Hesitant multiplicative preference relation (HMPR) is a straightforward and efficient tool for representing hesitant fuzzy information in decision making. The aim of this paper is to develop a method to obtain priority vectors from HMPRs in the context of multistage decision-making (MSDM). To start the investigation, a simple linear programming model motivated by the idea of orness is purposed to calculate the relative weights of different stages. Based on these obtained weights, we develop a least square deviation method as well as a convergent iterative algorithm for prioritizing and ranking the MSDM- HMPR problems. The prominent property of this method is then studied. Finally, a practical example concerning the selection of logistics service providers is given to illustrate the feasibility and applicability of the proposed approach.
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