The Airport Choice of Freighter Operators in Europe

The Airport Choice of Freighter Operators in
Europe:
Insights from a Discrete Choice Analysis
Franziska Kupfer
Department of Transport and Regional Economics
University of Antwerp
Work in cooperation with:
P. Goos, R. Kessels, E. Van de Voorde, A. Verhetsel
GARS Air Cargo Conference
– Wildau, 20 October 2011

1. Introduction
2. Previous Research
3. The Discrete Choice Approach
4. Conclusions
Overview
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Europe‘s Top 20 cargo airports 2010
Introduction
Own composition based on ACI data
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The Airport Choice of Freighter
Operators in Europe
All cargo airlines, cargo
subsidiaries, cargo divisions
with freighter operations
to/from Europe, with the
exeption of integrators
Airport choice concerns
choice for scheduled
freighter operations in
Europe
Introduction
Source: Lufthansa Cargo
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1. Introduction
2. Previous research
3. The Discrete Choice Approach
4. Conclusions
Overview
5

Previous Research
Studies with information about airport choice
mainly deal with the airport choices of passenger
airlines (see for example Huston, Butler, 1991 and Berechman, Wit, 1994) or
the hub choice (Watanabe et al, 2009, Ohashi et al., 2005, Martín, Román,
2004)
Methodologies used in literature: Weber Least
Cost Model (Wantanabe et al, 2009; Dennis, 1994) or general
surveys (see e.g. Gardiner, Ison, 2008)
Series of studies looking at airline choice of
passengers (Blackstone, Buck, Hakim, 2006; Pels, Nijkamp, Rietfeld, 2000;
Hess, Adler, Polak, 2007)
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Airport choice factors
Restrictions
Market factors
Cost factors
Time factors
Strategic factors
(Perception) of airport quality
Other factors
Previous Research
Source: Cargolux
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1. Introduction
2. Previous research
3. The Discrete Choice Approach
3.1. Experimental Setup and Data
3.2. Results
4. Conclusions
Overview
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Preliminary Interviews:
Experimental Setup and Data
5 airlines and 2 airports
Aim: narrow down
factors/attributes identified in
literature review
Rating of choice attributes
used as prior information for
choice design
Definition of factor levels
Source: Korean Air Cargo
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Experimental Setup and Data
Origin-Destination demand (potential revenue)
* 20% less origin-destination demand
* 10% less origin-destination demand
* Equal origin-destination demand
* 10% more origin-destination demand
* 20% more origin-destination demand
Night time restrictions
* No night time restrictions
* Limited or very expensive night time slots
* Night time flight prohibitions
Presence of forwarders
* No forwarders present
* Only major forwarders present
* Broad range of forwarders present
Airport charges (including handling)
* 20% lower airport charges
* 10% lower airport charges
* Equal airport charges
* 10% higher airport charges
* 20% higher airport charges
Presence of passenger airlines
* No passenger airline operations at airport
* Only passenger operations of own
airline/group or of main passenger airline partner
at airport
* Different passenger airline operations from
own airline/group as well as other airlines
Airport experience with cargo
* No experience with cargo
* Limited experience with cargo
* Extended experience with cargo
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Experimental Setup and Data
Partial profile design:
To deal with a large number of attributes
To reduce the complexity of the choice task so
as to overcome respondent fatigue and
inconsistent choices
To rule out lexicographic choice behavior, that
is, people who make choices based on the
levels of just one attribute or a small subset of
the attributes
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Experimental Setup and Data
2-stage design algorithm:
Stage 1: Determination of the
constant attributes in each
choice set
Stage 2: Determination of the
levels of the non-constant
attributes
Source: Avient
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Choice Design:
Experimental Setup and Data
As origin-destination demand was predicted to
be very dominant: 40 choice sets without
origin-destination demand
2 x 40 choice sets (four blocks of 10)
Each respondent had to make 20 (+1) choices
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Experimental Setup and Data
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Sample:
Experimental Setup and Data
26 airlines (32 completed
surveys)
More than 50% of population
From which:
11 independent cargo carriers
15 subsidiaries or cargo
divisions of combination
carriers
Source: Air France/KLM Cargo
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MNL MNL noPax MNL noPax
Clin DLin
parameter t-test parameter t-test parameter t-test
estimate
estimate
estimate
Night time
no restrictions 0.27563 0.2772 0.2777
limited 0.00937 0.1 0.0178 0.18 0.0163 0.17
prohibitions
Experience
-0.285 -2.17** -0.295 -2.24** -0.294 -2.25**
extended 0.6 0.587 0.592
limited -0.174 -1.82 -0.164 -1.74 -0.169 -1.8
no
Forwarders
-0.426 -3.22* -0.423 -3.21* -0.423 -3.21*
broad range 0.754 0.758 0.759
major 0.426 4.28* 0.422 4.25* 0.421 4.24*
no
Passenger
-1.18 -8.59* -1.18 -8.63* -1.18 -8.61*
different 0.1979
no -0.11 -1.1
sibling -0.0879 -0.9
Demand 0.0325 3.63
20% 0.69528 0.68948
10% 0.283 1.38 0.294 1.45
equal 0.00672 0.03 0.00152 0.01
-10% -0.387 -2.05** -0.383 -2.04**
-20% -0.598 -2.78* -0.602 -2.8*
Charges -0.0294 -5.11*
-20% 0.5373 0.53673
-10% 0.384 2.85* 0.384 0.384*
equal 0.0117 0.09 0.00527 0.04
10% -0.379 -2.72* -0.362 -2.63*
20% -0.554 -3.83* -0.564 -3.89*
Results
* significant at 1%
** significant at 5%
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Results
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Forwarders
Charges
Experience
Demand
Night time
0 20 40 60 80 100
L-R ChiSquare
Results
MML MML noPax ClinDlin
DF ChiSquare Prob>ChiSq ChiSquare Prob>ChiSq
Night time 2 6.291 0.043** 6.62 0.037**
Experience 2 27.625 < 0.0001* 27.454 < 0.0001*
Forwarders 2 91.854 < 0.0001* 92.45 < 0.0001*
Passenger 2 3.761 0.1525
Demand 4 13.396 0.0095* 13.316 0.0098*
Charges 4 28.913 < 0.0001* 28.106 < 0.0001*
* significant at 1%
** significant at 5%
Effects likelihood ratio tests
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Results
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Conclusions
Studies concerning airport choice mainly look at hub
choice and choices of passenger airlines
Analysis of factors brings more information on what is
important for airlines
Discrete choice approach brings new insights to problem
First results show that the presence of forwarders is the
most important attributes and passenger operations are
not significant
Further research:
* more advanced models (MMNL)
* integrate socio-economic factors
* calculate trade-offs
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Franziska Kupfer
Universiteit Antwerpen
Prinsstraat 13 – SB 408
2000 Antwerp
Franziska.Kupfer@ua.ac.be
+32 3 265 41 87
Contact
Source: www.kenlawrence.eu
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