Multi-attribute group decision-making method using single-valued neutrosophic credibility numbers with the Dombi extended power aggregation operator and its application in intelligent transportation system data collection scheme selection

The process of selecting an intelligent transportation system data collection scheme (ITSDCS) is a multi-attribute group decision-making (MAGDM) problem characterized by the involvement of several mutually supportive criteria. A major obstacle to the ITSDCS selection lies in dealing with uncertain information characterized by single-valued neutrosophic credibility numbers (SvNCNs), involving true fuzzy credibility numbers (FCNs), indeterminate FCNs, and falsity FCNs. Existing operators on SvNCNs suffer from insufficient ability to handle extreme values and lack of flexibility, and there is an urgent need to develop general and comprehensive operators to aggregate evaluation information. To address this gap, this study combines SvNCNs with the Dombi operator, the extended power average (EPA) operator, and the extended power geometric (EPG) operator. We propose the SvNCNs Dombi extended power weight average (SvNCNDEPWA) operator and the SvNCNs Dombi extended power weight geometric (SvNCNDEPWG) operator, along with their extended forms, and investigate some useful properties of these operators. The operator is effective in aggregating evaluation information in group decision-making scenarios, providing a higher degree of adaptability and flexibility in dealing with the complexity of the ITSDCS selection problem. The model also performs criteria weighting using the distance correlation-based CRiteria Importance Through Intercriteria Correlation (D-CRITIC) method and the principle of minimum identifying information. In addition, the proposed MAGDM model is used in a case study of ITSDCS selection to confirm its applicability and usefulness. The consistency, robustness, and effectiveness of the method were verified through sensitivity and comparative analysis.