A novel Pythagorean fuzzy FUCA driven MCGDM algorithm for evaluating green economy oriented corporate sustainability

The evaluation of corporate sustainability in the context of the green economy is challenging to perform because of uncertainty, the lack of information, and different criteria. To solve this, a new model, Pythagorean fuzzy FUCA (PyF-FUCA) driven multi-criteria group decision-making (MCGDM) model to gauge sustainability performance is proposed in this paper. It employs Pythagorean fuzzy sets (PyFS), which make the FUCA algorithm flexible with the possibility of reflecting the views of an expert and eliminating ambiguities in decision-making. The proposed framework is applicable, as evidenced by an in-depth case study where it was applied in terms of fifteen alternatives, nine criteria, and four decision-makers. Indeed, findings indicate that the global market in the green era is the most sustainable, and sensitivity analysis has ensured that the rankings remain stable under different criteria and weights of decision-makers. In addition, the comparison with the original methods of PyF-MCDM and classical methods shows the increased strength and flexibility of the developed model. In addition to the development of fuzzy methodologies of MCDM, the research can be helpful to managers and policy makers who need to integrate corporate strategy with the concept of a green economy.