Airport Capacity Benchmarking: Conventional Methods Critique and Runway Efficiency Analysis

1. 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

2. 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

3. Introduction • Need for benchmarking on airports • Focus on Capacity Benchmarking • Within Capacity: • Terminal Side • Airside(RWY and Apron) • Commonly Used Methods; • TFP • DEA • SFA 3

4. 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

5. 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

6. Literature • Common Outputs Used in these Analyses; • passengers, • cargo, • ATM, 6

7. Critics • Of the Input-Output Combination: • Runway vs. Terminal activities • Employee structures differ, both quantitative and qualitative • Different fleet mixes in different airports • Attractivity • Marketing • Core activity • Pure engineering 7

8. 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

9. 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

10. 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

11. 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

12. Data and Methodology • Basic Methodology: • Finding the daily capacity by observing the hours of operations and making additional assumptions • 2. Finding the yearly capacity (multiplying by 365) • Comparing the yearly capacity with the actual number of movements to find the utilization • For 4 different cases; • Near Saturated most of the day (only 4 airports) • 24h operation with no restriction • 24h operation, but night restrictions • No operation at night 12

13. 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

14. Empirical Results- 1 14

15. 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

16. Empirical Results- 2 16

17. 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

18. Empirical Results- 3 18

19. 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. •  Spain and Italy are under the average. •  Greece is characterised by a very poor performance • How about looking at different coordination levels??? •  Is the Airport Coordination Germany working very well? Effects of Seasonality? 19

20. 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

21. 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

22. 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

23. Thank you for your Attention... www.gap-projekt.de 23