The planning and design of efficient transportation systems require an in-depth understanding of the micro-behaviour governing vehicle movements. Recent efforts to analyze commercial vehicle movements have begun focusing on the collection and usage of detailed microdata sets. This paper contributes to these efforts by devising statistical models for predicting the number of outbound commercial vehicle trips at the firm level given a sample of establishments in the Windsor, Ontario region. A comparison was made between a model that can be created using microdata obtained through an establishment survey, a model that utilized commercial firm lists with basic firm attributes that include employment size and industry classification, and a modified model with the basic variables and limited detailed microdata. The results suggest that commercial firm datasets can be used to generate reasonable predictions. However, additional information about employment, industry, vehicle ownership and other firm characteristics certainly enhance the models’ predictive ability.

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