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Data Envelopment Analysis with Output-Bounded Data

Author

Listed:
  • Juan Du

    (School of Economics and Management, Tongji University, Shanghai 200092, P. R. China)

  • Jiazhen Huo

    (School of Economics and Management, Tongji University, Shanghai 200092, P. R. China)

  • Joe Zhu

    (College of Auditing and Evaluation, Nanjing Audit University, Nanjing 211815, P. R. China3Robert A. Foisie School of Business, Worcester Polytechnic Institute, Worcester, MA 01609, USA)

Abstract

In conventional data envelopment analysis (DEA), data are usually assumed to be non-negative with no specific bounds. However, many practical applications require some data, and thus their projections, to fall within certain limits. For example, percentage data such as the satisfactory rate cannot exceed 100% to make sense. This data characteristic is very likely to be violated under the assumption of constant returns to scale (CRS), due to its ray expansion property. In order to tackle this issue under CRS, a series of radial models are developed to constrain DEA projections within imposed bounds from the output side. Then efficient decision making units (DMUs) can be further discriminated simply by eliminating it from the reference set, avoiding the infeasibility problem existing in the VRS super-efficiency measures. The methodology is demonstrated with data consisting of 119 general acute care hospitals located in Pennsylvania, USA.

Suggested Citation

  • 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.
    • Handle: RePEc:wsi:apjorx:v:33:y:2016:i:06:n:s0217595916500500
    DOI: 10.1142/S0217595916500500
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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.
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