Key Findings of 2013 ATRS Global Airport Performance ... · &Marketing on behalf of ... ATRS Global...
Transcript of Key Findings of 2013 ATRS Global Airport Performance ... · &Marketing on behalf of ... ATRS Global...
Plenary Session II: “Airport Keynote & 2013 ATRS Global
Airport Performance Benchmarking Report Session”
Moderator: Mr. Mario Diaz,
Head, Houston Airports System, TX, USA Prof. Tae Hoon Oum, University of British Columiba, Canada
“Key Results of the 2014 ATRS Global Airport Performance Benchmarking Project” – 30 min.
Panelists: 50-60 min
Panelists:
• Balram Bheodari, Deputy GM, Hartsfield-Jackson Atlanta International Airport, Atlanta, GA, USA
• Mr. Kristian Durhuus, VP Operations, Copenhagen Airport, Demark
• Mrs. Ioanna Papadopoulou, Director, Commercial &Marketing on behalf of (Dr. Yannis Paraschis, President & CEO, Athens International Airport, Greece)
• Mr. Bjorn Oli Hauksson, Managing Director, Keflavik International Airport, Iceland
• Mr. Soon-Chun Park, Head Executive, Busan Regional Headquarters, Korea Airport Corp, Korea (on behalf of Mr. Seok-ki Kim, CEO, KAC)
• Ms. Marion Charlton, GM-Terminal and Commercial, Gold Coast Airport, Queensland Airports Limited, Australia
• Mr. Arturs Kokars, Director of Aviation Services Dept, Riga International Airport, Latvia
• Mr. Johan Vanneste, CEO, Luxembourg Findel Airport, Luxembourg
Key Findings
2014 ATRS Global Airport Performance Benchmarking Project
ATRS Global Airport Benchmarking Task Force: Asia Pacific: P. Forsyth, Xiaowen Fu, Yeong-Heok Lee, Yuichiro Yoshida, Japhet Law, Shinya Hanaoka
Europe: Nicole Adler, Jaap de Wit, Hans-Martin Niemeier, Eric Pels
North America: Tae Oum, Bijan Vasigh, Jia Yan, Chunyan Yu Middle East: Paul Hooper
Prof. Tae Hoon Oum, Dr. Sam Choo, Prof. Chunyan Yu
OUTLINE
Objective of the ATRS Benchmarking Study
Airports Included and ATRS Database
Some Characteristics of Sample Airports
Methodology
Key Results on Efficiency and Costs
User Charge Comparisons
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
OBJECTIVE OF THE BENCHMARKING STUDY
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
To provide a comprehensive, unbiased
comparison of airport performance focusing on
Productivity and Operating/Mgt Efficiency
Unit Cost Competitiveness
Airport User Charges
Our study does not treat service quality differentials across airports because of our research time & resource constraints
Airport Database
2014 ATRS Global Airport Performance Benchmarking Project
200 MAJOR AIRPORTS AROUND THE WORLD
Asia Pacific, 53
Europe, 69
N. America, 78
1 new airport
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Asia (37)
Oceania Countries
(16) United States
(66)
Canada (12)
2 new airports
2 new airports
26 AIRPORT GROUPS
Europe (17)
Asia Pacific ( 9)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
ATRS AIRPORT DATABASE, FY 2002-2012 (11 years)
The ATRS Database contains historic information (since FY 2002) including financial data, traffic and capacity data for the major airports and airport groups in the following geographic regions:
Asia Pacific including Oceania; Europe; North America
Limited data on S. America and Africa
The data in each continent is segregated into:
Traffic statistics and composition
Airport characteristics (runways, terminals, ownership form, etc)
Aeronautical Activities and Revenue
Non-Aeronautical Activities and Revenue
Labor input and other Operating Expenses
Financial info obtained from Balance Sheets
Visit http://www.atrsworld.org/Database.html for more details and to purchase.
