Stop frequency prediction model is one of the components of the
activity-based travel demand models. Most of the previous studies have
considered stops during commutes regardless
of their purposes. This approach does not yield the contribution of the
explanatory variables to the likelihood of making stops of different purposes.
Besides, most of the former studies have been conducted in larger metropolitan
areas. This study attempts to cover these gaps by using 2012 travel data of
Fargo-Moorhead medium-sized US metropolitan area and classifying stops on work
tours into escort, non-escort, and a combination of all stops. The results of
logit models indicate that personal characteristics of the commuters do not
contribute to the escort stop participation likelihood. In addition, household
size variables have a large impact on the likelihood of participating in escort
stops and participating in the combined stops on the outbound leg of the
commutes. Contrary to several previous studies, the significance and sign of
the coefficient of income level vary for different
stop purposes. Commuters seemed to be more likely to make more than one non-escort stop close to their
workplace on the outbound legs of their commutes. The general results
suggest separating the stop purposes yields more illustrative results rather
than using one model for the combined stops.
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