فصلنامه علمی پژوهشهای فضا و مکان در شهر

آینده‌پژوهی توسعۀ شهر چابک در راستای تاب‌آوری و پویایی شهری کلان‌شهر تهران

نوع مقاله : مقاله پژوهشی

نویسنده

نوید آهنگری

دکتری جغرافیا و برنامه‌ریزی شهری، دانشگاه خوارزمی، تهران، ایران

https://doi.org/10.22034/jspr.2025.2069072.1155
چکیده
شهر چابک، پاسخی نوین به تحولات پیچیده و چالش‌های نوظهور است که با بهره‌گیری از فناوری‌های هوشمند و حکمرانی داده‌محور، زمینۀ تاب‌آوری و پویایی شهری را برای دستیابی به توسعۀ آینده شهری فراهم می‌کند. در این راستا، پژوهش با هدف آینده‌پژوهی توسعۀ شهر چابک در راستای تاب‌آوری و پویایی شهری کلان‌شهر تهران تدوین شده است.
روش پژوهش رویکرد آینده‌پژوهی است که از لحاظ هدف کاربردی و به لحاظ نوع توصیفی-تحلیلی است. روش گردآوری داده‌ها کتابخانه‌ای و پیمایشی بر اساس روش دلفی بوده است. جامعۀ آماری خبرگان متخصص در مطالعات شهری می‌باشند که حجم نمونه به صورت هدفمند با روش نمونه‌گیری گلوله برفی‌70 ‌نفر انتخاب شده است. در بخش تجزیه و تحلیل برای ارزیابی، زمینه‌سازی و رتبه‌بندی شاخص‌ها از روش ماتریس اثرات متقابل (MICMAC) و برای تدوین سناریوهای نهایی از سناریو ویزارد (SCENARIOWIZARD) استفاده شده است.
شاخص اتکا به منابع پاک بیشترین تأثیرگذاری و برنامه‌ریزی مشارکتی بیشترین تأثیرپذیری را دارند. همچنین، تصمیمات داده‌محور و بازیافت مواد به‌عنوان پیشران‌های کلیدی شناخته شدند، درحالی‌که شاخص‌های رفاه اجتماعی و فرهنگ‌سازی زیست‌محیطی بیشتر تأثیرپذیر و کمتر تأثیرگذار هستند. در تحلیل سناریو، پنج حوزۀ کلیدی توسعه شامل فناوری‌های نوین، تاب‌آوری اقلیمی، اقتصاد دیجیتال، آموزش مستمر و زیرساخت‌های هوشمند شناسایی شده است که هریک بر پایداری و کارآمدی کلان‌شهر تهران تأثیرات متنوعی دارند.
توسعۀ شهر چابک مسیر تحقق مدیریت هوشمند، پویا و تاب‌آور را در کلان‌شهر تهران هموار ساخته و زمینه پاسخ‌گویی مؤثر به چالش‌های پیچیده شهری آینده را فراهم می‌کند.

کلیدواژه‌ها

آینده‌پژوهی
شهر چابک
تاب‌آوری شهری
پویایی شهری
کلان‌شهر تهران

موضوعات

عنوان مقاله English

Foresight of Agile City Development for Urban Resilience and Dynamism in the Metropolitan City of Tehran

نویسنده English

NAVID AHANGARI
PhD in Geography and Urban planning, Kharazmi University, Tehran, Iran.
چکیده English

Introduction
Cities are dynamic institutions continuously undergoing complex and unpredictable changes influenced by social, economic, environmental, and technological factors. Facing challenges such as climate change, pandemics, energy crises, and natural hazards, the need to reassess urban responsiveness capacities is more urgent than ever. These conditions have revealed the inefficiencies of traditional planning approaches and strengthened the trend toward innovative models like the "Agile City." An Agile City emphasizes smart governance, flexible infrastructures, efficient social services, and advanced technologies, pursuing goals beyond mere resilience to threats by intelligently redefining urban development pathways. This model integrates dynamism, resilience, data-driven decision-making, and civic participation, prioritizing environmental impact reduction, energy efficiency enhancement, and optimal resource management. Its realization requires a deep understanding of the interaction between space, citizens, and technology—a relationship where individual decisions across living, working, and recreational environments are intertwined with the city’s spatial and functional structures and evolve over time. Technologies such as the Internet of Things (IoT) and augmented reality enable real-time environmental data analysis, rapid decision-making, and improved efficiency in resource management, transportation, energy distribution, and pollution control. However, the gap between theoretical discourse and practical guidelines, alongside a shortage of operational research, poses significant barriers to actualizing the Agile City. Urban foresight with this approach is an indispensable necessity for achieving long-term resilience and sustainability. Within this framework, Tehran—a metropolis characterized by heterogeneous urban morphology, rapid population growth, and weak local governance—is highly vulnerable to environmental threats and requires an agile model more than ever; a model that identifies key indicators, develops developmental scenarios, and employs a qualitative-futures approach to enhance the city’s dynamism and resilience.
 
