Title A decision support model based on the combined structure of DEMATEL, QFD and fuzzy values
Authors YAZDANI, MORTEZA, Wang Z.X. , Chan F.T.S.
External publication No
Means Soft Comput.
Scope Article
Nature Científica
JCR Quartile 2
SJR Quartile 2
JCR Impact 3.643
SJR Impact 0.626
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078889196&doi=10.1007%2fs00500-020-04685-2&partnerID=40&md5=d6e657ae1717dd549cb228e76a01f7d5
Publication date 01/01/2020
ISI 000515822300003
Scopus Id 2-s2.0-85078889196
DOI 10.1007/s00500-020-04685-2
Abstract Uncertainty and risk are inevitable issues in decision making in supply chain systems. In knowledge-based communities, uncertain conditions are recognized, analyzed and eliminated using wide range of concepts and approaches. One intelligent tool to aid in decreasing impreciseness and in delivering an acceptable level of accuracy is fuzzy logic. This study reports a new version of the fuzzy multiple criteria decision-making family. The decision-making trial and evaluation laboratory (DEMATEL) is extended for the first time with interval fuzzy values and then integrated as an input for the quality function deployment (QFD) mechanism. Although the application of decision-making tools in the supply chain and its sustainable development is undeniable, the implementation of fuzzy decision support systems in sustainable supply chains still demands more research work. This study develops an IT2F DEMATEL-QFD model to evaluate and rank sustainable supply chain drivers in a group decision-making environment. The proposed fuzzy decision model is connected to a real research project for eliminating risks in the supply chain related to agricultural production systems. Sensitivity analysis confirms the stability of the model. It is concluded that the outcomes and advantages of the newly developed model will profit academic and non-academic partners. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
Keywords Agriculture; Artificial intelligence; Decision support systems; Function evaluation; Fuzzy logic; Knowledge based systems; Quality control; Quality function deployment; Sensitivity analysis; Supply ch
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