نوع مقاله : مقاله علمی - پژوهشی
نویسندگان
1 دانشجوی کارشناسی ارشد برنامه ریزی شهری،گروه شهرسازی ،دانشکده هنر و معماری،دانشگاه تربیت مدرس،تهران،ایران
2 دانشیار، گروه شهرسازی ، دانشکده هنر و معماری، دانشگاه تربیت مدرس، تهران، ایران
3 پژوهشگر دکتری، گروه شهرسازی دانشکده هنر و معماری، دانشگاه تربیت مدرس، تهران، ایران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Introduction: Urban development in large metropolitan areas has become increasingly complex due to demographic growth, economic volatility, environmental pressures, and spatial intensification. Traditional planning, often reliant on linear projections, cannot adequately address today’s uncertainties and systemic interdependencies. Futures studies provide a framework to identify drivers of change and explore alternative trajectories. District 5 of Tehran, situated in the western corridor, illustrates these dynamics. In recent decades, it has experienced rapid population growth, large-scale residential and commercial expansion, and growing service demand. While these trends have supported development, they have also produced congestion, declining green areas, air pollution, and widening inequalities. These conditions highlight the need to move from reactive planning toward anticipatory governance. This research applies futures studies to identify drivers shaping the district’s trajectory and to clarify their systemic roles for adaptive policy.
The Purpose of the Research: The study aims to identify, classify, and analyze the key drivers influencing the future development of District 5. It focuses on three questions: (1) Which drivers exert the greatest influence on the district’s trajectory? (2) How do they interact within a systemic network? (3) What insights can guide policy under uncertainty? The objectives are twofold: to contribute to urban foresight research and to provide practical insights for planners and policymakers in Tehran. By clarifying the most influential and sensitive drivers, the study strengthens the city’s capacity to anticipate disruption, build resilience, and pursue sustainable development strategies.
Methodology: A mixed-methods approach was adopted, combining qualitative exploration with quantitative analysis. First, environmental scanning and review of strategic documents—including the Tehran Comprehensive Plan, the District 5 Detailed Plan, and the Fourth Development Program—provided initial drivers. Second, a SWOT analysis highlighted strengths, weaknesses, opportunities, and threats. Third, fifteen semi-structured interviews with experts in urban planning, economy, infrastructure, and futures studies refined the driver list. Fourth, the drivers were grouped into four domains: socio-economic, environmental, spatial-physical, and transportation and infrastructure. Fifth, a 15×15 cross-impact matrix was completed by the experts, who assessed levels of influence using a four-point scale. Sixth, MICMAC software processed the data, identifying direct and indirect effects and classifying drivers as independent, dependent, or critical. Finally, results were interpreted systemically, highlighting leverage points for intervention. This framework ensured both rigor and practical relevance.
Findings and Discussion: Fifteen drivers were identified across four categories. Socio-economic drivers include inflation, investment, land and housing prices, housing ownership, social participation, income and employment, and marginalization. Environmental drivers consist of fossil fuel prices and air quality. Spatial-physical drivers include development budget, land-use change, density, and open spaces. Transportation and infrastructure drivers include public and clean transport and digital infrastructure.
MICMAC analysis revealed that investment, land and housing prices, inflation, employment, and land-use change are dual-critical—both highly influential and sensitive. These function as pivotal levers: their changes generate cascading effects across the system. Independent drivers such as inflation and development budgets exert strong upstream influence, while dependent drivers—including open spaces, air quality, and digital infrastructure—are more responsive outcomes.
This classification highlights the interdependent nature of urban systems. Managing dual-critical drivers is essential to avoid instability, while independent drivers provide opportunities for early intervention. Dependent drivers, though less influential, remain important indicators of quality of life. Integrating expert perspectives with structural modeling enhances methodological robustness and allows foresight-based recommendations. The results stress that sustainable development in District 5 requires addressing economic volatility, regulating housing and land markets, and ensuring balanced spatial growth while monitoring environmental and infrastructural performance.
Conclusion: The study concludes that District 5’s future will be shaped primarily by economic drivers, particularly investment, inflation, development budgets, housing prices, and employment. These variables, due to their dual influence and sensitivity, can either stabilize or destabilize the system depending on policy responses. Environmental and infrastructural drivers, though dependent, are critical indicators of sustainability and social welfare. The research contributes a systematic and replicable model combining document analysis, expert input, and MICMAC structural analysis. By bridging qualitative and quantitative approaches, it offers a practical tool for urban foresight. The findings emphasize that governance in District 5—and in other rapidly expanding metropolitan regions—must adopt anticipatory strategies that embrace complexity, prepare for uncertainty, and promote long-term sustainability. Ultimately, the study demonstrates how futures studies can enhance resilience and adaptability in urban planning under uncertain conditions.
کلیدواژه‌ها [English]
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