A Generalized Neural Logit Model for Airport and Access Mode Choice in Germany

Gelhausen, Marc Christopher (2007): A Generalized Neural Logit Model for Airport and Access Mode Choice in Germany. Published in: Proceedings of the 11th Air Transport Research Society World Conference (2007): pp. 1-42.

Abstract

The purpose of this paper is to present a new kind of discrete choice model called "Generalized Neural Logit Model" applied exemplarily to the case of airport and access mode choice. This approach employs neural networks to model the utility function of a discrete choice model and correlations within the alternative set and genetic algorithms to optimize the network structure.

To evaluate the new approach the application case of airport and access mode choice is chosen. Benchmark for the Generalized Neural Logit Model is a nested logit approach. The estimated market segment specific airport and access mode choice models are generally applicable to any number of airports and combinations of airports and access modes. Thereby it is possible to analyse future scenarios in terms of new airport constellations and new airport access modes. To achieve this, Kohonen’s Self-Organizing-Maps are used to identify different airport clusters and assign every airport to the appropriate cluster.

Although the nested logit model show a good model fit for most market segments, the Generalized Neural Logit approach produces a significant increase in model fit especially for those market segments whose nested logit model show less satisfying results.

• Item Type: MPRA Paper
• Institution: German Aerospace Center (DLR), Air Transport and Airport Research
• Language: English
• Keywords: Airport and access mode choice model; Artificial neural networks; Concept of alternative groups; Discrete choice model; Generalized Neural Logit Model; Kohonen’s Self-Organizing Maps; Nested logit model
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C25 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions ; Probabilities; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C45 - Neural Networks and Related Topics; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General

References

Anders, U. (1997), Statistische neuronale Netze, Vahlen: Munich.

Bhat, Ch. R. (2003), Econometric Choice Formulations: Alternative Model Structures, Estimation Techniques and Emerging Directions, Proceedings of the 10th International Conference on Travel Behaviour Research in Lucerne, Swiss, 1-36.

Ben-Akiva, M., Lerman, S. (1985), Discrete Choice Analysis: Theory and Applications to Travel Demand, MIT Press: Cambridge, MA.

Bentz, Y., Merunka, D. (2000), Neural Networks and the Multinomial Logit for Brand Choice Modelling: A Hybrid Approach, Journal of Forecasting, 19, 177-200.

Berster, P., Focke, H., Pabst, H. and Wilken, D. (2005), Gemeinsame Auswertung der ADV-Fluggastbefragung 2003, Cologne (unpublished).

Bishop, C. M. (2003), Neural Networks for Pattern Recognition, Oxford University Press: Oxford.

Domencich, T. A., McFadden, D. (1975), Urban Travel Demand - A Behavioral Analysis, Elsevier: New York.

Fausett, L. (1994), Fundamentals of Neural Networks - Architectures, Algorithms and Applications, Prentice Hall: Englewood Cliffs.

Gaudry, M. J. I., Dagenais, M. G. (1979), The Dogit Model, Transportation Research, 13 B, 105-111.

Gelhausen, M. Ch. (2003), Evaluation zufallsnutzenbasierter Verfahren und künstlicher neuronaler Netze zur Prognose von Flughafen- und Feeder-moduswahl, Diploma thesis, Technical University of Aachen: Aachen.

Gelhausen, M. Ch., Wilken, D. (2006), Airport and Access Mode Choice - A Generalized Nested Logit Model Approach, Proceedings of the 10th Air Transport Research Society Conference 2006 in Nagoya, Japan, 1-30.

Hornik, K., Stinchcombe, M. and White, H. (1989), Multilayer Feedforward Networks are Universal Approximators, Neural Networks, 3, 359-366.

Hruschka, H., Fettes, W., Probst, M. and Mies, Ch. (2002), A Flexible Brand Choice Model Based on Neural Net Methodology - A Comparison to the Linear Utility Multinomial Logit Model and its Latent Class Extension, OR Spectrum, 24, 127-143.

Kohonen, T. (2001), Self-Organizing Maps, Springer: Berlin.

LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W. and Jackel, L. D. (1989), Backpropagation Applied to Handwritten Zip Code Recognition, Neural Computation, 1, 541-551.

Maier, G., Weiss, P. (1990), Modelle diskreter Entscheidungen - Theorie und Anwendung in den Sozial- und Wirtschaftswissenschaften, Springer: Vienna.

McCarthy, P. S. (1997), The Role of Captivity in Aggregate Share Models of Intercity Passenger Travel, Journal of Transport Economics and Policy, 31 (3), 293-308.

McFadden, D. (1974), Conditional Logit Analysis of Qualitative Choice Behavior, in: Zarembka, P. (Ed.), Frontiers in Econometrics, Academic Press: New York, 105-142.

McFadden, D. (1978), Modelling the Choice of Residental Location, in: Karlqvist, A., Lundqvist, L., Snickars, F. and Weibull, J. (Eds.), Spatial Interaction Theory and Planning Models, Elsevier: Amsterdam, 75-96.

Miller, G. F., Todd, P. M. and Hedge, S. U. (1989), Designing Neural Networks Using Genetic Algorithms, in: Schaffer, J. D. (Ed.): Proceedings of the 3rd International Conference on Genetic Algorithms, Morgan Kaufmann, San Mateo, CA, 379-384.

NeuroDimension (2005), NeuroSolutions Version 5.02 NeuroSolutionsHelp, Gainesville.

Ortuzar, J. de D., Willumsen, L. G. (2001), Modelling Transport. Wiley & Sons: London.

Probst, M. (2002), Neuronale Netze zur Bestimmung nichtlinearer Nutzenfunktionen in Markenwahlmodellen, Europäischer Verlag der Wissenschaften: Regensburg.

Rumelhardt, D. E., Hinton, G.E. and Williams, R. J. (1986), Learning Internal Representations by Error Propagation, in: Rumelhart, D. E., McClelland, J. L. Parallel Distributed Processing: Exploration in the Microstructure of Cognition vol. 1: Foundations, MIT-Press: Cambridge, MA, 318-362.

Train, K. E. (2003), Discrete Choice Methods with Simulation, Cambridge University Press: Cambridge, UK.

Wilken, D., Berster, P. and Gelhausen, M. Ch. (2005), Airport Choice in Germany - New Empirical Evidence of the German Air Traveller Survey 2003, Proceedings of the 9th Air Transport Research Society Conference 2005 in Rio de Janeiro, Brazil, 1-29.