Developing network data envelopment analysis model for supply chain performance measurement in the presence of zero data

Performance measurement of supply chain (SC) has a vital impact on SC management and can increase efficiency of whole system and also brings competitive advantages for companies. Conventional data envelopment analysis (DEA) models treat the supply chain as a black box and do not deal with interactions of components within supply chain. Existence of zero data in supply chains can be a new assumption in performance evaluation. The main objective of this paper is to propose a new network DEA (NDEA) model in the presence of zero data. In addition, to rank supply chains, this paper proposes a novel super-efficiency formulation of NDEA using input saving and output surplus concepts. To demonstrate applicability of the proposed model, a case study is presented.