Evaluation Based on Distance from Average Solution (EDAS) Method: A Bibliometric Analysis

To provide a comprehensive view of the research by highlighting its evolution, key contributors, and influential areas, this paper offers an in-depth bibliometric analysis of a very popular multi-criteria decision-making (MCDM) method, called Evaluation-based on Distance from Average Solution (EDAS). Using R programming, VOSviewer, CiteSpace, and the Biblioshiny application of the Bibliometrix package, this analysis covers 201 articles from the Scopus database published between January 2015 and April 2024. China is identified as the leading contributor to this field, while India excels in international collaborations. The most influential paper, with 770 citations, is "Multi-criteria inventory classification using a new method of the evaluation based on distance from average solution (EDAS)" by Ghorabaee et al., Vilnius Gediminas Technical University is a notable institution in this field, and Zavadskas E.K. is the most cited author. Key terms related to the EDAS method include "EDAS", "EDAS method", and "multi-criteria decision making". The top three referenced journals are the Journal of Intelligent and Fuzzy Systems, IEEE Access, and Soft Computing. This study provides valuable insights for those interested in the applications of the EDAS method and future advancements in the MCDM area, contributing to ongoing discussions about its relevance.