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

Abstract

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.

DOI:10.5281/zenodo.15927110