prof. tae h. oum - welcome to the atrs homepage atrs 2008 24 july (2).pdf · ©air transport...

© Air Transport Research Society 1

Key Results of the 2008 ATRS Global Airport Performance Benchmarking Project

Prof. Tae H. OumThe Air Transport Research Society (ATRS),

www.atrsworld.org

The ATRS Global Airport Benchmarking Task Force Asia Pacific: P. Forsyth, Yeong-Heok Lee, Yuichiro Yoshida, Japhet Law

Europe: Nicole Adler, Jaap de Wit, Hans-Martin Niemeier, Eric PelsNorth America: David Gillen, Tae Oum, Bijan Vasigh, Jia Yan,

Chunyan Yu

http://www.atrsworld.org/


OutlineObjective of the Benchmarking StudyMethodologyKey Results on Efficiency and CostsAirport User Charge ComparisonsEffects of Business Strategies and Ownership formsConclusions


Objective of the Study

To provide a comprehensive, unbiased comparison of airport performance, including:– Productivity and Efficiency– Unit Cost Competitiveness– Aviation User Charges Levels


Airports Included in the studyCanada-U.S. 63 airportsEurope 38 airports and

10 airport groupsAsian Airport 24 airports

4 airport groupsAustralia and NZ 9 airports

-------------------------------------------------------------Total 134 airports and

14 airport groups

***Need your help in order to include more airports; Can you help us with the data?


Data Sources: 2001-06 (2007 data for airport user charges)

Airport’s Annual Reports, Financial Statements, and direct data requests;US FAA, DOT statistics;Association of European Airlines (AEA) StatisticsICAO Digest of Statistics:o annual and monthly traffic datao annual financial data -- not for all airports

ACI; IATAo annual traffic statistics; Capacity informationo general information surveys (Asia Pacific and Europe)

occasional and not complete IMF and World Bank – various price indices including GDP deflators for service sectors and PPP


Characteristics of

Sample Airports


Passenger Traffic - North American

7

Figure 3.4.1a: Passenger Traffic (2002/04/06)North America

0

10

20

30

40

50

60

70

80

90

ATL

OR

DLA

XD

FWD

EN

LAS

JFK

PH

XIA

HM

SP

DTW

MC

OS

FOE

WR

PH

LM

IAY

YZ

SE

AC

LTIAD

BO

SLG

AC

VG

FLL

SLCBW

IH

NL

TPA

MD

WD

CA

SA

NY

VR

OA

KS

TLP

DX

CLE

YU

LM

EM

SJCPIT

YY

CS

MF

MC

IS

NA

RD

UB

NA

IND

MS

YA

US

SA

TM

KE

ON

TP

BI

AB

QJA

XR

NO

YE

GY

OW

SD

FY

HZ

YW

GA

LBRIC

Mea

Mill

ions

2006 2004 2002


Passenger Traffic –Asia Pacific

8

3.4.1c: Passenger Traffic (2002/04/06) - Asia Pacific

0

10

20

30

40

50

60

PE

KH

KB

KK

SIN

NR

TC

GS

YD

DX

BIC

NP

VG

CA

NK

UL

TPE

ME

LS

HA

BO

SZX

MN

LK

IXD

EL

BN

ES

EL

AK

LX

MN

PE

RH

AK

AD

LC

HM

FMWL

HK

TC

NP

EN

CN

XH

DY

Mea

Mill

ions

2006 2004 2002


Passenger Traffic - Europe

9

Figure 3.4.1b: Passenger Traffic (2002/04/06) - Europe

0

10

20

30

40

50

60

70

80

LHR

CD

GFR

AA

MS

MA

DLG

WM

UC

FCO

BCN

OR

YS

TNM

AN

MX

PIS

TD

UB

CPHZR

HO

SLAR

NV

IEBR

UD

US

ATHLI

SH

ELH

AMTXL

PRG

GV

AC

GN

BH

XED

IBU

DW

AC

IAM

LARIX

SO

FK

EFB

TSTLL

LJU

KBPMea

M illion s

2006 2004 2002


Concession Revenue Shares – N. America

Concession Revenue Shares - North America (2006)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

