 DEA models incorporating uncertain future performanceTsung-Sheng Chang, Kaoru Tone and Chen-Hui Wu European Journal of Operational Research, 2016, vol. 254, issue 2, 532-549 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. Keywords: Data envelopment analysis; Volatility; Forecast; Dynamic; Entropy (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:254:y:2016:i:2:p:532-549 DOI: 10.1016/j.ejor.2016.04.005 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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