Objective Data
Airport Characteristics
Methodology Efficiency & Cost User Charge
Airport Characteristics
2014 ATRS Global Airport Performance Benchmarking Project
PASSENGERS TRAFFIC, FY2012 (IN ’000 PASSENGERS)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Asia Pacific Europe North America
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
PASSENGER TRAFFIC (’000)-
TOP 10 AIRPORTS: FY 2008, 2010, 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Asia Pacific Europe North America
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
2008 2010 2012
AIRCRAFT MOVEMENTS, FY 2012 (’000 ATM)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Asia Pacific Europe North America
0
100
200
300
400
500
600
700
800
900
1,000
PEK
HN
D
CA
N
CG
K
PV
G
HK
G
DX
B
BK
K
SIN
SYD
KU
L
DEL
ICN
BO
M
SHA
SZX
MN
L
NR
T
MEL
TPE
BN
E
AK
L
XM
N
SUB
GM
P
KIX
CJU
MA
A
PER
WLG
HA
K
NG
O
AD
L
CH
C
PU
S
HK
T
CM
B
PEN
GU
M
CN
S
MFM
OO
L
CN
X
TSV
DR
W
REP
DU
D
PN
H
NTL
NA
N
HD
Y
ZQN
CEI
CD
G
FRA
LHR
AM
S
MU
C
MA
D
IST
FCO
BC
N
ZRH
VIE
CP
H
LGW
OR
Y
OSL
BR
U
DU
S
AR
N
HEL
PM
I
TXL
MX
P
MA
N
GV
A
NC
E
DU
B
ATH
HA
M
LIS
STN
PR
G
LED
CG
N
SAW
WA
W
LYS
EDI
AG
P
STR
LPA
KB
P
TLV
LTN
LIN
BH
X
BU
D
BSL
HA
J
VC
E
LUX
BG
Y
GLA
RIX
BLQ
ALC
NA
P
BR
S
OP
O
TRN
CIA
TLL
BEG
SOF
ZAG
MLA
KEF
LJU
BTS
SZG
ATL
OR
D
DFW
DEN
LAX
CLT
IAH
LAS
PH
X
PH
L
DTW
YYZ
EWR
MSP
JFK
SFO
MIA
LGA
BO
S
SEA
IAD
MC
O
YVR
DC
A
SLC
MEM
BW
I
FLL
YYC
YUL
HN
L
MD
W
PD
X
AN
C
STL
SAN
CLE
TPA
RD
U
BN
A
IND
HO
U
CV
G
MC
I
SDF
OA
K
YEG
YOW
DA
L
PIT
SAT
MK
E
AU
S
YWG
CM
H
SJC
MSY
SMF
AB
Q
SNA
BD
L
YQB
PB
I
YHZ
ON
T
JAX
YYJ
RSW
RIC
BU
R
OK
C
TUL
TUS
PV
D
PASSENGERS PER AIRCRAFT MOVEMENTS, FY 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Asia Pacific Europe North America
0
20
40
60
80
100
120
140
160
180
200
HN
D
DX
B
HK
G
CM
B
BK
K
SIN
NR
T
CG
K
HK
T
TPE
ICN
CJU
PEK
OO
L
GM
P
KU
L
MEL
CEI
SHA
HD
Y
MN
L
PER
CA
N
PU
S
PV
G
BO
M
SYD
SZX
HA
K
DEL
CN
X
BN
E
XM
N
NG
O
MA
A
NA
N
SUB
MFM
KIX
PEN
AD
L
ZQN
PN
H
AK
L
CN
S
REP
DR
W
CH
C
NTL
TSV
WLG
GU
M
DU
D
LHR
LGW
ALC
TLV
PM
I
MLA
IST
CD
G
AG
P
DU
B
STN
BC
N
MA
D
AM
S
BG
Y
SAW
OR
Y
FCO
MA
N
FRA
TXL
LIS
OP
O
VC
E
MX
P
LTN
MU
C
BH
X
GLA
LPA
BR
S
SZG
BU
D
STR
CP
H
OSL
DU
S
NA
P
AR
N
ZRH
VIE
HA
M
LIN
KEF
CIA
LED
BLQ
EDI
HEL
KB
P
BR
U
ATH
GV
A
PR
G
WA
W
SOF
BEG
CG
N
LYS
RIX
NC
E
TRN
HA
J
BSL
BTS
ZAG
LJU
TLL
LUX
JFK
MC
O
LAX
SEA
SFO
RSW
FLL
MIA
TPA
ATL
SAN
SNA
PH
X
MD
W
DFW
BW
I
SMF
DEN
MSY
HN
L
EWR
LAS
BO
S
YYZ
AU
S
SJC
MSP
IAH
CLT
PD
X
MC
I
OR
D
JAX
DTW
IAD
PB
I
HO
U
OA
K
SLC
LGA
PV
D
SAT
PH
L
STL
DC
A
RN
O
BN
A
PIT
DA
L
BD
L
MK
E
TUS
BU
R
RD
U
YUL
ON
T
YVR
YYC
CM
H
OK
C
AB
Q
YHZ
IND
CLE
ALB
TUL
YEG
RIC
CV
G
YYT
YOW
YQR
YWG
MEM
AIR CARGO TRAFFIC, FY 2012 (’000 METRIC TONS)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Asia Pacific North America Europe
