Impact of capacity constraints on

airport choice of air travellers

Dr. Marc Ch. Gelhausen

Paris, 13.12.2007

Agenda

Introduction

Airport and access mode choice model

A hypothetical example

Conclusions

Introduction

Why consider capacity constraints in airport choice?

Limited airport infrastructure:

Runways

Terminals

Night curfews

…

Reduction of available capacity of an airport to handle passenger demand

Why model capacity constraints in airport choice specific?

• Air fares do not reflect the capacity situation at airports fully, at least over a short time horizon

• In an 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

Possible consequences of capacity constraints at airports

Travel Disutility

Airport capacity fixed?

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 consequences:

• Re-assignment to other airports

• Capacity expansion

• Lost demand

Importance of high speed trains!

e.g. CGN – FRA

Airport choice and future avenues

• State of the art: Show the dependence between airport and access mode characteristics and airport choice

Model currently employed by Deutsche Bahn AG (Gelhausen 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:

SPR: Spatial Planning Region

Airport and access mode choice model

„Key aspects“

Nested logit-model

Airport and access mode choice model

Abstraction from specific alternatives

Generally applicable model

Synthetic price concept

Consideration of capacity constraints

Forecasting philosophy of a nested logit-model

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, ...

Modelling capacity constraints in airport choice

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, e.g. 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: Increase so-called “synthetic price” to decrease airport attractiveness and thus redistribute excess demand until capacity constraints are met.

A simple hypothetical example

Airport choice in the Cologne region

Berlin

Access (car, train etc.)Flight

Barcelona

Dallas

Berlin Trip destination

Cologne

Cologne Trip origin

Market segments:

• Private / Business

• Domestic, Europe, Intercont

Airport choice and access quality

70 80 90 100 110 120 130

0.28

0.29

0.3

0.31

0.32

0.33

0.34

0.35

0.360.36

Access Time One-Way

Ma

rke

t S

ha

re o

f F

RA

Ticket Price = 35,30 € (ICE)

Travel Time ICE

Travel Time Transrapid

26 28 30 32 34 36 38 40 42

0.32

0.33

0.34

0.35

0.36

0.37

0.38

0.39

Ticket Price One-Way

Ma

rke

t S

ha

re o

f F

RA

Ticket Price ICE

Market Share of FRA with ICE

Travel Time = 70 minutes (Transrapid)

Airport Market share PaxFrankfurt/Main 42.86% 300Düsseldorf 14.29% 100Cologne 14.29% 100Dortmund 13.51% 95Niederrhein/Weeze 5.71% 40Frankfurt Hahn 3.70% 26Münster/Osnabrück 2.40% 17Sum 96.76% 678

Airport choice – unconstrained and constrained

Airport choice constrainedAirport choice unconstrained

Market segment Departing paxBRD Private 100BRD Business 100EUR Short Stay 100EUR Holiday 100EUR Business 100INT Private 100INT Business 100Sum 700

Airport Capacity departing paxFrankfurt/Main 300Cologne 100Düsseldorf 100Sum 500

Airport Market share PaxFrankfurt/Main 9.26% 65Düsseldorf 33.10% 232Cologne 54.33% 380Dortmund 1.13% 8Niederrhein/Weeze 0.88% 6Frankfurt Hahn 0.62% 4Münster/Osnabrück 0.26% 2Sum 99.58% 697

Sensitivity to capacity constraints per market segment

Sensitivity is much higher for domestic (190/30)* and European (216/236/11)** travel than for intercontinental (59/49)* travel.

Sensitivity is much higher for private than for business travel.

However, sensitivity depends also on the level of attractiveness of an airport the higher the attractiveness, the less the sensitivity.

However, demand is distributed among more airports with especially small airports increasing their market share significantly.

* (Private/business)

** (Short stay/holiday/business)

Increase of travel time as one reason of airport constraints

Value of travel time in Euro

Further negative effects:

Increase of travel cost, flight plan, etc.

Increase of travel time from Cologne to (shortest travel time in minutes, single trip)Market segment Euro/minute Frankfurt/Main Dortmund Niederrhein/Weeze Frankfurt Hahn Münster/Osnabrück

64 70 81 82 131BRD Private 0.32 20.48 22.40 25.92 26.24 41.92BRD Business 0.75 48.00 52.50 60.75 61.50 98.25EUR Short Stay 0.31 19.84 21.70 25.11 25.42 40.61EUR Holiday 0.49 31.36 34.30 39.69 40.18 64.19EUR Business 0.37 23.68 25.90 29.97 30.34 48.47INT Private 0.39 24.96 27.30 31.59 31.98 51.09INT Business 0.57 36.48 39.90 46.17 46.74 74.67

Conclusions

Consequences of capacity constraints at airports

Reduction of welfare for air travellers (e.g. increase of travel time)

Spill-over effects and thus leading to capacity constraints at further

airports

Decreased competition at constrained airports

Demand is distributed among more airports, with small remote airports

benefiting

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.deTel: +49 2203 601 2463