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Airport Choice in Germany - New Empirical Evidence of the German Air Traveller Survey 2003


  • Wilken, Dieter
  • Berster, Peter
  • Gelhausen, Marc Christopher


The paper deals with the quantitative relationship between the number of air travellers in any region and the airports chosen in Germany in 2003. The purpose of the paper is to present results of an analysis of airport choice behaviour of total air passenger demand in Germany, based on data of the German air traveller survey conducted at 17 international and 5 regional airports. About 210 000 passengers were interviewed about their trip origin, destination, choice of travel mode to the airport, purpose of their journey and further journey and person related attributes. As a result of the analysis so far, the distribution of airports chosen by all passengers coming from any region in Germany can be shown in relation to the journey purpose and destination. Based on these data, logit models have been calibrated for each market segment to forecast airport choice in relation to the accessibility and attractiveness of airports. As a further methodological step the outline of a combined neural and nested logit model of access mode and airport choice is given, which will be calibrated on the basis of the data of the German air traveller survey. Typically, the nearest airport will be chosen by most travellers, there are, however, on average eight airports serving one region (defined as a Spatial Planning Region, of which there are 97 in Germany). If there is an international airport in a region about two thirds of the demand coming from that region will choose that airport, and about one third will choose to depart from one of seven other airports. Vice versa, each airport attracts passengers coming from almost 40 regions. There is thus an intense interaction between an airport and a large influential area.

Suggested Citation

  • Wilken, Dieter & Berster, Peter & Gelhausen, Marc Christopher, 2005. "Airport Choice in Germany - New Empirical Evidence of the German Air Traveller Survey 2003," MPRA Paper 5631, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:5631

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    References listed on IDEAS

    1. Gaudry, Marc J.I., 1981. "The inverse power transformation logit and dogit mode choice models," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 97-103, April.
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    Cited by:

    1. Stephen J. Redding & Daniel M. Sturm & Nikolaus Wolf, 2011. "History and Industry Location: Evidence from German Airports," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 814-831, August.
    2. Gelhausen, Marc Christopher, 2006. "Flughafen- und Zugangsverkehrsmittelwahl in Deutschland - Ein verallgemeinerter Nested Logit-Ansatz," MPRA Paper 16002, University Library of Munich, Germany.
    3. Gelhausen, Marc Christopher, 2006. "Airport and Access Mode Choice in Germany: A Generalized Neural Logit Model Approach," MPRA Paper 4236, University Library of Munich, Germany, revised Sep 2006.
    4. Gelhausen, Marc C., 2011. "Modelling the effects of capacity constraints on air travellers’ airport choice," Journal of Air Transport Management, Elsevier, vol. 17(2), pages 116-119.
    5. Gelhausen, Marc Christopher, 2007. "A Generalized Neural Logit Model for Airport and Access Mode Choice in Germany," MPRA Paper 4313, University Library of Munich, Germany, revised 2007.
    6. Gelhausen, Marc Christopher & Wilken, Dieter, 2006. "Airport and Access Mode Choice : A Generalized Nested Logit Model Approach," MPRA Paper 4311, University Library of Munich, Germany, revised 2006.
    7. Gelhausen, Marc Christopher, 2008. "Airport Choice in a Constraint World: Discrete Choice Models and Capacity Constraints," MPRA Paper 9675, University Library of Munich, Germany.
    8. Gelhausen, Marc Christopher, 2007. "Passengers' Airport Choice," MPRA Paper 16037, University Library of Munich, Germany.

    More about this item


    Regional air travel demand; airport choice; air traveller survey; catchment areas of airports; travel route from origin via departing airport to destination area; logit model on airport choice; neural networks;

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods


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