Vafadarnikjoo, A. orcid.org/0000-0003-2147-6043, Tavana, M., Botelho, T. et al. (1 more author) (2020) A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria. Annals of Operations Research, 289 (2). pp. 391-418. ISSN 0254-5330
Abstract
The best–worst method (BWM) is a multiple criteria decision-making (MCDM) method for evaluating ≤a set of alternatives based on a set of decision criteria where two vectors of pairwise comparisons are used to calculate the importance weight of decision criteria. The BWM is an efficient and mathematically sound method used to solve a wide range of MCDM problems by reducing the number of pairwise comparisons and identifying the inconsistencies derived from the comparison process. In spite of its simplicity and efficiency, the BWM does not consider the decision-makers’ (DMs’) confidence in their pairwise comparisons. We propose a neutrosophic enhancement to the original BWM by introducing two new parameters as the DMs’ confidence in the best-to-others preferences and the DMs’ confidence in the others-to-worst preferences. We present two real-world cases to illustrate the applicability of the proposed neutrosophic enhanced BWM (NE-BWM) by considering confidence rating levels of the DMs.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Springer Science+Business Media, LLC, part of Springer Nature. This is an author-produced version of a paper subsequently published in Annals of Operations Research. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | decision analysis; multiple criteria decision-making; best-worst method; neutrosophic sets; pairwise comparisons |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Jan 2022 08:46 |
Last Modified: | 25 Jan 2022 09:37 |
Status: | Published |
Publisher: | Springer Nature |
Refereed: | Yes |
Identification Number: | 10.1007/s10479-020-03603-x |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:182843 |