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DEA with efficiency classification preserving conditional convexity

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  • Kuosmanen, Timo

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  • Kuosmanen, Timo, 2001. "DEA with efficiency classification preserving conditional convexity," European Journal of Operational Research, Elsevier, vol. 132(2), pages 326-342, July.
    • Handle: RePEc:eee:ejores:v:132:y:2001:i:2:p:326-342
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    34. Laurens Cherchye & Timo Kuosmanen & Thierry Post, 2000. "What Is the Economic Meaning of FDH? A Reply to Thrall," Journal of Productivity Analysis, Springer, vol. 13(3), pages 263-267, May.
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    Cited by:

    1. Mehdiloozad, Mahmood & Podinovski, Victor V., 2018. "Nonparametric production technologies with weakly disposable inputs," European Journal of Operational Research, Elsevier, vol. 266(1), pages 247-258.
    2. Cherchye, L. & Post, G.T., 2001. "Methodological Advances in Dea," ERIM Report Series Research in Management ERS-2001-53-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Podinovski, V. V., 2005. "Selective convexity in DEA models," European Journal of Operational Research, Elsevier, vol. 161(2), pages 552-563, March.
    4. Kuosmanen, Timo & Post, Thierry, 2001. "Measuring economic efficiency with incomplete price information: With an application to European commercial banks," European Journal of Operational Research, Elsevier, vol. 134(1), pages 43-58, October.
    5. R H Green & W D Cook, 2004. "A free coordination hull approach to efficiency measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1059-1063, October.
    6. Brandon Pope & Andrew Johnson, 2013. "Returns to scope: a metric for production synergies demonstrated for hospital production," Journal of Productivity Analysis, Springer, vol. 40(2), pages 239-250, October.
    7. Olesen, Ole B. & Ruggiero, John, 2014. "Maintaining the Regular Ultra Passum Law in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 235(3), pages 798-809.
    8. Kaoru Tone & Miki Tsutsui, 2013. "How to deal with S-shaped curve in DEA," GRIPS Discussion Papers 13-10, National Graduate Institute for Policy Studies.
    9. Victor Podinovski, 2004. "Efficiency and Global Scale Characteristics on the “No Free Lunch” Assumption Only," Journal of Productivity Analysis, Springer, vol. 22(3), pages 227-257, November.
    10. Kounetas, Konstantinos E. & Polemis, Michael L. & Tzeremes, Nickolaos G., 2021. "Measurement of eco-efficiency and convergence: Evidence from a non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 291(1), pages 365-378.
    11. Monge, Juan F. & Ruiz, José L., 2023. "Setting closer targets based on non-dominated convex combinations of Pareto-efficient units: A bi-level linear programming approach in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1084-1096.
    12. Timo Kuosmanen, 2003. "Duality Theory of Non-convex Technologies," Journal of Productivity Analysis, Springer, vol. 20(3), pages 273-304, November.
    13. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    14. An, Qingxian & Tao, Xiangyang & Chen, Xiaohong, 2023. "Nested frontier-based best practice regulation under asymmetric information in a principal–agent framework," European Journal of Operational Research, Elsevier, vol. 306(1), pages 269-285.
    15. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.
    16. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
    17. T Kuosmanen, 2009. "Data envelopment analysis with missing data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1767-1774, December.
    18. Laurens Cherchye & Timo Kuosmanen & Thierry Post, 2001. "FDH Directional Distance Functions with an Application to European Commercial Banks," Journal of Productivity Analysis, Springer, vol. 15(3), pages 201-215, January.
    19. Cherchye, Laurens & De Rock, Bram & Hennebel, Veerle, 2014. "The economic meaning of Data Envelopment Analysis: A ‘behavioral’ perspective," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 29-37.
    20. Michael L. Polemis & Thanasis Stengos & Nickolaos G. Tzeremes, 2020. "Modeling the effect of competition on US manufacturing sectors’ efficiency: an order-m frontier analysis," Journal of Productivity Analysis, Springer, vol. 54(1), pages 27-41, August.
    21. Timo Kuosmanen & Thierry Post, 2002. "Nonparametric Efficiency Analysis under Price Uncertainty: A First-Order Stochastic Dominance Approach," Journal of Productivity Analysis, Springer, vol. 17(3), pages 183-200, May.
    22. V V Podinovski, 2004. "Local and global returns to scale in performance measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 170-178, February.
    23. Timo Kuosmanen & Mika Kortelainen, 2012. "Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints," Journal of Productivity Analysis, Springer, vol. 38(1), pages 11-28, August.

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