An integrated fermatean fuzzy decision framework for urban-focused green development performance

Accelerating global urbanization necessitates aligning economic growth with urban sustainability; thus, evaluating green development performance requires a holistic approach that incorporates both macroeconomic and urban-focused indicators. However, existing performance evaluations often neglect the spatial dimension of urban sustainability and struggle to handle the deep uncertainty and ambiguity inherent in multidimensional global datasets. Motivated by these limitations, this study proposes a novel and integrated model to evaluate the Urban-Oriented Green Development Performance of 155 countries. By combining the United Nations Sustainable Cities and Communities Index with the Global Green Growth Index, the analyses are conducted within a Fermatean Fuzzy Sets (FFS) environment to manage data ambiguity at the broadest level. In the proposed two-stage methodology, criteria importance levels are objectively determined using Shannon Entropy, while country rankings are calculated through the Fermatean Fuzzy Compromise Ranking of Alternatives from Distance to Ideal Solution (FFCRADIS) method. The findings indicate that the 'Sustainability Level of Cities and Communities' emerges as the most influential determinant of the model. Spatial visualizations using Natural Breaks and Excess Risk methods reveal a pronounced 'North-South' divide, with Switzerland, Austria, and Sweden consistently exhibiting the highest performance across all scenarios. Overall, this study provides policymakers with a robust, uncertainty-sensitive framework to strategically plan decentralized, urban-oriented green development policies rather than relying solely on macro-level national indices.