Spherical bipolar fuzzy decision model for green infrastructure selection

Increasing urbanization, brought on by population expansion and industrialization, is posing a number of environmental concerns for urban and suburban areas. Urban communities are adapting to the intricacies brought about by a number of factors, including pollution, temperature variations, and climate change. However, achieving adaptation sustainably remains a significant challenge because many existing adaptation strategies lack sustainability, particularly in the context of urban development. Sustainable urban development can be achieved through green initiatives, with green infrastructure (GI) practices playing an essential role in its implementation. Nevertheless, selecting one of the available GI practices might be challenging since their execution necessitates careful assessment of all relevant factors. To this end, we seek the aid of a fuzzy multi-criteria decision-making framework. This study considers six GI practices as alternatives, assessed based on environmental, economic, and social dimensions encompassing fourteen criteria. Spherical bipolar fuzzy sets (SBFS) are employed to represent the evaluation information. The significance of each criterion is established using the distance correlation-based criteria importance through inter-criteria correlation (D-CRITIC) technique, while the alternatives are ranked through the preference ranking on the basis of ideal-average distance (PROBID) approach. The proposed SBFS-based D-CRITIC-PROBID framework is a significant addition to the literature as a distinctive study on GI assessment. Further, the effectiveness and robustness of the findings are validated through comparison and sensitivity analyses.