Sampling for freight trip generation studies

Paper i proceeding, 2026

Freight Trip Generation (FTG) models link establishment characteristics to delivery activity and are widely used in urban freight planning. While their reliability depends on establishment surveys, the implications of sampling design remain poorly understood. This paper examines how alternative sampling strategies affect FTG model performance and cost, using population data to sample from establishments in Stockholm. The authors compare simple random, stratified, and hybrid sampling across proportional, Neyman, and optimal allocation rules, as well as three levels of sector aggregation. Results show that simple random sampling overrepresents large, low-impact sectors and underrepresents freight-intensive ones. Stratified approaches improve accuracy, but only when allocation accounts for sectoral variance and survey costs. Aggregation reduces required sample sizes, with moderate aggregation offering a practical compromise and high aggregation suited for strategic planning.