A Novel Approach for Systematic Literature Reviews Using Multi-Criteria Decision Analysis

Abstract

This study investigates the application of Multi-Criteria Decision Analysis (MCDA) methods to the classification of research papers within a Systematic Literature Review (SLR). Distinctions are drawn between compensatory and non-compensatory MCDA approaches, which, despite their distinctiveness, have often been applied interchangeably, leading to a need for clarification in their usage. To address this, the methods of Entropy Weight Method (EWM), Analytic Hierarchy Process (AHP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were utilized to determine the parameters for ranking papers within an SLR portfolio. The source of this ranking comprised publications from three major databases: Scopus, ScienceDirect, and Web of Science. From an initial yield of 267 articles, a final portfolio of 90 articles was established, highlighting not only the compensatory and non-compensatory classifications but also identifying methods that incorporate features of both. This nuanced categorization reveals the complexity and necessity of selecting an appropriate MCDA method based on the dataset characteristics, which may exhibit attributes of both approaches. The analysis further illuminated the geographical distribution of publications, leading contributors, thematic areas, and the prevalence of specific MCDA methods. This study underscores the importance of methodological precision in the application of MCDA to systematic reviews, providing a refined framework for evaluating academic literature.