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  Low cost carriers  EU expansion  Necessity of explicit analysis of airport choice determinants

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

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)

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

Case Study: E – 75 HCAS

Stage 1 Specification  100 % flight frequency (FF) ~ 15 % of fare  1 h difference in travel time (ATD) ~ % of fare  Linear AF to ATD relationship  The compensating frequency ratio FR k = a*e b*ATD

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

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)

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

1. FR k = *e *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 ]

Stage 2 Application Example Airport Choice of Business Travelers, Munich Trip

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)

Base Case Belgrade Airport Market Shares

Belgrade Market Growth, SC1

Belgrade Market Growth, SC2

SC3 Nis Airport Market Share

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

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