Assessing sustainability of supply chains by chance-constrained two-stage DEA model in the presence of undesirable factors

Sustainable supply chain is recognized as a key component of corporate responsibility. Despite conventional data envelopment analysis (DEA) models that view decision making units (DMUs) as black boxes, two-stage DEA models take into account intermediate measures within a DMU. However, there might be stochastic data. Objective of this paper is to present a new stochastic two-stage DEA model in the presence of undesirable data. We present some linear models that obtain lower and upper bounds of efficiencies of stages 1 and 2. Also, we propose a linear model that calculates overall efficiency of DMUs. Meanwhile, we extend our proposed model for dealing with stochastic data in the presence of undesirable data. A case study demonstrates applicability of our approach.