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.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 31 (1997)
Issue (Month): 4 ()
|Note:||Received: June 1996 / Accepted: February 1997|
|Contact details of provider:|| Web page: http://link.springer.de/link/service/journals/00168/index.htm|
More information through EDIRC
|Order Information:||Web: http://link.springer.de/orders.htm|
When requesting a correction, please mention this item's handle: RePEc:spr:anresc:v:31:y:1997:i:4:p:411-429. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Rebekah McClure)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.