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An enhanced BAM for unbounded or partially bounded CRS additive models

Author

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  • Pastor, Jesus T.
  • Aparicio, Juan
  • Alcaraz, Javier
  • Vidal, Fernando
  • Pastor, Diego

Abstract

The Bounded Adjusted Measure (BAM), initially defined for the additive model, which is a variable returns to scale (VRS) model, was extended to the constant returns to scale (CRS) case [7]. The added range-bounds, which maintain unaltered the production possibility set (PPS) under VRS, showed an influential effect under CRS, reducing the corresponding PPS, as well as a negative effect, excluding some of the original CRS projections. Here we propose an enhanced extension that, by considering a different set of less restrictive bounds, eliminates the negative effect. Moreover, we customize this new extension for the family of partially bounded CRS additive models, i.e., models where at least one variable is naturally bounded from below, if it is an input, or from above, if it is an output.

Suggested Citation

  • Pastor, Jesus T. & Aparicio, Juan & Alcaraz, Javier & Vidal, Fernando & Pastor, Diego, 2015. "An enhanced BAM for unbounded or partially bounded CRS additive models," Omega, Elsevier, vol. 56(C), pages 16-24.
  • Handle: RePEc:eee:jomega:v:56:y:2015:i:c:p:16-24
    DOI: 10.1016/j.omega.2015.02.009
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    References listed on IDEAS

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    1. Jesus Pastor & Juan Aparicio & Juan Monge & Diego Pastor, 2013. "Modeling CRS bounded additive DEA models and characterizing their Pareto-efficient points," Journal of Productivity Analysis, Springer, vol. 40(3), pages 285-292, December.
    2. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
    3. Atici, Kazim Baris & Podinovski, Victor V., 2015. "Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: An application to agriculture," Omega, Elsevier, vol. 54(C), pages 72-83.
    4. Aparicio, Juan & Pastor, Jesus T., 2014. "Closest targets and strong monotonicity on the strongly efficient frontier in DEA," Omega, Elsevier, vol. 44(C), pages 51-57.
    5. Kao, Chiang, 2014. "Efficiency decomposition in network data envelopment analysis with slacks-based measures," Omega, Elsevier, vol. 45(C), pages 1-6.
    6. Cooper, W.W. & Pastor, Jesus T. & Aparicio, Juan & Borras, Fernando, 2011. "Decomposing profit inefficiency in DEA through the weighted additive model," European Journal of Operational Research, Elsevier, vol. 212(2), pages 411-416, July.
    7. 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.
    8. Fang, Lei, 2015. "Centralized resource allocation based on efficiency analysis for step-by-step improvement paths," Omega, Elsevier, vol. 51(C), pages 24-28.
    9. Fang, Hsin-Hsiung & Lee, Hsuan-Shih & Hwang, Shiuh-Nan & Chung, Cheng-Chi, 2013. "A slacks-based measure of super-efficiency in data envelopment analysis: An alternative approach," Omega, Elsevier, vol. 41(4), pages 731-734.
    10. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    11. William Cooper & Jesús Pastor & Fernando Borras & Juan Aparicio & Diego Pastor, 2011. "BAM: a bounded adjusted measure of efficiency for use with bounded additive models," Journal of Productivity Analysis, Springer, vol. 35(2), pages 85-94, April.
    12. Sungmook Lim & Joe Zhu, 2015. "DEA cross-efficiency evaluation under variable returns to scale," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(3), pages 476-487, March.
    13. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
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    Cited by:

    1. Podinovski, Victor V. & Bouzdine-Chameeva, Tatiana, 2019. "Cone extensions of polyhedral production technologies," European Journal of Operational Research, Elsevier, vol. 276(2), pages 736-743.
    2. Aparicio, Juan & Pastor, Jesus T. & Vidal, Fernando, 2016. "The directional distance function and the translation invariance property," Omega, Elsevier, vol. 58(C), pages 1-3.
    3. Aparicio, Juan & Ortiz, Lidia & Pastor, Jesus T., 2017. "Measuring and decomposing profit inefficiency through the Slacks-Based Measure," European Journal of Operational Research, Elsevier, vol. 260(2), pages 650-654.
    4. Juan Du & Jiazhen Huo & Joe Zhu, 2016. "Data Envelopment Analysis with Output-Bounded Data," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(06), pages 1-17, December.
    5. Jesus T. Pastor & Juan Aparicio & Javier Alcaraz & Fernando Vidal & Diego Pastor, 2018. "Bounded directional distance function models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 985-1004, December.

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