Journal
TRANSPORTATION PLANNING AND TECHNOLOGY
Volume 34, Issue 8, Pages 857-869Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/03081060.2011.600092
Keywords
freight mode choice; truck and rail competition; fuel cost fluctuation; machine learning
Categories
Funding
- Illinois Department of Transportation
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This paper develops a behavioral analysis of freight mode choice decisions that could provide a basis for an acceptable analytical tool for policy assessment. The paper specifically examines the way that truck and rail compete for commodity movement in the US. Two binary mode choice models are introduced in which some shipment-specific variables (e.g. distance, weight and value) and mode-specific variables (e.g. haul time and cost) are found to be determinants. The specifications of the non-selected choice are imputed in a machine learning module. Shipping cost is found to be a central factor for rail shipments, while road shipments are found to be more sensitive to haul time. Sensitivity of mode choice decisions is further analyzed under different fuel price fluctuation scenarios. A low level of mode choice sensitivity is found with respect to fuel price, such that even a 50% increase in fuel cost does not cause a significant modal shift between truck and rail.
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