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
% NON-AERO REVENUE, FY 2012
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
HK
G
GM
P
OO
L
TSV
PU
S
CA
N
CH
C
CM
B
ICN
BN
E
CJU
DU
D
SIN
SYD
MEL
HA
K
AK
L
NTL
GU
M
ZQN
PEK
NR
T
AD
L
PV
G
SZX
WLG
BK
K
CEI
CN
X
HD
Y
HK
T
DR
W KIX
XM
N
NG
O
KU
L
PEN
CG
K
KEF
FRA
BSL
OSL
CD
G
OR
Y
ATH HA
J
AM
S
CP
H
TRN
TLL
DU
B
TLV
IST
CIA
FCO
ZRH
BH
X
VIE
STR
LTN
ZAG
BU
D
LJU
LIN
MX
P
AR
N
MA
N
GV
A
MU
C
BG
Y
RIX
HA
M
SOF
LGW ED
I
NA
P
SAW
STN
LIS
OP
O
SZG
LHR
VC
E
DU
S
CG
N
ALC
AG
P
BLQ TX
L
LPA
WA
W
MLA
BC
N
HEL
PM
I
MA
D
LED
BEG
BN
A
OK
C
JAX
BU
R
TPA
MC
I
RIC YY
J
FLL
YQR
ATL
MC
O
PH
X
IND
RD
U
CM
H
MK
E
PB
I
DA
L
YYC
TUS
RN
O
DFW YV
R
SLC
YEG
MSP SJC
YQB
SNA
ALB
SAT
RSW AU
S
CLT
LAS
AB
Q
YYT
TUL
SMF
SDF
SAN
PV
D
YHZ
BO
S
HO
U
YOW
PD
X
YUL
ON
T
HN
L
SFO
DTW OA
K
DC
A
BD
L
CV
G
BW
I
YWG
LAX
DEN SE
A
PIT
IAH
MSY
MD
W
MIA
YYZ
OR
D
IAD
PH
L
CLE ST
L
EWR
LGA
JFK
MEM
% Non-Aero Rev Mean
Asia Pacific Europe North America
Non-Aeronautical Revenue Share (2012) –Asia Pacific
Asian Airports Oceanian Airports Airport Group
Asia:1st Gimpo (KAC), 1st Hong Kong, 3rd Busan-Gimhae (KAC)
Oceania: 1st Gold Cost, 1st Townsville, 3rd Christchurch
Non-Aeronautical Revenue Share (2012) –Europe
Europe:1st Keflavik, 2nd Frankfurt, 3rd EuroAirport Basel-Mulhouse-Freiburg
Non-Aeronautical Revenue Share (2012) –N. America
Europe:1st Nashville 2nd Oklahoma City, 3rd Jacksonville
Methodology
2014 ATRS Global Airport Performance Benchmarking Project
AIRPORT PRODUCTIVITY INDEX
Outputs
• Aircraft movement
• Passenger
• {Cargo tonnes}
• Non-aeronautical revenue output
Inputs
• Labour
• Other non-capital (soft-cost) input
• [Runways, terminal size, # of gates]
© Air Transport Research Society (ATRS) Objective Data
Airport Characteristics
Methodology Efficiency & Cost User Charge
METHODOLOGY: EFFICIENCY MEASUREMENT
Variable Factor Productivity (VFP) Index Impossible - Total Factor Productivity (TFP)
because of capital input cost accounting problem (comparable across different countries)
Unit Operating Cost Competitiveness Index: Combines VFP and Input Price Index
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
MULTILATERAL AGGREGATION METHOD
• This multilateral output (input) index procedure uses the following revenue (cost) shares to aggregate output (inputs)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
GROSS VARIABLE FACTOR PRODUCTIVITY (VFP) ASIAN AIRPORTS (HKG=1.0), FY 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
CJU
PUS
HKG
GM
P
HA
K
ICN
CGK
SIN
CAN
PEK
GU
M
PVG
XMN
CNX
HD
Y
CEI
HKT
BKK
NRT SZ
X
PEN
KUL
KIX
NG
O
CMB
KAC
API
I
AO
T
MA
HB
Gross VFP
Airport GroupsAirports
POTENTIAL REASONS FOR THE MEASURED PRODUCTIVITY (GROSS VFP) DIFFERENTIALS
