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DEA models incorporating uncertain future performance

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  • Chang, Tsung-Sheng
  • Tone, Kaoru
  • Wu, Chen-Hui

Abstract

Conventional data envelopment analysis (DEA) models are designed for measuring the productive efficiency of decision making units (DMUs) based merely on historical data. However, in many practical applications, such past results are not sufficient for evaluating a DMU's performance in highly volatile operating environments, such as those with highly volatile crude oil prices and currency exchange rates. That is, in such environments, a DMU's whole performance may be seriously distorted if its future performance, which is sensitive to crude oil price volatility and/or currency fluctuations, is ignored in the evaluation process. However, despite its importance, to our knowledge, there are no DEA models proposed in the literature that explicitly take future performance volatility into account. Hence, this research aims at developing a new system of DEA models that incorporate a DMU's uncertain future performance, and thus can be applied to fully measure their efficiency.

Suggested Citation

  • Chang, Tsung-Sheng & Tone, Kaoru & Wu, Chen-Hui, 2016. "DEA models incorporating uncertain future performance," European Journal of Operational Research, Elsevier, vol. 254(2), pages 532-549.
    • Handle: RePEc:eee:ejores:v:254:y:2016:i:2:p:532-549
    DOI: 10.1016/j.ejor.2016.04.005
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    References listed on IDEAS

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    1. Nada R. Sanders & Karl B. Manrodt, 1994. "Forecasting Practices in US Corporations: Survey Results," Interfaces, INFORMS, vol. 24(2), pages 92-100, April.
    2. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    3. 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.
    4. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, September.
    5. Tsung-Sheng Chang & Kaoru Tone & Chen-Hui Wu, 2015. "Past-present-future Intertemporal DEA models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(1), pages 16-32, January.
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    Cited by:

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