Predicting and Structural Explicating of the Factors affecting Population Changes in Ahvaz Metropolis

جغرافیا و توسعه فضای شهری

Volume 11, Issue 3, December 2024, Pages 83-106   

Document Type: Scientific-Research

DOI: 10.22067/jgusd.2022.78296.1242

Authors

Mahnaz Hosseini Siahgoli¹; Saeed Amanpour^{* 2}; Saeed Maleki³

¹PhD Candidate in Geography and Rural Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

²Associate Professor, Department of Geography and Urban Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

³Professor, Department of Geography and Urban Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

Abstract

Extended Abstract
1. Introduction
City as a living and dynamic entity has always been changing and developing. That is, rapid changes of urban life have brought about different concepts, theories, methods, and those issues related to the cities. One of the significant causes of urban changes is population. It is also one of the key elements of socio-economic development. The exact prediction of the population structure will make a significant ground for future economic development. Accordingly, awareness of the population structure and trend, as well as its dimensions and extent, will be an ensuring tool for effective decision-making and planning for all issues. Therefore, attention to population structure is a must. This study tried to explore the trend of population changes in Ahvaz metropolis. It took into account the components that shape and change the population structure. The purpose was to include human factor in the related issues. For the purpose, the macro population component, including age, gender, population growth, population density, fertility, literacy, migration, etc. were included. The aim of the inclusion was to identify the criteria of the population structure and to explicate the status of these components at the city level, and finally, to predict and provide desirable scenarios for improving the population of the city. This study tried to see: to what extent are the population components effective in changing the population of Ahvaz? and, what are the most significant population scenarios in Ahvaz?
2. Method
This applied study used a descriptive-analytical method. At the first stage, using Delphi method and based on the opinions of 15 university professors and experts of relevant organizations, the components that explain population changes were identified. In the analysis stage, 11 factors were used as strong factors that influence on population changes in Ahvaz metropolis. Interpretive Structural Modeling (ISM) and MicMac software were used for this purpose. Finally, using Spectrum software, the population was predicted in horizon of 2051.
3. Results
At first the factors affecting population change in Ahvaz metropolis were identified. Then, these factors were entered into a Structural Self-Interaction Matrix (SSIM). To do this, a questionnaire was designed. This questionnaire asked the respondents to specify the type of pairwise relationships between the factors. SSIM states that the opinions of experts should be obtained through various management techniques such as brainstorming, nominal group, and development of content relationships between variables. Therefore, the self-interaction matrix was formed using four modes of conceptual relationships and was completed by 15 university professors and experts of the subject matter. The data was summarized based on the structural-interpretive modeling method, and the final structural self-interaction matrix was formed. The results showed that seven factors of age structure, gender structure, population growth, fertility, mortality, migration, and life expectancy (with a penetration power of 11) had exerted the greatest impact, and unemployment, active population, and literacy, with a total penetration power of 11, and the population density with a penetration power of 6 exerts the least impact. Regarding the dimensions, the results showed that 7 factors (with a penetration power of 11) cab be considered the main dimensions of population change in Ahvaz. Except for the population density that is in the group of dependent variables, other factors are in the first group; that is, related variables that according to the experts have high penetration power and dependence and exert the greatest impact on population changes of the city. The decreased fertility and emigration were identified as the two main factors in reducing the population growth of Ahvaz. The population growth rate was 4.95 in 1976 and reached 3.34 in 2016. This number was predicted to be 1.82 in the horizon of 2051. Moreover, the fertility rate is below the replacement level. The emigration status of this city that has always had negative over the past decades. The two factors were identified as the two main factors in the sharp decline of the population growth of the city. Several studies have identified the two factors as the main factors in reducing the population growth rate in human settlements.
4. Discussion and Conclusion
The results revealed that gender structure, population density, fertility, unemployment, active population, and literacy are among the factor that exert the most influence on population changes. The factors of age structure, population growth, mortality, migration, and life expectancy are among the most affected factors. Moreover, the results of MicMac revealed that all factors except the population density are among the related variables. Finally, the best scenario for population prediction in the horizon of 2051 was the third scenario (reduced fertility). The scenario recorded more than 98% accuracy in population estimation.

