Modal Split Analysis Using Logit Models
Publication: Journal of Transportation Engineering
Volume 113, Issue 5
Abstract
This study attempts to identify the mode and the factors that contribute to the selection of a particular mode for commodity movements provincially based on average shipment size, control, loads, hire, and type of commodity. The main objective of this study is to propose a more comprehensive and statistically credible method to analyze the vast data required in transportation planning. It involves the application of standard statistical techniques such as the log‐linear and logit models. The data are collapsed to form multidimensional contingency tables in order to develop these models. The data from both shippers and consignees are taken from a survey conducted by Alberta Transportation, Canada. From the analysis it is found that truck and rail are the only two major carriers of freight across the province. Truck mode dominates over rail in transporting all commodities. The less‐than‐full‐load market belongs exclusively to truck mode. The rail mode shares a very small percentage of the full‐load market, and is used to transport specific bulk commodities under higher average shipment size.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
American Association of State Highway and Transportation Officials. (1977). “A manual on user benefit analysis of highway and bus‐transit improvements.” Washington, D.C.
2.
Baker, Henry H., et al. (1981). “From freight flow and cost patterns to greater profitability and better service for a motor carrier.” Interfaces, II(6), Dec., 4–19.
3.
Berenson, M. L., et al. (1983). Intermediate statistical methods and applications: A computer package approach. Prentice‐Hall Inc., Englewood Cliffs, N.J.
4.
Berkson, J. (1944). “Applications of logistic function to bio‐assay.” J. Amer. Stat. Assoc. 39, 357–365.
5.
Desauliners, Y., and Mozes, S. L. (1985). “The Canadian trucking industry.” Proc.20, Canad. Transp. Res. Forum, Toronto, Canada.
6.
Dillon, W. R., and Goldstein, M. (1984). Multi‐variate analysis; Methods and applications. John Wiley and Sons, New York, N.Y.
7.
Fox, J. (1984). Linear statistical models and related methods. John Wiley and Sons, New York, N.Y.
8.
Fienberg, S. (1980). The analysis of cross classified categorical data. 2nd ed., MIT Press, Cambridge, Mass.
9.
National Research Council (1983). “Application of statewide freight demand forecasting techniques.” Rep. 260 NCHRP, Transportation Research Board, Washington, D.C.
10.
Randolph, W. H. (1985). “Dependence between shipment size and mode in freight transportation.” Transp. Sci., 19(4), Nov., 436–444.
11.
Roth, R. D. (1977). “Approach to measurement of model advantage.” Transp. Res. Rec. 637, Washington, D.C.
12.
Trimac Consulting Services Ltd. (1977). “Pilot study of Alberta freight transportation, for Alberta transportation.” Alberta Transportation, Edmonton, Alberta, Canada.
13.
Trimac Consulting Services Ltd. (1978). “Final study, Alberta commodity transport study for Alberta transportation.” Alberta Transportation, Edmonton, Alberta, Canada.
Information & Authors
Information
Published In
Copyright
Copyright © 1987 ASCE.
History
Published online: Sep 1, 1987
Published in print: Sep 1987
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.