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

• 作者: Guoqiang Shen Jiahui Wang
• 来源期刊: 交通科技期刊(英文)
• 学科: 医学
• 关键词: BINARY LOGIT Regression FREIGHT Mode CHOICE CEREAL Grains
• 年，卷（期）: 2012,（2）
• 页码范围: 175-188
• 页数: 14页
• 分类号: R73

摘要

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 (FAF2.2) 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.