low cost carriers and airline punctuality in europe - atrs 2013

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    GERMAN AIRPORTPERFORMANCE

    GERMAN AVIATIONBENCHMARKING

    Contents

    1. Introduction and Literature Review2. Data Collection3. Model Description4. Results

    5. Conclusions

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    GERMAN AIRPORTPERFORMANCE

    GERMAN AVIATIONBENCHMARKING

    Contribution

    Provide empirical evidence in favor of a "low-cost externality" for flight delay European picture of the issue, previous empirical works

    exclusively focus on U.S. airports where data is readily available(Ater, 2012; Forbes, 2008a and 2008b; Forbes and Lederman,

    2010; Forbes et al., 2011; Mazzeo, 2003; Rupp, 2009) Fits into related literature on market concentration and firm

    performance.

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    GERMAN AIRPORTPERFORMANCE

    GERMAN AVIATIONBENCHMARKING

    Dataset

    102 European airports in around 80 cities Period: Daily schedules from April 2011 - December 2012 Sample size 3,486,376 observations: 23,402 flight codes, 3,300

    routes, however we collected over 12 mio observations onaround 15,000 different routes

    Airline is defined low-cost if it is a member of European LowFares Airline Association (ELFAA) during the sampling period.ELFAA Members (2012) are Blue Air, EasyJet, Flybe, Jet2,Norwegian Air Shuttle, Ryanair, Sverigeflyg, Transavia.com,

    Vueling and Wizz Air. Schedules and Weather observations are matched in Universal

    time (UTC).

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    GERMAN AIRPORTPERFORMANCE

    GERMAN AVIATIONBENCHMARKING

    Distribution of Delays

    Page 9

    0%

    5%

    10%

    15%

    20%

    25%

    30%

    35%

    40%

    45%

    - 1 2 0 - -

    1 0 6

    - 1 0 5 - -

    9 1

    - 9 0 - -

    7 6

    - 7 5 - -

    6 1

    - 6 0 - -

    4 6

    - 4 5 - -

    3 1

    - 3 0 - -

    1 6

    - 1 5 - -

    1

    0 - 1

    4

    1 5 - 2

    9

    3 0 - 4

    4

    4 5 - 5

    9

    6 0 - 7

    4

    7 5 - 8

    9

    9 0 - 1

    0 4

    1 0 5 - 1

    1 9

    1 2 0 - 1

    3 4

    1 3 5 - 1

    4 9

    1 5 0 - 1

    6 4

    1 6 5 - 1

    7 9

    % o

    f t o t a

    l f l i g

    h t s

    Delays

    FSC LCC

    ATRS Bergamo 28.06.2013 Branko Bubalo

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    GERMAN AIRPORTPERFORMANCE

    GERMAN AVIATIONBENCHMARKING

    Model

    Delay dat = Xdat + Zdat + da + t + dat ,

    where f indices the flight code, d the airport of destination and tthe day of observation.

    Delay d: Minutes of delay at the airport of destination Vector X: Variable of interest; LCC share at origin Vector Z: Set of Controls; LCC share at destination, Delay at

    origin, Airport congestion, dummy variables for weather

    condition, e.g. Foggy, Rainy, Snowy or Thundery. Routecompetition (number of airlines serving the route).

    da : Controls for unobservable and immeasurable effects dat : Error term

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    GERMAN AVIATION

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    GERMAN AIRPORTPERFORMANCE

    GERMAN AVIATIONBENCHMARKING

    Further research

    Step up in the crawling and in building a big database. Maybe observe all 200 airports included in the ATRSBenchmarking report for Level-of-Service indicators

    Limits are set by computer resources. The crawler could run ondifferent machines, which collect subsamples.

    Outlook: Collecting Information on delays, weather and ticketfares.

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    GERMAN AIRPORT GERMAN AVIATION

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    GERMAN AIRPORTPERFORMANCE

    GERMAN AVIATIONBENCHMARKING

    Thank you for your attention!Questions?

    Suggestions and Comments are welcome.

    Please see our paper published inthe ATRS Proceedings.

    [email protected]

    [email protected]

    www.gap-projekt.de

    Page 14ATRS Bergamo 28 06 2013 Branko Bubalo

    mailto:[email protected]:[email protected]://www.gap-projekt.de/http://www.gap-projekt.de/http://www.gap-projekt.de/http://www.gap-projekt.de/mailto:[email protected]:[email protected]