1. Consequences of constraints on airport choice Dr. Marc Ch. Gelhausen Brussels, 18.09.2007

2. Relevant constraints Runways Aprons Terminals Curfews & night bans Political constraints Environmental capacities: Noise & emissions Surface access Terminal area Air service agreements (ASA) Yearly / hourly capacity Options for research: Quantification of each constraint Quantification of impacts of constraints on: Demand Airport choice …

3. Options to handle capacity exceeding demand Travel Disutility Airport capacity expandable? Low YesHigh / No Airport capacity expansion Re-assignment of demand Mixed strategy Restricted growth of demand e.g. DUS e.g. HHN e.g. MGL e.g. HOQ Three options/strategies: Re-assignment to other airports Capacity expansion Lost demand Importance of high speed trains!

4. Airport choice and future avenues Aim: Show the dependence between airport and access mode characteristics and airport choice Model currently employed by Deutsche Bahn AG (2006) Innovation: Inclusion of capacity constraints at airports to show dependence between airport choice, airport & access mode characteristics and capacity constraints at airports Additional output: Number of air Passengers to reassign to neighbour airports because of capacity constraints

5. Airport system in Germany – airport choice 19 international airports (2 Hubs) 5 regional airports No. of airports serving a SPR: Minimum 3 airports Maximum 14 airports On average 8 airports 67 % choose nearest airport Some facts from the German Air Traveller Survey 2003:

6. Average distribution: Private car driver 18 % Car passenger 34 % Rental car driver 4 % Taxi passenger 19 % Bus passenger 9 % Urban railway passenger 11 % Train passenger 5 % Airport system in Germany – access mode choice Urban AreaShare of IC Trains (%) Distance to Frankfurt (kms) Hamburg83495 Bremen57445 Hannover68350 Berlin36545 Dortmund57225 Düsseldorf70220 Köln68180 Leipzig82385 Stuttgart50205 Nürnberg44225 München66390 Good Rail Access

7. Key aspects Nested logit-model Airport and access mode choice model Abstraction from specific alternatives Generally applicable model Linear programming (LP) Consideration of capacity constraints

8. Forecasting philosophy Traveller: Which alternative is the best for me? Evaluation of alternatives by means of utility Forecaster: Which alternative is most likely the best for him? Lack of observability, measurement errors, … Choice probabilities Summing up over homogenous populations Market segment specific market shares of all alternatives Access cost, access time, flight plan,...

9. Analysing airport and access mode choice Airport and access mode choice Airport and access mode characteristics Point of view: air traveller Discrete choice models Utility functionDistribution of error term U = V(x) + i.e. U(FRA/Car) = a*(Access time) + b*(Access cost) +... +

10. Cluster groups and airport categories Limited number of different generic airport/access mode combinations 3 airport categories 7 access mode categories Cluster analysis according to flight services Group-specific correlation structure among alternatives Airport categories as different product types Values in % Absolute values Hub, medium and low-cost airports

11. Why consider capacity constraints in airport choice? Air fares do not reflect the capacity situation at airports fully, at least over a short time horizon In a equilibrium of air fares and airport capacities, the first choice of an air traveller regarding the departure airport is not necessarily met Air fares are often not included in airport choice models due to data problems Most airport choice models assume unconstrained airport capacities

12. Implementing capacity constraints Idea: The higher the loss in personal welfare (utility) from alternative to alternative, the higher the efforts to get a slot for the best alternative, i.e. by early booking or paying higher prices. Approach: Capacity at airports is filled up in this manner simultaneously across market segments, trip origin and trip destination. Realisation: Minimisation of the sum of personal welfare subject to capacity constraints (LP). First step: Unconstrained airport and access mode choice model based on a discrete choice approach, e.g. nested logit-model Second step: Redistribution of excess demand by a decision-rule based LP- approach Capacity module as add-on

13. + 450 PAX - 450 PAX A simple hypothetical example 1000 PAX per market segment LP-Redistribution Market shares with capacity constraints Loss of air travellers welfare about 5%

14. Conclusions Airport choice is significantly different in the presence of capacity constraints Decision-rule based LP-approach enables to model capacity constraints apart from the price mechanism Quantification of airport capacity as well as access mode capacity constraints Model shows also: Loss of welfare due to capacity constraints is considerable from the point of view of the air traveller = assessment of regional airport supply instrument to optimise supply side

15. Thank you for your attention Contact: Dr. Marc Ch. Gelhausen DLR - German Aerospace Center Air Transport and Airport Research Linder Höhe 51147 Köln/Germany Marc.Gelhausen@dlr.de