Evaluation of Key Factors Influencing the Realization of Sustainable Housing within the context of Circular Economy under Conditions of Uncertainty: A Future Study in the City of Yazd

Document Type : Original Article

Authors

1 M.S. Student, Department of Urban Planning & Design, Faculty of Art and Architecture, Yazd University, Yazd, Iran

2 Associate Professor, Department of Urbanism, Faculty of Art and Architecture, Yazd University, Yazd, Iran

Abstract

Introduction: Urban population growth, resource scarcity, and environmental degradation necessitate innovative urban development models. Sustainable housing, a critical component of urban systems, mitigates environmental impacts, enhances resilience, and improves quality of life. Conventional linear housing planning faces challenges such as rising environmental costs and resource inefficiency. The circular economy, which emphasizes material recycling, waste reduction, and the integration of renewable energy sources (e.g., solar energy), offers a transformative framework for sustainable housing. Yazd, located in Iran’s central plateau, faces rapid population growth, increasing housing demand, water scarcity, and spatial inequalities that threaten sustainability. Despite its rich cultural heritage and significant solar-energy potential, inefficiencies in material recycling and policy coordination hinder progress. Previous studies in Iran have focused primarily on the technical or social dimensions of housing while neglecting the integration of circular-economy principles and futures-oriented planning. This study identifies the key factors influencing sustainable housing in Yazd through a circular-economy lens, employing futures studies to forecast trends and develop policy scenarios under conditions of uncertainty. It provides a localized framework for Yazd that can be scaled to similar arid cities, thereby enriching the literature on urban planning and sustainability.
Methodology: Conducted in Yazd, a culturally significant city with unique climatic challenges, this study adopted a futures-studies approach using structural and cross-impact analysis through MICMAC software. The research process consisted of the following steps:

Literature Review: Criteria were extracted from scientific publications and strategic planning documents.
Expert Interviews: Semi-structured interviews with urban planning and environmental experts were conducted to identify key factors and uncertainties.
Delphi Technique: A panel of 12 experts scored a 20 × 20 cross-impact matrix (0 = no effect; 3 = strong effect) to assess interactions among factors.
MICMAC Analysis: The data were analyzed to classify factors as key, dependent, or regulatory variables.
Sensitivity Analysis: Perturbations of ±5% and ±10% were applied to 20 indicators (e.g., C02: material recycling, C04: waste management, and C20: solar energy) using MATLAB, and changes in rankings were visualized.

Results: MICMAC analysis revealed a complex system with a matrix fill rate of 71%, indicating dense interactions among factors (284 of 400 relationships were significant: 116 no effect, 99 weak, 90 moderate, and 95 strong). Total influence and dependence scores were balanced at 564. Key findings include:

Influential Factors: Material recycling (C02), waste management (C04), and the housing–security–happiness linkage (C08) exhibited high levels of direct influence (Figures 3 and 4).
Dependent Factors: Green technology adoption (C01), institutional coordination (C16), and solar-energy capacity (C20) were highly dependent variables.
Dominant Dimensions: Environmental factors (e.g., recycling and climate change) and social factors (e.g., quality of life) were dominant, whereas technological and managerial factors were primarily dependent.
Sensitivity Analysis: C02 and C04 were highly stable (0–3 ranking changes), C08 exhibited moderate stability (3–7 ranking changes), whereas C01, C18 (local resource utilization), and C20 were highly sensitive (16–18 ranking changes), reflecting systemic vulnerabilities.

Influence–dependence maps and graphical analyses identified C02, C04, and C08 as key drivers, while potential relationships highlighted the need for adaptive and dynamic planning strategies.
Discussion: The study maps a dynamic network for sustainable housing in Yazd that depends on environmental, social, technological, and institutional strategies:

Resource Recycling: The prominence of C02 and C04 is consistent with studies identifying recycling and waste management as core pillars of the circular economy. Yazd’s industrial waste streams (e.g., steel and tile waste) offer significant circularity potential, requiring investment in recycling infrastructure.
Quality of Life: The role of C08 in promoting social sustainability, supported by studies on resident satisfaction, suggests that innovative approaches such as product–service systems (PSS) can enhance social acceptance.
Green Technologies: The high sensitivity of C01 and C20 underscores Yazd’s considerable solar-energy potential while highlighting barriers to adoption, thereby necessitating greater technological investment.
Institutional Coordination: The instability of C16 reflects governance challenges that require stronger policy alignment and stakeholder collaboration.

Policy Implications: The proposed framework, which is scalable to other arid cities, integrates recycling, technology, and governance while emphasizing social acceptance. Policymakers should prioritize the development of recycled-material databases, investment in solar-energy infrastructure, community engagement initiatives, and enhanced institutional coordination.
Conclusion: This study provides the first structural and sensitivity-based futures analysis of sustainable housing within a circular-economy framework in a desert city of the Global South. The combination of MICMAC structural analysis and local sensitivity assessment revealed that the future of Yazd’s housing system depends on a small set of highly influential yet differentially robust drivers. Three drivers proved highly stable and dominant across direct, indirect, potential, and perturbed conditions: the rate of building-material recycling (C02), the efficiency of construction-waste management (C04), and the relationship between housing and residents’ sense of security and happiness (C08). These variables constitute the robust backbone of the system and should serve as the non-negotiable core of any effective policy package.  In contrast, technology adoption (C01), local resource utilization (C18), solar-energy integration (C20), and inter-institutional coordination (C16) exhibited high sensitivity, with ranking shifts of up to 18 positions under ±5–10% perturbations.

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References

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Urban Planning Knowledge
Volume 10, Issue 2
June 2026
Pages 1-22

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  • Receive Date: 28 April 2025
  • Revise Date: 08 December 2025
  • Accept Date: 05 June 2026

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