A novel probabilistic linguistic group decision-making method driven by DEA cross-efficiency and trust relationship

In this paper, a new group decision-making (GDM) method is proposed to improve the quality and efficiency of decision-making. This method considers the degree of preference of decision makers (DMs) for different linguistic terms and adopts the probabilistic linguistic preference relations (PLPRs) model. First, a multiplicative consistency adjustment procedure is proposed to obtain a PLPR with acceptable consistency. Then, the trust matrix among experts is used to determine the weight vector of experts and realize the effective integration of information. After obtaining the collective PLPR, a DEA cross-efficiency model is designed to seek the target decision-making units (DMUs), which are the most efficient in the production possibility set. In addition, an integrated GDM method is designed to rank all alternatives adequately. Finally, the numerical analysis is carried out using the real estate company evaluation as an example. Comparative analysis with other methods quantifies the results, which enables us to evaluate the presented GDM method objectively.