Factors Beyond Managerial Control:
• Airport size (Scale of aggregate output)
• Average aircraft size using the airport
• Share of international traffic
• Share of air cargo traffic
• Extent of capacity shortage - congestion delay
• Connecting/transfer ratio
We compute residual (Net) Variable Factor Productivity (RVFP) after removing effects of these Factors
© Air Transport Research Society (ATRS) 26 Objective Data
Airport Characteristics
Methodology Efficiency & Cost User Charge
GROSS VARIABLE FACTOR PRODUCTIVITY VS RESIDUAL VFP: ASIA (HKG=1.0), FY 2012
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
PUS
CJU
HKG
HA
K
GM
P
ICN
CGK
SIN
GU
M
CAN
PEK
PVG
XMN
CNX
HD
Y
NRT BK
K
CEI
PEN
SZX
HKT
KUL
KIX
NG
O
CMB
KAC
API
I
AO
T
MA
HB
Gross VFP Residual VFP
Airport GroupsAirports
Key Results on Efficiency & Cost
2014 ATRS Global Airport Performance Benchmarking Project
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
PUS
CJU
HKG
HA
K
GM
P
ICN
CGK
SIN
GU
M
CAN
PEK
PVG
XMN
CNX
HD
Y
NRT BK
K
CEI
PEN
SZX
HKT
KUL
KIX
NG
O
CMB
KAC
API
I
AO
T
MA
HB
Airport GroupsAirports
RESIDUAL (NET) VARIABLE FACTOR PRODUCTIVITY (VFP): ASIA (HKG=1.0), FY 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Busan Gimhae, Jeju, Hong Kong
GROSS VARIABLE FACTOR PRODUCTIVITY VS RESIDUAL VFP: Europe Large Airports
(CPH=1.0), FY 2012
0
0.2
0.4
0.6
0.8
1
1.2
CP
H
ZRH
OSL
AM
S
BC
N
STN
FCO
MX
P
AR
N
CD
G
IST
PM
I
MA
N
LIS
LGW
OR
Y
VIE
DU
B
LHR
MA
D
FRA
DU
S
MU
C
TXL
Sch
iph
ol
AD
R
AD
P
MA
G
Swe
dav
ia
SEA
AN
A
DA
A
He
ath
row
Frap
ort
Avi
no
r
Fin
avia
PP
L
TAV
AEN
A
Be
rlin
Gross VFP Residual VFP
Airport GroupsAirports
CPH
ZRH
OSL
AM
S
BCN
STN
FCO
MXP
ARN
CDG
IST
PMI
MA
N
LIS
LGW
ORY
VIE
DU
B
LHR
MA
D
FRA
DU
S
MU
C
TXL
Schi
phol
AD
R
AD
P
MA
G
Swed
avia
SEA
AN
A
DA
A
Hea
thro
w
Frap
ort
Avi
nor
Fina
via
PPL
TAV
AEN
A
Berl
in
0
0.2
0.4
0.6
0.8
1
1.2
Airport GroupsAirports
RESIDUAL (NET) VARIABLE FACTOR PRODUCTIVITY (VFP): EUROPE LARGE AIRPORTS (CPH=1.0), FY 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Copenhagen Kastrup, Zurich, Oslo
GROSS VARIABLE FACTOR PRODUCTIVITY VS RESIDUAL VFP: Europe Small & Medium Airport
(CPH=1.0), FY 2012
0
0.2
0.4
0.6
0.8
1
1.2
1.4
ATH
GVA BS
L
CIA
BHX
SAW TLV
VCE
KEF
HAJ
LJU
TLL
EDI
LTN
BGY
LPA
RIX
MLA
NAP
TRN
ALC
BLQ
HA
M
SZG
AG
P
BUD
STR
HEL
LIN
ZAG
BEG
CGN
WAW SO
F
LED
Gross VFP Residual VFP
ATH
GVA
BSL
CIA
BHX
SAW
TLV
VCE
KEF
HA
J
LJU
TLL
EDI
LTN
BGY
LPA
RIX
MLA
NA
P
TRN
ALC
BLQ
HA
M
SZG
AG
P
BUD
STR
HEL
LIN
ZAG
BEG
CGN
WA
W
SOF
LED
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
RESIDUAL (NET) VARIABLE FACTOR PRODUCTIVITY (VFP): EUROPE SMALL & MEDIUM AIRPORTS (CPH=1.0), FY 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Athens, Geneva, Basel
GROSS VARIABLE FACTOR PRODUCTIVITY VS RESIDUAL VFP: N. American Large Airports
