In chapter 2 the micro-economic approach for representing a spatial system was presented and discussed. Although the models that can be derived have a strong theoretical content, the nature of the simplifying assumptions, their mathematical representation and their operational difficulties, forces them to stay as theoretical propositions only, providing no useful analytical tools for the practitioner. The main shortcomings of this approach can be summarised as follows:

1. (a) Both users and suppliers are assumed to have perfect information about market conditions. Limited information would be a more realistic assumption.

2. (b) Bidders or suppliers are assumed to have deterministic utility functions. Faced with the same options, they will always make the same choices. Variations in individual behaviour should be considered instead.

3. (c) Bidders or suppliers have frictionless mobility, and they can even appear or disappear at no cost. Restricted dynamics would produce more realistic results.

4. (d) There is no way to aggregate demand or supply functions. With a large population, the resulting models are impractical. If, in order to solve this, the analyst applies the same models to socioeconomic and spatial aggregates, the results would be unreal, because it would imply large groups showing identical behaviour.

Spatial interaction models, as explained in chapter 3, were derived by maximising an entropy function, subject to some known constraints. The resulting distributions, as has been pointed out, are the least prejudiced statements about the system being modelled, that is, they are the distributions that make the weakest assumptions about the system apart from what is known and reflected in the constraints.