Evaluating after-sales service units by developing inverse network data envelopment analysis model

Reza Farzipoor Saen*, Seyed Shahrooz Seyedi Hosseini Nia

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Purpose: The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems. Design/methodology/approach: The authors estimate inputs’ variations based on outputs so that the efficiencies of decision-making unit under evaluation (DMUo) and other decision-making units (DMUs) are constant. Findings: The new INDEA model is developed to allocate resources such that inputs are not increased while efficiency scores of all DMUs remain constant. Furthermore, the authors obtain new combinations of inputs and outputs, together with a growth in efficiency score of DMUo such that efficiency scores of other DMUs are not changed. A case study is provided. Originality/value: This paper proposes INDEA model to estimate inputs (outputs) without changing efficiency scores of DMUs.

Original languageEnglish
Pages (from-to)695-707
Number of pages13
Issue number2
Publication statusPublished - Mar 21 2020


  • After-sales service
  • Data envelopment analysis (DEA)

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management

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