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A consensual peer-based DEA-model with optimized cross-efficiencies - Input allocation instead of radial reduction

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  • Rödder, W.
  • Reucher, E.

Abstract

Data Envelopment Analysis DEA is a method for estimating (in-)efficiencies of Decision Making Units DMUs by means of weighted output - to input - ratios, being the weights optimal virtual prices of such ex-post activities for all units. The cross-efficiency matrix then evaluates these output - to input - relations with respect to all optimal price systems, and hence permits efficiency rankings for the DMUs by aggregating the matrix entries line - and/or columnwise. In this contribution the classical input oriented DEA approach is generalized twofold: its first aim is an optimal efficiency improving input allocation rather than a mere radial input reduction. The second aim is the choice of a peer-DMU, the price system of which is acceptable for the remaining units. As free input allocation permits substitutional effects and so rises productivities in view of possible peers and for all units, it supports such consensual choice. Numerical examples show the positive effects of the new concept.

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  • Rödder, W. & Reucher, E., 2011. "A consensual peer-based DEA-model with optimized cross-efficiencies - Input allocation instead of radial reduction," European Journal of Operational Research, Elsevier, vol. 212(1), pages 148-154, July.
    • Handle: RePEc:eee:ejores:v:212:y:2011:i:1:p:148-154
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    1. Wu, Jie & Liang, Liang & Yang, Feng, 2009. "Achievement and benchmarking of countries at the Summer Olympics using cross efficiency evaluation method," European Journal of Operational Research, Elsevier, vol. 197(2), pages 722-730, September.
    2. 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.
    3. Jie Wu & Liang Liang & Dexiang Wu & Feng Yang, 2008. "Olympics ranking and benchmarking based on cross efficiency evaluation method and cluster analysis: the case of Sydney 2000," International Journal of Enterprise Network Management, Inderscience Enterprises Ltd, vol. 2(4), pages 377-392.
    4. 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.
    5. Homburg, Carsten, 2001. "Using data envelopment analysis to benchmark activities," International Journal of Production Economics, Elsevier, vol. 73(1), pages 51-58, August.
    6. Chen, Tser-yieth, 2002. "An assessment of technical efficiency and cross-efficiency in Taiwan's electricity distribution sector," European Journal of Operational Research, Elsevier, vol. 137(2), pages 421-433, March.
    7. C-P Bao & T-H Chen & S-Y Chang, 2008. "Slack-based ranking method: an interpretation to the cross-efficiency method in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(6), pages 860-862, June.
    8. 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.
    9. Muhittin Oral & Ossama Kettani & Pascal Lang, 1991. "A Methodology for Collective Evaluation and Selection of Industrial R&D Projects," Management Science, INFORMS, vol. 37(7), pages 871-885, July.
    10. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    11. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    12. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, December.
    13. Fandel, Gunter, 2007. "On the performance of universities in North Rhine-Westphalia, Germany: Government's redistribution of funds judged using DEA efficiency measures," European Journal of Operational Research, Elsevier, vol. 176(1), pages 521-533, January.
    14. Liang Liang & Jie Wu & Wade D. Cook & Joe Zhu, 2008. "The DEA Game Cross-Efficiency Model and Its Nash Equilibrium," Operations Research, INFORMS, vol. 56(5), pages 1278-1288, October.
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    2. Hamid Kiaei & Reza Farzipoor Saen & Reza Kazemi Matin, 2023. "Cross-efficiency evaluation and improvement in two-stage network data envelopment analysis," Annals of Operations Research, Springer, vol. 321(1), pages 281-309, February.
    3. Rödder, W. & Reucher, E., 2012. "Advanced X-efficiencies for CCR- and BCC-models – towards Peer-based DEA controlling," European Journal of Operational Research, Elsevier, vol. 219(2), pages 467-476.
    4. Wang, Yizhong & Jeong, Sujong & Hang, Ye & Wang, Qunwei, 2024. "Multi-sector environmental efficiency and productivity: A general Leontief optimization method," Omega, Elsevier, vol. 126(C).
    5. Yang, Guo-liang & Yang, Jian-bo & Liu, Wen-bin & Li, Xiao-xuan, 2013. "Cross-efficiency aggregation in DEA models using the evidential-reasoning approach," European Journal of Operational Research, Elsevier, vol. 231(2), pages 393-404.

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