(YVR=1.0), FY 2012
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
ATL
CLT
MSP
YVR
TPA
MC
O
PH
X
SFO
LGA
FLL
SLC
BO
S
DTW
EWR
MD
W
SEA
DFW JF
K
LAS
HN
L
PH
L
BW
I
SAN
IAH
MIA
DEN
OR
D
DC
A
LAX
IAD
Gross VFP Residual VFP
ATL
CLT
MSP
YVR
TPA
MC
O
PH
X
SFO
LGA
FLL
SLC
BO
S
DTW
EWR
MD
W
SEA
DFW
JFK
LAS
HN
L
PH
L
BW
I
SAN
IAH
MIA
DEN
OR
D
DC
A
LAX
IAD
0.000
0.200
0.400
0.600
0.800
1.000
1.200
RESIDUAL (NET) VARIABLE FACTOR PRODUCTIVITY (VFP): NORTH AMERICA LARGE AIRPORTS (YVR=1.0), FY 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Atlanta, Charlotte, Minneapolis St. Paul
GROSS VARIABLE FACTOR PRODUCTIVITY VS RESIDUAL VFP: N. AmericanSmall & Medium
Airport (YVR=1.0), FY 2012
0.000
0.200
0.400
0.600
0.800
1.000
1.200
OK
C
YYC
RD
U
RIC
BN
A
YEG
PV
D
SJC
PD
X
YYJ
IND
BD
L
SAT
JAX
TUS
PB
I
AB
Q
MK
E
YYT
MC
I
SNA
MSY
RN
O
RSW AU
S
YOW
HO
U
MEM TU
L
YUL
YWG
SMF
SDF
DA
L
OA
K
YHZ
STL
CM
H
ALB
BU
R
CV
G
CLE PIT
ON
T
AN
C
YQB
Gross VFP Residual VFP
OK
C
YYC
RD
U
RIC
BN
A
YEG
PV
D
SJC
PD
X
YYJ
IND
BD
L
SAT
JAX
TUS
PB
I
AB
Q
MK
E
YYT
MCI
SNA
MSY
RN
O
RSW
AU
S
YOW
HO
U
MEM
TUL
YUL
YWG
SMF
SDF
DA
L
OA
K
YHZ
STL
CM
H
ALB
BU
R
CV
G
CLE
PIT
ON
T
AN
C
YQB
0.000
0.200
0.400
0.600
0.800
1.000
1.200
RESIDUAL (NET) VARIABLE FACTOR PRODUCTIVITY (VFP): N. AMERICA SMALL & MEDIUM AIRPORTS (YVR=1.0), FY 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Oklahoma City, Calgary, Raleigh-Durham
GROSS VARIABLE FACTOR PRODUCTIVITY VS RESIDUAL VFP: Oceanian Airports
(SYD=1.0), FY 2012
0.000
0.200
0.400
0.600
0.800
1.000
1.200
SYD DUD MEL AKL BNE TSV OOL DRW PER CHC ZQN WLG ADL NTL APAC QAL ADG
Gross VFP Residual VFP
Airport GroupsAirports
0.000
0.200
0.400
0.600
0.800
1.000
1.200
SYD DUD MEL AKL BNE TSV OOL DRW PER CHC ZQN WLG ADL NTL APAC QAL ADG
Residual VFP Mean
Airport GroupsAirports
RESIDUAL (NET) VARIABLE FACTOR PRODUCTIVITY (VFP): OCEANIA (SYD=1.0), FY 2012
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Sydney, Dunedin, Melbourne
TOP EFFICIENCY PERFORMERS (2014) (based on Net VFP index=operating/management efficiency)
• Asian Airports:
• Busan Gimhae, Jeju, Hong Kong
• Oceania Airports:
• Sydney, Dunedin, Melbourne
Asia Pacific:
• Large Airports (> 15 million pax):
• Copenhagen Kastrup, Zurich, Oslo
• Small/Medium Airports (< 15 millions Pax):
• Athens, Geneva, Basel
Europe:
© Air Transport Research Society (ATRS) 40 Objective Data
Airport Characteristics
Methodology Efficiency & Cost User Charge
TOP EFFICIENCY PERFORMERS (2014) (based on Net VFP index=operating/management efficiency)
• Large Airports (> 15 million pax):
• Atlanta, Charlotte, Minneapolis St Paul
• Small/Medium Airports (< 15 millions Pax):
• Oklahoma City, Calgary, Raleigh-Durham
North America:
