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.
|Title of host publication||Advances in DEA Theory and Applications|
|Subtitle of host publication||With Examples in Forecasting Models|
|Number of pages||36|
|State||Published - 21 Oct 2016|
- Data envelopment analysis