term perspective.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.6 no.1
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• pp.29-39
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• 1992

In this paper, the basic idea of optimum electric system design by means of the forecasting of maximum demand is presented, and the load characteristics and practical operating conditions are based on the technical data. After reconstruction of th model plant by use of above method, power supply reliability, future extention, initial cost, and running cost saving effects are analyzed. As a result, it is verified that the systems wherein the power is supply to each load frm main transformer whose capacity is calculated by forecasting are economic rather than the systems wherein the power is supply to each electric feeders from each corresponding transformer.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.292-294
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• 1998

It is very important for electric utility to expand generating facilities and transmission equipments in accordance with the increase of electricity demand. Regional electricity demand forecasting is among the most important step for long-term investment and power supply planning. The main objectives of this paper are to develop the methodologies for forecasting regional load demand. The Model consists of four models, regional economy, regional electricity energy demand, areal electricity energy demand. and areal peak load demand. This paper mainly suggests regional electricity energy demand model and areal peak load demand. A case study is also presented.

• Journal of The Korean Society of Integrative Medicine
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• v.6 no.4
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• pp.149-169
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• 2018

Purpose : This study was to develop a strategy for modeling future workforce projections to serve as a basis for analyzing annual supply of and demand for physical therapists across the South Korea into 2030. Methods : In-and-out movement model was used to project the supply of physical therapists. The demand was projected according to the demand-based method which consists of four-stages such as estimation of the utilization rate of the base year, forecasting of health care utilization of the target years, forecasting of the requirements of clinical physical therapists and non-clinical physical therapists based on the projected physical therapists. Results : Based on the current productivity standards, there will be oversupply of 39,007 to 40,875 physical therapists under the demand scenario of average rate in 2030, undersupply of 44,663 to 49,885 under the demand scenario of logistic model, oversupply of 16,378 to 19,100 under the demand scenario of logarithm, and oversupply of 18,185 to 20,839 under the demand scenario of auto-regressive moving average (ARIMA) model in 2030. Conclusion : The result of this projection suggests that the direction and degree of supply of and demand for physical therapists varied depending on physical therapists productivity and utilization growth scenarios. However, the need for introduction of a professional physical therapist system and the need to provide long-term care rehabilitation services are actively being discussed in entering the aging society. If community rehabilitation programs for rehabilitation of disabled people and the elderly are activated, the demand of physical therapists will increase, especially for elderly people. Therefore, healthcare policy should focus on establishing rehabilitation service infrastructure suitable for an aging society, providing high-quality physical therapy services, and effective utilization of physical therapists.

• Korean System Dynamics Review
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• v.7 no.1
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• pp.67-90
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• 2006

A series of system dynamics model was developed for forecasting demand and supply of human resource in the electricity industry. To forecast demand of human resource in the electric power industry, BLS (Bureau of Labor Statistics) methodology was used. To forecast supply of human resource in the electric power industry, forecasting on the population of our country and the number of students in the department of electrical engineering were performed. After performing computer simulation with developed system dynamics model, it is discovered that the shortage of human resource in the electric power industry will be 3,000 persons per year from 2006 to 2015, and more than a double of current budget is required to overcome this shortage of human resource.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.399-410
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• 2015

The primary goal of the study is to examine the possibility of applying the time series model to forecasting demand and supply of social services. In the study, we used survey data based on a nationally represented sample which is secondary processed data. We selected developmental rehabilitation service. The analysis, we made models of a demand and a supply using time series analysis. Utilizing the estimates, we identified each model's pattern. This study provides an empirical evidence to suggest benefits of using the time series model for forecasting the demand and the supply pattern of newly introduced social services. We also provide discussions on policy implications of utilizing demand and supply time series models in the process of developing new social services.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4812-4818
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• 2013

This paper contains material of the supply-demand forecasting of solar salt for food in Korea. The solar salt was granted admission for food by the act of salt management in 2007. So, the yearly statistics of solar salt for food are not enough to forecast the supply-demand unsing econometrics. However, the related industry become interested in market size of the solar salt for food and the growth potential of the market. This study deal with the supply-demand forecasting of solar salt for food in light of industry of solar salt, consumption trends, export-import quantity, etc. This research results indicate that the production quantity will be 222-384 thousand MT, the export quantity will be 498-565 thousand MT, the export quantity will be 2.67-3.62 thousand MT, the consumption quantity will be 767-996 thousand MT.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.103-111
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• 2013

As the demand-oriented management has been getting important in Supply Chain Management (SCM), various forecasting methods have been suggested including regression analyses. However, dependency structures among variables have been captured by a correlation coefficient, only. It results in inaccurate demand predictions. This paper suggests a new and effective forecasting modeling framework using student's t-copula function. In order to show overall modeling procedures framework, heavy tail typed numerical data and its copula estimations are provided. The suggested methodology can contribute to decrease the bullwhip effect and to stabilize volatile environment in a supply chain network.