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Key Findings of 2012 ATRS Global Airport Performance Benchmarking project

ww.atrsworld.org

© Air Transport Research Society (ATRS)

Prof. Tae Hoon Oum, Sauder School of Business, University of British Columbia, CanadaDr. Yapyin Choo, The Air Transport Research Society (ATRS),Prof. Chunyan Yu, Embry Riddle Aeronautical University, Daytona Beach, FL, USA)

ATRS Global Airport Benchmarking Task Force Asia Pacific: P. Forsyth, Xiaowen Fu, Yeong-Heok Lee, Yuichiro Yoshida, Japhet Law, Shinya HanaokaEurope: Nicole Adler, Jaap de Wit, Hans-Martin Niemeier, Eric PelsNorth America: Tae Oum, Bijan Vasigh, Jia Yan, Chunyan Yu Middle East: Paul Hooper

http://www.atrsworld.org/

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© Air Transport Research Society (ATRS) 2

Objective of the Benchmarking Study

To provide a comprehensive, unbiased comparison of airport performance focusing on Productivity and Operating/Mgt Efficiency Unit Cost Competitiveness Comparison of User Charge Levels

Our study does not treat service quality differentials across airports

© Air Transport Research Society (ATRS) 3

Airports Included in the 2012 Report


Canada-US 77 airports

Europe 55 airports16 airport groups

Asia Pacific 9 airport groups 35 Asian airports16 Oceania airports

----------------------------------------------------------Total 183 airports

25 airport groups

ATRS Airport Database, 2001-2010 The ATRS Database contains historic information (since FY 2001) including

financial data, traffic and capacity data of the major airports and airport authorities (groups) in the following geographic regions:

Asia Pacific including Oceania; Europe; North America Limited data on S. America and Africa

The data in each regions is segregated into:

Traffic statistics and composition Airport characteristics (capacity, type of

ownership etc) Aeronautical Activities and Revenue Non-Aeronautical Activities and Revenue Labor and other Operating Expenses

5

Outline




Methodology



Passengers Traffic, FY2010 (in ’000 passengers)


0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

PEK

HN

DH

KG DXB

CGK

SIN

BKK

CAN

PVG

SYD

KUL

ICN

NRT

SHA

DEL

BOM

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MEL TP

EM

NL

BNE

GM

PKI

XAK

LXM

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BM

AA PER

NG

OH

AK ADL

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MFM CN

SCN

XG

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PNH

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HDY

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DUD

CEI

LHR

CDG

FRA

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AMS

FCO

MU

CIS

TLG

WBC

NO

RYZR

HCP

H VIE

OSL

DUS

MXP STN

DUB

MAN BRU

ARN

ATH TXL

LIS

HAM HEL TL

VG

VA ISG

CGN

NCE

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WAW ED

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DN

AP HAJ

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TLL

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ORD LA

XDF

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N JFK

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LAS

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PHX

MIA CLT

MCO

EWR

MSP

DTW YY

ZSE

APH

LBO

SLG

AIA

DBW

IFL

LSL

CH

NL

DCA

MDW SA

NYV

RTP

APD

XYU

LYY

CST

LM

CIM

EM MKE

OAK CL

ERD

UBN

ASM

FSN

AH

OU

AUS

SJC

MSY PI

TSA

TCV

GDA

LIN

DRS

WCM

HYE

G PBI

ABQ JAX

BDL

ANC

ON

TYO

WBU

RPV

DRN

OTU

SYH

ZO

KCYW

GSD

FRI

CAL

BYY

JYQ

BYY

TYQ

R

Europe North AmericaAsia Pacific


Passenger Traffic (000)- Top 10 Airports:2006, 2008, 2010

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

PEK

HND

HKG

DXB

CGK

SIN

BKK

CAN

PVG

SYD

LHR

CDG

FRA

MAD

AMS

FCO

MUC IS

TLG

WBC

N

ATL

ORD LA

XDF

WDE

NJF

KIA

HLA

SSF

OPH

X

2006 2008 2010

Asia Pacific Europe North America

Aircraft Movements, 2010 (’000 ATM)


0

100

200

300

400

500

600

700

800

900

1,000

PEK

CGK

SIN

BOM

MNL AK

LM

AA PER

NAN

GUM

CMB

REP

HDY

CDG

AMS

IST

CPH

DUS

GVA

TXL

LIS

EDI

BHX

CRL

BSL

BEG

MLA LA

XLA

SCV

GYY

ZSL

CSF

ODC

AFL

LPD

XSA

NSM

FBN

ADA

LAB

QBU

RPV

DRS

WYO

W


Passengers per Aircraft Movements,2010


0

20

40

60

80

100

120

140

160

180

200


Air Cargo Traffic, 2010 (’000 metric tons)


