A Freight Mode Choice Analysis Using a Binary Logit Model and GIS: The Case of Cereal Grains Transportation in the United States

Guoqiang Shen, Jiahui Wang

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Division of Regional and City Planning, College of Architecture, School of Industrial Engineering College of Engineering, The University of Oklahoma, Norman, USA.

DOI: 10.4236/jtts.2012.22019                

Abstract

Mode choice is important in shipping commodities efficiently. This paper develops a binary logit model and a regression model to study the cereal grains movement by truck and rail in the United States using the publically available Freight Analysis Framework (FAF^2.2) database and U.S. highway and networks and TransCAD, a geographic information system with strong transportation modeling capabilities. The binary logit model and the regression model both use the same set of generic variables, including mode split probability, commodity weight, value, network travel time, and fuel cost. The results show that both the binary logit and regression models perform well for cereal grains transportation in the United States, with the binary logit model yielding overall better estimates with respect to the observed truck and rail mode splits. The two models can be used to study other commodities between two modes and may produce better results if more mode specific variables are used.

Keywords

Binary Logit; Regression; Freight; Mode Choice; Cereal Grains

Conflicts of Interest

The authors declare no conflicts of interest.

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