ارزیابی فضایی و اجتماعی عوامل موثر بر قیمت مسکن، مطالعه موردی: شهر ارومیه

A B S T R A C T
The housing sector's performance in developing countries has become acute and critical, and the share of housing costs in urban households accounts for 60-70%. Housing prices are influenced by economic, political, social, physical, etc. components and are consistently reproduced. In terms of the purpose, the current research is of an applied type, which was carried out using a descriptive-analytical method. To evaluate and analyze the spatial and social patterns affecting housing prices through the colonial competition algorithm and to spatialize the studied indicators, the Tracking Analyst Tools method has been used. According to the results, more than 50% of the population distribution pattern was inhabited in an area equal to 1585801.6 square meters with cluster and zone functions. In connection with the basic housing price index, 41.7 of the residential use levels are distributed in the higher-than-average price range with 5-10 million tomans per meter and above. Among the social variables, the index of the geographical direction of population distribution and ethnic and cultural clusters based on the majority of residents in the neighbourhoods are known as the most important social factors affecting the growth of urban housing prices. The index of the geographical direction of population distribution as a control variable has hurt housing price growth and is significant at a high level; This means that areas with lower population distribution and development have had lower price growth
Extended Abstract
Introduction
As the 10th largest city in Iran, Urmia metropolis has faced intense physical and demographic development and various ethnic migrations during the past two decades. Based on the evidence, the gap in housing prices in different areas and neighborhoods of the city clearly shows the failure of housing planning and the distribution of facilities and services in this city, which causes the formation of bipolar and multipolar neighborhoods and ethnic-linguistic segregation according to the economic and social base of people. In this way, the function of price plays a more prominent role in separating and doubting Urmia's noble, cultural, and poor neighborhoods. At the same time, this kind of urban development is contrary to the principles of sustainable urban development, which can cause many problems in managing a city in the future.
Concerning the above, it can be added that among the different regions of Urmia city, the distinct and prominent role of several prosperous and high-income northern regions with high volumes of construction and buying and selling strengthens the possibility of the role of price drivers between regions and is proposed as the first hypothesis of the present study. In this way, despite the difference in housing price levels in different regions within a geographical area, the trend of prices and the direction of fluctuations are very similar between regions. In each region, due to the interruptions in the housing market and the high correlation observed in the prices, the influence of past values on future prices is strong and impressive. However, the important question in this research is whether, in addition to the past values of prices in one region and economic factors, values with price breaks in other regions can also affect the formation of prices in one region or other regions. In other words, can the fluctuation of housing prices in one or more areas in Urmia city be the source and trigger of price movements in other areas concerning spatial and social factors? In fact, the research questions can be asked as follows:
 
-What are the most important spatial and social indicators affecting housing prices in Urmia?
-What are the most important reflections of spatial differences in the formation of housing price patterns between city areas?
 
Methodology
In terms of the purpose, the research is of an applied type, which was carried out by a descriptive-analytical method based on documentary library studies and field investigations. Considering the nature of the data and the impossibility of controlling the behavior of the effective variables in the problem, this research was of a non-experimental type. It was carried out within the framework of the analytical-case model. The studied community was the statistical block and all urban and residential uses of Urmia city. The main data was obtained mainly by using the data of the urban blocks of the Iranian Statistics Center and the available documents, including the comprehensive and detailed plan. Available information layers, field observations, targeted questioning of experts in the field, and specific data produced in the GIS geographic information system software environment, as well as document and library study, have provided another part of the information needed for the article. Since there is no strong and explicit rule about the selection method and the number of specialists, and their number depends on the homogenous or heterogeneous factors of the sample and the goal or scope of the problem, the population under investigation in this research includes 30 specialists with a purposeful sampling method.
 
Results and discussion
The spatial autocorrelation coefficient shows how much the housing price growth in Urmia city has been affected by the shock on the growth pattern and population distribution in the city. Among the social variables, the index of the geographical direction of the population distribution and ethnic and cultural clusters based on the majority living in the neighborhoods are known as the most important social factors affecting the growth of urban housing prices. The index of the geographical direction of population distribution as a control variable has a negative effect on housing price growth and is significant at a high level; this means that areas with lower population distribution and growth have had lower price growth. In this way, population growth and cluster distribution are considered among the most important driving factors of urban development.
Investigating the final situation of housing prices in Urmia city, the price changes were shown at the level of 12 indicators. So that at this stage, after collecting the mentioned indicators in the ARC-GIS software environment, the final situation of the price of residential use concerning spatial and social factors, separately from very low to a very high level, for planning income groups and household deciles in the direction of the program Urban planning and management to deal with housing speculation and possible crises are categorized, which can be seen by different levels and colors. Significant parts of Urmia city's fabric are in the middle to very high price range. In such a way that the central part of the city, in accordance with the historical core, due to having commercial-administrative and mixed residential use on the one hand, the lack of standard structural system and sustainable materials, as well as the lack of financial ability of the residents, has caused the formation of areas with an unstable housing pattern.
 
Conclusion
According to the population concentration or differentiation index results, more than 50% of the population distribution pattern has been inhabited in an area equal to 1585801.6 square meters with cluster and area functions. Concerning the basic housing price index, 41.7 of the residential use levels are distributed in the price range above the average with 5-10 million per meter and above. Among the social variables, the index of the geographical direction of the population distribution and ethnic and cultural clusters based on the majority living in the neighborhoods are known as the most important social factors affecting the growth of urban housing prices. The index of the geographical direction of population distribution as a control variable has a negative effect on housing price growth and is significant at a high level; this means that areas with lower population distribution and growth have had lower price growth.
 
Funding
There is no funding support.
 
Authors’ Contribution
 Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.