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AIR-TRAVEL DEMAND FORECASTING

AIR-TRAVEL DEMAND FORECASTING. In Brief. Observe past and current trends in air travel demand Inventory the variations in economic, social, demographic and technological factors affecting air travel demand

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AIR-TRAVEL DEMAND FORECASTING

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  1. AIR-TRAVEL DEMAND FORECASTING

  2. In Brief • Observe past and current trends in air travel demand • Inventory the variations in economic, social, demographic and technological factors affecting air travel demand • Establish relationship between travel demand and those factors found to be significant in altering travel demand • Project the values of those factors affecting travel demand into the future • Use the model and the forecasts to obtain the future air travel demand

  3. PRINCIPAL ITEMS FOR WHICH DEMAND FORECASTS ARE MADE • Volumes and peaking characteristics of passengers, aircraft, vehicle, freight and mail • Number and types of aircraft needed to serve the above traffic • Performance and operating characteristics of ground access systems

  4. DATA TO BE COLLECTED FOR AIR TRAVEL DEMAND FORECASTING • Airport service area • Air travel market area (i.e., Origins and Destinations of trips by both residents and nonresidents) • Demographic and population data of the area to be served by the airport • Economic character of the area GDP, Per capita income, Employment, Retail, commercial, and wholesale trade sales, and bank deposits, Hotel registrations, Price of travel • Trends in the existing air travel demand (passenger and cargo) • Trends in national air traffic and the influencing variables • Distance, population, and industrial character of nearby areas having air service

  5. FORECASTING METHODOLOGIES • Forecasting by Judgment - Delphi Method • Trend Models -  Linear -  Exponential -  Logistic • Market Share Models • Econometric Models

  6. Simple Trend Models • Linear Pn=Po+an • Exponential Pn=Po(1+)n • Modified Pn= P -n(P- Po) Exponential • Double • Exponential • Logistic

  7. Typical Trend Models

  8. Comparative Models Also known as -Ratio methods -Mrket share models Typical Comparative Models PTA= kAPTN PTA= kA (PTN – b) PTA= kPBT-t

  9. Trend of Proportion of traffic

  10. A Top-Down Approach • Aggregate Forecast for the Nation by Econometric/Trend Model • Allocation to specific region based on historical share/economic growth • Airport choice model for allocation to airports with in the metropolis • Estimation of Induced traffic because of hub facility by market surveys/stated preference surveys • Refine forecasts based on experts’ opinion

  11. Econometric Trend Models • Relate Economic and Social Factors to Aviation Activity • Trip generation Models -Multiple Linear Regression Technique • Distribution Models - Gravity Model

  12. Explanatory Variables used inEconometric Models • Size and Traffic Potential - Population - GDP -  Industrial production - Per capita income -  Personal expenditure -  Leisure time -  Interregional Linkages: Economic and Social

  13. Transportation - Accessibility Distance to airport, Travel time to airport - Competition relative cost, relative travel time, schedule and reliability of alternate modes -  Cost of air travel average fare, total travel cost and value of travel time -   Schedule convenience service frequency, time of departure, necessary connections -    Service reliability on time performance, Cancellation history -    Transport time airport-to-airport time, door-to-door time

  14. Typical Econometric Models Domestic air travel at Frankfurt Airport Yt = -1.5298 + 0.61GDPt (1.877) (6.637) R2 = 0.82 International air travel at Frankfurt Airport Yt = -15.754 + 2.607GDPt (-6.316) (9.765) R2 = 0.87

  15. Statistical Testing Coefficient of determination Standard Error of estimate t-statistic t-value = Parameter estimate/Standard error

  16. Passenger Traffic in Important Airports

  17. Example Problem Develop a top-down forecast for the 1997 enplaned passengers at the city airport by fitting a suitable trend model for the region.   Develop an econometric model of enplaned passenger growth at the city airport. Also prepare a bottom-up forecast of the enplaned passengers at the city airport in 1997 if it is expected that the percapita disposable income will be $15,000 and the population will be 310,000.

  18. Gravity Type Cross-sectional Model General form A Typical Model

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