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Multi-dimensional Nondiscretionary Factors in Data Envelopment Analysis: A Slack-Based Measure

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Abstract

Various extension using data envelopment analysis (DEA) are available in the literature for performance measurement in public sector. The existence of multiple non- discretionary factors in DEA based public sector models leads to overestimation of the efficiency. This paper proposes a two-step procedure to handle non-discretionary factors in DEA models. In the first step, the multiple non-discretionary factors are transformed into a single artificial factor and then, using a slack-based model the performance assessment is done. To highlight the comparison, an analysis using simulated data is performed. The results show that the proposed two-stage approach is relatively better than existing approaches when we apply the slack based measure of efficiency.

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Acknowledgments

Financial support by Rasht branch, Islamic Azad University Grant No. 4.5830 is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Applied mathematics, Islamic Azad University, Rasht, Iran

    Alireza Amirteimoori & Mahnaz Maghbouli

  2. Department of Applied mathematics, Islamic Azad University, Lahidjan, Iran

    Sohrab Kordrostami

Authors
  1. Alireza Amirteimoori
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  2. Mahnaz Maghbouli
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  3. Sohrab Kordrostami
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Correspondence to Alireza Amirteimoori.

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Amirteimoori, A., Maghbouli, M. & Kordrostami, S. Multi-dimensional Nondiscretionary Factors in Data Envelopment Analysis: A Slack-Based Measure. Comput Econ 48, 211–223 (2016). https://doi.org/10.1007/s10614-015-9525-4

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  • DOI: https://doi.org/10.1007/s10614-015-9525-4

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