A consensus process based on regret theory with probabilistic linguistic term sets and its application in venture capital

This paper proposes a consensus model for multi-experts multi-criteria decision making (MEMCDM) problems with probabilistic linguistic term sets (PLTSs), which also considers the regret-rejoice emotions of decision makers (DMs) in their decision-making processes. Additionally, the Dempster-Shafer theory is applied to estimate the probability of the market status which is related to the perceived values of the alternatives. Moreover, an algorithm is given to determine the weight of each DM. Then, a detailed consensus procedure is proposed and an illustrative example is used to show the feasibility of the proposed model. Finally, some comparative analyses are carried out to demonstrate the advantages of the proposed consensus process. (c) 2021 Elsevier Inc. All rights reserved.

Automated summary

This paper presents a consensus model for multi-experts multi-criteria decision making problems with probabilistic linguistic term sets, taking into account the regret-rejoice emotions of decision makers. The Dempster-Shafer theory is utilized to estimate the probability of market status related to perceived values of alternatives. An algorithm is provided for determining the weight of each decision maker. The detailed consensus procedure and illustrative example demonstrate the feasibility of the proposed model, and comparative analyses highlight the advantages of the consensus process.