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Identifying Critical Measures in DEA

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 213))

Abstract

Since each DMU has its own inherent tradeoffs among the multiple measures that significantly influence the performance, it is extremely important for the management to know the critical measures. The current chapter introduces the approach of Chen and Zhu (Annals of Operations Research, 124 (1–4), 225–244, 2003) for identifying the critical measures to DMUs’ performance. Note that once the DEA evaluation is done, the management needs to either (i) maintain the best practice for the efficient DMUs or (ii) achieve the best practice for the inefficient DMUs. Thus, when a set of multiple performance measures is determined, measures that are influential to maintaining and achieving the best practice should be regarded as critical to the performance of DMUs. Also, it is believed that a critical measure is signaled by whether changes in its value affect the performance, not by whether inclusion or exclusion of the measure affects the performance.

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Notes

  1. 1.

    Note that for example, if the second input of DMU A decreases its current level to 3, the level used by DMU B, then we no longer have the efficient facet AB. Since DMU B becomes inefficient.

References

  • Chen, Y., & Zhu, J. (2003). DEA models for identifying critical performance measures. Annals of Operations Research, 124 (1–4), 225–244.

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  • Wilkens, K., & Zhu, J. (2001). Portfolio evaluation and benchmark selection: A mathematical programming approach. Journal of Alternative Investments, 4 (1), 9–19.

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Correspondence to Joe Zhu .

17.1 Electronic Supplementary Material

The online version of this chapter (doi:10.1007/978-3-319-06647-9_17) contains supplementary material, which is available to authorized users.

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Zhu, J. (2014). Identifying Critical Measures in DEA. In: Quantitative Models for Performance Evaluation and Benchmarking. International Series in Operations Research & Management Science, vol 213. Springer, Cham. https://doi.org/10.1007/978-3-319-06647-9_17

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