Food Distribution Supply Chain Data Collection: Supply Chain Firm Interviews and Truck Counts

Goodchild, Anne V.; Ukrainczyk, Luka · 2016 · ROSA P / Washington (State). Dept. of Transportation. Office of Research and Library Services

archive: archived pipeline: cataloged verified

Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)

Summary

This study, conducted for the Washington State Department of Transportation, investigates the food distribution supply chain in the Puget Sound region to understand its transportation characteristics and potential responses to policies promoting natural gas vehicles. The research aims to improve freight demand modeling and inform future data collection strategies by examining the logistics, fleet composition, and operational behaviors of food distributors, retailers, and producers. The methodology combined qualitative interviews with manual truck counts. Researchers interviewed eleven employees from ten diverse firms, including large national grocery chains, large food distributors, and smaller local producers and distributors. These interviews explored business challenges, fleet management, and attitudes toward alternative fuels. Additionally, manual truck counts were conducted at twelve grocery stores across urban, suburban, and rural locations between 6:00 am and 12:00 pm. Observers recorded truck types, arrival and departure times, parking behavior, and stop durations. An online survey was also attempted but yielded insufficient data due to a low response rate. The findings reveal distinct operational differences between firm sizes. Large firms utilize larger trucks, travel longer distances with significant highway mileage, and deliver three to four times per week via rear loading docks. In contrast, smaller firms use smaller trucks, operate primarily on urban streets, and make more frequent daily deliveries, often using front doors and customer parking lots. Regarding natural gas adoption, three of five large distributors had implemented pilot programs, but reported issues with truck power, range, and high costs. No smaller firms with fleets under 40 trucks had adopted natural gas technology. While smaller firms operate on routes ideal for emission reductions, they lack the resources to procure natural gas vehicles and find government incentive processes cumbersome. Conversely, large firms found that current natural gas trucks were ill-suited for their highway-heavy, high-power requirements. The study concludes that current natural gas incentives are not effectively tailored to smaller firms, which are priced out of the market despite having operational profiles conducive to alternative fuel benefits. The authors recommend that future policy interventions should better target small-to-medium enterprises and address infrastructure gaps. The research also validates manual truck counting and qualitative interviews as effective methods for capturing complex freight behaviors, providing a foundation for more responsive freight models and targeted emission reduction policies.

Key finding

Smaller food distribution firms are ideal candidates for natural gas adoption due to short urban routes but are currently excluded from the market due to high vehicle costs, lack of infrastructure, and cumbersome grant processes.

Methodology

mixed_methods

Sample size: 22

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).

StageOutcomeToolModelPromptAttemptsCompleted
discover success rosap 2 2026-05-23
archive success 1 2026-05-23
extract success cached 2 2026-06-10
clean success 1 2026-06-01
chunk success 1 2026-06-01
embed success 1 2026-06-02
enrich success 1 2026-05-23
promote success 1 2026-05-23
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.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.