Transcript Privatization, restructuring and its effects on performance: a

Capacity Measurements in Airport Sector:
Drawbacks of Conventional Methods and
Benchmarking Airports Using Declared Capacity
Tolga Ülkü
Presented in:
2008 GAP Workshop, FHW Berlin
October 10, 2008
1
Outline
• Introduction
• Literature Review on Airport Benchmarking
 Critics of Conventional Methods (inputs and outputs)
• Declared Runway Capacity
• Data and Methodology
• Empirical Analysis
 Runway Utilization – By Yearly Capacity
 Runway Utilization – By Peak Hour Capacity
 Runway Utilization – Country Comparison
 Runway Utilization – By Level of Coordination
• Conclusion
2
Introduction
• Need for benchmarking on airports
Focus on Capacity Benchmarking
• Within Capacity:
Terminal Side
Airside(RWY and Apron)
• Commonly Used Methods;
i. TFP
ii. DEA
iii. SFA
3
Literature
Main Literature on Conventional Methods
Using the DEA;
• Gillen and Lall (1997)
 Consider terminal and airside seperately
• Sarkis (2000,2004)
 Finance and labor included
• Pels et. al. (2001)
• Bazargan and Vasigh (2003)
4
Literature
Common Inputs Used in these Analyses;
•
•
•
•
•
•
•
airport area,
number of runways,
runway area,
number of gates,
number of check-in counters,
operating costs,
number of employees,
5
Literature
Common Outputs Used in these Analyses;
• passengers,
• cargo,
• ATM,
6
Critics
Of the Input-Output Combination:
1.
Runway
• Core activity
• Pure engineering
vs.
Terminal
activities
• Attractivity
• Marketing
 Employee structures differ, both quantitative and qualitative
 Different fleet mixes in different airports
7
Critics
Of the Chosen Inputs:
Number of Runways;
-
Main problems by benchmarking stem from;
•
Runway System
 Distance between two Runways
 Parallel vs. Crossing
 Length and Width
 Taxiways
•
Apron Capacity
 Number of Parking Positions (on terminal or remote)
•
Terminal Capacity
•
Fleet Mix
8
One Example
- Some Facts: Frankfurt Airport
“The new landing runway will
be some 2,800 meters long.
The centerline separation
from the existing North
runway will be approx. 1,400
meters. This will allow for
simultaneous
landing
operations on these two
runways, which are not
possible on the existing
parallel runways because
they are not far enough
apart. “
www.fraport.de
9
Declared Runway Capacity
• There is no consensus on how to define the runway capacity.
Some examples;

The number of movements which can be handled in one hour.

The maximum number of aircraft that can be handled by a facility
during a specified time period under conditions of continuous demand
regardless of delay magnitude to aircraft, is called ultimate capacity
(Hockaday and Kanafani, 1974)

Maximum throughput capacity (MTC) or saturation capacity
indicates the average number of movements that can be performed
on the runway system in 1h in the presence of continuous demand,
while adhering to all the separation requirements imposed by the ATM
system. (De Neufville & Odoni, 2003)

A measure of the maximum number of aircraft operations, which can
be accommodated at the airport or airport component in an hour (US
Federal Aviation Administration, Advisory Circular, AC 150/5060-5,
1983).

The ability of a component of the airfield to accommodate aircraft. It is
expressed in operations (arrivals and departures) per unit of time,
typically in operations per hour (Ashford and Wright, 1992).
10
Data and Methodology

RUNWAY CAPACITY
•
Definitions are somehow confusing. However,
rather than using Number of Runways Declared capacity
•
Focus on Runway efficiency. Terminal efficency is not included at
all, and left for further research.
•

Data Source;
“Airport Capacity/Demand Profiles” (2003) by ACI, ATAG and IATA
•
64 European Airports
•
Variables Used;



Declared Peak Hour Runway Capacity
Number of Aircraft Movements (yearly and peak hour)
Hours of Operation
11
Data and Methodology
Basic Methodology:
1. Finding the daily capacity by observing the hours of operations and
making additional assumptions
2. Finding the yearly capacity (multiplying by 365)
3. Comparing the yearly capacity with the actual number of
movements to find the utilization
•
For 4 different cases;
1.
2.
3.
4.
Near Saturated most of the day (only 4 airports)
24h operation with no restriction
24h operation, but night restrictions
No operation at night
12
Data and Methodology
Case 1. Frankfurt/Main, London Gatwick, London Heathrow and Stockholm, Near
Saturation:
Daily Capacity =
Peak Hour Declared Capacity * Hours without Restrictions +
Peak Hour Declared Capacity/3 * Hours with Restrictions
Case 2. The airport operates 24 hours without restrictions:
Daily Capacity =
Peak Hour Declared Capacity * 10 +
Peak Hour Declared Capacity/2 * 8 +
Peak Hour Declared Capacity/4 * 6
Case 3. The airport operates 24 hours with restrictions:
Daily Capacity =
Peak Hour Declared Capacity * 10 +
Peak Hour Declared Capacity/2 * Rest without restrictions +
Peak Hour Declared Capacity/6 * Rest with restrictions
Case 4. The airport operates for a determined part of the day:
Daily Capacity =
Peak Hour Declared Capacity * 10 +
Peak Hour Declared Capacity/2 * Rest
13
Empirical Results- 1
14
Empirical Results- 1
 Big airports are mostly on the top of the table.
Economies of Scale!
 Some airports are almost fully efficient.
Unlike in DEA, absolute numbers, but not relative comparison
SOME CRITICS
 Definition of Declared Runway Capacity is not unique,
Some airports do not take the same considerations into account,
Seasonality
How about looking at Peak Hour Declared and Actual Capacity???

15
Empirical Results- 2
16
Empirical Results- 2
 Many airports utilize (much) more than their declared capacity on the
peak hours
In some cases, there is an extreme difference,
e.g. Nuremberg : Declared: 30 Actual: 65
Maximum Declared Capacity understates the actual one!
One possible explanation:
Some airports work for just a period, by employing more labor, by
foregoing the level of quality(e.g. more waiting times etc.)
To understand the reason behind that,
An in-depth analysis of each airport is necessary!
How about looking at the countries and compare them???

17
Empirical Results- 3
18
Empirical Results- 3
 Countries with a small number of airports in the sample can be ignored.
However it is interesting that Turkey(IST) leads, followed by Belgium(BRU)
 Among other countries with more airports in the sample;
 Germany is doing the best, followed by the UK and France.
Is the Airport Coordination Germany working very well?
 Spain and Italy are under the average.
 Greece is characterised by a very poor performance
Effects of Seasonality?
How about looking at different coordination levels???

19
Empirical Results- 4
European airports are divided into three categories in terms of slot
coordination:
Level 1: Non-coordinated airports (8)
Level 2: Schedules facilitated airports (13)
Level 3: Fully coordinated airports (39)
-- Numbers in the parentheses show the number of airports in the
sample with this level of coordination
20
Empirical Results- 4
Fully coordinated airports have a
higher average score than others
Do the slot coordinated airports
perform their runway operations
better than the others?
21
Self Critic and Conclusion
 Terminal
side is totally ignored. How complete is the
analysis only by observing the runways?
A similar data for terminal capacity is available.
Next step is to do a similar analysis for terminal?
 Does it make sense to calculate the yearly capacity in this
way?
 Do the airports declare unique, comparable data on
runway?
There are different consideration taken into account;
•Noise Consideration (12)
•ATC Consideration (29)
•Runway Consideration (29)
•Apron Consideration (15)
•Terminal Consideration (13)
22
Thank you for your Attention...
www.gap-projekt.de
23