Türkiye`de hava ulaştırması yolcu talebi

Abstract

Both the linear model (7.1) and the logarithmic model (7.2) were calibrated for the study period of 15 years. Statistical validity of both models was found to be satisfactorily high. However all of the indicators positively support the higher statistical validity of the logarithmic model. This analysis indicate a structural relationship and provide an analytical point of view to planners and engineers. -xiii-

The most common stratification in microanalysis is by origin and destination. The resulting models are called city pair models. In this study micromodels are discussed briefly. Chapter 6 In this chapter present demand forecasting system in THY is evaluated and forecasting approaches by objectives are presented. Data used for forecasting in THY mainly comes from the `Data Processing Center` of the company. After its appearance, the results of point to point analysis of THY is circulated among several units of company. Then, an expert opinion forecasting system is applied. The company's actual performance in the market becomes meaningful when it is compared to forecast. Each type of forecast (short, medium or long-term) serves a particular purpose. Some important factors affecting air transport demand are economic growth, fares, international trade, vacation habits and alternatives to air travel. Especially, integration and liberalization in world civil aviation affect the European carriers. The most important factor that stems from this change is globalization. Thus, factors affecting (or are affected from) 'demand are inclined to be approximately common. 'Chapter 7 In this chapter a time series analysis of air transportation passenger demand is used. The following two models were estimated and tested: PASSENGER-KM = a, + E>4 REAL PERCAPITA GNP + H) REAL AVERAGE PASSENGER FARE + 9, DUMMY VARIABLE + Uf (7.1) Ln PASSENGER-KM = <xz + B*. REAL PERCAPITA GNP +Q, REAL AVERAGE PASSENGER FARE + 9 DUMMY VARIABLE + UA (7.2) Where U« : error term <*?,, &r, ^j / 9.: coefficients to be estimated, i=l,2 -xi i-Both the linear model (7.1) and the logarithmic model (7.2) were calibrated for the study period of 15 years. Statistical validity of both models was found to be satisfactorily high. However all of the indicators positively support the higher statistical validity of the logarithmic model. This analysis indicate a structural relationship and provide an analytical point of view to planners and engineers. -xiii-The most common stratification in microanalysis is by origin and destination. The resulting models are called city pair models. In this study micromodels are discussed briefly. Chapter 6 In this chapter present demand forecasting system in THY is evaluated and forecasting approaches by objectives are presented. Data used for forecasting in THY mainly comes from the `Data Processing Center` of the company. After its appearance, the results of point to point analysis of THY is circulated among several units of company. Then, an expert opinion forecasting system is applied. The company's actual performance in the market becomes meaningful when it is compared to forecast. Each type of forecast (short, medium or long-term) serves a particular purpose. Some important factors affecting air transport demand are economic growth, fares, international trade, vacation habits and alternatives to air travel. Especially, integration and liberalization in world civil aviation affect the European carriers. The most important factor that stems from this change is globalization. Thus, factors affecting (or are affected from) 'demand are inclined to be approximately common. 'Chapter 7 In this chapter a time series analysis of air transportation passenger demand is used. The following two models were estimated and tested: PASSENGER-KM = a, + E>4 REAL PERCAPITA GNP + H) REAL AVERAGE PASSENGER FARE + 9, DUMMY VARIABLE + Uf (7.1) Ln PASSENGER-KM = <xz + B*. REAL PERCAPITA GNP +Q, REAL AVERAGE PASSENGER FARE + 9 DUMMY VARIABLE + UA (7.2) Where U« : error term <*?,, &r, ^j / 9.: coefficients to be estimated, i=l,2 -xi i-Both the linear model (7.1) and the logarithmic model (7.2) were calibrated for the study period of 15 years. Statistical validity of both models was found to be satisfactorily high. However all of the indicators positively support the higher statistical validity of the logarithmic model. This analysis indicate a structural relationship and provide an analytical point of view to planners and engineers. -xiii-The most common stratification in microanalysis is by origin and destination. The resulting models are called city pair models. In this study micromodels are discussed briefly. Chapter 6 In this chapter present demand forecasting system in THY is evaluated and forecasting approaches by objectives are presented. Data used for forecasting in THY mainly comes from the `Data Processing Center` of the company. After its appearance, the results of point to point analysis of THY is circulated among several units of company. Then, an expert opinion forecasting system is applied. The company's actual performance in the market becomes meaningful when it is compared to forecast. Each type of forecast (short, medium or long-term) serves a particular purpose. Some important factors affecting air transport demand are economic growth, fares, international trade, vacation habits and alternatives to air travel. Especially, integration and liberalization in world civil aviation affect the European carriers. The most important factor that stems from this change is globalization. Thus, factors affecting (or are affected from) 'demand are inclined to be approximately common. 'Chapter 7 In this chapter a time series analysis of air transportation passenger demand is used. The following two models were estimated and tested: PASSENGER-KM = a, + E>4 REAL PERCAPITA GNP + H) REAL AVERAGE PASSENGER FARE + 9, DUMMY VARIABLE + Uf (7.1) Ln PASSENGER-KM = <xz + B*. REAL PERCAPITA GNP +Q, REAL AVERAGE PASSENGER FARE + 9 DUMMY VARIABLE + UA (7.2) Where U« : error term <*?,, &r, ^j / 9.: coefficients to be estimated, i=l,2 -xi i-Both the linear model (7.1) and the logarithmic model (7.2) were calibrated for the study period of 15 years. Statistical validity of both models was found to be satisfactorily high. However all of the indicators positively support the higher statistical validity of the logarithmic model. This analysis indicate a structural relationship and provide an analytical point of view to planners and engineers. -xiii-