The Huff model is an established theory in spatial analysis. It is based on the principle that the probability of a given consumer visiting and purchasing at a given site is some function of the distance to that site, its attractiveness, and the distance and attractiveness of competing sites.

This specific model, made in the area of spatial interaction research, was refined and made operational by Dr. David Huff of the University of Texas in 1963.

In practice, census polygons (for example, block groups) are substituted for individual consumers. The calculated probability for each polygon is multiplied by some data element in the polygon database (for instance, households and dollars spent on groceries). This measure can then be summarized to give an estimate of the total. Some measure of size, such as gross leasable area (GLA), is often used as a surrogate for attractiveness.

A site has many attributes that make it attractive to consumers. Attractiveness can be computed as a function of many attributes. For a retail store, these would be its retail floor space, number of parking spaces, or product pricing. Attractiveness of a car dealership could be a function of its display area, frontage, and advertisement. The attractiveness of an office building could be a function of how many offices are within it. Attractiveness is expressed as one number that combines all the factors that make a center attractive. This number is usually referred to as an index. An index of attractiveness for a center is one number describing the factors that make it attractive to its customers. This index could also be derived by counting how many people come to that destination or by conducting a consumer survey.

You can control the distance that the Huff model extends. Type a value that will encompass all your competitors.

You can choose miles or kilometers as the distance units.

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