• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.1
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• pp.66-75
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• 2012

The purpose of this study is to analyze the effect of intervention variables which may affect the air travel demand for Jeju domestic flights and to anticipate the air travel demand for Jeju domestic flights. The air travel demand forecasts for Jeju domestic flights are conducted through ARIMA-Intervention Model selecting five intervention variables such as 2002 World Cup games, SARS, novel swine-origin influenza A, Yeonpyeongdo bombardment and Japan big earthquake. The result revealed that the risk factor such as the threat of war that is a negative intervention incident and occurred in Korea has the negative impact on the air travel demand due to the response of risk aversion by users. However, when local natural disasters (earthquakes, etc) occurring in neighboring courtiers and global outbreak of an epidemic gave the negligible impact to Korea, negative intervention incident would have a positive impact on air travel demand as a response to find alternative due to rational expectation of air travel customers. Also we realize that a mega-event such as the 2002 Korea-Japan World Cup games reduced the air travel demand in a short-term period unlike the perception in which it will increase the air travel demand and travel demands in the corresponding area.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.141-154
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• 2018

In order to meet the ever-increasing demand for international air travel, several plans are underway to open new airports and expand existing provincial airports. However, existing air demand forecasts have been based on the total air demand in Korea or the air demand among major cities. There is not much forecast of regional air demand considering local characteristics. In this study, the outbound air travel demand in the southeastern region of Korea was analyzed and the fixed-effects model using panel data was proposed as an optimal model that can reflect the inherent characteristics of metropolitan areas which are difficult to observe in reality. The results of model validation show that panel data analysis effectively addresses the spurious regression and unobserved heterogeneity that are difficult to handle in a model using only a few macroeconomic indicators with time series characteristics. Various statistical validation and conformance tests suggest that the fixed-effects model proposed in this study is superior to other econometric models in predicting demand for international demand in the southeastern region.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.901-922
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• 2007

To see how the electricity demand for air-conditioning responds to weather condition and what kind of weather condition works better in forecasting maximum daily electricity demand, four different regression models, which are linear, exponential, power and S-curve, are adopted. The regression outcome turns out that the electricity demand for air-conditioning is inclined to rely on the exponential model. Another major discovery of this study is that the electricity demand for air-conditioning responds more sensitively to the weather condition year after year along with the higher non-air-conditioning electricity demand. In addition, it has also been found that the discomfort index explains the electricity demand for air-conditioning better than the highest temperature.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1931-1936
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• 2007

Demand forecasting for railroad traffic is fairly important to establish future policy and plan. The future demand of railroad traffic can be predicted by analyzing the demand of air, marine and bus traffic which influence the demand of railroad traffic. In this study, forecasting the demand of railroad traffic is implemented through neural network using the demand of air, marine and bus traffic. Estimate accuracy of the demand of railroad traffic was shown about 84% through neural net model proposed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.16 no.1
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• pp.46-57
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• 2008

Since the 90's, Korean Air transport market has been more expanded because of economic growth, the construction of airport infrastructure, and the advent of low cost carrier. Especially, the air traffic demand in Busan metropolitan area has been increasing steadily. Therefore, in this paper, we developed a new forecasting model which could expect the future air traffic demand in Busan area. This model is developed by regression analysis using social-economic variables such as GRDP, income, and the number of people, and dummy variables, for instance, KTX opening, Japan economic depression, SARS and so on. Result from demand forecasting by this new model suggests that the new airport system is needed in order to sustain the increasing air traffic demand in Busan area.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.4
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• pp.52-64
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• 2019

The purpose of this study is to analyze the impact of macroeconomic variables on air passenger demand and provide useful information to airport managers and policymakers. Therefore, using the quarterly macroeconomic indicators from 2002 to 2017, the relationship with air passenger demand was demonstrated by multiple regression analysis. In the previous studies, they used GDP, Korea Treasury Bond, KOSPI index, USD/KRW Exchange Rate, and WTI Crude Oil Price variables. In this study, we used the Coincident Composite Index, Employment Rate, Consumer Sentiment Index, and Private Consumption Rate used as additional variables. It has confirmed that if the consumption of research results expands or the economic environment is right, it will affect the increase in international passengers. In other words, it confirmed that the overall economic situation acts as the main factor determining air passenger demand. It confirmed that the economic environment at the past has a significant impact on air passenger demand.

• Journal of the military operations research society of Korea
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• v.35 no.3
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• pp.1-15
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• 2009

Central supply depot of Air Force has been receiving and storing the goods from the inside and outside of the country. And it also has been distributing the goods to the air base by air, rail, road, etc. These goods have been called central goods. Among these central goods, 10% of them are transported by air and the amount of freight is increasing day by day. So, air transportation in the Air Force has been more important than ever. But, studies of demand estimation for activating air transportation are very difficient. This study verified the main factors affecting to air transportation and the function of regression model will be useful data for estimating air freight demand.

• Journal of the Korean Home Economics Association
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• v.34 no.3
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• pp.283-290
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• 1996

The objectives of this study was to research and analyze the actual conditions of using air-conditioning, which will help to understand the households' demand on a air-conditioning. The target of this study was the households in the seoul area. The data was collected by considering housing type, size & heating systems. On the basis of these findings, are the result of the demand for air-conditioning. 1)The possibility of purchasing this air-conditioning was higher among the households with ￦1,000,000 monthly income. Especially, the households with ￦2,000,000 to ￦2,500,000 monthly income were the main class of the demand. 2)The possibility of purchasing it was higher from husband's age over 30. 3)Both apartment and detached house dwellers were high in purchasing it. 4)The bigger the house was, the higher the possibility of purchasing it. Also, the function and the condition of air-cleaning function, which was concerning most on the economic point of view.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.3
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• pp.98-105
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• 2019

In the past 30 years, our aviation demand has been growing continuously. As such, the importance of the demand forecasting field is increasing. In this study, the factors influencing Korea's international air demand were selected, and the international air demand was analyzed, forecasted and reviewed through OLS multiple regression analysis. As a result, passenger demand was affected by GDP per capita, oil price and exchange rate, while cargo demand was affected by GDP per capita and private consumption growth rate. In particular, passenger demand was analyzed to be sensitive to temporary external shocks, and cargo demand was more affected by economic variables than temporary external shocks. Demand forecasting, OLS multiple regression analysis, passenger demand, cargo demand, transient external shocks, economic variables.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.3
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• pp.203-209
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• 2003

Control algorithms of an air handling unit by using the mixing box plenum pressures were developed and verified by experiments. Control algorithms developed for this study were the setpoint algorithms for the outdoor damper position, the outdoor/fixed plenum pressure, and the return/exhaust plenum pressure. The outdoor/fixed plenum pressure setpoint was used to control the bypass damper position, and the return/exhaust plenum pressure setpoint was used to control the return fan speed. Experimental results showed the good control of the required outdoor air demand. Therefore, setpoint algorithms developed for this study may effectively be applied for the control of the VAV air handling unit.