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Some alternative models for DEA cross-efficiency evaluation

  • Wang, Ying-Ming
  • Chin, Kwai-Sang
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    Cross-efficiency evaluation is an effective method for ranking decision-making units (DMUs) in data envelopment analysis (DEA) and can be performed with different formulations (aggressive or benevolent), secondary goals, and models. This paper proposes some new alternative models for DEA cross-efficiency evaluation to provide more methodological options for the decision maker (DM) to choose from. The proposed new alternative models are illustrated with two numerical examples. The results are believed to be more realistic than those obtained by the alternative secondary goals suggested by Liang et al. [Liang, L., Wu, J., Cook, W.D. and Zhu, J., 2008a. Alternative secondary goals in DEA cross-efficiency evaluation. International Journal of Production Economics 113 (2), 1025-1030].

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    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 128 (2010)
    Issue (Month): 1 (November)
    Pages: 332-338

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    Handle: RePEc:eee:proeco:v:128:y:2010:i:1:p:332-338
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    1. Wu, Desheng Dash, 2009. "Performance evaluation: An integrated method using data envelopment analysis and fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 194(1), pages 227-235, April.
    2. Kao, Chiang, 2010. "Congestion measurement and elimination under the framework of data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 123(2), pages 257-265, February.
    3. Liang, Liang & Wu, Jie & Cook, Wade D. & Zhu, Joe, 2008. "Alternative secondary goals in DEA cross-efficiency evaluation," International Journal of Production Economics, Elsevier, vol. 113(2), pages 1025-1030, June.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Xu, Jiuping & Li, Bin & Wu, Desheng, 2009. "Rough data envelopment analysis and its application to supply chain performance evaluation," International Journal of Production Economics, Elsevier, vol. 122(2), pages 628-638, December.
    6. Bruni, M.E. & Conforti, D. & Beraldi, P. & Tundis, E., 2009. "Probabilistically constrained models for efficiency and dominance in DEA," International Journal of Production Economics, Elsevier, vol. 117(1), pages 219-228, January.
    7. Tofallis, C., 1996. "Improving discernment in DEA using profiling," Omega, Elsevier, vol. 24(3), pages 361-364, June.
    8. Barros, Carlos Pestana & Peypoch, Nicolas, 2009. "An evaluation of European airlines' operational performance," International Journal of Production Economics, Elsevier, vol. 122(2), pages 525-533, December.
    9. Lu, Wen-Min & Lo, Shih-Fang, 2007. "A closer look at the economic-environmental disparities for regional development in China," European Journal of Operational Research, Elsevier, vol. 183(2), pages 882-894, December.
    10. Ertay, Tijen & Ruan, Da, 2005. "Data envelopment analysis based decision model for optimal operator allocation in CMS," European Journal of Operational Research, Elsevier, vol. 164(3), pages 800-810, August.
    11. Leleu, Hervé & Briec, Walter, 2009. "A DEA estimation of a lower bound for firms' allocative efficiency without information on price data," International Journal of Production Economics, Elsevier, vol. 121(1), pages 203-211, September.
    12. Green, Rodney H. & Doyle, John R. & Cook, Wade D., 1996. "Preference voting and project ranking using DEA and cross-evaluation," European Journal of Operational Research, Elsevier, vol. 90(3), pages 461-472, May.
    13. Shang, Jen & Sueyoshi, Toshiyuki, 1995. "A unified framework for the selection of a Flexible Manufacturing System," European Journal of Operational Research, Elsevier, vol. 85(2), pages 297-315, September.
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