A fuzzy rough network data envelopment analysis approach for evaluating the sustainability of supply chains: a case study in the pasta industry

Evaluation of the sustainability of supply chains is a complex decision-making problem. One of the techniques, which are used for assessing the sustainability of supply chains is data envelopment analysis (DEA). Conventional DEA models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration the internal interactions of DMUs. Also, they assume inputs and outputs are crisp. In this research, the network DEA (NDEA) model for assessing the sustainability of supply chains in the presence of fuzzy rough data is developed. The main contribution of this paper is to develop a novel NDEA model in the existence of internal and external uncertainties. To validate the proposed model, a case study for evaluating the sustainability of the supply chain in the pasta industry is presented.

Automated summary

Evaluation of supply chain sustainability is a complex decision-making problem, and data envelopment analysis (DEA) is used to assess sustainability in supply chains. This research develops a network DEA (NDEA) model that considers fuzzy rough data to assess sustainability. The proposed model takes into account the internal interactions of decision-making units (DMUs) and assumes fuzzy inputs and outputs.