Consequences of constraints on airport choice

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

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. Low Re-assignment of demand Mixed strategy e.g. DUS e.g. MGL Travel Disutility Restricted growth of demand Airport capacity expansion e.g. HOQ e.g. HHN High / No Yes Airport capacity expandable? Options to handle capacity exceeding demand • 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. Some facts from the German Air Traveller Survey 2003: • 19 international airports (2 Hubs) • 5 regional airports • 67 % choose nearest airport • No. of airports serving a SPR: • Minimum 3 airports • Maximum 14 airports • On average 8 airports Airport system in Germany –airport choice

6. Good Rail Access Airport system in Germany – access mode choice • 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 %

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

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

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

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

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. 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. First step: Unconstrained airport and access mode choice model based on a discrete choice approach, e.g. nested logit-model Approach: Capacity at airports is filled up in this manner simultaneously across market segments, trip origin and trip destination. Second step: Redistribution of excess demand by a decision-rule based LP- approach Realisation: Minimisation of the sum of personal welfare subject to capacity constraints (LP). Capacity module as „add-on“ Implementing capacity constraints

13. - 450 PAX + 450 PAX A simple hypothetical example 1000 PAX per market segment LP-Redistribution Market shares with capacity constraints Loss of air traveller‘s 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. Contact: Dr. Marc Ch. Gelhausen DLR - German Aerospace Center Air Transport and Airport Research Linder Höhe 51147 Köln/Germany Marc.Gelhausen@dlr.de Thank you for your attention