Stochastic Two-stage Network-structures Under P-models: A DEA Based Approach

Abstract

Regular NDEA models for calculating the efficiency of DMUs with two-stage construction requires the data set to be deterministic. In the real world, however, there are many observations that have stochastic behavior. This paper proposes a network DEA with two-stage structures models by the attention to stochastic data. The stochastic two-stage network DEA models are formulated based on the P-models of chance constrained programming and leader-follower concepts.