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PASSENGERS’ CHOICE BETWEEN COMPETING AIRPORTS

PASSENGERS’ CHOICE BETWEEN COMPETING AIRPORTS. Radosav Jovanovic Faculty of Transport and Traffic Engineering, University of Belgrade. Introduction. Liberalization of airline regulation – changes to management and planning of airports Increased competition

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PASSENGERS’ CHOICE BETWEEN COMPETING AIRPORTS

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  1. PASSENGERS’ CHOICE BETWEEN COMPETING AIRPORTS Radosav Jovanovic Faculty of Transport and Traffic Engineering, University of Belgrade

  2. Introduction • Liberalization of airline regulation – changes to management and planning of airports • Increased competition • Low cost carriers • EU expansion • Necessity of explicit analysis of airport choice determinants

  3. On the paper • A model to predict the distribution of business passengers in a MAS • Case study: E-75 HCAS • Data used: 2001, 2002, 2003 FTTE air passengers surveys at Belgrade a/p, 2001 FTTE survey of Serbia originating passengers departing from Budapest a/p

  4. Background • US MASs, London airport system • Different functional forms and explanatory variables • Usually: MNL, nested logit model • Relevant variables: air fare, flight frequency, airport accessibility (ground access characteristics)

  5. Proposed Airport Demand Allocation Model • Exponential formula to calculate the effects of choice attributes (FF, ATD, AF) on airport attractiveness • Stage 1 – Indifference equation to relate FRk to ATD variable • Stage 2 – To establish a pattern of airport attractiveness alteration in the region observed

  6. Case Study: E – 75 HCAS

  7. Stage 1 Specification • 100 % flight frequency (FF) ~ 15 % of fare • 1 h difference in travel time (ATD) ~ 20-40 % of fare • Linear AF to ATD relationship • Thecompensatingfrequencyratio FRk = a*eb*ATD

  8. Equal-attractiveness point (EAP):ATD = p*lnFR – q [hours]

  9. Stage 1 Application Example • Trip to Munich • Belgrade versus Budapest airport • 2 vs 7 daily-direct flights (FR=7/2) • 80 kmph average highway speed • 30 minutes border stopping => ATD = 94 min, EAP in Backa Topola (157 km north of Belgrade)

  10. Stage 2 Specification • Input variables: • Daily-direct FFs • ATD • “S”-curve α parameter-how airport’s frequency share affects its market share • Five-sequences procedure to calculate the market share attracted

  11. 1. FRk = 1.1025*e0.7392*ATD 2. FFD(k) = FRk * FFC 3. LRFD = FFD / FFD(k) 4. RFD = LRFD / (LRFD + LRFC) 5. PSD = (RFD)α / [(RFD)α + (1 - RFD)α]

  12. Stage 2 Application ExampleAirport Choice of Business Travelers, Munich Trip

  13. Different Scenarios Considered • Nine destinations (MUN, FRA, LON, PAR, AMS, MIL, ZUR, VIE, MOS) • Base case (BC) – current levels of airline services • SC1 – BEG FF+1 • SC2 – BEG FF+1, BUD FF+1 • SC3 – NIS vs BEG distribution (ZUR trip)

  14. Base Case Belgrade Airport Market Shares

  15. Belgrade Market Growth, SC1

  16. Belgrade Market Growth, SC2

  17. SC3 Nis Airport Market Share

  18. Limitations – Possible Improvements • Absence of authentic preference structure of a Serbian air traveler • Credible calibration of the "S"-curve α parameter (origin and/or destination zone specific) • Getting quantitative perceptive scales from qualitative survey data

  19. Conclusions • Sensitivity analysis (predicting FF and ATD changes effects-redistribution) • “What to offer” at or “where to locate” a new airport • To match the aircraft capacity to demand attracted

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