Performance measures for hierarchical organizations: Frontier analysis as a decision support tool
We extend the standard frontier efficiency models (data envelopment analysis [DEA] and stochastic frontier analysis [SFA]) by allowing the “decision making units” (DMUs) whose performances are assessed to consist of two different levels within hierarchical organizations. Generally, the lower level unit is responsible for “operations;” while higher level units are assumed to make “strategic” decisions. Our primary contribution in this paper is thus to extend the use of frontier efficiency models to assess each level performance with relevant technical and allocative inefficiency measures. We illustrate our approach using DEA applied to data from a sample of 1,585 branches of a major French bank. A second contribution of the paper is to explicitly relate the efficiency to differences in the operating environments and the sizes of the bank branches. We believe that the simple, easy to implement method we introduce can serve as a valuable component of a “balanced score card” approach to benchmarking performance within hierarchical settings such as a banking network.
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