Novel score function and standard coefficient-based single-valued neutrosophic MCDM for live streaming sales

Abstract

Single-valued neutrosophic sets (SVNS) provide a comprehensive approach to express uncertainty in decision scenarios, surpassing the utility of fuzzy sets (FS) and intuitionistic fuzzy sets (IFS). Yet, current SVNS score function concepts stem from FS and IFS construction methods, showing inconsistencies. Thus, we introduce a novel SVNS score function based on inherent uncertainty essence. Additionally, we devise a standard coefficient to gauge SVNS standardization akin to fuzzy sets. Addressing SVNS researchability and limitations in fundamental concepts, especially the score function, we propose an SVNS-based multi-criteria decision-making (MCDM) model. This leverages the new score function and standard coefficient. We demonstrate its effectiveness on two decisions: “software engineer recruitment” with known weights and “investment selection” with unknown weights. Ultimately, we successfully applied the model to the field of live streaming sales to solve the actual MCDM problem. By comparing with existing methods, we affirm the model's validity and practicality. Compared to prior approaches, the new method exhibits: (1) Enhanced stability and credibility in result values and rankings, promoting robust optimal solutions. (2) Reduced computational steps and workload, enhancing usability and practicality.