Imprecise Revenue Efficiency under Productivity Change

Traditional data envelopment analysis (DEA) models evaluate the performance of decision-making units (DMUs) with the exact data and do not assume evaluation in the condition that the environment is uncertain. When some data are unknown, such as interval data, the DEA model is called imprecise DEA (IDEA). In this paper, we develop a new Malmquist productivity index(MPI) for dealing with interval data in DEA. Then, an approach for measuring the Malmquist productivity index using revenue efficiency is extended, too. The capabilities of the presented approach are shown by means of an example.