Modeling the effects of economic development indicators in 22 districts of Tehran metropolis
Subject Areas :arman moslemi 1 , jamileh tavakoli nia 2 , zohreh fanni 3 , lotfali kozehgar kaleji 4
1 - دانشجوی دکترا جغرافیا و برنامه ریزی شهری دانشگاه شهید بهشتی
2 - Associate Professor, Department of Human Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran
3 - Professor, Department of Human Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran
4 - Assistant Professor, Department of Human Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran
Keywords: Tehran, economic development, dispersion, Leveling, Urban Economy,
Abstract :
the most important and complex developments in the last half century is the rapid growth of urbanization and the problems that exist in the development of less developed or more developed cities. Inequality in having indicators of urban economic development changes the spatial structure of the city; Therefore, the purpose of this study is to model the effects of economic development indicators in 22 areas of Tehran. The present research is based on the purpose of applied research and based on the nature and method of descriptive-analytical research and the data collection method is collected as a field (questionnaire). The statistical population of this study was all the citizens of Tehran in 1400 who according to Cochran's formula 384 people were randomly asked as a sample. The validity of the questionnaire was confirmed by a panel of experts and Cronbach's alpha coefficient was used to evaluate the research variables and reliability of the questions. The reliability of the questionnaire of citizens and experts has been confirmed with values of 0.90 and 0.93, respectively. After conducting field studies, for data collection and data analysis from statistical methods (factor analysis and correlation analysis) was performed using SPSS software. In addition to the structural equation model (SEM) using the partial least squares method in software (SMART) PLS3) AHP technique and Expert Choice software have also been used to level the regions in terms of economic development indicators. The results of factor analysis showed that the four identified factors were able to explain 75% of the variance of the effects of economic development indicators on the 22 metropolitan areas of Tehran. The results obtained from structural equations showed that among all indicators of economic development, T-coefficients between indicators (welfare-trade, industrial, resources and mines and goods-services) are above 1.96, ie the relationship between independent and dependent variable dimensions in the sample population with 99% confidence Confirmed. The results obtained from the AHP technique in the Expert Choice software showed that the highest score of the economic development index belongs to the 3rd district of Tehran and the lowest coefficient belongs to the 17th district.
Extended Abstract
Introduction
Cities are growing today, and in addition to increasing physically, their populations are growing (Catney, 2018: 138; Baffoe, 2021: 176). More than half of the world's population lives in cities, and it is expected that by 2050 the world's urban population will reach 75 or 80 percent (Rshtbar et al, 2019: 109; World Bank, 2019: 165). It continues and this leads to population concentration in cities, growth of service sector and consequently increase of GDP in cities (Musterd & et al, 2017: 38) Tehran is one of the 10 underdeveloped metropolises among the 124 metropolises in the world that suffer from problems such as poverty and abnormality, unemployment, wide gaps in living standards, inequality and imbalance in urban areas. In such a way that there is a significant difference between the 22 districts of Tehran in terms of economic development. Less developed and undeveloped areas are mostly in the south and southeast, and medium and relatively developed areas are located in the center and west of Tehran, and developed areas are located in the north of the city. In this regard, urban management and policy makers play an important role that the recognition and adjustment of these inequalities and planning for these problems should be on their agenda. In fact, regional policy-making has been proposed as a conscious and public effort of the government to change the spatial distribution of economic and social phenomena such as population, income, government revenues, production of goods and services, transportation facilities and other social and economic infrastructure and even political power. The study of economic inequalities between urban areas is one of the most important and fundamental tasks for better planning and management for more balanced economic development and achieving social justice. Therefore, the first step to achieve optimal conditions is to know its current state. Accordingly, in order to achieve appropriate economic conditions, it is necessary to study the current conditions of society and examine the movement of society. Therefore, the purpose of this study is the economic development of 22 districts of Tehran metropolis in the form of the following question:
1- What is the relationship between the economic development indicators of the 22 districts of Tehran metropolis?
2- Which of the 22 districts of Tehran metropolis have been able to find a suitable position among other districts?
Methodology
The present study is quantitative in terms of applied purpose and in terms of descriptive and analytical methods. In order to collect data from documentary and field methods, information has been prepared and analyzed and combined. In the documentary stage, information has been collected from books, publications, statistics, maps and websites as well, in order to identify and study the indicators of economic development (Statistics Center of Iran and statistical yearbook of 2016 in Tehran). A questionnaire was used to collect field data. The questionnaire was designed based on 25 indicators of economic development in order to measure the importance of each indicator and their performance with a Likert scale ranging from a very low value of 1 to a very high value of 5. The questionnaire was distributed according to the population (20-70 years old) of each region. The statistical population of the study consists of all 22 districts of Tehran metropolis. According to the 2016 census, Tehran metropolis has 2911065 households and a population of 8693706. Using Cochran's formula, 384 citizens and 15 experts were selected by snowball method as a sample. 10 people finally answered; The validity of the questionnaire was confirmed by a panel of experts and the reliability of the questionnaire of citizens and experts was confirmed with values of 0.90 and 0.93, respectively. Statistical methods in this study are descriptive statistics (mean and standard deviation) and inferential statistics (using factor analysis and correlation analysis) using SPSS software. In addition, software (SMART PLS3) was used to model structural equations (SEM). In this study, AHP technique and Expert Choice software were used to weight the criteria and sub-criteria to level the regions in terms of economic development indicators.
Results and discussion
The results of factor analysis test show that the four identified factors have been able to explain 75% of the variance of the effects of economic development indicators on the 22 metropolitan areas of Tehran. The percentage of explanation of each of the identified factors are in order of importance: the first factor is 13.890%, the second factor is 571.51%, the third factor is 2.971% and the fourth factor is 2.330%.In order to investigate the relationship between economic development indicators, Pearson correlation coefficient has been used. ), (0.215) and (0.543) and there is a significant relationship at the level of 99%.
Conclusion
In order to investigate the relationship between economic development indicators, Pearson correlation coefficient has been used. ), (0.215) and (0.543) and there is a significant relationship at the level of 99%. Also, there is a significant relationship between the industrial index with mineral resources and goods and services to education with a correlation coefficient (0.264) and (0.612) at the level of 99%. The highest correlation coefficient between the industrial index and goods and services (0.612) and There is the lowest value of correlation coefficient between trade-welfare index with mineral resources (0.612) which is consistent with the results of Mirzaei et al. (2014), Maleki et al. (2015), Mohammadkhani et al. (1400); Also to test the first hypothesis of the structural equation model (SEM) using the partial least squares method in software (SMART PLS3) which according to the results obtained from this test, the first hypothesis of the research is confirmed by the results (Qiao et al , 2021), (Beijing etal, 2020) and (liu et al, 2021) are consistent; AHP technique and Expert Choice software have been used to weight the criteria for leveling the regions in terms of economic development indicators. The results obtained from the highest score of economic development index belong to Tehran's 3rd urban region and the lowest coefficient belongs to 17th region. As shown in the figure, the highest coefficients are related to 3, 1, 2, 6 and 5 urban areas of Tehran, respectively, and the lowest coefficients are related to 17, 19, 18, 15, 16 and 20 urban areas of Tehran, respectively. Which is consistent with the results of Mirzaei et al. (2014), Mohammadkhani et al. (1400), Maleki et al. (2015), Sadeghi and Zanjari (2015) and Jafari et al. (2015). The superiority of the present study over other studies in this regard has been to examine the impact of economic development indicators on each other using factor analysis and correlation analysis as well as modeling using structural equations with software (SMART PLS).
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