A Refined Neutrosophic α-Discounting Framework for Evaluating E-Commerce Logistics Service Quality in Mobile Environments

In e-commerce ecosystems, the reliability of logistics service quality (LSQ) directly influences customer satisfaction and operational sustainability. With the growing dependence on mobile information systems, there arises a need for intelligent, uncertainty-aware decision-making models that reflect real-world ambiguity, contradiction, and temporal variability. This paper introduces a novel framework that synthesizes α-Discounting Multi-Criteria Decision-Making (α-D MCDM) with Refined and SuperHyper Neutrosophic Logic. Unlike traditional MCDM approaches, the proposed model addresses inconsistency across multiple dimensions of uncertainty— truth, indeterminacy, and falsity—by applying a triadic α-discounting mechanism. The model further generalizes decision criteria into higher-order power sets to handle complex and dynamic evaluations via mobile-enabled platforms. Through rigorous mathematical modeling, detailed numerical examples, and real-time contextual weighting, we demonstrate the model’s capacity to deliver more consistent, interpretable, and adaptable service evaluations. The results highlight improved accuracy and resolution in multi-layered e-logistics decision environments.