A Modified Fuzzy TOPSIS Method Aggregating 8.921 Partial Rankings For Companies’ Attractiveness

Zoumpolia Dikopoulou*, Gonzalo Nápoles, Elpiniki Papageorgiou, Koen Vanhoof

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review


Real-life environments are inadequate to be modelled by crisp values, since human reasoning is often uncertain and ambiguous. Therefore, the aggregation of fuzzy concept of decision makers is represented sufficiently with fuzzy (imprecise) data. The purpose of this paper is the development of a powerful and useful method based on fuzzy TOPSIS which is able to aggregate judgements of 8.921 decision makers in a real fuzzy environment. The main goal of the proposed modified fuzzy TOPSIS method is the efficiently ordering of a big volume of partial ranking lists related with 17 factors which are associated with the job satisfaction in fifteen different sectors. The results are very promising to continue our research to this direction and make further investigations.
Original languageEnglish
Title of host publicationThe Application of Fuzzy Logic for Managerial Decision Making Processes: Latest Research and Case Studies
EditorsAndreas Meier, Edy Portmann, Kilian Stoffel, Luis Terán
Place of PublicationCham
PublisherSpringer International Publishing
Number of pages13
ISBN (Print)978-3-319-54048-1
Publication statusPublished - 2017
Externally publishedYes


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