consequences of constraints on airport choice dr. marc ch. gelhausen brussels, 18.09.2007
TRANSCRIPT
Consequences of constraints on airport choice
Dr. Marc Ch. Gelhausen
Brussels, 18.09.2007
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• …
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!
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
Airport system in Germany – airport choice
FDH
MUC
STR
SCN
NUE
HHN FRA
CGN ERFDRS
DUSLEJ
DTM PAD
FMOSXFHAJ
THF
TXL
BRE
HAMLBC
FKB
NRN
• 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:
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 Area Share of IC Trains (%)
Distance to Frankfurt (kms)
Hamburg 83 495
Bremen 57 445
Hannover 68 350
Berlin 36 545
Dortmund 57 225
Düsseldorf 70 220
Köln 68 180
Leipzig 82 385
Stuttgart 50 205
Nürnberg 44 225
München 66 390
Good Rail Access
FDH
MUC
STR
SCNNUE
HHN FRA
CGN ERFDRS
DUSLEJ
DTM PAD
FMOSXFHAJ
THF
TXL
BRE
HAMLBC
FKB
NRN
„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
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, ...
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 function Distribution of error term
U = V(x) + i.e. U(FRA/Car) = a*(Access time) + b*(Access cost) + ... +
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“
LCBRD CCBRD FSBRD LCEUR CCEUR FSEUR LCINT CCINT FSINT NUMBRD NUMEUR NUMINT
AP 1 3.18 0.43 20.39 0.87 5.83 55.81 0.00 1.24 12.25 8.31 60.27 31.42
AP 2 8.97 0.58 28.27 11.65 11.76 37.24 0.02 0.71 0.79 16.23 74.62 9.16
AP 3 1.29 0.86 39.22 32.57 15.57 10.05 0.02 0.42 0.00 19.94 78.90 1.16
LCBRD CCBRD FSBRD LCEUR CCEUR FSEUR LCINT CCINT FSINT NUMBRD NUMEUR NUMINT
AP 1 106 16 756 32 225 2138 0 49 517 19 144 83
AP 2 104 7 348 129 153 487 0 11 11 17 80 12
AP 3 3 1 80 47 25 39 0 0 0 6 22 1
Values in %
Absolute values
Hub, medium and low-cost airports
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
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“
Airport 1 Airport 2EUR S 720 280EUR H 80 920∑ PAX 800 1200
+ 450 PAX- 450 PAX
A simple hypothetical example
Airport 1 Airport 2EUR S 72% / 350 U 28% / 150 UEUR H 53% / 280 U 47% / 220 U
Airport 1 Airport 2EUR S 720 280EUR H 530 470∑ PAX 1250 750Capacity 800 1200
Airport 1 Airport 2EUR S 72% 28%EUR H 8% 92%
1000 PAX per market segment
LP-Redistribution
Market shares with capacity constraints
Loss of air traveller‘s welfare about 5%
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
Thank you for your attention
Contact:
Dr. Marc Ch. Gelhausen DLR - German Aerospace Center Air Transport and Airport Research Linder Höhe 51147 Köln/Germany