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Spatial choice behaviour: logit models and neural network analysis

Listed author(s):
  • Peter Nijkamp

    (Department of Economics, Free University, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands)

  • Tommaso Tritapepe

    (Department of Economics, University of Bologna, Piazza Scaravilli 2, I-40126 Bologna, Italy)

  • Aura Reggiani

    (Department of Economics, University of Bologna, Piazza Scaravilli 2, I-40126 Bologna, Italy)

Neural networks are becoming popular analysis tools in spatial research, as is witnessed by various applications in recent years. The performance of neural network analysis needs to be carefully judged, however, since the theoretical underpinning of neuro-computing is still weakly enveloped. In the present paper we will use the logit model as a benchmark for evaluating the result of neural network models, based on an empirical case study from Italy. The present paper aims to assess the foreseeable impact of the high-speed train in Italy, by investigating competition effects between rail and road transport modes. Two statistical models will then be compared, viz. the traditional logit model and a new technique for information processing, viz. the feedforward neural network model. In the study two different cases - corresponding to a different set of attributes - are investigated, namely by using only `time' attributes and by using both `time' and `cost' attributes. From an economic viewpoint, both models appear to highlight the advantage of introducing the high-speed train system in that they show high probabilities of choosing the improved rail transport mode. The feedforward neural net model seems to provide reasonable predictions compared to those obtained by means of a logit model. An important lesson however, is that it is important to define properly the neural network architecture and to train sufficiently the network during the learning phase.

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Article provided by Springer & Western Regional Science Association in its journal The Annals of Regional Science.

Volume (Year): 31 (1997)
Issue (Month): 4 ()
Pages: 411-429

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Handle: RePEc:spr:anresc:v:31:y:1997:i:4:p:411-429
Note: Received: June 1996 / Accepted: February 1997
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