Air Transport Research Society Key Results of the 2007 ATRS Global Airport Benchmarking Report Prof. Tae H. Oum Sauder School of Business, University of

Air Transport Research Society

Key Results of the 2007 ATRS Global Airport Benchmarking Report

Prof. Tae H. OumSauder School of Business, University of British Columbia

And The Air Transport Research Society (ATRS)

www.atrsworld.org

The ATRS Global Airport Benchmarking Task Force Asia Pacific: Peter Forsyth, Japhet Law, Yeong-Heok Lee, Jia Yan

Yuichiro YoshidaEurope: Jaap de Wit, Nicole Adler, Hans-Martin Niemeier, Eric Pels North America: David Gillen, Tae Oum, Bijan Vasigh, Chunyan Yu

http://www.atrsworld.org/


2

Outline

Objective of the Benchmarking Study Methodology Key Results on Efficiency and Costs Airport User Charge Comparisons Effects of Business Strategies and

Ownership forms Conclusions


3

Objective of the Study

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


4

Objective of the Study – Cont’d

Identify effects of – Business environment within which an airport

operates– Ownership and Institutional forms– Extent of focus on non-aviation (commercial)

activities– Extent of outsourcing

On productivity, unit cost, financial performance, and Airport User Charges


5

Many Previous Studies have one or more of

the following shortcomings Limited to analysis of airports in a certain country

or continent. Used less than comprehensive measures; Ignored Multiple Outputs/Services –especially

ignoring Non-Aeronautical Services (Commercial; Development, etc)

Ignored so-called soft-cost inputs including outsourcing services

Did not control for the factors beyond managerial control


6

Airports Included in the 2007 Report*

Canada-U.S. 63 airportsEurope 43 airports and

10 airport groups

Asia 27 airports and 5 airport groupsAustralia and NZ 9 airports-------------------------------------------------------------Total 142 airports and

14 airport groups

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


7

Data Sources: 2001-05

Airport’s Annual Reports, Financial Statements, and direct data requests;

US FAA, DOT statistics; Association of European Airlines (AEA) Statistics ICAO Digest of Statistics:

– annual and monthly traffic data– annual financial data -- not for all airports

ACI; IATA– annual traffic statistics; Capacity information– 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


8

Characteristicsof

Sample Airports

Passenger volumes – N. America Figure 3.4.1a: Passenger Traffic (2002/05) - North America

0

10

20

30

40

50

60

70

80

90

100

AT

LO

RD

LAX

DF

WD

EN

LAS

JFK

PH

XIA

HM

SP

DT

WM

CO

SF

OE

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PH

LM

IAY

YZ

SE

AC

LT IAD

BO

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NL

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AM

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DC

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AN

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NA

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UB

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SA

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KE

ON

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NO

YE

GY

OW

SD

FY

HZ

YW

GA

LB RIC

Mea

n

Mill

ion

s

2005 2002

Passenger Volumes - Europe

Figure 3.4.1b: Passenger Traffic (2002/04/05) - Europe

0

10

20

30

40

50

60

70

80

LHR

CD

GF

RA

AM

SM

AD

LGW

FC

O

MU

CB

CN

OR

YS

TN

MA

NC

PH

MX

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TD

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BR

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GV

AE

DI

WA

W CIA

MLA RIX

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EF

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BT

SLJ

UM

ean

Mill

ion

s

2005 2004 2002

Passenger Volumes : Asia-Pacific

3.4.1c: Passenger Traffic (2002/04/05) - Asia Pacific

0

5

10

15

20

25

30

35

40

45

PE

KB

KK

HK

GS

INN

RT

SY

DC

GK

ICN

DX

BC

AN

PV

GK

UL

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AS

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HC

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LG

MF

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HK

TC

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NH

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a

Mil

lio

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2005 2004 2002

Concession Revenue Shares – N. America

Concession Revenue Share (2005) - North America

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

LAS

FLL

MCO

TPA

ABQ

PHX

SJC

YEG

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PHL

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DEN

MCI

PIT

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OAK

PDX

BOS

MEM

DFW

LGA

EWR

IAH

YYZ

JFK

NA-

Concession Revenue Shares – Europe

Concession Revenue Share (2005) - Europe

0%

10%

20%

30%

40%

50%

60%

70%

SOF

STN

GVA

CPH

LGW

DUS

HAM

EDI

MAN

ATH

LHR

AMS

ZRH

BRU

MLA

TLL

ARN

VIE

Mean DAA

BAA

CAA(

FIN) ADR

ANA

ADP

Frap

ort

Mean

(gr

oup)

