Measuring the performances of decision-making units using geometric average efficiency
提出将乐观和悲观两种效率整合为几何平均效率，以更全面衡量决策单元的整体表现，并证明其区分能力优于单一效率。
The performances of decision-making units (DMUs) can be measured from two different points of view: optimistic or pessimistic, which leads to two different efficiencies for each DMU: the best relative efficiency and the worst relative efficiency. The conventional data envelopment analysis (DEA) considers only the best relative efficiency. It is argued that the two different efficiencies should be considered together and any approach considers only one of them is biased. This paper proposes to integrate the two different efficiencies into a geometric average efficiency, which measures the overall performance of each DMU. It is found that the geometric average efficiency has better discriminating power than either of the two efficiencies. This is illustrated by two numerical examples.