A cutting-edge data envelopment analysis model for measuring sustainable supplier performance like never before

Amin Zoghi, Farhad Hosseinzadeh Lotfi, Reza Farzipoor Saen*, Saber Saati

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

One of the challenges for suppliers is to increase their market share due to the limited target market. In other words, in the supply chain, the demand for suppliers' products is limited. Therefore, suppliers produce a determined share of the required amount by producers. However, when it comes to the share in the amount of output among suppliers, the output of suppliers in this indicator is interdependent. In the classical data envelopment analysis (DEA) models, there are no models that assess the suppliers according to the dependence of at least one output on each other. In this paper, a model is presented that can assess sustainable suppliers in the presence of interdependent output among suppliers by using DEA models and their extension. It can also determine the total benchmarks of decision making units (DMUs) in such a way that satisfies the interdependent output constraint. In other words, benchmarks are not determined independently. Ultimately, an approach is presented to determine efficient projections for inefficient DMUs by considering the concept of interdependent output. To represent the applicability of our proposed model, a dataset for two consecutive years including 32 sustainable suppliers with consideration of interdependent output has been implemented using the model presented in this paper. The resulting sustainability has been compared with a classical model.

Original languageEnglish
Article number142714
JournalJournal of Cleaner Production
Volume462
DOIs
Publication statusPublished - Jul 10 2024

Keywords

  • Data envelopment analysis
  • Independent output
  • Interdependent output
  • Sustainable suppliers

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • General Environmental Science
  • Strategy and Management
  • Industrial and Manufacturing Engineering

Cite this