Concession Revenue Shares – Asia-Pac

Concession Revenue Share (2005) - Asia Pacific

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

CHC

MEL

AKL

WLG

SYD

ADL

PER

BNE

CNS

Mean SIN

SEL

HKG

ICN

NRT

AOT

TPE

MAHB MFM

PEK

CAN

HAK

Mean

Share of Non-Aeronautical Revenue

YYZ

Figure S-5: Non-Aeronautical Revenue Share (2005)

0%

10%

20%

30%

40%

50%

60%

70%

80%

TP

AR

DU

FLL

MC

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TM

FM

NR

TM

AH

BP

TII

SA

A

North America

Europe

Asia Pacific

International Passenger Share

N. America

Europe

Asia-Pac

Share of International Passengers (2005)

0%

20%

40%

60%

80%

100%

120%

YUL

YYZ

YVR

MIA

JFK

EWR

LAX

YYC

YOW

SFO

HNL

IAD

IAH

YHZ

YEG

YWG

BOS

ORD PH

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WFL

LSE

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MSY IN

DAU

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WA

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UC ARN

ATH

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CPE

KBN

EPV

GCG

KM

ELXM

NW

LG HDY

CNX

SEL

CAN

ADL

HAK

SHA

SZX

CEI

North America

Europe

Asia Pacific


17

Airport Productivity

Outputs Inputs

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

including concessions

• Labour

• Other non-capital (soft cost) inputs

• Runways

• Terminals

• Gates


18

Methodology for productivity

MEASUREMENT Partial Factor Productivity (PFP) Measures:

– Labor Productivity– Capital Input Productivity - capital input accounting problem– Productivity of Soft Cost InputsPFP does not tell the whole story

Need to go beyond PFPs

Variable Factor Productivity (VFP)Total Factor Productivity (TFP: capital input

accounting problem) Unit Cost Competitiveness


19

Methodology for productivity MEASUREMENT – cont’d

Multiple Outputs:Aircraft movements, passengers, Cargo Tonnes, and non-

aeronautical services output

The first step for computing any productivity is to aggregate these multiple outputs into a single output index

Similarly, airports use multiple inputs which need to be aggregated into a single input index.


20

Efficiency Measurement Method:Our Choice

Index number approach:

Productivity = Output Index / Input Index

VFP = Output Index / Variable Input Index

Variable Factor Productivity– Revenue shares use as weights for output

aggregation– Cost shares are used as weights for input

aggregation.


21

Potential Reasons for the Measured Productivity (gross VFP) Differentials

(A) 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 the Factors Beyond Managerial Control (A)

(B) Factors within Managerial Control:– Emphasis on commercial activities (non-aeronautical)– Quality of Service (incl. passenger satisfaction)– The Extent of outsourcing activities– Managerial and technical efficiency (which we are trying to measure)


22

Results on Effects of Airport Characteristics on ‘gross’ VFP

(Airport size: some mixed results on the effects of airport output scale: larger airports are expected to have higher ‘gross’ VFP, however, the effects may level off once airports reach certain size);

%International: airports with higher proportion of international passengers are likely to have lower ‘gross’ VFP.

%Cargo: airports with larger proportion of cargo traffic are expected to have higher VFP.

Capacity Constraints: congested airports are likely to have higher ‘gross’ VFP.

These factors beyond airport’s managerial control have been removed from our VFP measure before computing the ‘residual VFP’.

Residual (Net) Variable Factor Productivity: Overall operating efficiency measure – Asia-Pacific

Figure S-4c Residual Variable Factor Productivity (2005) - Asia PacificHKG=1.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

SY

D

BN

E

AD

L

ME

L

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PE

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CN

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MA

HB

KIX

PE

K

SA

A

NR

T

Me

an

HK

G=

1.0

Residual (Net) Variable Factor Productivity: Overall operating efficiency measure - Europe

Figure S-4b Residual Variable Factor Productivity (2005)- EuropeCPH=1.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

OS

LA

TH

GV

AB

RU

ZR

HC

PH

BH

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AD

PL

FV

BA

AF

RA

PP

LD

AA

Be

rlin

Me

an

(g

rou

p)

CPH

= 1.

