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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23122

Title: A Modified Fuzzy TOPSIS Method Aggregating 8.921 Partial Rankings for Companies’ Attractiveness
Authors: Dikopoulou, Zoumpolia
Nápoles Ruiz, Gonzalo
Papageorgiou, Elpiniki
Vanhoof, Koen
Issue Date: 2017
Publisher: Springer International Publishing AG
Citation: Meier, Andreas; Portmann, Edy; Stoffel, Kilian; Teran, Luis (Ed.). Proceedings of the ICFMsquare 2016 - International Conference on Fuzzy Management Methods, Springer, p. 59-71
Series/Report: Fuzzy Management Methods
Abstract: Real-life environments are inadequate to be modelled by crisp values, since hu-man reasoning is often uncertain and ambiguous. Therefore, the aggregation of fuzzy concept of decision makers is represented sufficiently with fuzzy (impre-cise) 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 mod-ified 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 re-search to this direction and make further investigations.
URI: http://hdl.handle.net/1942/23122
DOI: 10.1007/978-3-319-54048-1_6
ISI #: 000418798000006
ISBN: 9783319540481; 9783319540474
ISSN: 2196-4130
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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