Analysis of the spatial distribution of financial institutions and the factors influencing it (Case study: Ardabil)

Financial institutions are among the most important functions of urban economics that underlie the competition between urban and inner-city neighborhoods across the city provides. Hence, Identify the spatial distribution of facilities and adhere to a balanced distribution of these facilities is essential. This is influenced by several factors. Spatial data models and tools that are designed in geographic information systems can identify and measure the spatial distribution of financial institutions and credit and to determine the factors influencing the spatial distribution of this facility are used. This research aimed to investigate the spatial distribution of financial institutions and credit in Ardabil and to assess the relationship between population density and the distribution of financial centers in the city and to identify factors influencing the spatial distribution of these facilities is done. To measure the spatial distribution of financial institutions and credit nearest neighbor models, the standard deviation curves and clustering high and low, in order to examine the spatial correlation between population density and the number of financial centers index and for modeling the factors affecting the distribution of bivariate Moran These facilities spatial regression model and ordinary least squares and geographical weight regression(GWR) is used. The results of the research findings show that financial institutions and credit Ardabil to cluster in north and south direction the city has established. Between the population and the number of financial centers in each area as well as spatial autocorrelation, there was a weak positive, indicating little attention to this factor is the positioning of financial institutions and credit. Also geographical weighted regression model with determination coefficient of 0.88 and adjusted coefficient of determination of 0.84 indicating influence of independent variables in the spatial distribution of financial and credit institutions.