Fuzzy Weighted Zero Inconsistency Method (FWZIC) for Multi-Criteria Decision-Making Weighting Criteria: A Systematic Literature Review

Researchers in various fields have consistently used Multi-Criteria Decision-Making (MCDM)methods for discipline improvement, employing both standard and novel approaches. Selecting a weightingmechanism for evaluation criteria is critical in MCDM problems. Recognizing the importance of remaining up todate on such developments in methodology, this study aims to review several innovative methods integrated withFuzzy Weighted Zero Inconsistency (FWZIC). Relying on the papers taken from the significant databases: IEEEXplore (IEEE), ScienceDirect (SD), Scopus, and PubMed from 23 August 2023 to 30 October 2023, where eachmethod was read and analyzed for its characteristics and steps. These indexes were deemaed extensive anddependable enough to encompass the scope of our literature review. A total number of articles, n = 26 were chosenbased on the criteria for inclusion and exclusion have been selected for this systematic review. By usingbibliometric and content analysis, this study examined the developing ways with (FWZIC), as well as studycomponents (sources, authors, different countries, and affiliations), areas of application, case studies, fuzzyimplementations, hybrid studies (use of other weighting methods), and application tools for these methods. Theresults of this literature systematic review (LSR) provide an accurate depiction of each new development related tothe weighting method and its utilization, such as: 1- Extracting the types of development employed in the FWZICapproach based on Fuzzy Set. 2- Extracting types of aggregation operators. 3- Analyzing integration methods withFWZIC (hybridized with other methods), and 4- Case study types showing how MCDM approaches may helpdecision-makers in a variety of decisions. Also, a set of recommendations has been presented to the researchers forthe development of new method types, as a new direction for future work. This will provide academics andpractitioners in the field of MCDM with valuable insights and significant expertise for data analysis and decisionmaking.