© Air Transport Research Society (ATRS) 41 Objective Data
Airport Characteristics
Methodology Efficiency & Cost User Charge
PAST AIRPORT EFFICIENCY EXCELLENCE TOP PERFORMERS, 2009 - 2013
North America
Europe
Asia-Pacific
2013 Hartsfield-Jackson
Atlanta International Airport
Minneapolis St. Paul International Airport
Oklahoma City Will Rogers World Airport
Large Airport Category: Copenhagen Kastrup International Airport
Small/Medium Airport Category:
Genève Aéroport
Asian Airport Excellence Award:
Seoul Gimpo International Airport
Oceania Excellence Award:
Sydney Airport
2009
Hartsfield-Jackson Atlanta International
Airport
Copenhagen Kastrup International Airport
Hong Kong International Airport
2010
Hartsfield-Jackson Atlanta International
Airport
Large Airport Category:
Oslo International Airport
Small/Medium Airport Category:
Geneva Cointrin International Airport
Large Airport Category: Hong Kong International
Airport
Small/Medium Airport Category:
Seoul Gimpo International Airport
2011
Hartsfield-Jackson Atlanta International
Airport
Large Airport Category: Oslo International Airport
Copenhagen Kastrup International Airport
Small/Medium Airport Category:
Genève Aéroport
Asian Airport Excellence Award:
Hong Kong International Airport
Oceania Excellence Award:
Sydney Airport
2012
Hartsfield-Jackson Atlanta International
Airport
Large Airport Category: Copenhagen Kastrup International Airport
Small/Medium Airport Category:
Genève Aéroport
Asian Airport Excellence Award:
Seoul Gimpo International Airport
Oceania Excellence Award:
Sydney Airport
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
HA
K
PU
S
CG
K
CJU
HK
G
XM
N
CM
B
GM
P
CN
X
PEN
HD
Y
SZX
CEI
ICN
PEK
PV
G
CA
N
HK
T
BK
K
KU
L
SIN
GU
M
NG
O
KIX
NR
T
KA
C
AP
II
AO
T
MA
HB
-2
-1.5
-1
-0.5
0
0.5
Airport GroupsAirports
COST COMPETITIVENESS = NET VFP AND INPUT PRICE EFFECT ASIA (HKG=0.0) – THE HIGHER THE BETTER
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Haikou, Busan Gimhae, Jakarta
CPH
LIS
IST
FCO
PMI
MXP
MA
NST
NA
MS
FRA
BCN
VIE
CDG
MA
DD
UB
ARN
MU
CD
US
LGW
LHR
ORY
TXL
OSL
ZRH
PPL
AN
ATA
VM
AG
AD
RFr
apor
tSc
hiph
olSE
AD
AA
Hea
thro
wA
DP
Swed
avia
AEN
ABe
rlin
Fina
via
Avi
nor
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
Airport GroupsAirports
COST COMPETITIVENESS = NET VFP AND INPUT PRICE EFFECT EUROPE - LARGE AIRPORTS (CPH=0.0)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Copenhagen, Lisbon, Istanbul Ataturk
RIX
TLL
LJU
ATH
SOF
MLA
BSL
CIA
BEG
SAW
BUD
ZAG
BHX
VCE
WA
W
LTN
HA
J
BGY
LPA
KEF
EDI
TLV
TRN
ALC
NA
P
AG
P
LED
BLQ
HA
M
STR
LIN
SZG
CGN
HEL
GVA
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
COST COMPETITIVENESS = NET VFP AND INPUT PRICE EFFECT EUROPE - SMALL & MEDIUM AIRPORTS (CPH=0.0)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Riga (Latvia), Tallinn (Estonia), Ljubljana (Slovenia)
