Forecasting freight transportation demand with the space-time multinomial probit model
AbstractFreight transportation demand is a highly variable process over space and time. A multinomial probit (MNP) model with spatially and temporally correlated error structure is proposed for freight demand analysis for tactical/operational planning applications. The resulting model has a large number of alternatives, and estimation is performed using Monte-Carlo simulation to evaluate the MNP likelihoods. The model is successfully applied to a data set of actual shipments served by a large truckload carrier. In addition to the substantive insights obtained from the estimation results, forecasting tests are performed to assess the model's predictive ability for operational purposes.
Download InfoIf 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.
Bibliographic InfoArticle provided by Elsevier in its journal Transportation Research Part B: Methodological.
Volume (Year): 34 (2000)
Issue (Month): 5 (June)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Bhat, Chandra R. & Guo, Jessica, 2004. "A mixed spatially correlated logit model: formulation and application to residential choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 147-168, February.
- Russo, Francesco & Musolino, Giuseppe, 2013. "Estimating demand variables of maritime container transport: An aggregate procedure for the Mediterranean area," Research in Transportation Economics, Elsevier, vol. 42(1), pages 38-49.
- Liu, Yu-Hsin, 2011. "Incorporating scatter search and threshold accepting in finding maximum likelihood estimates for the multinomial probit model," European Journal of Operational Research, Elsevier, vol. 211(1), pages 130-138, May.
- Joseph Chow & Choon Yang & Amelia Regan, 2010. "State-of-the art of freight forecast modeling: lessons learned and the road ahead," Transportation, Springer, vol. 37(6), pages 1011-1030, November.
- Mohamed Abdel-Aty & M. Abdalla, 2004. "Modeling drivers' diversion from normal routes under ATIS using generalized estimating equations and binomial probit link function," Transportation, Springer, vol. 31(3), pages 327-348, August.
- Hunt, Len M. & Boxall, Peter C. & Boots, Barry, 2007. "Accommodating Complex Substitution Patterns in a Random Utility Model of Recreational Fishing," Marine Resource Economics, Marine Resources Foundation, vol. 22(2).
- Chandra Bhat & Ipek Sener, 2009. "A copula-based closed-form binary logit choice model for accommodating spatial correlation across observational units," Journal of Geographical Systems, Springer, vol. 11(3), pages 243-272, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
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.