Abstract:Locational analysis of retail activity is gaining increasing attention as a result of the changing urban and transportation patterns in the United States. Locational decision making models developed in the past have not been able to rigorously predict urban areas of high retail potential as they did not assess the growth in retail activity over time and did not account for multivariate relationships among economic, demographic and commercial characteristics in the decision-making process. This paper proposes a new measure of retail potential which overcomes these drawbacks and compares its performance in identifying cities of high retail growth with those of other measures proposed in past research. The proposed measure is found to predict cities of high retail growth with greater accuracy thus showing the importance of accounting for dynamic multivariate relationships in explaining retail growth.