Spatial choice behaviour: logit models and neural network analysis

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. <!--ID="" Acknowledgements. The authors wish to acknowledge helpful comments given on a previous version of their paper by J. Poot and L. Schintler. Also constructive comments of two anonymous referees have to be acknowledged. The second author gratefully acknowledges the CNR "Finalizzato Trasporti 2" Project, contract no. 96.00098.PF74. The third author acknowledges a Human Capital and Mobility Research Grant of the EC (Strategic Infrastructure Networks in Europe, Contract no. ERBCHBGCT920162), as well as the good facilities to carry out this study at the host institution (Economic and Social Institute, Department of Economics, Free University, Amsterdam).-->