Dea models incorporating uncertain future performance

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter


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, no DEA models have been 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 efficiency.

Original languageEnglish
Title of host publicationAdvances in DEA Theory and Applications
Subtitle of host publicationWith Examples in Forecasting Models
PublisherWiley Blackwell
Number of pages36
ISBN (Electronic)9781118946688
ISBN (Print)9781118946701
StatePublished - 21 Oct 2016


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

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    Chang, T-S., Tone, K., & Wu, C. H. (2016). Dea models incorporating uncertain future performance. In Advances in DEA Theory and Applications: With Examples in Forecasting Models (pp. 480-515). Wiley Blackwell.