Abstract:Urban segregation is an inherent feature of cities and becomes a problem when excluding or hindering certain groups from accessing services, activities and spaces. In Brazil, segregation by social class is dominant in the structure of cities and public policies rarely address urban configuration as part of the segregation problem. This work addresses segregation with a shift in emphasis from traditional housing segregation to segregation as the restraint of socio-spatial interactions, thus including other facets of the phenomenon that have not yet been properly explored and seeking new spatially relevant metrics. This paper aims to present a methodology of segregation analysis based on configurational models and develop an empirical application in a Brazilian city. Representing the probabilities of interaction between different socio-economic groups in public spaces, a configurational model was used, addressing retail-residence spatial relationship. The attributes of population size, household income and number of retail establishments were considered. The results allowed identifying the probabilistic residence-retail trajectories for high and low income groups, providing a first measure of spatial segregation. The conclusions seek to highlight the importance of configurational approaches for segregation studies, as well as to show potentialities and limits of this methodology.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.