Materials and Methods
This research adopts a futures studies approach and is applied in purpose and descriptive-analytical in type. Data collection was conducted through library research, document analysis, and surveys utilizing the Delphi method. The Delphi panel was selected through purposive sampling based on criteria including theoretical mastery, practical experience, willingness and ability to participate, and accessibility. The expert population comprised university professors, urban planning managers from the municipality, IT experts, urban resilience researchers, and urban regeneration consultants. Due to the absence of a comprehensive database, snowball sampling was employed, resulting in a sample size of 70. Initially, nine components and 48 indicators were identified as drivers, then reviewed by experts, narrowing down to 30 final indicators for analysis. A semi-structured questionnaire was distributed among experts who evaluated variables’ influence and dependence using a cross-impact matrix with scores of 0 (no effect), 1 (weak), 2 (moderate), 3 (strong), and P (potential effect). Cross-impact analysis was performed using MICMAC software, and final scenarios were developed with Scenario Wizard to extract key indicators influencing the system’s future.
Results
Analysis of the direct impact matrix showed that out of 900 cells, 826 (91.78%) had non-zero values, with the highest frequency pertaining to strong and moderate influences, reflecting extensive and robust relationships among indicators. Among influential and dependent indicators, reliance on clean energy sources and energy consumption optimization had the highest direct influence, whereas climate impact assessment and mitigation had the lowest. Participatory planning showed the highest direct dependence, while digital business and platform expansion had the least. Regarding indirect effects, data-driven decisions had the greatest influence, and reliance on clean energy had the least. Direct and indirect impact diagrams illustrated complex interrelations of varying intensities among indicators, identifying key metrics for smart policymaking in Tehran’s urban governance. Indicators were categorized into five zones: Zone 1 (bilateral with high influence and dependence, e.g., material recycling and new technologies), Zone 2 (influential with high influence and low dependence, e.g., data-driven decisions and climate resilience), Zone 3 (dependent with low influence and high dependence), Zone 4 (independent with low influence and dependence), and Zone 5 (regulatory with balanced influence and dependence). Ranking showed reliance on clean energy and energy optimization leading in influence and dependence, and climate impact assessment ranking lowest. Scenario analysis via Scenario Wizard assessed these five zones under strong, plausible, and weak scenarios depicting various futures for Tehran’s technology, digital economy, infrastructure, and education, ultimately enhancing intelligent decision-making and effective urban governance policies.
 
Discussion and Conclusion
In today’s complex and high-risk world, futures studies have become essential tools for designing and managing resilient and agile cities. Tehran faces challenges including unbalanced urban expansion, infrastructure strain, air pollution, and climate change, requiring scenario-based and agile approaches in planning and governance. This study identified key drivers for Tehran’s agile city development, with data-driven decision-making as paramount. Without up-to-date data governance, anticipating and responding swiftly to urban threats is hindered, consistent with recent studies on smart city data reliance. Circular economy and resource recycling were highlighted as critical drivers, emphasizing that agile city development extends beyond technology to energy efficiency and resource recirculation. Reliance on clean energy also emerged as a vital driver reinforcing ecological resilience. Conversely, indicators such as participatory planning and institutional interaction showed highest dependence, underscoring social cohesion’s role in achieving urban agility. Intelligent traffic management and smart transportation function as regulatory indicators supporting system performance in crises. Analysis of three potential scenarios—strong, plausible, and weak—revealed Tehran’s future could range from sustainable to chaotic depending on institutional integration, technology, and data-driven governance. Ultimately, the research offers a practical model for enhancing Tehran’s resilience but faces limitations like incomplete stakeholder participation and weak dynamic data, necessitating further studies. Advanced analytical methods and local engagement are recommended to design more precise scenarios.

کلیدواژه‌ها English

Futures Studies
Agile City
Urban Resilience
Urban Dynamics
Metropolitan Tehran

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