Keywords

Population; Population Changes; Traditional Structure; Spectrum; Structural Self-Interaction Matrix

References

1. بهاروند، پ. (1400). بررسی اثر تغییرات جمعیتی و سرمایه انسانی بر رشد اقتصادی در ایران. پایان نامه کارشناسی ارشد، گروه اقتصاد،دانشگاه شهید چمران اهواز، دانشکده اقتصاد و علوم اجتماعی.
2. جعفری امیدوار، ه. (1399). پیامدهای امنیتی تغییرات جمعیتی در ایران. کرمانشاه: پایان نامه کارشناسی ارشد، دانشگاه رازی ، دانشکده علوم اجتماعی و تربیتی.
3. خسروی، م. (1397). بررسی چالش های سیاسی جمعیت ایران در دهه آینده. پایان نامه کارشناسی ارشد، گروه علوم سیاسی ، دانشگاه بین‌المللی امام خمینی (ره)، دانشکده علوم اجتماعی.
4. دانشور، ف.؛ صابری، ح. (1400). آینده‌پژوهی راهبردی کلانشهر اصفهان (بر مبنای آنالیز چالش‌ها با مدل علت و معلولی). جغرافیا و توسعه فضای شهری، 8(1)، 145-164.
5. زنجانی، ح. (1376). تحلیل جمعیت شناختی. قم: انتشارات سمت.
6. شایان، ح. (1390). تحلیلی بر وضعیت مرگ و میر در استان خراسان رضوی. تهران: همایش تحلیل روندهای جمعیتی.
7. شریف زاده، ا. (1401). تدوین سناریوهای موثر بر گذار از پیامدهای امنیتی سالخوردگی جمعیت در ایران با رویکرد آمایش سرزمین. پایان­نامه کارشناسی ارشد، ارومیه: دانشگاه ارومیه، دانشکده ادبیات و علوم انسانی.
8. شمس قهفرخی، م. (1394). بررسی تأثیر ویژگی های اشتغال زنان بر باروری (مطالعه موردی شهر اصفهان)،
9. شیری، م.، و نوراللهی، ط.(1391). تغییرات ساختار جمعیت و تقاضای اجتماعی آموزش عالی در ایران. مجله‌ی بررسی‌های آمار رسمی ایران. ۲۳ (۱) ،۱۰۲-۸۳.
10. فولادی، م. (۱۳۹۸). تحلیلی بر تغییر و تحولات جمعیتی در ایران؛ با تاکید بر فرصت طلایی پنجره جمعیتی. معرفت فرهنگی اجتماعی، 10(3)، ۴۳-۶۰.
11. فولادی، م.(۱۳۹۹). تحلیل بر پیامده‌های کاهش باروری و جمعیت در ایران. معرفت فرهنگی اجتماعی، 11(3)، ۶۹-۸۸.
12. قاسمی، ن. (1394). بررسی و تحلیل تأثیر ابعاد جمعیتی و فعالیتی بر ساختار فضایی استان آذربایجان غربی. تهران: دانشگاه تربیت مدرس، دانشکده هنر.
13. قربانی، ر.، علیزاده، ه.، و کرمی، س. (1400). تحلیلی بر علل نزول جایگاه کلان شهر تبریز در نظام شهری ایران و پیش بینی جمعیت و جایگاه آن تا افق 1410. آمایش سرزمین، 13(1 )، 83-114.
14. کرمی، س. (1399). آینده­پژوهی تقاضای مسکن شهری در انطباق با تحولات ساختاری جمعیت (مورد مطالعه کلانشهر تبریز). رساله دکتری، تبریز:دانشگاه تبریز، دانشکده برنامه­ریزی و علوم محیطی.
15. گودرزی، و.، و وارثی، ح. (1401). تحلیل سیستمی عوامل کلیدی مؤثر بر برنامه ریزی مسکن پایدار با رویکرد آینده پژوهی (مطالعه موردی؛ مناطق 22 گانه شهر تهران). جغرافیا و توسعه فضای شهری، 19،109-126.
16. ملک‌زاده، ن.، بزاززاده، م.، و رفیعیان، م. (1395). شناسایی و تحلیل عوامل کلیدی مؤثر بر توسعۀ شهری با رویکرد آینده‌نگاری (مطالعۀ موردی: کلان‌شهر کرج). جغرافیا و توسعه فضای شهری، 3(2)، 35-52.
17. منصوریان، ف. (1395). سناریوهای آینده رشد جمعیت در کلان شهر تهران. پایان نامه کارشناسی ارشد، تهران: دانشگاه تهران، دانشکده مدیریت.

