Trade-Area Models and Choice-Based Samples: Methods

Abstract

The use of choice-based data to generate parameters of a trade-area gravity model is described in detail in this paper. The importance of being able to estimate parameters with data collected from individuals who have selected a particular alternative is explained. The main advantage of the new method is that it allows the efficient use of easily collected data. It also allows inferences to be made about the distance-decay rates and attraction parameters, even when only a small subset of stores is sampled from an area. This new version of the retail gravity model has been tested extensively with data for 6 major retail centers in Dallas. The detailed studies include a demonstration of the conventional approaches to trade-area mapping and an explanation of exactly what is different about the method proposed here. Interpretation of the model results indicates areas where a store either gains an unexpectedly high (or low) share of its sales. These methods have immediate application in screening potential locations because the variables used to run the model are generic and easily gathered for other cases. The results also encourage the rethinking of the Huff-based gravity model.