In spatial analysis, the Huff model is a widely used tool for predicting the probability of a consumer visiting a site, as a function of the distance of the site, its attractiveness, and the relative attractiveness of alternatives. It was formulated by David Huff in 1963.^[1] It is used in marketing, economics, retail research and urban planning,^[2] and is implemented in several commercially available GIS systems.

Its relative ease of use and applicability to a wide range of problems contribute to its enduring appeal.^[3]

The formula is given as:

${\displaystyle P_{ij}={\frac {A_{j}^{\alpha }D_{ij}^{-\beta }}{\sum _{k=1}^{n}A_{k}^{\alpha }D_{ik}^{-\beta }}}}$

where :

• ${\displaystyle A_{j}}$ is a measure of the attractiveness of store j
• ${\displaystyle D_{ij}}$ is the distance from the consumer's location, i, to store j.
• ${\displaystyle \alpha }$ is an attractiveness parameter
• ${\displaystyle \beta }$ is a distance decay parameter
• ${\displaystyle n}$ is the total number of stores, including store j