Mapping the Research Landscape of Multi-Objective Optimization by Ratio Analysis (MOORA) within Multi-Criteria Decision-Making: A Comprehensive Bibliometric and Science Mapping Analysis from 2012 to 2024
-
Juni Ismail
*
Politeknik Bisnis Indonesia, Simalungun,
Indonesia
- Alfry Aristo Jansen Sinlae Universitas Katolik Widya Mandira, Kupang, Indonesia
- Zulfikar Zulfikar Politeknik Kampar, Bangkinang, Indonesia
- Yanto Saputra Institut Teknologi Bisnis Riau, Riau, Indonesia
- Elsy Rahajeng Universitas Islam Negeri Syarif Hidayatullah, Banten, Indonesia
- Mesran Mesran Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia (*) Corresponding Author
Abstract
The Multi-Objective Optimization by Ratio Analysis (MOORA) method has become an increasingly prominent technique within the multi-criteria decision-making (MCDM) family due to its computational simplicity, mathematical stability, and strong capacity to rank alternatives under conflicting criteria, yet the intellectual structure of this rapidly expanding field remains fragmented and insufficiently mapped. This study aims to systematically chart the global research landscape of MOORA within the MCDM domain and to identify its leading contributors, foundational works, dominant publication outlets, and prevailing thematic structures. A bibliometric research design guided by the PRISMA protocol was adopted, drawing on 275 English-language documents retrieved from the Scopus database for the period 2012 to 2024. The data were analysed using VOSviewer and Scopus analytical tools to examine annual publication trends, subject-area distribution, leading sources, co-citation networks, and keyword co-occurrence patterns. The results reveal a field that has accelerated sharply since 2018 and again after 2020, reaching a peak of seventy-one documents in 2024, with output concentrated in Engineering and Computer Science and disseminated through a heterogeneous ecosystem of mechanical-engineering, cleaner-production, and intelligent-systems outlets. Co-citation analysis confirms a theoretical base anchored in the canonical contributions of Brauers and Zavadskas, while keyword mapping shows MOORA functioning as a central decision-making nucleus closely tied to ratio analysis, optimisation, and surface-roughness applications, with TOPSIS, AHP, and WASPAS emerging as salient companion techniques. The novelty of this study lies in its focused mapping of the MOORA intersection rather than MCDM in general, exposing a loosely integrated thematic structure and a reliance on a narrow citation canon dominated by methodological pioneers. Its principal contribution is a consolidated knowledge map that clarifies the field's foundations and directs future methodological, fuzzy-extension, and interdisciplinary innovation
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