.png){kind=icon}
.png){kind=icon}
Return
A stochastic fuzzy multi-criteria decision-making framework to develop city 5.0 based on circular economy and industry 5.0
.png){kind=icon}
PRE
AI
R
S
E
DOI：10.1007/s10098-026-03546-0.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This study develops a hybrid stochastic fuzzy decision-making framework to identify the most effective strategies for smart city development by integrating circular economy principles with Industry 5.0 (I5.0) dimensions, including sustainability, resilience, human centricity, and digitalization. The proposed framework, termed Circular Economy-based Smart City 5.0 (CESC5.0), supports strategic urban planning under uncertainty. Initially, 25 evaluation criteria across five dimensions are identified through expert input and literature analysis. The relative importance of these criteria is determined by using the Stochastic Fuzzy Best–Worst Method (SFBWM), yielding a high level of consistency (CR = 0.044), indicating reliable expert judgments. The results show that citizen health monitoring (0.0485), telemedicine and remote monitoring (0.0477), education and empowerment (0.0476), 5R principles (0.0464), and clean and renewable transportation (0.0454) are the most influential criteria. Subsequently, five strategic alternatives are evaluated using the newly developed Stochastic Fuzzy Evaluation based on Distance from Average Solution (SFEDAS) method. The ranking results indicate that AI-based urban planning interfaces (AS ≈ 1.26) represent the most effective strategy, followed by personalized health monitoring systems (AS ≈ 1.11) and smart mobility solutions (AS ≈ 1.06). Comparative analysis with established Multi-Criteria Decision-Making (MCDM) methods confirms the robustness and stability of the proposed approach. From a sustainability perspective, the findings demonstrate that integrating AI-driven planning, digital health technologies, and circular resource management significantly enhances urban efficiency, reduces environmental impact, and improves citizen well-being. Therefore, this study contributes by (i) advancing decision support technologies through a novel stochastic fuzzy MCDM framework and (ii) providing actionable, technology-oriented insights for designing sustainable, resilient, and human-centric smart cities.
Keywords:
Smart city
Circular economy
Industry 5.0
City 5.0
Stochastic fuzzy evaluation based on distance from average solution
Stochastic fuzzy best–worst method
Journal
IF:
3.9
Papers:
3.4K
Citations:
7.9K
Organization
Cited Papers