A Bibliometric Perspective: Research Trends in Multi-Criteria Decision Making (MCDM) and Mahalanobis Taguchi Gram-Schmidt (MTGS)

Abstract

This study presents a comparative bibliometric analysis of two decision-making methodologies: Multi- Criteria Decision Making (MCDM) and the Mahalanobis Taguchi Gram-Schmidt (MTGS) method. The primary objective is to examine the scholarly landscape, research growth trajectories, and geographic dissemination of these approaches better to understand their academic evolution and potential for future research. MCDM has been extensively utilized across diverse disciplines to address complex decision-making problems involving multiple criteria. In contrast, MTGS represents a relatively nascent technique that mitigates multicollinearity through Gram-Schmidt orthogonalization. Drawing upon the Scopus database as the sole data source, this study systematically analyzes publications from 2020 to 2025. Key bibliometric indicators, including annual publication trends, subject area distributions, and contributing countries, are evaluated using Microsoft Excel, VOSviewer, and Harzing’s Publish or Perish. The findings indicate a pronounced dominance of MCDM in the literature, with 228 publications primarily situated within thedomains of Computer Science, Engineering, and Mathematics. Conversely, MTGS is represented by only 10
publications, predominantly within technical fields such as Engineering and Computer Science. In terms of geographic contribution, India, China, and Iran emerge as leading contributors to MCDM research, while MTGS-related studies are primarily concentrated in China and Malaysia. It is important to acknowledge that this study is limited to Scopus-indexed publications within the 2020 to 2025 timeframe, which may restrict the comprehensiveness of the analysis by excluding relevant literature from other databases or earlier periods.