Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)




Professor Fred L. Hall


The research reported in this thesis constitutes an attempt to address some of the methodological problems in the existing Urban Transportation Modelling System for trip generation analysis, and to provide new empirical evidence on the effect of locational factors and accessibility on discretionary trip making using data from the Greater Toronto Area (GTA).

Three separate analyses were performed using an ordered response model, a type of discrete choice model that exploits the ordering of information in the dependent variable in situations where there are more than two responses. One type of analysis examined the effects of geographic location of households on weekday, home-based shopping trips. Five zones (planning districts) within the GTA were chosen to reflect different types of location. The statistical results of this analysis show that, after controlling for some household's socioeconomic characteristics, its location within the metropolitan area has some effect on its weekday, home-based shopping trip generation. In particular, households located in the older urban area are likely to make fewer trips than those living in the suburbs.

The second type of analysis focused on Metropolitan Toronto, which constitutes a greater part of the GTA. In this analysis, gravity measures of accessibility were calculated and used along with the socio-economic characteristics to estimate the ordered response model. The results of this analysis in terms of asymptotic t-statistics suggest that accessibility is not a significant input into trip generation decisions of households in the metropolitan area.

The third analysis has two objectives. The first objective is to investigate the direct spatial transfer of an ordered response model. Investigating the impact of a scaling updating technique on the transferred ordered response model in another spatial context is the second objective. The results of this spatial transferability analysis show that a directly transferred model (without any updating of the transferred coefficients) performs reasonably well in predicting the choice probabilities in the application (new) context. Revising the constant terms and scalars in the ordered response model using the scaling updating technique substantially improves the predictive ability of the transferred model.

Overall, two implications can be identified from these analyses. First, the ordered response model is a useful methodology for the analysis of trip generation. The trip-making decision should therefore be treated as a multiple response with a natural order, not as a continuous variable or a dichotomous response. The other implication is that while weekday, home-based shopping trip generation is sensitive to the location of the households, the gravity-based measure of accessibility was not found to be a significant factor in the trip-making decision.

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