Luke Johnson

The Huff Model allows researchers to model retail catchment areas using the distance from consumers to stores. To represent the real world as closely as possible, network distance should be used as an input for the Huff Model, but existing tools are either expensive or very slow. The goal of this research is to develop a new, open-source tool to calculate network distance and illustrate the tool’s role as an input to the Huff model on a case study examining major grocery store catchment areas in the City of Toronto. The new tool was developed in Python as a script to be executed in QGIS. To improve upon existing tools, the Python library igraph was utilized, which helped decrease the run time of calculations compared to an existing tool by a factor of 268, while maintaining accuracy of the output. The case study found that some catchment areas for Metro grocery stores are very large and there might be an opportunity for a competitor to move in to capitalize on an underserved market.