Developing a nondiscretionary slacks-based measure model for supplier selection in the presence of stochastic data

Majid Azadi, Reza Farzipoor Saen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Supplier selection has a strategic importance for every company. Nondiscretionary Slacks-based Measure (SBM) model is one of the models in Data Envelopment Analysis (DEA). In many real world applications, data are often stochastic. A successful approach to the address uncertainty in data is to replace deterministic data via random variables, leading to Chance-con strained DEA (CCDEA). In this study, the concept of chance-constrained programming approach is used to develop nondiscretionary SBM model in the presence of stochastic data and also its deterministic equivalent which is a nonlinear program is derived. Furthermore, it is shown that the deterministic equivalent of the stochastic nondiscretionary SBM model can be converted into a quadratic program. Finally, a numerical example demonstrates the application of the proposed model.

Original languageEnglish
Pages (from-to)103-120
Number of pages18
JournalResearch Journal of Business Management
Issue number4
Publication statusPublished - 2012


  • Chance-constrained data envelopment analysis
  • Nondiscretionary slacks-bared measure
  • Quadratic program
  • Sensitivity analysis
  • Supplier selection
  • Supply chain management

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management
  • Organizational Behavior and Human Resource Management
  • Management of Technology and Innovation

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