0

Residual (Net) VFP: Overall operating efficiency measure – North America

Figure S-4a, Residual Variable Factor Productivity (2005), North AmericaYVR = 1.0

0.0

0.5

1.0

1.5

2.0

2.5

AT

LR

DU

TP

AM

CO

FLL

MS

PLA

SY

VR

CLT

BN

AY

OW

YU

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BQ

RN

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WI

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ITY

YZ

MIA

EW

RO

NT

JFK

SA

T

YV

R=

1.0

Global Comparison – Net VFP

Figure S-4, Residual Variable Factor Productivity (2005)

0.0

0.5

1.0

1.5

2.0

2.5

AT

LR

DU

TP

AM

CO

FLL

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North America

Europe


27

Cost Competitivenessconsists of:

Productive Efficiency – Residual (Net) VFP

Input Prices:– Labor price– Soft cost input price (incl. outsourcing

price)

Figure 5.4a Cost Competitiveness 2005 - North AmericaYVR=0.0

AT

LR

DU

TP

AF

LLM

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ean

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

Figure 5.4b Cost Competitiveness 2005 - EuropeCPH =0.0

AT

H

TL

L

SO

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-0.4

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0.2

0.4

0.6

0.8

Figure 5.4c Cost Competitiveness (2005) - Asia PacificHKG=0.0

WL

G

AD

L

CN

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BN

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CH

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-1

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-0.4

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0

0.2

0.4

0.6

0.8


31

Top PerformersTop Operating Efficiency Performers based on Net

VFP (Labor + Soft cost inputs only): Canada/US: Atlanta, Raleigh-Durham , Tampa, Europe: Oslo, Athens, Geneva Asia: Hong Kong, Singapore Oceania: Sydney, Brisbane

Top Performers Based on Unit Cost Competitiveness Index

Canada/US: Atlanta, Raleigh-Durham, Tampa Europe: Athens, Tallinn, Sofia Asia: Guangzhou, Shenzhen, AOT, Oceania: Wellington, Adelaide


32

Outline

Objective of the Benchmarking Study Airports Included Methodology Key Results on Efficiency and Costs Airport User Charges

Comparison Conclusions

Landing Charges for Boeing 747 - North America 2005

0

2000

4000

6000

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Landing Charges for B747 - Europe2005

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$2,000

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Landing Charges for B747 - Asia Pacific2005

$0

$1,000

$2,000

$3,000

$4,000

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Air Transport Research Society (ATRS)

