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Erschienen in: Soft Computing 15/2018

15.06.2018 | Focus

An enhanced fuzzy evidential DEMATEL method with its application to identify critical success factors

verfasst von: Yuzhen Han, Yong Deng

Erschienen in: Soft Computing | Ausgabe 15/2018

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Abstract

Due to the frequent occurrence of accidental and destructive disasters, it is essential to improve the performance of emergency systems. Facing the fact that the performance of emergency system depends on various factors and it is not feasible to optimize all these factors simultaneously due to the limitation of resources. A feasible solution is to select and improve some important factors. In this paper, a novel enhanced fuzzy evidential decision-making trial and evaluation laboratory (DEMATEL) method to identifying critical success factors (CSFs) is proposed. In the proposed method, we combine Dempster–Shafer evidence theory and DEMATEL method. Firstly, direct relations between factors are evaluated by multiple domain experts with intuitionistic fuzzy numbers (IFNs). Then, IFNs are transformed to basic probability assignments (BPAs) and can be combined by Dempster combination rule. In addition, the uncertainty and fuzziness of BPAs due to the lack of knowledge are taken into consideration to make final decision. Finally, implementing DEMATEL method, we can figure out cause–effect categories of factors with the DEMATEL method. The cause factors are identified as CSFs. The proposed method can well tackle subjectivity and fuzziness of experts evaluations. Based on the proposed method, the optimization of emergency management can be significantly simplified into optimizing CSFs. Through optimizing these CSFs, the performance of the whole systems can be significantly improved.

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Metadaten
Titel
An enhanced fuzzy evidential DEMATEL method with its application to identify critical success factors
verfasst von
Yuzhen Han
Yong Deng
Publikationsdatum
15.06.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 15/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3311-x

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