Statistical Analysis of Truckload Transportation Rates

Times series freight rates for trucking is notoriously difficult to obtain. The industry is comprised of different kinds of trucks (e.g., vans and flatdecks), serves different traffic lanes and has a very large number of carriers and shippers. Moreover, the data varies with the tempo of the general economy and seasonal variations. Aggregate data is generally not meaningful or comparable.
This project will provide access to a unique data set based on actual transactions for a multiple of origins/destinations and different truck configurations. The analysis will enable study of some accepted by not proven concepts, such as the tapering of freight rates with distance, the general traffic flows as illustrated by fronthaul/backhaul rates, and the differences for transport by different trailer types. A further benefit is economic forecasting. Trucking is known to be an early indicator of economic change, and these data will permit the development of accurate forecasting models.

Faculty Supervisor:

Barry Prentice

Student:

Partner:

Evotrux Inc.

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program: