DEA cross efficiency evaluation in presence of linear and nonlinear data

Cross-efficiency is an effective approach for evaluation of DMUs which can be performed with different secondary goals. DEA and cross-efficiency view all variables as behaving in a linear fashion and regardless of the amounts of a variable held by DMUs, DEA apply a same multiplier to those various amounts. But in certain situations, this linearity assumption is not appropriate, and the conventional models need to be altered to accommodate nonlinear representations. This paper proposed a modified cross efficiency structure of Liang et al. that captures certain form of nonlinear behavior. A numerical example is provided to illustrate the approach.