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Anchor points in DEA

Author

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  • Bougnol, M.-L.
  • Dulá, J.H.

Abstract

Anchor points play an important role in DEA theory and application. They define the transition from the efficient frontier to the "free-disposability" portion of the boundary. Our objective is to use the geometrical properties of anchor points to design and test an algorithm for their identification. We focus on the variable returns to scale production possibility set; our results do not depend on any particular DEA LP formulation, primal/dual form or orientation. Tests on real and artificial data lead to unexpected insights into their role in the geometry of the DEA production possibility set.

Suggested Citation

  • Bougnol, M.-L. & Dulá, J.H., 2009. "Anchor points in DEA," European Journal of Operational Research, Elsevier, vol. 192(2), pages 668-676, January.
  • Handle: RePEc:eee:ejores:v:192:y:2009:i:2:p:668-676
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    Cited by:

    1. Victor V. Podinovski & Finn R. Førsund, 2010. "Differential Characteristics of Efficient Frontiers in Data Envelopment Analysis," Operations Research, INFORMS, vol. 58(6), pages 1743-1754, December.
    2. Chia-Yen Lee, 2017. "Directional marginal productivity: a foundation of meta-data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 544-555, May.
    3. Vladimir Krivonozhko & Finn Førsund & Andrey Lychev, 2015. "Terminal units in DEA: definition and determination," Journal of Productivity Analysis, Springer, vol. 43(2), pages 151-164, April.
    4. Mostafaee, A. & Soleimani-damaneh, M., 2014. "Identifying the anchor points in DEA using sensitivity analysis in linear programming," European Journal of Operational Research, Elsevier, vol. 237(1), pages 383-388.
    5. Tao Jie, 2020. "Parallel processing of the Build Hull algorithm to address the large-scale DEA problem," Annals of Operations Research, Springer, vol. 295(1), pages 453-481, December.
    6. J H Dulá, 2009. "A geometrical approach for generalizing the production possibility set in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1546-1555, November.
    7. Amin Mostafaee & Majid Soleimani-Damaneh, 2016. "Some Conditions for Characterizing Anchor Points," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(02), pages 1-17, April.
    8. Vladimir E. Krivonozhko & Finn R. Førsund & Andrey V. Lychev, 2017. "On comparison of different sets of units used for improving the frontier in DEA models," Annals of Operations Research, Springer, vol. 250(1), pages 5-20, March.
    9. 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.
    10. Chia -Yen Lee & Andrew L. Johnson, 2015. "Measuring Efficiency in Imperfectly Competitive Markets: An Example of Rational Inefficiency," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 702-722, February.
    11. Mehdiloo, Mahmood & Podinovski, Victor V., 2021. "Strong, weak and Farrell efficient frontiers of technologies satisfying different production assumptions," European Journal of Operational Research, Elsevier, vol. 294(1), pages 295-311.
    12. Førsund, Finn & Krivonozhko, Vladimir W & Lychev, Andrey V., 2016. "Smoothing the frontier in the DEA models," Memorandum 11/2016, Oslo University, Department of Economics.
    13. Lim, Dong-Joon, 2016. "Inverse DEA with frontier changes for new product target setting," European Journal of Operational Research, Elsevier, vol. 254(2), pages 510-516.
    14. Krivonozhko, Vladimir E. & Førsund, Finn R. & Lychev, Andrey V., 2012. "Identifying Suspicious Efficient Units in DEA Models," Memorandum 30/2012, Oslo University, Department of Economics.
    15. Soleimani-damaneh, Majid & Mostafaee, Amin, 2015. "Identification of the anchor points in FDH models," European Journal of Operational Research, Elsevier, vol. 246(3), pages 936-943.
    16. Amin Mostafaee & Sevan Sohraiee, 2019. "The role of hyperplanes for characterizing suspicious units in DEA," Annals of Operations Research, Springer, vol. 275(2), pages 531-549, April.
    17. J. H. Dulá, 2011. "An Algorithm for Data Envelopment Analysis," INFORMS Journal on Computing, INFORMS, vol. 23(2), pages 284-296, May.
    18. Thanassoulis, Emmanuel & Kortelainen, Mika & Allen, Rachel, 2012. "Improving envelopment in Data Envelopment Analysis under variable returns to scale," European Journal of Operational Research, Elsevier, vol. 218(1), pages 175-185.

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