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Study on the Selection of Pharmaceutical E-Commerce Platform Considering Bounded Rationality under Probabilistic Hesitant Fuzzy Environment

The selection of a pharmaceutical e-commerce platform is a typical multi-attribute group decision-making (MAGDM) problem. MAGDM is a common problem in the field of decision-making, which is full of uncertainty… Click to show full abstract

The selection of a pharmaceutical e-commerce platform is a typical multi-attribute group decision-making (MAGDM) problem. MAGDM is a common problem in the field of decision-making, which is full of uncertainty and fuzziness. A probabilistic hesitant fuzzy multi-attribute group decision-making method based on generalized TODIM is proposed for the selection of pharmaceutical e-commerce under an uncertain environment. Firstly, the credibility of a probabilistic hesitant fuzzy element is defined, and a credibility-based method for adjusting the weights of decision-makers and determining attribute weights is proposed, which fully considers the reliability of information provided by the decision-makers. Secondly, the power average (PA) operator is extended to the probabilistic hesitant fuzzy environment. The probabilistic hesitant fuzzy power average (PHFPA) operator and the probabilistic hesitant fuzzy power weighted average (PHFPWA) operator are defined, and their properties are discussed. Thirdly, considering the usual information expression of decision-makers in real life and the different risk attitudes towards gain and loss, the generalized TODIM method is extended to the probabilistic hesitant fuzzy environment to construct a prospect theory-based group decision-making method in the probabilistic hesitant fuzzy environment. Finally, the feasibility of the method in this paper is proved through the case of pharmaceutical e-commerce platform selection, and the stability of the method in this paper is verified by sensitivity analysis.

Keywords: probabilistic hesitant; decision; environment; hesitant fuzzy

Journal Title: Mathematics
Year Published: 2023

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