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

Mohammad Tavassoli, Reza Farzipoor Saen, Gholam Reza Faramarzi

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)381-391
Number of pages11
JournalExpert Systems
Issue number3
Publication statusPublished - Jun 1 2015


  • network data envelopment analysis
  • performance measurement
  • supply chain management
  • zero data

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

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