Factors affecting the housing prices in the metropolis of Tehran

被引:0
|
作者
Rajaei, Seyed Abbas
Mottaghi, Afshin
Sahar, Hussein Elhaei
Bahadori, Behnaz [1 ]
机构
[1] Univ Tehran, Fac Geog, Dept Human Geog, Tehran, Iran
关键词
Spatial analysis; Housing prices; Geographically weighted regression; Tehran metropolis; ArcGIS; Factors on housing prices; GEOGRAPHICALLY WEIGHTED REGRESSION; SPATIAL VARIATION; ACCESSIBILITY; LANDSCAPE; HANGZHOU; MODELS; IMPACT; SCALE;
D O I
10.1108/IJHMA-10-2023-0135
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
PurposeThis study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).Design/methodology/approachThe method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units' price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.FindingsBased on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.Originality/valueIdentifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.
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页数:24
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