Recent advances in spatial interaction modelling: an application to the forecasting of shopping travel
A common problem in the use of singly-constrained spatial interaction shopping models has been that of finding optimal parameter values. This problem has been exacerbated where improvements to the model have involved extra parameters to be estimated. In this paper it is shown that calibration of quite complex models can be achieved through modification of the conventional `gravity' model to a generalised linear model with Poisson error structure and logarithmic link function. Data on observed trips between fifteen residential zones and eighty-three shopping destinations in Cardiff are used to test several models through application of the GLIM computing package. Models involving extra explanatory variables, origin-specific distance-decay parameters, and competing-destinations terms are all shown to offer worthwhile improvements in performance over the conventional singly-constrained model. An individual-specific model is also tested for a small sample of shoppers. Finally, some comments are made concerning the relevance of the Cardiff findings and the wider significance of these methodological advances.
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