Evaluating Sustainable Business Model Innovations Under ESG by Signed Distance Based Intuitionistic Fuzzy MCDM Method

This paper addresses critical limitations in the application of intuitionistic fuzzy sets (IFSs) for complex decision‐making problems under uncertainty. While IFSs offer a robust framework for modeling imprecision through membership, nonmembership, and hesitancy degrees, existing methodologies often simplify the multiplication of intuitionistic fuzzy numbers (IFNs) to linear approximations, overlooking potential nonlinear interactions. Furthermore, a comprehensive signed distance measure for triangular IFNs (TIFNs) and a method for intuitionistic fuzzy nonlinear signed distance are largely absent from the literature. To bridge these gaps, this study develops novel equations for the multiplication of two IFNs, treating the result as a nonlinear IFN, thereby enhancing the precision of fuzzy arithmetic. The practical utility of the proposed methodology is demonstrated through an application involving sustainable business model innovations (SBMI) evaluation under ESG principles. The numerical example is provided, showcasing how the developed techniques can provide an accurate and nuanced assessment for complex multicriteria decision‐making problems.