2-Tuple unbalanced linguistic multiple-criteria group decision-making using prospect theory data envelopment analysis

The linguistic terms used to describe the qualitative data in problems are symmetrical about central word. With increasing complexity and a large number of DMs with different domain expertise involved decision-making, symmetric term set seems constricted. This paper examines multiple-criteria group decision-making which decision-makers use unbalanced 2-tuple alternative–criteria assessments matrices. We adopt envelopment analysis (DEA) approach develop linear programming model evaluate alternatives criteria weights for each decision-maker. non-rational factor risk gets modeled using value function from prospect theory. values gain loss, respectively, on cost benefit parameters computed applied formulate DEA assess criterion alternative. Eventually, cross-efficiency scores their entropy provide ranking alternatives. A numerical example is presented illustrate methodology. comparative proposed method fuzzy ordinal priority TOPSIS performed illustrative example. Finally, an application faculties end-semester feedback class students academic institute presented.