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AuthorKutty, Adeeb A.
AuthorKucukvar, Murat
AuthorOnat, Nuri C.
AuthorAyvaz, Berk
AuthorAbdella, Galal M.
Available date2023-06-15T08:57:47Z
Publication Date2023-06
Publication NameCities
Identifierhttp://dx.doi.org/10.1016/j.cities.2023.104293
CitationKutty, A. A., Kucukvar, M., Onat, N. C., Ayvaz, B., & Abdella, G. M. (2023). Measuring sustainability, resilience and livability performance of European smart cities: A novel fuzzy expert-based multi-criteria decision support model. Cities, 137.
ISSN0264-2751
URIhttps://www.sciencedirect.com/science/article/pii/S0264275123001051
URIhttp://hdl.handle.net/10576/44504
AbstractCities of the 21st century are buffeted with challenges, leaving potentially serious consequences on the future of urban living. Smartening development in cities has reinvented hopes of melting down predicaments in the early 2000s'. However, perplexed by the intensifying complexities of smart cities, urban living in smart cities needs to be evaluated with multiple conflicting criteria. Multi-criteria-based evaluations have been an answer to this case when attempting to gauge the composite performance of multiple decision-making entities. Several multi-criteria assessment techniques exist when dealing with selection problems. Nonetheless, the vagueness associated with the methodologies accompanied by uncertainties and complexities is inevitable in multi-attribute assessments. Fuzzy-based multi-criteria models are often an answer to such uncertainties when modelling real-world problems. The study thus presents a novel fuzzy expert-based multi-criteria decision support model, where the Analytical Hierarchy Process (AHP) is combined with the Evaluation based on Distance from Average Solution (EDAS) approach under a spherical fuzzy environment to create a composite index for comprehensive performance monitoring. The case of 35 high-tech European cities was used to empirically validate the proposed novel approach and thus construct a composite index. The composite index considers the intricate facet of integrating the concept of smart cities with sustainability, urban resilience, and livability under a unified framework. The fuzzy c-means partitioning technique was then used to segment smart cities into high, medium, and low-performing classes. A comparative analysis considering several distance-based approaches under a fuzzy environment with the SF-AHP and EDAS methodology is conducted to validate the robustness and stability of the proposed novel decision support model. The results revealed London as the top-ranked smart city that promotes sustainability, resilience, and livability in its current urban development model. Dusseldorf, Zurich, Munich, Oslo, Dublin, Amsterdam, Hamburg, Rome, Moscow, and Stockholm were no exemption from addressing the tritactic goals of sustainability, urban resilience, and livability well into their urban development plan and were placed in the high-performance cluster. The proposed model is efficient to express decision makers' preferences in a larger space and modelling functional parameters including hesitancy independently in the 3-dimensional domain. The model supports decision-makers and relocation analysts to assess the performance of smart cities and set targets to improve performance to remodel urban development to a more sustainable, resilient, and livable pattern.
Languageen
PublisherElsevier Ltd
SubjectSustainability
Livability
Urban resilience
Smart cities
Fuzzy sets
Multi-criteria decision making
Sustainable development
TitleMeasuring sustainability, resilience and livability performance of European smart cities: A novel fuzzy expert-based multi-criteria decision support model
TypeArticle
Volume Number137
ESSN1873-6084


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