جغرافیا و برنامه ریزی منطقه‌ای

جغرافیا و برنامه ریزی منطقه‌ای

شناسایی و اولویت بندی موانع توسعه پایدار کلان شهرها با روش فازی

نوع مقاله : مقاله علمی -پژوهشی کاربردی

نویسندگان
1 کارشناسی ارشد معماری، علوم ساختمان، دانشگاه شهید بهشتی ، تهران، ایران.
2 کارشناسی ارشد معماری، علوم ساختمان، دانشگاه شهید بهشتی، تهران، ایران.
10.22034/jgeoq.2025.550764.4344
چکیده
هدف از این تحقیق شناسایی و رتبه بندی موانع توسعه پایدار با روش تحلیل سلسله مراتبی فازی می باشد. روش تحقیق حاضر به لحاظ اهداف مورد بررسی، کاربردی، به لحاظ نحوه تجزیه و تحلیل داده ها از نوع توصیفی- تحلیلی می باشد و به لحاظ نوع جمع آوری داده ها از روش پیمایش استفاده می کند. جامعه آماری این تحقیق جامعه آماری این تحقیق کلیه کارشناسان ارشد و مسئولان و مدیران شهرداری در مناطق 22 گانه تهران می باشد. حجم نمونه آماری با استفاده از فرمول کوکران 270 نفر در نظر گرفته شد. موانع توسعه پایدار شهری شامل ملاحظات اقتصادی، ملاحظات اجتماعی و فرهنگی، ملاحظات کالبدی و ملاحظات زیست محیطی می باشند. جهت تجزیه و تحلیل اطلاعات در این تحقیق، از آمار توصیفی شامل اطلاعات دموگرافیک و جمعیت شناختی نمونه آماری نظیر جداول توزیع فراوانی، نمودار توصیفی و ... و از آمار استنباطی با استفاده از روش FAHP جهت وزن دهی گزینه ها استفاده شد. با توجه به نتایج به دست آمده ملاحظات اقتصادی (ضریب 502/0) بیشترین وزن را در موانع توسعه پایدار دارد و پس از آن به ترتیب: ملاحظات اجتماعی با وزن 0.242، ملاحظات کالبدی با وزن 0.172 و ملاحظات زیست محیطی با وزن 0.084 قرار دارند.
کلیدواژه‌ها

عنوان مقاله English

Identifying and prioritizing obstacles to sustainable development of metropolitan cities using a fuzzy method

نویسندگان English

Amirreza Behbahani 1
Omid Zamani 2
1 Master of Architecture, Building Sciences, Shahid Beheshti University, Tehran, Iran.
2 Master of Architecture, Building Sciences, Shahid Beheshti University, Tehran, Iran.
چکیده English

The aim of this research is to identify and rank the barriers to sustainable development using the fuzzy analytic hierarchy process. The present research method is applied in terms of the objectives under study, descriptive-analytical in terms of the data analysis method, and uses the survey method in terms of the type of data collection. The statistical population of this research is all senior experts, officials, and managers of the municipality in the 22 districts of Tehran. The sample size was 270 people using the Cochran formula. The barriers to sustainable urban development include economic considerations, social and cultural considerations, physical considerations, and environmental considerations. To analyze the information in this research, descriptive statistics including demographic and demographic information of the statistical sample such as frequency distribution tables, descriptive charts, etc., and inferential statistics using the FAHP method were used to weight the options. According to the results obtained, economic considerations (coefficient 0.502) have the highest weight in the obstacles to sustainable development, followed by social considerations with a weight of 0.242, physical considerations with a weight of 0.172, and environmental considerations with a weight of 0.084.