CLT
ATL
TPA
MC
O
MSP
PH
X
SLC
FLL
YVR
LAS
IAH
DTW
DFW
SEA
BW
I
DEN
MIA
OR
D
SAN
MD
W
HN
L
BO
S
LAX
PH
L
DC
A
SFO
IAD
EWR
JFK
LGA
-2
-1.5
-1
-0.5
0
0.5
1
COST COMPETITIVENESS = NET VFP AND INPUT PRICE EFFECT N. AMERICA - LARGE AIRPORTS (YVR=0.0)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Charlotte, Atlanta, Tampa
OKC
RDU
RIC
IND
SAT
ABQ
YYC
BNA
TUS
JAX
TUL
SDF
MCI
DA
LM
SY PBI
MEM
MKE
HO
URN
OA
US
PDX
PVD
CMH
RSW
YYJ
ALB ST
LBU
RCL
EPI
TCV
GBD
LSM
FYW
GSN
AYY
TYU
LSJ
CYE
GYQ
BYH
ZYO
WO
AK
AN
C
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
COST COMPETITIVENESS: = NET VFP AND INPUT PRICE EFFECT N. AMERICA - SMALL & MEDIUM AIRPORTS (YVR=0.0)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Oklahoma City, Raleigh-Durham,Richmond (Virginia)
DU
D
AK
L
SYD
TSV
OO
L
CH
C
BN
E
MEL
WLG
ZQN
PER
DR
W
AD
L
NTL
QA
L
AP
AC
AD
G
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
Airport GroupsAirports
COST COMPETITIVENESS = NET VFP AND INPUT PRICE EFFECT OCEANIA (SYD=0.0)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Dunedin, Auckland, Sydney
User Charge Comparison
2014 ATRS Global Airport Performance Benchmarking Project
LANDING CHARGES FOR AIRBUS 320, 2013 (IN US$)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
KU
L (L
CC
s)K
UL
GU
MC
MB
DX
BTP
ESU
BB
KK
CEI
CN
XH
DY
HK
TC
GK
BN
EB
NE-
Pe
akP
ENM
NL
SIN
-Off
Pe
akP
NH
REP
CA
NH
AK
PEK
PV
GSH
ASZ
XX
MN
CJU
PU
SG
MP
ICN
MFM
NA
NZQ
NSI
NM
AA
DEL
BO
MC
HC
AK
LP
ERH
KG
AD
LN
TLTS
VK
IX-O
ff P
eak
KIX
(LC
Cs)
-Off
Pe
akD
UD
WLG
-Off
Pe
akO
OL
WLG
-Sh
ou
lder
WLG
-Pe
akN
TL-N
igh
tN
GO
KIX
KIX
(LC
Cs)
DR
WN
RT(
1N
)N
RT(
1S)
NR
T (2
)SY
DH
ND
NA
PB
GY
AR
NM
LA STR
TRN
LTN
RIX
BSL
(Fra
nce
) B
LQLU
XM
UC
BR
ULI
SV
IED
US
OP
OH
ELST
N-O
ff P
eak
BSL
(Sw
iss)
GV
AK
BP
HA
MTX
LK
EFG
LA EDI
CP
HFR
AZA
GSA
WM
AN
-Off
Pe
ak LYS
IST
ZRH
FCO
-Off
Pe
akLE
DN
CE
CIA
PR
GST
N-P
eak
CG
NA
GP
ALC
LPA
PM
IM
XP
BEG HA
JTL
LB
CN
TLV
CD
GO
RY
OSL
LGW
-Off
Pe
akM
AD
FCO
-Pe
akV
CE
AM
SSO
FW
AW
MA
N-P
eak
BU
DB
HX
LIN
LJU
BTS
ATH BR
SSZ
GD
UB
LGW
-Pe
akLH
R
CLT RIC
TUS
MEM SA
TB
NA
PB
IM
SYSL
CSA
NP
HL
TPA
IND
PH
XO
NT
RD
USD
FB
UR
HO
UA
BQ
FLL
MC
IM
CO
SNA
JAX
SJC
MIA
MSP
RN
O*
YVR
OK
CM
DW
CM
HTU
LH
NL
*A
NC
IAH
*YQ
RR
SW *YY
JLA
SA
LBSE
A*
YYC
PD
XO
AK
*YO
WA
TL*
YEG
AU
S*
YHZ
DTW DC
AC
VG
PIT
IAD
DFW DEN
SMF
BW
I*
YWG
*YU
LM
KE
LAX
BO
S*
YYT
CLE
OR
DSF
O*
JFK
Off
Pe
ak*
YQB
*JF
K P
eak
*EW
R O
ff P
eak ST
L*
YYZ
*EW
R P
eak
*LG
A O
ff P
eak
*LG
A P
eak
US$
Asia Pacific Europe North America
AP Mean Europe Mean
N. America Mean
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
TPE
DEL
HK
G
DU
D
BO
M
KU
L (L
CC
s)
MA
A
GU
M
CJU
PU
S
MN
L
CA
N
HA
K
PEK
PV
G
SHA
SZX
XM
N
GM
P
SUB
SIN
-Off
Pe
ak
CG
K
