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2023 | OriginalPaper | Chapter

5. A Hesitant Multiplicative Best-Worst Method for Multiple Criteria Decision-Making

Authors : Yejun Xu, Dayong Wang

Published in: Advances in Best-Worst Method

Publisher: Springer Nature Switzerland

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Abstract

The classical Best-Worst Method (BWM) and its expansion form in the multiple criteria decision-making problem under different backgrounds are widely used to calculate the weights of criteria. The traditional BWM uses the accurate value based on Saaty’s scale to describe a decision maker (DM)’s preferences. However, a DM may be unsure about his preference and may give several possible values to express his preferences. In this situation, the hesitant multiplicative elements may be truly reflected the DM’s preference relation. This paper incorporates the BWM, the hesitant multiplicative preference relations (HMPR), and proposes HMBWM. Three different models are proposed to determine the weights from hesitant multiplicative best-to-others (HMBO) and hesitant multiplicative others-to-worst (HMOW) vectors. Finally, a case study of choosing commercial endowment insurance products is constructed to illustrate the practicality and correctness of the proposed model.

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previous chapter Which Prioritization Method Is Better for Deriving Priority from Best-Worst Preferences? A Theoretical and Experimental Analysis
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Metadata
Title
A Hesitant Multiplicative Best-Worst Method for Multiple Criteria Decision-Making
Authors
Yejun Xu
Dayong Wang
Copyright Year
2023
Book
Advances in Best-Worst Method

Print ISBN: 978-3-031-40327-9

Electronic ISBN: 978-3-031-40328-6

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-3-031-40328-6_5

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