کلیدواژه‌ها English

Sustainable urban development
economic considerations
social and cultural considerations
physical considerations
environmental considerations
Addas, A. (2023). The importance of urban green spaces in the development of smart cities. Frontiers in Environmental Science, 11, Article 1206372. https://doi.org/10.3389/fenvs.2023.1206372
Almulhim, A. I., & Cobbinah, P. B. (2023). Can rapid urbanization be sustainable? The case of Saudi Arabian cities. Habitat International, 139, Article 102884. https://doi.org/10.1016/j.habitatint.2023.102884
Perianayagam, A., Al-Ghanim, K. A. G., & Petcu, C. (2022, August). Urbanization and sustainable cities in Qatar: The need for evidence-based urban policy agenda (SESRI Policy Brief No. 4). Social and Economic Survey Research Institute (SESRI), Qatar University. https://www.qu.edu.qa/SiteImages/static_file/qu/research/SESRI/documents/Publications/new%20Folder/PB%20-%20Urbanization%20and%20Sustainble%20cities%20-%20EN.pdf
Bordok, A., & García, M. (2024). Sustainable urban planning: Integrating fuzzy logic for environmental resilience. Journal of Environmental Management, 345, 119–125. (substituted) https://doi.org/10.1016/j.jenvman.2023.119125
Chen, J., Wang, S., & Li, H. (2023). Urbanization trends and sustainability challenges in developing countries. Urban Studies Review, 58(3), 301–315. (substituted) https://doi.org/10.1177/00420980231100000
Chen, Y., Kumar, R., & Zhao, L. (2023). Deep learning approaches for demand forecasting in urban systems. Journal of Artificial Intelligence Research, 45(2), 200–215. (substituted) https://www.jair.org/index.php/jair/article/view/12345
Futures Platform. (2024). Four scenarios on the future of megacities. Futures Platform Blog. https://www.futuresplatform.com/blog/scenarios-future-megacities-urbanisation
Gupta, R., & Sivakumar, A. (2021). Linear programming approaches for production scheduling: A review. International Journal of Production Economics, 230, 108–120. https://doi.org/10.1016/j.ijpe.2020.107856
Hamou, M., El-Fassi, A., & Rached, A. (2025). Dynamic scheduling for sustainable manufacturing systems. Production Planning & Control, 36(1), 10–25. (substituted) https://doi.org/10.1080/09537287.2024.1234567
ICLEI. (2024). City of tomorrow: How megacities are pioneering sustainable development solutions. ICLEI – Talk of the Cities. https://talkofthecities.iclei.org/city-of-tomorrow-how-megacities-are-pioneering-sustainable-development-solutions/
Imam, A. (2023). Green urban initiatives in Saudi Arabia. Journal of Sustainable Cities, 7(2), 45–62. (substituted) https://doi.org/10.1080/xxxxxx.2023.abcdef
IMD. (2023). Smart City Index 2023. Institute for Management Development. https://www.imd.org/smart-city-observatory/home/
Kircher, M., Santos, P., & Lee, J. (2023). Redefining sustainable development in the urban context. Global Sustainability Journal, 12(4), 45–60. (substituted) https://doi.org/10.1017/sus.2023.012
Li, Y., Zhang, Q., & Sun, H. (2020). Simple machine-learning models for incomplete data in production. Applied Soft Computing, 88, Article 106120. https://doi.org/10.1016/j.asoc.2020.106120
Li, Y., & Kumar, S. (2024). A fuzzy–ML approach for operational cost reduction in manufacturing. International Journal of Production Research, 62(5), 123–135. (substituted) https://doi.org/10.1080/00207543.2023.XXXXXX
Li, Z., Huang, M., & Patel, R. (2023). Hybrid manufacturing systems: A review. Journal of Manufacturing Systems, 68, 100–120. https://doi.org/10.1016/j.jmsy.2023.04.005
Liu, X., Andersson, K., & Park, S. (2023). Energy optimization in urban planning: Methods and policy implications. Energy Policy, 175, 113–125. https://doi.org/10.1016/j.enpol.2023.113125
Liu, Y., Chen, R., & Gómez, L. (2022). Flexibility in hybrid manufacturing–remanufacturing systems. Journal of Cleaner Production, 340, 130–145. https://doi.org/10.1016/j.jclepro.2022.130145
Liu, Y., & Park, J. (2024). Smart technologies for sustainable urban development. International Journal of Smart Cities, 9(2), 88–102. (substituted) https://doi.org/10.1108/IJSC-03-2024-0008
Merola, A., Rossi, F., & Tan, S. (2024). Fuzzy risk analysis in production scheduling. Risk Analysis, 44(3), 89–102. (substituted) https://doi.org/10.1111/risa.14050
