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Network-based method for ranking of efficient units in two-stage DEA models

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Journal of the Operational Research Society

Abstract

This study presents a methodology that is able to further discriminate the efficient decision-making units (DMUs) in a two-stage data envelopment analysis (DEA) context. The methodology is an extension of the single-stage network-based ranking method, which utilizes the eigenvector centrality concept in social network analysis to determine the rank of efficient DMUs. The mathematical formulation for the method to work under the two-stage DEA context is laid out and then applied to a real-world problem. In addition to its basic ranking function, the exercise highlights two particular features of the method that are not available in standard DEA: suggesting a benchmark unit for each input/intermediate/output factor, and identifying the strengths of each efficient unit. With the methodology, the value of DEA greatly increases.

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Acknowledgements

The authors would like to thank anonymous referees for their constructive comments that have much improved the readability of this article. This work is in part supported by Taiwan’s National Science Council grant NSC 99-2410-H-011-003.

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Authors and Affiliations

  1. National Taiwan University of Science and Technology, Taipei, Taiwan

    J S Liu

  2. National Defense University, Taipei, Taiwan

    W-M Lu

Authors
  1. J S Liu
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  2. W-M Lu
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Correspondence to J S Liu.

Appendix

Appendix

Table A1

Table A1 Data applied to demonstrate the network-based ranking method in a two-stage process, taken from Chen and Zhu (2004)
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Liu, J., Lu, WM. Network-based method for ranking of efficient units in two-stage DEA models. J Oper Res Soc 63, 1153–1164 (2012). https://doi.org/10.1057/jors.2011.132

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