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PASSENGERS’ CHOICE BETWEEN COMPETING AIRPORTS Radosav Jovanovic Faculty of Transport and Traffic Engineering, University of Belgrade
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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
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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
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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)
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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 FR k to ATD variable Stage 2 – To establish a pattern of airport attractiveness alteration in the region observed
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Case Study: E – 75 HCAS
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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 The compensating frequency ratio FR k = a*e b*ATD
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Equal-attractiveness point (EAP): ATD = p*lnFR – q [hours]
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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)
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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
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1. FR k = 1.1025*e 0.7392*ATD 2. FF D (k) = FR k * FF C 3. LRF D = FF D / FF D (k) 4. RF D = LRF D / (LRF D + LRF C ) 5. PS D = (RF D ) α / [(RF D ) α + (1 - RF D ) α ]
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Stage 2 Application Example Airport Choice of Business Travelers, Munich Trip
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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)
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Base Case Belgrade Airport Market Shares
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Belgrade Market Growth, SC1
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Belgrade Market Growth, SC2
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SC3 Nis Airport Market Share
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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
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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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