%


Concession Revenue Shares – Asia-Pacific

Concession Revenue Shares - Asia Pacific (2006)

0%

10%

20%

30%

40%

50%

60%

CH

CM

EL

AK

LW

LGS

YD

AD

LP

ER

BN

EC

NS

Mea

n

HK

GIC

NA

AI

SIN

SE

LP

EK

TPE

CN

XA

OT

MAH

BP

TII

HA

KC

AN

Mea

n

%


Concession Revenue Shares – Europe

Concession Revenue Share - Europe (2006)

0%5%

10%15%20%25%30%35%40%45%50%

STN

LGW

GV

AE

DI

CPH

HA

MLH

RA

THM

AN

AM

SZR

HBR

UM

LAD

US

VIE

Mea

n

BA

AFi

navi

aA

DR

AN

AS

chip

hA

DP

Frap

ort

LFV

AE

NA

PP

LM

ean

%

Share of Non-Aeronautical Revenue

YYZ

Figure S-5: Non-Aeronautical Revenue Share (2006)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

North America

Europe


Methodology: EFFICIENCY MEASUREMENT

INDEX NUMBER APPROACH:Need to go beyond Partial Factor Productivity (PFP) such as labor productivity ⇒Variable Factor Productivity (VFP)⇒Total Factor Productivity (TFP: capital input accounting problem)⇒ Unit Cost Competitiveness Index = Combines VFP and Input

Price Index

Complementary approaches we are exploring:Data Envelopment Analysis (DEA)Econometric Cost Function Approach including Stochastic

Frontier Cost Function


Airport Productivity Index

Outputs Inputs

• Aircraft movement• Passengers• (Cargo)• Other revenues

including concessions

• Labour• Other non-capital (soft

cost) inputs• Runways• Terminals• Gates


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)’ productivity measures after removing effects of these Factors


Residual (Net) Variable Factor Productivity: Overall Efficiency Measure – North AmericaFigure S-4a, Residual Variable Factor Productivity (2006), North America

YVR = 1.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

ATL

RD

UM

SPTP

AR

NO

MC

OPB

IR

ICYV

RFL

LH

NL

BNA

MKE

PDX

YYC

YOW

LAS

LGA

CLT

SAT

JAX

SDF

SNA

ABQ

DC

AIA

HO

AKBO

SIN

DIA

DSE

AM

CI

PHX

AUS

YUL

DEN

SLC

DTW SA

NM

EMM

DW

CVG SF

OYE

GYW

GEW

RYH

ZSJ

CO

RD

JFK

SMF

CLE

ALB

PHL

DFW LA

XM

SY STL

PIT

BWI

ON

TM

IA

Mea

n

YVR

=1.0

YYZ asked us not to include it in efficiency analysis.


Residual (Net) Variable Factor Productivity: Overall Efficiency Measure –Asia Pacific

18

Figure S-4c Residual Variable Factor Productivity (2006) - Asia PacificHKG=1.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

BNE

SYD

AKL

MEL

CH

C

ADL

PER

CN

S

WLG

Mea

n

HKG SI

N

ICN

AOT

CAN HAK

PEK

XMN

MFM

MAH

B

KIX

SZX

NR

T

AAI

PVG

Mea

n

HKG

=1.0


Residual (Net) Variable Factor Productivity: Overall Efficiency Measure – Europe

Figure S-4b Residual Variable Factor Productivity (2006)- EuropeCPH=1.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

CPH

OSL

AMS

GVA AT

HBR

UIS

TM

LAZR

HST

ND

US

EDI

BHX

FCO

HAM

MAN

LGW

WAW VI

ER

IXLH

RPR

GC

GN

MU

CM

ean

Schi

phol

ANA

ADR

Berli

nD

AAAD

PFi

navi

aBA

ALF

VPP

LAE

NA

Frap

ort

Mea

n

CPH

= 1.

0


Global Comparison – Net VFP

Figure S-4, Residual Variable Factor Productivity (2006)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

North America

EuropeAsia Pacific


Cost Competitiveness –North America (= net VFP + input price effect)

21

Figure 5.4a Cost Competitiveness 2006 - North AmericaYVR=0.0

ATL

RD

UTP

AR

ICM

CO

CLT

HN

LPB

ISA

TR

NO

MSP

LAS

FLL

BNA

SDF

ABQ

YVR

JAX

YYC

MKE

IND

PDX

AUS

MC

ISL

CSN

APH

XSM

FD

CA

MSY

YUL

YOW

MEM IAH

OAK

ALB

SEA

CLE

CVG

BOS

SAN

DTW ST

LD

ENO

RD

PHL

YEG

YHZ

SJC

PIT

MD

WIA

DD

FW LAX

BWI

YWG

ON

TSF

OLG

AM

IAJF

KEW

RM

ean

-1.000

-0.800

-0.600

-0.400

-0.200

0.000

0.200

0.400

0.600

0.800

YYZ asked not to be included in the analysis.


Cost Competitiveness–Asia Pacific (= Net VFP plus Input Price (how low input prices are)

22

Figure 5.4c Cost Competitiveness (2006) - Asia PacificHKG=0.0

BN

E

AK

L

SY

D

CH

C

ME

L

CN

S

ADL

WLG

PE

R

mea

n

HA

K

XMN

AO

T

PEK

CAN

SZX

MA

HB

HKG

PVG

ICN

SIN

MFM

KIX

NR

T

mea

n

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6


Cost Competitiveness –Europe (= Net VFP plus Input Price (how low input prices are)

23

Figure 5.4b Cost Competitiveness 2006 - EuropeCPH =0.0

MLA

ATH

RIX

IST

PRG

CPH

AMS

FCO

EDI

BR

UO

SL

DU

SM

ANLG

WG

VA

WAW

BH

XV

IELH

RZR

HC

GN

MU

CH

AM

mea

n

PPL

AN

AS

chip

hol

ADR

Ber

linB

AA

Fina

via

DA

AA

DP

Frap

ort

LFV

AE

NA

Mea

n

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3


Top PerformersTop Operating Efficiency Performers based on Net

VFP (Labor + Soft cost inputs only):Canada/US: Atlanta, Raleigh-Durham, Minneapolis Europe: Copenhagen, Oslo, AmsterdamAsia-Pacific: Hong Kong, Singapore, Seoul-Incheon Oceania: Brisbane, Sydney, Auckland

Top Performers Based on Unit Cost Competitiveness IndexCanada/US: Atlanta, Tampa, Raleigh-Durham, Europe: Riga, Athens, Malta, IstanbulAsia: Haikou, Xiamen, AOTOceania: Brisbane, Auckland


OutlineObjective of the Benchmarking StudyAirports IncludedMethodologyKey Results on Efficiency and Costs2007-Airport User Charges ComparisonConclusions