0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500


% Non-Aero Revenue, 2010


0%

10%

20%

30%

40%

50%

60%

70%

80%

SIN

OO

L

TSV

HKG AKL

CAN

DU

D

PER

MEL

NA

N

CMB

BNE

DEL

GM

P

SYD

ICN

NG

O

WLG

CHC

HA

K

ZQN

NTL

GU

M

NRT

PVG

PEK

AD

L

CEI

BKK

HD

Y

HKT

CNX

MA

A

XMN

SZX

DRW KU

L

KIX

PEN

CGK

FRA

BSL

CDG

ORY

OSL

NCE HA

J

IST

DU

B

AM

S

TLL

CPH

CIA

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BUD

ATH TL

V

VIE

TRN

LTN

ZRH

MXP LIN

BHX

MA

N

GVA NA

P

HA

M LJU

SZG

SOF

LGW

ARN

MU

C

RIX

LHR

STN

EDI

ISG LIS

BRU

MLA

CGN

DU

S

TXL

BTS

BCN

MA

D

WA

W

HEL

BEG

JAX

OKC TPA

RIC

BUR

PHX

YYJ

MCI

BNA

MCO ATL

RNO

YEG

CMH

RDU

MSP IND

YQR

DA

L

SAT

FLL

PBI

SLC

TUS

MKE

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DFW YV

R

YWG

RSW

SNA

CLT

ALB

SAN

YQB

SMF

AU

S

ABQ SJ

C

PVD

YYT

YUL

LAS

SDF

YHZ

DCA BO

S

OA

K

HN

L

DTW

YOW

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BDL

PDX

SFO

IAD

SEA

HO

U

LAX

ON

T

DEN PI

T

BWI

CLE

MSY

MD

W

PHL

MIA YYZ

IAH

ORD

EWR

LGA

STL

MEM JF

K

AN

C

% Non-Aero Rev Mean

North AmericaEuropeAsia Pacific

Outline




Methodology



Airport Productivity Index

14

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)

Methodology: EFFICIENCY MEASUREMENT

Variable Factor Productivity (VFP) Index Impossible - Total Factor Productivity (TFP)

because of capital input cost accounting problem

Unit Operating Cost Competitiveness Index: Combines VFP and Input Price IndexWe explored Alternative approaches: Data Envelopment Analysis (DEA) Econometric Cost Function Approach including

Stochastic Frontier methodsNote: Industry acceptance of our report using more

advanced/sophiscated methods is one of our major concern 15

Multilateral Aggregation Method

• This multilateral output (input) index procedure uses the following revenue (cost) shares to aggregate output (inputs).


Outline




Methodology



Outline

Objective of the Benchmarking StudyAirports IncludedMethodologyKey Results on Efficiency and CostsAirport User Charge ComparisonsEffects of Business StrategiesConclusions

18

Gross Variable Factor Productivity (VFP)Asia (HKG=1.0), 2010


0

0.2

0.4

0.6

0.8

1

1.2

GMP

ICN

HKG

CAN

SIN CGK

HAK

GUM

XMN

PEK

CNX

HKT

HDY

PVG

BKK

SZX

NRT

DEL

KUL

PEN KIX

NGO

CMB

KAC

APII

AAI

AOT

MAH

B

Mean Mean

Airports Airport Groups

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• [2010 Iceland volcano ash cloud (For European airports)]

We compute residual (Net) variable factor productivity (RVFP) measures after removing effects of these Factors


Gross Variable Factor Productivity vs Residual VFP: Asia (HKG=1.0), 2010


0

0.2

0.4

0.6

0.8

1

1.2

Gross VFP Residual VFP

Residual (Net) Variable Factor Productivity: (after removing factors beyond managerial control ) :

Asia (HKG=1.0)


GMP

ICN

HKG

SIN

CAN

GUM

CGK

HAK

HDY

CNX

HKT

XMN

PEK

BKK

PVG

DEL

SZX

KUL

NRT

PEN

KIX

NGO

CMB

KAC

AAI

APII

AOT

MAH

B

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Residual VFP Mean

Airport GroupsAirports

Gimpo, Incheon, Hong Kong

Residual (Net) Variable Factor ProductivityOceania (SYD=1.0)