 

18. Bastianoni, S., Niccolucci, V., Pulselli, R.M., Marchettini, N. (2012) Indicator and indicandum: “Sustainable way” vs “prevailing conditions” in the Ecological Footprint. Ind., 16, 47–50.
19. Benassi, F., & Carella, M. (2022). Modelling geographical variations in fertility and population density of Italian and foreign populations at the local scale: a spatial Durbin approach for Italy (2002–2018). Quality & Quantity, 1-18.
20. Benassi, F., Busetta, A., Gallo, G., Stranges, M. (2021). Local heterogeneities in population growth and decline. A spatial analysis for Italian municipalities. Paper presented at the 50th Scientific Meeting of the Italian Statistical Society (SIS), Pisa, June 21–25.
21. Campisi, N., Kulu, H., Mikolai, J., Klüsener, S., Myrskylä, M. (2020). Spatial variation in fertility across Europe: Patterns and determinants. Population Space Place, 26(4),1-50.
22. Chai, L., & Xu, Z. (2016). Forecast of China population under different fertility policy. Open Journal of Social Sciences, 4(7), 213-229.
23. Chen, L., Mu, T., Li, X., & Dong, J. (2022). Population Prediction of Chinese Prefecture-Level Cities Based on Multiple Models. Sustainability, 14(8), 4844.
24. Costanza, R., McGlade, J., Lovins, H., & Kubiszewski, I. (2014). An overarching goal for the UN sustainable development goals. Solutions, 5(4), 13–16.
25. GAO, Z., Tan, N., Geddes, R. R., & Ma, T. (2019). Population distribution characteristics and spatial planning response analysis in metropolises: A case study of Beijing. International Review for Spatial Planning and Sustainable Development, 7(1), 134-154.
26. Genereux, A. (2007). A review of migration and fertility theory through the lens of African immigrant fertility in France. Rostock: Max Planck Institute for Demographic Research.
27. Kim, H., & Kim, D. (2022). Changes in Urban Growth Patterns in Busan Metropolitan City, Korea: Population and Urbanized Areas. Land, 11(8), 13-19.
28. Meisner, J., & Albrechtsen, A. (2022). Haplotype and population structure inference using neural networks in whole-genome sequencing data. Genome Research, gr-276813.
29. Naccarato, A., & Benassi F. (2020). World population densities. Convergence, stability, or divergence? Popul. Stud.
30. Naccarato, A., Benassi, F. (2018). On the relationship between mean and variance of world’s human population density: a study using Taylor’s power law. Spat. Resour. Sci., 11(3), 307–314.
31. National Infrastructure Commission. (2016). Smart power, A report examining how the UK can balance supply and demand within the electricity market.
32. Nguyen, D. (2010). Evidence of the impacts of urban sprawl on social capital. Plann. b. Plann. Des, 37(4), 610–627.
33. Park, Y., LaFrombois, M., Heim, E. (2019). Planning for growth in depopulating cities: An analysis of population projections and population change in depopulating and populating US cities. Cities. 90. 237-248.
34. Parrado, E. A. (2015). Migration and fertility. Social Behavioral Sciences, 397-406.
35. Pendall, R., Freiman, L., & Myers, D. (2012). Demographic challenges and opportunities for U.S. housing markets. Bipartisan Policy Center.
36. Polinesi, G., Recchioni, M.C., Turco, R., Salvati, L., Rontos, K., Rodrigo-Comino, J., & Benassi, F. (2020). Population trends and urbanization: simulating density effects using a local regression approach. ISPRS Int. J. Geo Inf., 9(7), 454.
37. Salvati, L., Benassi, F., Miccoli, S., Rabiei-Dastjerdi, H., & Matthews, S.A. (2020). Spatial variability of total fertility rate and crude birth rate in a low-fertility country: Patterns and trends in regional and local scale heterogeneity across Italy, 2002–2018. Geogr., 124.
38. Salvati, L., Carlucci, M., Serra, P., & Zambon, I. (2019). Demographic transitions and socioeconomic development in Italy, 1862–2009: a brief overview. Sustainability, 11(1), 242.
39. Terama, E., Clarke, E., Rounsevell, M. D., Fronzek, S., & Carter, T. R. (2019). Modelling population structure in the context of urban land use change in Europe. Regional environmental change, 19(3), 667-677.
40. Vitali, A., & Billari, F.C. (2017). Changing determinants of low fertility and diffusion: a spatial analysis for Italy. Space Place, 23(2), 1-38.
41. Warami, H., & Marit, E. L. (2022). Characteristics, fertility, and mortality of the population in Teluk Bintuni Regency, West Papua Province. International Journal of Educational Research & Social Sciences, 3(2), 728-746.

Xu, M., & Cohen, J.E. (2019). Analyzing and interpreting spatial and temporal variability of the United States county population distributions using Taylor’s law. PLoS ONE, 14(12), e0226096.