DEA cross-efficiency framework for efficiency evaluation with probabilistic linguistic term sets

Data envelopment analysis (DEA) is widely used in various practical problems as a general framework for efficiency-evaluation by containing the input-output data. With increasingly complex factors practice, portraying uncertainty necessary ensuring reasonableness of results. As probabilistic linguistic term set (PLTS) powerful tool depicting uncertain information comprehensively, we aim to propose DEA cross-efficiency efficiency evaluation under environment, which includes (1) defining preference-based expectation function PLTS, (2) establishing model, (3) developing an algorithm based on dual form and (4) building positive ideal-seeking model. Furthermore, simulation tests are made provide guidance decision makers value assignment problems. A case study conducted verify applicability proposed framework.