Performance metrics used by freight transport providers.
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Summary
This report investigates the performance metrics utilized by freight transport providers in the United States, addressing the lack of standardized measurement systems across the industry. The research was motivated by the National Cooperative Freight Research Program’s (NCFRP) initiative to establish consistent performance metrics for freight transportation. As freight demand outstrips infrastructure capacity, resulting in congestion and increased costs, there is a critical need to quantify system distress to inform public and private decision-making. The study specifically examines the perspective of freight providers—such as trucking, railroad, maritime, pipeline, and aviation companies—to identify how they measure efficiency, productivity, and financial performance. The methodology involves a comprehensive review of existing literature on freight performance measurement and an analysis of industry data from major providers across five primary modes: trucking, railroads, maritime, pipelines, and aviation. The report categorizes providers by mode and scale, detailing infrastructure networks, leading companies, and operational characteristics. It contrasts the interests of the public sector, which focuses on policy justification, safety, and environmental impacts, with those of private providers, who prioritize economic measures, equipment utilization, and customer service. The analysis draws on data from sources such as the Bureau of Transportation Statistics and industry reports to characterize the diversity of metrics currently in use. The findings reveal significant heterogeneity in performance measurement across and within freight modes. There is little uniformity or consensus on the "best" metrics, with some providers using hundreds of distinct measures, many of which are financial ratios. However, the study identifies six metrics common to all five major modes: average length of haul, operating ratio, revenue per ton-mile, tonnage, ton-miles (or barrel-miles), and terminal dwell time or empty miles factor. These shared metrics serve as key benchmarks for productivity and financial health. The report also highlights that while trucks dominate shipment value and short-distance transport, railroads lead in long-distance ton-miles, and pipelines and maritime transport handle significant volumes of energy and bulk goods. Aviation, while minor in domestic tonnage, is crucial for high-value international shipments. The significance of this research lies in its contribution to the development of a unified framework for national and international goods movement performance measurement. By identifying common metrics and highlighting the distinctions between public and private sector interests, the report provides a basis for comparing analyses across different freight modes. The authors conclude that establishing consistent metrics is essential for assessing system performance, identifying critical data needs, and ultimately relieving industry distress to support economic growth. The study suggests that future efforts, such as NCFRP Project 03, should build on these findings to create a robust measurement system that facilitates optimization and better understanding of freight transport issues.
Key finding
Six performance metrics are consistently used across all five major freight transport modes: average length of haul, operating ratio, revenue per ton-mile, total tonnage, ton-miles, and terminal dwell time or empty miles factor.
Methodology
review
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
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| extract | success | cached | — | — | 2 | 2026-06-10 |
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| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 24 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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