Figure S-8b Landing Charges for Airbus 320, 2007North America

0

500

1000

1500

2000

2500

ATL

CLT

SLC

TPA

FLL

PBI

SAT

RIC

LAS

MC

IM

EMR

DU

SDF

OAK

SNA

SJC

PHL

MD

WR

NO

HN

LAL

BM

CO

IND

ABQ

CVG SA

NIA

DYV

R*

MSP

DC

API

TD

TW SEA

YYC

*D

ENLA

XYO

W*

MIA

PDX

YHZ*

AUS

YEG

*YW

G*

IAH

OR

DSF

OYU

L*YM

X*BO

SD

FW STL

JFK*

EWR

*LG

AYY

Z*

US$


Figure S-8b Landing Charges for Airbus 320, 2007Asia Pacific

0

200

400

600

800

1000

1200

1400

1600

1800KU

LD

XBC

NX

CEI

HD

YH

KTBK

KAD

LC

GK

MAA DEL

BOM

MN

LSI

NC

NS

TPE

SEL

ICN

HKG

MFM PE

RPE

KPV

GC

ANXM

NSH

AH

AK SZX

NR

TKI

XW

LG

US$


Figure S-8b Landing Charges for Airbus 320, 2007Europe

0200400600800

10001200140016001800

TXL

FRA

LGW

-off-

peak

STN

-off

peak

MU

CM

LAG

VA FCO

MXP CIA LIS

ZRH

STN

-pea

kAR

ND

US

HEL

HAM KE

FC

DG

OR

YM

AN-o

ffpea

kPR

GVI

EED

IIS

TM

AD BCN

KBP

ATH

RIX

SOF

AMS

LGW

-pea

kC

PHD

UB

BUD

CG

NM

AN-p

eak

LHR

TLL

WAW OSL

BTS

LJU

BHX

BRU

US$


2007: A320 Landing Fees – Global Comparison

NRTKIX

Figure S-8b Landing Charges for Airbus 320, 2007

0

500

1000

1500

2000

2500

US$

EuropeNorth AmericaAsia Pacific


Figure S-8a Landing Charges for Boeing 747, 2007North America

0

2000

4000

6000

8000

10000

12000

14000

US$


© Air Transport Research Society (ATRS)

Figure S-8a Landing Charges for Boeing 747, 2007Asia Pacific

010002000

3000400050006000

70008000

US$


Figure S-8a Landing Charges for Boeing 747, 2007Europe

010002000300040005000600070008000

US$

Global Comparison: 2007 B747 Landing fee

NRTKIX

Figure S-8a Landing Charges for Boeing 747, 2007

0

2000

4000

6000

8000

10000

12000

14000

US$

Europe


Summary – Landing/Takeoff Charges

Global Results: Airports charging highest aircraft movement charges:– Boeing 747: Toronto, Kansai, Birmingham– Airbus 320: Toronto, Brussels, Wellington

North American Results (both B747 and A320):– Highest charges: Toronto, LaGuardia, Newark,

JFK– Lowest aircraft movement charges: Atlanta,

Charlotte, Tampa, Salt Lake City


Summary – Landing Charges (cont’d)

Asia-Pacific Results:– Highest charges for B747: Kansai, Narita,

major Chinese airports, Incheon; – Highest charges for A320: Kansai, Narita,

Wellington, Major Chinese airports

– Lowest charges: Kuala Lumpur, Thailand airports; Dubai; Adelaide, Jakarta Soekarno-Hatta, Singapore


Summary – Landing Charges (cont’d)

European Results:– Highest charges for B747: Brimingham;

Ljubljana, Bratislava, Tallinn, Warsaw– Highest charges for A320: Brussels,

Ljubljana, Bratislava, Warsaw

– Lowest charge for B747: Gatwick-offpeak; Manchester-offpeak; Stansted; Berlin Tegal;

– Lowest charges for A320: Berlin Tegal, Frankfurt, Gatwick-offpeak, Stansted Off Peak,


OutlineObjective of the Benchmarking StudyAirports IncludedMethodologyKey Results on Efficiency and CostsAirport User Charge ComparisonsEffects of Business Strategies and

Ownership Forms


Results on Business StrategiesDiversification of Revenue Source is good:– Airports with larger share of non-aeronautical

revenue achieves higher Net VFP (efficiency)

Outsourcing:– Airports who contract out their terminal

operations to outside operator achieve higher efficiency

– Outsourcing entire terminal operations to expert firms improve efficiency


Empirical Results on Ownership Forms

Majority private sector ownership is bestPPP with with a government majority is worse than even 100% government owned arm length corporation.On Average, Independent Airport Authorityare better performer than City Owned AirportsU.S. airports operated by port authorities are worst efficiency performers.Cities with multiple airports (e.g. New York):Privatization of one or more airports would improve the efficiency of all airports


Please Note

The ATRS Global Airport Performance Benchmarking Report : 3 volumes, over 400 pages with valuable data and analysisCan be purchased by visiting

www.atrsworld.org


Thank You

prof. tae h. oum - welcome to the atrs homepage atrs 2008 24 july (2).pdf · ©air transport...

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