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

In: Advances in Best-Worst Method

Author

Listed:
  • Yejun Xu

    (Tianjin University)

  • Dayong Wang

    (Hohai University)

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.

Suggested Citation

  • Yejun Xu & Dayong Wang, 2023. "A Hesitant Multiplicative Best-Worst Method for Multiple Criteria Decision-Making," Lecture Notes in Operations Research, in: Jafar Rezaei & Matteo Brunelli & Majid Mohammadi (ed.), Advances in Best-Worst Method, chapter 0, pages 61-75, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-40328-6_5
    DOI: 10.1007/978-3-031-40328-6_5
    as

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