WLG
-Off
Pe
ak
WLG
-Sh
ou
lde
r
WLG
-Pe
ak
KU
L
MFM SI
N
PEN ICN
AD
L
DX
B
CH
C
CEI
CN
X
HD
Y
HK
T
TSV
BK
K
KIX
(LC
Cs)
-O
ff P
eak
CM
B
REP
NTL
PN
H
MEL
OO
L
AK
L
PER
DR
W
KIX
(LC
Cs)
NTL
-Nig
ht
ZQN
HN
D
CN
S
SYD
BN
E
BN
E-P
eak
NR
T(1
N)
NR
T(1
S)
NR
T (2
)
NG
O
KIX
-Off
Pe
ak KIX
Mean
ASIA PACIFIC: COMBINED LANDING AND PASSENGER CHARGES FOR AIRBUS 320, 2013
(IN US$)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Lowest charges: Taipei Taoyuan, New Delhi
Highest charges: Osaka Kansai, Nagoya
0
2,000
4,000
6,000
8,000
10,000
12,000
LUX
RIX
NA
P
BG
Y
CIA
MA
N-O
ff P
eak
BLQ HEL
KEF TL
L
AR
N
BSL
(Fra
nce
Se
cto
r)
CG
N
OSL
ZAG
GV
A
CP
H (L
CC
s)
BSL
(Sw
iss
Sect
or)
STR
AG
P
ALC
LPA
PM
I
TRN
MA
N-P
eak
LTN
STN
-Off
Pe
ak
NC
E
IST
SOF-
Pe
ak
GLA
KB
P
STN
-Pe
ak
CP
H
EDI
HA
J
MLA
HA
M
VC
E
LYS
TXL
DU
S
OP
O
BEG
(LC
Cs)
TLV
(LC
Cs)
SAW
LED LIS
BH
X
VIE
AM
S
ZRH
LGW
-Off
Pe
ak
MU
C
WA
W
DU
B
BU
D (
LCC
s)
BU
D
MX
P
SZG
BEG
BR
U
BTS LJU
BC
N
FCO
-Off
Pe
ak LIN
ATH FR
A
FCO
-Pe
ak
PR
G
BR
S
MA
D
CD
G
OR
Y
TLV
LGW
-Pe
ak
LHR
US$
Mean
EUROPE: COMBINED LANDING AND PASSENGER CHARGES FOR AIRBUS 320, 2013
(IN US$)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
Lowest charges: Luxembourg, Riga (Latvia) Highest charges: London Heathrow, London Gatwick- Peak
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
CLT
BUR
ATL
DA
LFL
LBN
ASL
CTP
AM
CIPH
XJA
XO
KC LAS
DFW
MCO RI
CRD
UM
SPM
EM SDF
HO
UTU
STU
LA
LBM
KESA
NRN
OPB
ISA
TM
DW
CMH
RSW
ABQ AU
SIA
HBW
IBD
LD
TW PHL
AN
CSN
AIN
DH
NL
MSY
OA
KPV
DCV
GO
NT
PDX
DEN LA
XSJ
CD
CA BOS
SEA
ORD ST
LSM
FSF
OCL
ELG
API
TM
IAEW
RIA
DJF
K
YYJ
YQR
YYC
YEG
YVR
YHZ
YOW
YQB
YWG
YUL
YYZ
$US
US Mean
Canadian Mean
NORTH AMERICA: COST PER ENPLANED PASSENGER, 2012 (IN US$)
Objective Data Airport
Characteristics Methodology Efficiency & Cost User Charge
United States: Lowest CPE: Charlotte, California Bob Hope (Burbank,CA) Highest CPE: New York JFK, Washington Dulles
Canada: Lowest CPE: Victoria, Regina Highest CPE: Toronto, Montreal
ATRS AIRPORT DATA & BENCHMARKING REPORTS
The ATRS Global Airport Performance Benchmarking Report : 3 volumes, over 700 pages of valuable data and analysis
Can be purchased by visiting
www.atrsworld.org
Report sale finances our annual benchmarking research project
© Air Transport Research Society (ATRS) 54
ACKNOWLEDGEMENT OF APPRECIATION
Houston Airport System
Permanent corp members: • Airbus • Boeing • Copenhagen International Airport • German Aerospace Center (DLR)
Fixed term members: • Gatwick Airport Ltd • Geneva Aeroport • Korea Airports Corporation • Kazan international airport, Russia • Istanbul Sabiha Gockcen Int’l • YVR International Airport
Gold Corporate Members
Corporate Members
Thank You
See you at 2015 ATRS World
Conference in Singapore!