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Export Reference (APA) 
Çipi, A., Ferreira, N. C. M. Q. F., Ferreira, F. A. F., Ferreira, J. J. M. & Smarandache, F. (2026). Leveraging AI and generative AI in urban design and planning: Unveiling advantages and challenges through problem structuring methods. Technovation. 151
Export Reference (IEEE) 
A. Çipi et al.,  "Leveraging AI and generative AI in urban design and planning: Unveiling advantages and challenges through problem structuring methods", in Technovation, vol. 151, 2026
Export BibTeX 
@article{çipi2026_1768314062782,
	author = "Çipi, A. and Ferreira, N. C. M. Q. F. and Ferreira, F. A. F. and Ferreira, J. J. M. and Smarandache, F.",
	title = "Leveraging AI and generative AI in urban design and planning: Unveiling advantages and challenges through problem structuring methods",
	journal = "Technovation",
	year = "2026",
	volume = "151",
	number = "",
	doi = "10.1016/j.technovation.2025.103465",
	url = "https://www.sciencedirect.com/journal/technovation"
}
Export RIS 
TY  - JOUR
TI  - Leveraging AI and generative AI in urban design and planning: Unveiling advantages and challenges through problem structuring methods
T2  - Technovation
VL  - 151
AU  - Çipi, A.
AU  - Ferreira, N. C. M. Q. F.
AU  - Ferreira, F. A. F.
AU  - Ferreira, J. J. M.
AU  - Smarandache, F.
PY  - 2026
SN  - 0166-4972
DO  - 10.1016/j.technovation.2025.103465
UR  - https://www.sciencedirect.com/journal/technovation
AB  - The integration of Artificial Intelligence (AI) in general—and its subfield Generative AI (GenAI) in particular—into urban design and planning is revolutionizing traditional methodologies, providing innovative solutions to complex challenges in city development. Despite their transformative potential, existing research underscores a critical need to better understand the multifaceted advantages and challenges associated with these technologies. This study addresses this gap by investigating the causal relationships between the advantages and challenges of AI and GenAI integration in urban design and planning. Leveraging a novel combination of cognitive mapping and neutrosophic DEcision-MAking Trial and Evaluation Laboratory (DEMATEL), the research identifies and evaluates key factors shaping this integration. The findings reveal that dynamic digital city simulations and scenario modeling emerge as the most significant advantages, underscoring their capacity to drive data-informed innovation in urban development. Conversely, ethical concerns surface as the most critical challenge, exhibiting strong interdependencies with other issues, including the “black box” nature of AI systems and the biases embedded in training data. This study provides a comprehensive framework for understanding the interplay between these factors, offering actionable insights to guide both academic research and practical implementation. By addressing a pressing need in the field, the research paves the way for more responsible and effective applications of AI and GenAI in creating smarter, more sustainable urban environments.
ER  -