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A variant of radial measure capable of dealing with negative inputs and outputs in data envelopment analysis

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  • Cheng, Gang
  • Zervopoulos, Panagiotis
  • Qian, Zhenhua

Abstract

Data envelopment analysis (DEA) is a linear programming methodology to evaluate the relative technical efficiency for each member of a set of peer decision making units (DMUs) with multiple inputs and multiple outputs. It has been widely used to measure performance in many areas. A weakness of the traditional DEA model is that it cannot deal with negative input or output values. There have been many studies exploring this issue, and various approaches have been proposed.

Suggested Citation

  • Cheng, Gang & Zervopoulos, Panagiotis & Qian, Zhenhua, 2013. "A variant of radial measure capable of dealing with negative inputs and outputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 225(1), pages 100-105.
  • Handle: RePEc:eee:ejores:v:225:y:2013:i:1:p:100-105 DOI: 10.1016/j.ejor.2012.09.031
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    References listed on IDEAS

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    1. Muliaman D. Hadad & Maximilian J. B. Hall & Wimboh Santoso & Karligash Kenjegalieva & Richard Simper, 2009. "A New Approach to Dealing With Negative Numbers in Efficiency Analysis: An Application to the Indonesian Banking Sector," Discussion Paper Series 2009_20, Department of Economics, Loughborough University, revised Dec 2009.
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    3. Emrouznejad, Ali & Amin, Gholam R. & Thanassoulis, Emmanuel & Anouze, Abdel Latef, 2010. "On the boundedness of the SORM DEA models with negative data," European Journal of Operational Research, Elsevier, vol. 206(1), pages 265-268, October.
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    9. 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.
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    Cited by:

    1. Cordero Ferrera, Jose Manuel & Alonso Morán, Edurne & Nuño Solís, Roberto & Orueta, Juan F. & Souto Arce, Regina, 2013. "Efficiency assessment of primary care providers: A conditional nonparametric approach," MPRA Paper 51926, University Library of Munich, Germany.
    2. repec:pal:jorsoc:v:68:y:2017:i:11:d:10.1057_s41274-016-0137-8 is not listed on IDEAS
    3. 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.
    4. Kerstens, Kristiaan & Van de Woestyne, Ignace, 2014. "A note on a variant of radial measure capable of dealing with negative inputs and outputs in DEA," European Journal of Operational Research, Elsevier, pages 341-342.
    5. Cordero, José Manuel & Alonso-Morán, Edurne & Nuño-Solinis, Roberto & Orueta, Juan F. & Arce, Regina Sauto, 2015. "Efficiency assessment of primary care providers: A conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 235-244.
    6. Li, Tao & Yang, Wenyue & Zhang, Haoran & Cao, Xiaoshu, 2016. "Evaluating the impact of transport investment on the efficiency of regional integrated transport systems in China," Transport Policy, Elsevier, vol. 45(C), pages 66-76.
    7. Banker, Rajiv & Chen, Janice Y.S. & Klumpes, Paul, 2016. "A trade-level DEA model to evaluate relative performance of investment fund managers," European Journal of Operational Research, Elsevier, vol. 255(3), pages 903-910.
    8. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.

    More about this item

    Keywords

    Data envelopment analysis; Negative data; Variant of radial measure; Unit invariance;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

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