SYD

ZQN

DUD

MEL

DRW

AKL

BNE

CHC

PER

NTL

NAN

ADL

WLG

APAC

QAL

ADG

0

0.2

0.4

0.6

0.8

1

1.2

SYD ZQN DUD MEL DRW AKL BNE CHC PER NTL NAN ADL WLG APAC QAL ADG

Residual VFP Mean

Airport Groups

Airports Sydney, Queenstown

Residual (Net) Variable Factor Productivity: Europe – Passengers > 15 million ( CPH=1.0)


CPH

OSL

ZRH

ATH

IST

BRU

CDG

AMS

MAD

FCO

BCN

ARN

STN

DUB

MAN

LGW

ORY

MXP

VIE

MU

CLH

RFR

ADU

S

Schi

phol

ANA

ADR

Avin

orSw

edav

iaBA

ADA

AAD

PM

AGAE

NA

Fina

via

Frap

ort

SEA

Berli

nTA

V

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Residual VFP Mean

AirportGroups

Airports

Copenhagen, Oslo, Zurich

Net Variable Factor Productivity: Europe – Passengers < 15 million ( CPH=1.0)


GVA

NCE

EDI

LIS

CIA

BHX

BSL

HAJ

LTN

ISG

TLL

LJU

NAP

TLV

TRN

MLA

RIX

SZG

BUD

HEL

HAM

TXL

WAW

LIN

SOF

BTS

CGN

BEG

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Residual VFP Mean

Geneva, Nice, Edinburgh

Net Variable Factor Productivity: N. America – Passengers > 15 million (YVR=1.0)


ATL

CLT

MSP

YVR

MCO

TPA

PHX

FLL

SFO

HNL

SEA

LGA

SLC

BOS

JFK

MDW

EWR

PHL

DTW

SAN

LAS

DCA

IAD

IAH

DFW

BWI

ORD

MIA

LAX

DEN

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Residual VFP Mean

Atlanta, Charlotte, Minneapolis/St Paul

Residual (Net) Variable Factor Productivity: N. America – Passengers < 15 million (YVR=1.0)


RDU

RIC

OKC

RNO

YYC

BNA

JAX

SNA

PBI

YEG

YQR

TUS

MKE

DAL

PDX

YYJ

YOW

IND

YYT

PVD

RSW

ABQ

CMH

MEM

OAK

SMF

YWG

MSY

SJC

YHZ

SAT

MCI

AUS

ALB

BUR

CVG

YUL

ANC

SDF

HOU

ON

TPI

TCL

EST

LYQ

B

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Residual VFP Mean

Raleigh-Durham, Richmond, Oklahoma City

Top Efficiency Performers (2012)(based on Net VFP index=operating/management efficiency)

• Asian Airports:• Gimpo, Incheon, Hong Kong

• Oceania Airports:• Sydney, Queenstown

Asia Pacific:

• Large Airports (> 15 million pax):• Copenhagen, Oslo, Zurich

• Small/Medium Airports (< 15 millions Pax):• Geneva, Nice, Edinburgh

Europe:

• Large Airports (> 15 million pax):• Atlanta, Charlotte, Minneapolis/St Paul

• Small/Medium Airports (< 15 millions Pax):• Raleigh-Durham, Richmond, Oklahoma City

North America (Canada/US):




Asian Airport Category:

Gimpo International Airport

Runner up: Incheon International Airport

GMP Mean

Labour Productivity (HKG=1.0) 0.538 0.343

Soft Cost Productivity (HKG=1.0) 1.240 0.963

Residual VFP (HKG=1.0) 1.133 0.631



Oceania Airport Category:

Sydney Airport

Runner up: Queenstown Airport

SYD Mean

Labour Productivity 1.000 0.548

Soft Cost Productivity 1.000 0.684

Residual VFP 1.000 0.695



Europe Large Airports (> 15 million pax) Category:

Copenhagen Airport Kastrup

Runner up: Oslo Airport

CPH Mean

Labour Productivity 1.000 1.263

Soft Cost Productivity 1.000 0.439

Residual VFP 1.000 0.660



Europe Small/Medium Airports (< 15 million pax) Category:

Genève Aéroport

Runner up: Nice Cote D’Azur Airport

GVA Mean

Labour Productivity (CPH=1.0) 1.375 1.263

Soft Cost Productivity (CPH=1.0) 0.580 0.439

Residual VFP (CPH=1.0) 0.844 0.541



N. America Large Airports (> 15 million pax) Category:

Hartsfield-Jackson Atlanta International Airport

Runner up: Charlotte Douglas International Airport

ATL Mean

Labour Productivity (YVR=1.0) 1.546 0.553

Soft Cost Productivity(YVR=1.0) 1.481 0.875

Residual VFP (YVR=1.0) 1.251 0.712

Past Airport Efficiency Excellence Top Performers, 2007 - 2011

North America

Europe

Asia-Pacific

2007

Hartsfield-Jackson Atlanta International

Airport

Oslo Airport

Hong Kong International Airport

2008


Airport

Copenhagen KastrupInternational Airport


2009


Airport

Copenhagen KastrupInternational Airport


2010


Airport

Large Airport Category: Oslo International

AirportSmall/Medium Airport

Category:Geneva Cointrin

International Airport

Large Airport Category:Hong Kong International

AirportSmall/Medium Airport

Category:Seoul Gimpo

International Airport

2011


Airport

Large Airport Category: Oslo International

AirportCopenhagen KastrupInternational AirportSmall/Medium Airport

Category:Genève Aéroport

Asian Airport Excellence Award:


Oceania Excellence Award:

Sydney Airport


Cost Competitiveness: = Net VFP and Input Price Effect Asia (HKG=0.0) – the higher the better

CGK

HAK

XMN

GMP

DEL

HDY

CNX

HKG

CAN

HKT

CMB

ICN

PEK

PVG

SZX

BKK

PEN

KUL

SIN

GUM

NGO

NRT KIX

AAI

APII

KAC

AOT

MAH

B

-1.6

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

Cost Competitiveness Mean

Airport GroupsAirports

Airports Authority of India, Jakarta Soekarno-Hatta


Cost Competitiveness = Net VFP and Input Prices EffectEurope – Passengers > 15 million (CPH=0.0)

IST

ATH

CPH

MAN

BRU

FCO

STN

AMS

LGW

ARN

ZRH

OSL

MXP

DUB

FRA

VIE

LHR

DUS

ORY

MU

CCD

GBC

NM

AD

ANA

MAG

ADR

Schi

phol

Frap

ort

TAV

Swed

avia

BAA

DAA

SEA

AEN

AAD

PBe

rlin

Fina

via

Avin

or

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4


Istanbul Ataturk, Athens


Cost Competitiveness = Net VFP and Input Prices EffectEurope – Passengers < 15 million (CPH=0.0)

TLL

RIX

SOF

BSL

LJU

BUD

LIS

BTS

BHX

BEG

EDI

LTN

WAW ISG

CIA

NCE

HAJ

NAP

MLA

TRN

HAM

TLV

SZG

LIN

TXL

HEL

CGN

GVA

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3


Tallinn, Riga


Cost Competitiveness = Net VFP and Input Price Effect N. America – Passengers > 15 million (YVR=0.0)

CLT

ATL

TPA

MCO

MSP

PHX

FLL

SLC

YVR

IAH

LAS

DFW

SEA

DTW

HNL

BWI

DCA

SAN

MDW ORD

DEN

PHL

IAD

BOS

LAX

SFO

MIA

EWR

JFK

LGA

-2

-1.5

-1

-0.5

0

0.5

1


Charlotte, Atlanta

Outline




Methodology



Landing Charges for Boeing 767-400, 2011 (in US$)

