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An Alternative Approach to Rank Efficient DMUs in DEA via Cross-Efficiency Evaluation, Gini Coefficient, and Bonferroni Mean

  • Zahra Behdani
  • Majid DarehmirakiEmail author
Article
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Abstract

In this paper, we focus on a critical problem in data envelopment analysis (DEA) and propose a simple resolution for it. The major problem of the DEA is the existence of several efficient decision-making units (DMUs). To deal with this issue, we introduce a method that involves cross-efficiency evaluation, Gini coefficient, and Bonferroni mean. First, a cross-efficiency matrix is developed. Then, mixing the Gini coefficient and Bonferroni mean, a Gini–Bonferroni (GB) index is proposed for ranking efficient DMUs, where the DMUs with bigger GB are ranked higher. The proposed method broke the tie between efficient DMUs. Finally, a numerical example and real application of this method are presented in the ranking of research and development (R&D) investment companies in the pharmaceutical and biotechnology industries.

Keywords

Data envelopment analysis Efficiency Gini coefficient Bonferroni mean Cross-efficiency evaluation Ranking Efficient units 

Mathematics Subject Classification

90B50 97K80 
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Notes

Acknowledgements

The authors thank the organizers of ICO2018, 4–5th October 2018, Hard Rock Hotel, Pattaya, Thailand, for the opportunity to presents their research results in this paper.

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Copyright information

© Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsBehbahan Khatam Alanbia University of TechnologyBehbahanIran

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