Multi-Criteria Decision-Making (MCDM) Method for Quality Service Assessment: A Systematic Literature Review

Abstract

The increasing complexity of digital service ecosystems has led to an increase in the need for reliable Quality Service Assessment Methods (QSAMs) that can assess systems from both technical and experiential perspectives. The current research study demonstrates a systematic literature review (SLR) of QSAMs, which includes Multi-Criteria Decision-Making (MCDM) methods, with guidance by the Evaluation Theory and the PRISMA 2020 protocol. In this regard, around Seventy-eight peer-reviewed studies were published between the period of 2010 and 2025 and were analyzed across seven Evaluation Theory dimensions, which are evaluation criteria, target, measurement scale, data-gathering method, synthesis technique, evaluation process, and validation approach. According to the review, the MCDM techniques — primarily AHP, TOPSIS, Fuzzy MCDM, and hybrid combinations — Improved both the clarity and consistency of QSAM decision-making. Hence, this methodological sophistication has not been matched by equal attention to validation, sensitivity testing, and evaluation-process design. Building on that, the current research paper suggests a set of practical guidelines for sensitivity analysis in QSAMs and outlines a conceptual model, AET-QSAM, in an attempt to address the validation and process gaps identified. In addition, the current paper aims to contribute to a theory-grounded framework for diagnosing the completeness of existing QSAMs and a research agenda for developing more transparent, trustworthy, and adaptable assessment methods for future e-services.