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Developing Common Set of Weights with Considering Nondiscretionary Inputs and Using Ideal Point Method

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  • Reza Kiani Mavi
  • Sajad Kazemi
  • Jay M. Jahangiri

Abstract

Data envelopment analysis (DEA) is used to evaluate the performance of decision making units (DMUs) with multiple inputs and outputs in a homogeneous group. In this way, the acquired relative efficiency score for each decision making unit lies between zero and one where a number of them may have an equal efficiency score of one. DEA successfully divides them into two categories of efficient DMUs and inefficient DMUs. A ranking for inefficient DMUs is given but DEA does not provide further information about the efficient DMUs. One of the popular methods for evaluating and ranking DMUs is the common set of weights (CSW) method. We generate a CSW model with considering nondiscretionary inputs that are beyond the control of DMUs and using ideal point method. The main idea of this approach is to minimize the distance between the evaluated decision making unit and the ideal decision making unit (ideal point). Using an empirical example we put our proposed model to test by applying it to the data of some 20 bank branches and rank their efficient units.

Suggested Citation

  • Reza Kiani Mavi & Sajad Kazemi & Jay M. Jahangiri, 2013. "Developing Common Set of Weights with Considering Nondiscretionary Inputs and Using Ideal Point Method," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-9, December.
    • Handle: RePEc:hin:jnljam:906743
    DOI: 10.1155/2013/906743
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    Cited by:

    1. Kiani Mavi, Reza & Kiani Mavi, Neda, 2021. "National eco-innovation analysis with big data: A common-weights model for dynamic DEA," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    2. 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.
    3. Javad Gerami & Reza Kiani Mavi & Reza Farzipoor Saen & Neda Kiani Mavi, 2023. "A novel network DEA-R model for evaluating hospital services supply chain performance," Annals of Operations Research, Springer, vol. 324(1), pages 1041-1066, May.
    4. Kiani Mavi, Reza & Kiani Mavi, Neda & Farzipoor Saen, Reza & Goh, Mark, 2022. "Common weights analysis of renewable energy efficiency of OECD countries," Technological Forecasting and Social Change, Elsevier, vol. 185(C).

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