This section provides the scope, different modes, and variables considered in the freight mode choice literature. This will provide a bigger picture of the advantages and limitations of various methodologies, datasets, and estimation procedures. The types of modes, scope, and geographical levels included in each publication on freight mode choice are shown in Table 15. The majority of the recent literature deals with different types of trucks (Arunotayanun and Polak 2007, Cavalcante and Roorda 2010, Lloret-Batlle and Combes 2013, Abate and de Jong 2014). There are just two references that consider all four mode choices. Only three references consider air mode, and waterways. Table 15 also shows that some references (e.g., (Cunningham 1982, Gray 1982)) did not consider any specific mode, as these studies are theoretical. No study in supply chain models considers air mode. Truck and rail are the predominant mode shares studies in freight mode choice. Many references on econometric models concentrate on practical applications, while the majority of studies on supply chain methods are theoretical. Mode choice studies predominantly focus on national-level freight movements, while regional-level freight flows are studied by only a few publications. However, a deeper look into the modeling, data, and geography reveal that none of the publications have a solid national-wide model estimated using a reasonable sample size to provide better estimates for modal splits. This project is the first to fill this gap by using 2012 confidential Commodity Flow Survey (CFS) data with nearly two million observations at the national level.
Table 16 shows the variables considered in publications on freight mode choice, with freight rate, transit time, shipment size, and reliability being some of the most important. The table shows that econometric models are able to provide solid depictions of freight mode choice with a smaller number of independent variables than supply chain models. The ITIC models: Federal Railroad Administration (2005) and Federal Highway Administration (2006) consider 20-25 variables each (see Table 14) require huge amount data to estimate the mode choice. Especially data on reliability, capacity, and inventory costs are difficult to obtain for all commodities in the US, in order to utilize these models to estimate nation-wide freight modal shifts.