Analysis of the Affecting Economic Components on Sustainable Housing (Case Study: Kermanshah City)

In recent years, the physical development of the city of Kermanshah can be seen in indicators such as horizontal expansion or external development, the per capita non-realization of service spaces - suggested by the comprehensive plan, and the lack of fair distribution of services. The result of this issue is housing and its instability in access to economic indicators with features such as lack of access and quality, economic inability, absence or deficiency in monitoring construction, which has led to the instability of the housing sector. According to the nature of the subject and its general purpose, the present research was of a descriptive and analytical type and based on survey and interview methods and expert-oriented questionnaire tools, including 50 experts with a purposeful sampling method. In order to measure the influence of 25 economic components of sustainable housing, t-test and regression in SPSS software and spatial autocorrelation and spatial clustering analysis in ArcGIS have been used. According to the results, the variables of bank credit facilities and subsidies have a far greater contribution compared to other variables in predicting the dependent variable, so that a unit change in the standard deviation of bank credit facilities and subsidies causes the standard deviation of the dependent variable (stable housing) to Change the size of 56 and 50%. While a unit change in the standard deviation of the wholesale and retail variable of construction materials only causes the standard deviation of the dependent variable to change by 2%. Also, the bank credit facility variable is the only variable that shows a significance level of 0.05 and this variable can have a significant effect on sustainable housing. the results of spatial autocorrelation, while there are spatial effects in the model, the difference of sustainable housing indicators in the 8 regions of Kermanshah metropolis with three factors of distance, degree of concentration and access factor is significant at a high level. According to the statistics of the spatial dependence test, the shock caused by the price change of one region has spread to other regions, and its significant relationship with other physical and social components of housing, especially the pattern of distribution or population density, tells.