© Air Transport Research Society (ATRS)40

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

KUL

GU

MD

XBCM

BSU

BBK

KCE

ICN

XH

DY

HKT

CGK

MN

LPN

HRE

PBO

MD

ELM

AA

CAN

HA

KPE

KPV

GSH

ASZ

XXM

NTP

ED

UD

MFM IC

NG

MP

HKG

ZQN

PER

SIN

NA

NW

LG AKL

NTL

TSV

OO

LN

TL-N

ight

SYD

NG

ON

RTD

RW KIX

HN

D

DU

SST

N-o

ff pe

akA

RN LTN

BRU

STN

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kM

LALG

W-o

ff-pe

ak FRA

BSL-

FR s

ecto

rRI

XTR

NM

UC

FCO

NA

PM

XP LUX

LIN

CIA LIS

BSL-

CH s

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TV

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AM

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AKE

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kM

AN

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eak

TXL

SOF-

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eak

HEL

CPH

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NCE

CGN

SOF-

peak

ZRH

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DH

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BUD

TLL

CDG

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BCN

TLV

ATH

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SLH

RW

AW

BHX

ZAG

LGW

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kBT

SLJ

USZ

GD

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CLT

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ABQ

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TSJ

CLA

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LB IAH

OKC

RSW

RNO

SEA

OA

KYV

RA

US

PDX

MD

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DCA BD

LCL

EYQ

RD

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GD

FWYO

WPV

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TW HN

LYE

GSM

FPI

TCM

HBW

ILA

XYH

ZYY

CYW

GBO

SO

RD YUL

SFO

JFK

Off

Peak

JFK

Peak

YQB

STL

EWR

Off

Peak

EWR

Peak

LGA

Off

Peak

LGA

Pea

kYY

Z

US$

Landing Charges for Boeing 767 Mean

Asia Pacific Europe

North America

Asia Pacific: Combined Landing and Passenger Charge for Boeing 767, 2011 (in US$)


KUL-

LCCT

DUD

TPE HK

GBO

MDE

LM

AA GUM SIN

-LCC

TKU

L CMB

MN

LM

FM CAN

HAK

PEK

PVG

SHA

SZX

XMN

SIN SU

BGM

PCG

KPE

RZQ

NDX

BIC

N ADL

WLG CE

ICN

XHD

YHK

TBK

KM

EL TSV PN

HRE

P NTL OO

LDR

WN

TL-N

ight

CNS

SYD BN

E BNE-

PEAK

NRT

-1N

NRT

-1S

NRT

-2N

GO HND

AKL

KIX

NAN

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

US$

Combined Landing and Passenger Charges for Boeing 767 Mean

Lowest charges: Kuala Lumpur Low Cost Carrier Terminal, Dunedin (New Zealand)Highest charges: Nadi (Fiji), Kansai

Europe: Combined Landing and Passenger Charge for Boeing 767, 2011 (in US$)


RIX LU

X MAN

-offp

eak

NAP CIA KEF

ARN FC

O -

T1, T

2TL

LBS

L-FR

sect

or

CGN

GVA

STN

-off

peak

MAN

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kLT

NHE

LST

N-p

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CPH

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TFC

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T1

TRN

LIN MXP NCE LG

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akCP

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L-CH

sect

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IDU

SSO

F-of

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kM

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MHA

JSO

F-pe

akM

LA LIS TX

LLJ

U VIE LED

BUD

BRU

BEG

-T1

MU

CBH

XAM

SDU

BTL

V -T

1FR

AAT

H LGW

-pea

kZA

G SZG

BEG

WAW

ZRH

BTS

ORY CD

GTL

VLH

R

0

2000

4000

6000

8000

10000

12000

14000

16000

US$

Combined Landing and Passenger Charges for Boeing 767 Mean

Lowest charges: Riga, LuxembourgHighest charges: London Heathrow, Ben Gurion (Tal Aviv)

BUR

DAL AT

LSL

C MEM

MCI

PHX

TPA

JAX

SAT

MSP

BNA

MKE

FLL

MCO

RIC

OKC RD

UDF

WSA

NSD

FRN

OTU

SCM

HPB

ILA

SAL

BRS

W HOU

CVG

AUS

BDL

DTW

ABQ

PHL

MDW AN

CO

AKBW

IM

SYSN

AHN

LLA

XIA

HPV

DIN

DSJ

CSE

A SMF

PDX

DEN

CLE

DCA

ON

TBO

SO

RD IAD

SFO

STL

LGA

MIA PI

TEW

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$US

North America: Cost per Enplaned Passenger, 2010 (in US$)


Canada:Lowest CPE: Victoria, ReginaHighest CPE: Toronto, Montreal

United States:Lowest CPE: Bob Hope, Dallas Love FieldHighest CPE: New York JFK, Newark Liberty

Effects of Business Strategies

Diversification of Revenue Source is Good– Airports with larger share of non-aeronautical

revenue achieve higher efficiency (Net VFP)

Outsourcing improves efficiency Airports contracting out various services to

outside operator achieve higher efficiency Outsourcing terminal operations improve

efficiency44

ATRS Airport Benchmarking Report The ATRS Global Airport

Performance Benchmarking Report : 3 volumes, over 600 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)45

Thank You2013 ATRS World Conference

(Bergamo, Italy in late June, 2013)

key findings of 2012 atrs global airport performance ... · pdf filekey findings of 2012 atrs...

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