B747 Landing fee -2005

Figure S-8a Landing Charges for Boeing 747, 2005

0

2000

4000

6000

8000

10000

12000

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$8,000

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AKL

HKG IC

NPE

KPV

GSH

AC

AN SZX

NR

TKI

X

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

KUL

HKT

CN

XBK

KH

DY

DXB AD

LC

GK

SIN

MAA DEL

BOM

MN

LC

NS

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BNE

MFM AK

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NPE

R

HKG SH

AC

AN PVG

SZX

PEK

CH

CN

RT

KIX

North AmericaEurope

Asia Pacific

NRTKIX

Landing Charges for Airbus 320 - North America2005

0

500

1000

1500

2000

2500

BNA

ATL

CLT

SLC

TPA

RD

UFL

LM

SY SAT

PHX

RIC

LAS PB

IM

CO

OAK SD

FSJ

CM

DW

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NL

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SAN

BWI

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SFO

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SEA

YEG

AUS

YHZ

BOS

DTW

YVR IAH

DEN ST

LD

FW JFK

EWR

LGA

YYZ

US

$

Landing Charges for Airbus 320 - Europe2005

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

TX

LM

XP

FC

OC

IALG

W-o

ff pe

ak FR

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TN

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BR

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AN

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GM

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AN

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kV

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-pea

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SL

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BH

X

US

$

Landing Charges for Airbus 320 - Asia Pacific2005

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

KU

LH

KT

CN

XB

KK

HD

Y

DX

BA

DL

CG

K

SIN

MA

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EL

BO

MM

NL

CN

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ICN

PE

R

HK

GS

HA

CA

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PE

KC

HC

NR

TK

IX

US

$

A320 Landing Fees - Global

Figure S-8b, Landing Charges for Airbus 320, 2005

0

500

1000

1500

2000

2500

BN

AA

TL

CLT

SLC

TP

AR

DU

FLL

MS

YS

AT

PH

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SP

BI

MC

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NP

ER

H

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KC

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US

$

Landing Charges for B747 - Europe

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

LGW

-off

peak

Man

-Off

TX

LLG

W-P

eak

ST

NLH

R-o

ff pe

akM

XP

FC

OC

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RU

DU

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AT

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VA

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RH

IST

Man

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EL

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DI

MA

DB

CN

OS

LC

DG

OR

YC

PH

MB

XD

UB

WA

WT

LLB

TS

AM

SLJ

UB

HX

US

$

Landing Charges for Airbus 320 - Europe

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

TX

LM

XP

FC

OC

IALG

W-o

ff pe

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RA

MLA

OR

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ST

N LIS

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AN

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WA

WA

TH

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R-p

eak

OS

LLJ

UB

HX

US

$

North America Europe Asia Pacific

NRTKIX

Ave. Terminal Fee per Pax – N.America- 2005

Average Terminal Fee per Passenger - North American

0

1

2

3

4

5

6

AT

LC

LTM

KE

DF

WC

VG

MC

IM

DW

DT

WM

SP

SLC

SM

FR

NO

FLL

LAX

RD

UB

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SA

NS

AT

JAX

OR

DY

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PH

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ME

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MS

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GH

NL

PB

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AB

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UL

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CLE

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AY

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BO

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VR

PH

LY

OW

IAD

JFK

SE

AO

NT

DC

AY

YZ PIT

PD

XE

WR

DE

NS

FO

MIA

US

$


42

User Charge vs. Service Quality Trade Off

Airport should be run as efficiently as possible But when it comes to

User Charge vs. Service Quality trade-off ?

Go for providing high service quality to airlines and passenger even if you raise user charges


43

Summary – Landing/Takeoff Charges

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

North American Results (both B747 and A320):– Highest charges: Toronto, LaGuardia, Newark, JFK– Lowest aircraft movement charges: Nashville,

Atlanta, Charlotte, Tampa, Salt Lake City


44

Summary – Landing Charges (cont’d)

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

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

Chrischurch, Major Chinese airports, Hong Kong

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


45

Summary – Landing Charges (cont’d)

European Results:– Highest charges for B747: Brimingham; Amsterdam,

Bratislava, Tallinn, Warsaw– Highest charges for A320: Ljubljana, Oslo, Heathrow-

Peak, Vienna

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

– Lowest charges for A320: Berlin Tegal, Milan Malpensa, Rome Fiumicino, Rome Ciampino, Gatwick-offpeak, Frankfurt, Malta


46

Outline

Objective of the Benchmarking Study Airports Included Methodology Key Results on Efficiency and Costs Airport User Charge Comparisons Effects of Business Strategies and

Ownership Forms Conclusions


47

Results on Business Strategies Diversification 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


48

Effects of Ownership and Institutional

Forms of Airport Organization

Method: Advanced econometric work: translog stochastic cost frontier method which allows for individual heterogeneity in the cost frontiers

Alternative methods: Residual VFP, DEA, conventional SFM, etc.


49

Empirical Results on Ownership Forms

Cost Efficiency Ranking: 1. Airports with private majority ownership (>50%);

BAA, Australia, some NZ, Copenhagen, Rome, etc. 2. U.S. & Canadian Airport Authority 3. 100% Public Corporation (Crown Corp.) 4. U.S. City Run Airports 5. Mixed enterprise with government majority ownership 6. Airports with shared multiple govt ownership 7. U.S. Port Authority run Airports – the least efficient

form (3 NY-NJ; Boston; Seattle; Portland; Oakland) Airports with private majority ownership achieves

highest profit margin, and pays employees well


Thank You


51

Please Note

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

www.atrsworld.org

2008 ATRS World Conference: July 6-9, 2008 to be hosted by Hellenic Aviation Society, Athens, Greece

Documents

Air Transport Research Society Key Results of the 2007 ATRS Global Airport Benchmarking Report Prof. Tae H. Oum Sauder School of Business, University of