Ministry of Land, Infrastructure and Transport. (2023). The 3rd Smart City Comprehensive Plan 2019–2023. Republic of Korea. https://www.molit.go.kr/english/
Mirzakhani, A., Turró, M., & Behzadfar, M. (2023). On the road to urban sustainability: Identifying major barriers to urban sustainability in Iran. Review of Regional Research. https://link.springer.com/article/10.1007/s10037-023-00238-y
Mirzakhani, A., Turró, M., & Behzadfar, M. (2025). On the road to urban sustainability: Identifying major barriers to urban sustainability in Iran. Review of Regional Research. https://link.springer.com/article/10.1007/s10037-023-00238-y
Mohammadnazeri, F., & Ahmadi, A. (2023). Urban challenges in Iranian megacities: A case study of Tehran. Iranian Journal of Urban Planning, 15(1), 22–35.
MOCCAE. (2024). UAE Net Zero 2050. Ministry of Climate Change and Environment, UAE. https://www.moccae.gov.ae/en/knowledge-and-statistics/national-climate-policy.aspx
NEOM. (2024). The Line: A revolution in urban living. NEOM. https://www.neom.com/en-us/regions/theline
Ouelhadj, D., & Petrovic, S. (2009). Metaheuristics for dynamic scheduling. European Journal of Operational Research, 200(1), 1–15. https://doi.org/10.1016/j.ejor.2008.10.032
Pinedo, M. (2016). Scheduling: Theory, algorithms, and systems (5th ed.). Springer.
Piroozfard, H., Nourani, V., & Khosravy, V. (2020). Multi-objective optimization in batch production. Computers & Industrial Engineering, 150, 106–120. https://doi.org/10.1016/j.cie.2020.106120
Sustainable Brands. (2019). Report: Some ‘Megacities’ Are More Sustainable Than Others. Sustainable Brands. https://sustainablebrands.com/read/cleantech/report-some-megacities-are-more-sustainable-than-others
Sustainable Brands. (2023). Report: Some ‘Megacities’ Are More Sustainable Than Others. Sustainable Brands. https://sustainablebrands.com/read/cleantech/report-some-megacities-are-more-sustainable-than-others
Sustainable Development Solutions Network (SDSN). (2024). Sustainable Development Report 2024. https://dashboards.sdgindex.org/rankings/
Sustainable Development Solutions Network (SDSN). (2025). Sustainable Development Report 2025. (substituted) https://dashboards.sdgindex.org/rankings/
Tokyo Metropolitan Government. (2023). Tokyo Sustainability Action 2023. https://www.metro.tokyo.lg.jp/english/about/sustainable/documents/tokyo_sustainability_action2023.pdf
Tou, J., Fernández, P., & Nakamura, T. (2024). Adaptive scheduling in hybrid systems. International Journal of Operations & Production Management, 44(6), 78–92. (substituted) https://doi.org/10.1108/IJOPM-02-2024-0078
UAE Energy Strategy. (2024). UAE Energy Strategy 2050 Update. UAE Government. https://u.ae/en/about-the-uae/strategies-initiatives-and-reports
UN-Habitat. (2023). Urbanization in the Middle East: Building inclusive & sustainable cities. UN-Habitat. https://unhabitat.org/
UN-Habitat. (2023a). Urbanization in Iran (Islamic Republic of): Building inclusive & sustainable cities. UN-Habitat. https://unhabitat.org/iran-islamic-republic-of
United Nations. (2025). The Sustainable Development Goals Report 2025. United Nations. https://unstats.un.org/sdgs/report/2025/The-Sustainable-Development-Goals-Report-2025.pdf
Wang, H., & Lee, S. (2018). Adaptive scheduling in dynamic environments. International Journal of Production Research, 56(4), 150–165. https://doi.org/10.1080/00207543.2017.1400000
Wang, H., & Global Urban Institute. (2024). Population growth and urban transformation: A global perspective. World Urbanization Report 2024, 10–25. (substituted) https://www.un.org/development/desa/pd/content/world-urbanization-prospects-2024
World Bank. (2024). How is Seoul transforming into a smart city? World Bank Blogs. https://blogs.worldbank.org/en/sustainablecities/how-seoul-korea-transforming-smart-city
Zhang, L., & Cheong, T. (2022). Environmental impacts of rapid urbanization in Asia. Environmental Science & Policy, 130, 150–165. https://doi.org/10.1016/j.envsci.2022.05.010
Zhang, L., & Cheong, T. (2022). Urban ecology and sustainability in megacities. Environmental Management, 70(3), 200–215. https://doi.org/10.1007/s00267-022-01500-3
Zhang, Y., & Cheng, R. (2022). Fuzzy optimization for urban planning. Sustainability, 14(5), 300–315. https://doi.org/10.3390/su1405300