DEA models incorporating uncertain future performance

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

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.

Original languageEnglish
Pages (from-to)532-549
Number of pages18
JournalEuropean Journal of Operational Research
Volume254
Issue number2
DOIs
StatePublished - 16 Oct 2016

Keywords

  • Data envelopment analysis
  • Dynamic
  • Entropy
  • Forecast
  • Volatility

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