Identifying urban neighborhoods with higher potential for social investment using GIS-FIS approach

Abstract

Today, participation in social investment is a critical concern of urban management in metropolitan areas. To be effective in both public and private sectors, such participation requires an accurate knowledge of geographical distribution of resources and social needs in different parts of the city in order to better manage these investments. To this end, the present research aimed at providing an objective and tangible integrated approach to identify urban neighborhoods with high potential for social investment. The research area was neighborhoods located in Mashhad, Iran. Thirty-one criteria in three dimensions of empowerment, education, and culture were identified. Having determined, normalized, and weighted the values of each criteria in different neighborhoods using the analytic hierarchy process (AHP) method, the weight scores of each neighborhood in each dimension were added up by GIS approach and Arc GIS 10.1 software. Then, in order to conclude the overall status of social investment in different neighborhoods, a fuzzy inference system (FIS) was designed in the MATLAB 2014a environment according to experts’ opinions. Finally, based on the output of the designed system, the overall status of each neighborhood studied was determined in terms of social investment and neighborhoods with high potential for social investment were identified. The approach presented provides an insight for urban mangers, companies, and philanthropic investors to invest more effectively given the appropriate social investment opportunities.