A central topic in the retail analysis is store location, which is related to its attractiveness and even with its profitability. In order to determine the force of attraction of a given point of sale, methodologies based on gravitational models have been developed. More recently, classic models have been integrated with Geographic Information Systems (GIS). This paper explores a methodology for retail spatial analysis in a GIS environment, and it aims to: (a) model the degree of influence of different store location attributes on the consumer choice among a collection of retail options, and (b) develop an empirical application for the clothing retail business sector in the city of Santa Maria, RS, Brazil. The study selects three relevant location attributes of store choice: retail market clustering, local accessibility of the street network, and topographic slope of the terrain. These three location features were taken as inputs for the attractiveness evaluation of each store, using the Huff model. As a result, we were able to model the trading areas of each shop related to the selected attributes. The paper provides a methodology for modelling the performance of retail location attributes and building different scenarios of probabilities for consumer patronage, allowing a first measure of the influence of each selected store location attribute.
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