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Developing a new chance-constrained DEA model for suppliers selection in the presence of undesirable outputs

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  • Majid Azadi
  • Reza Farzipoor Saen

Abstract

Supplier selection is a significant and widely studied theme since it has a significant influence on purchasing management in supply chain. Slacks-based measure – undesirable output (SBM-undesirable output) model is one of the new models in data envelopment analysis (DEA). In many real-world applications, data are often stochastic. A successful approach to address uncertainty in data is to replace deterministic data via random variables, leading to chance-constrained DEA. In this paper, a SBM-undesirable output model is developed to assist the decision makers to determine the most appropriate suppliers in the presence of both undesirable factors and stochastic data, and also its deterministic equivalent which is a non-linear programme is derived. Furthermore, it is shown that the deterministic equivalent of the stochastic SBM-undesirable output model can be converted into a quadratic programme. In addition, sensitivity analysis of the SBM-undesirable output model is discussed with respect to changes on parameters. A case study demonstrates the application of the proposed model.

Suggested Citation

  • Majid Azadi & Reza Farzipoor Saen, 2012. "Developing a new chance-constrained DEA model for suppliers selection in the presence of undesirable outputs," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 13(1), pages 44-66.
    • Handle: RePEc:ids:ijores:v:13:y:2012:i:1:p:44-66
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    Citations

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    Cited by:

    1. Kiani Mavi, Reza & Saen, Reza Farzipoor & Goh, Mark, 2019. "Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 553-562.
    2. Azadi, Majid & Shabani, Amir & Khodakarami, Mohsen & Farzipoor Saen, Reza, 2015. "Reprint of “Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 74(C), pages 22-36.
    3. Yin, Xu & Wang, Jing & Li, Yurui & Feng, Zhiming & Wang, Qianyi, 2021. "Are small towns really inefficient? A data envelopment analysis of sampled towns in Jiangsu province, China," Land Use Policy, Elsevier, vol. 109(C).
    4. Azadi, Majid & Shabani, Amir & Khodakarami, Mohsen & Farzipoor Saen, Reza, 2014. "Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 324-338.

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