Network data envelopment analysis: efficiency analysis of organizations with complex internal structure

Network data envelopment analysis: efficiency analysis of organizations with complex internal structure

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Article ID: iaor2005666
Country: United Kingdom
Volume: 31
Issue: 9
Start Page Number: 1365
End Page Number: 1410
Publication Date: Aug 2004
Journal: Computers and Operations Research
Authors: ,
Keywords: performance, statistics: data envelopment analysis
Abstract:

DEA models treat the DMU as a “black box.” Inputs enter and outputs exist, with no consideration of the intervening steps. Consequently, it is difficult, if not impossible, to provide individual DMU managers with specific information regarding the sources of inefficiency within their DMUs. We show how to use DEA to look inside the DMU, allowing greater insight as to the sources of organizational inefficiency. Our model applies to DMUs that consist of a network of Sub-DMUs, some of which consume resources produced by other Sub-DMUs and some of which produce resources consumed by other Sub-DMUs. Our Network DEA Model allows for either input orientation or an output orientation, any of the four standard assumptions regarding returns to scale in any Sub-DMU, and adjustments for site characteristics in each Sub-DMU. We demonstrate how to incorporate reverse quantities as inputs, intermediate products or outputs. Thus, we can apply the Network DEA Model presented here in many managerial contexts. We also prove some theoretical properties of the Network DEA Model. By applying the Network DEA Model to Major League Baseball, we demonstrate the advantages of the Network DEA Model over the standard DEA Model. Specifically, the Network DEA Model can detect inefficiencies that the standard DEA Model misses. Perhaps of greatest significance, the Network DEA Model allows individual DMU managers to focus efficiency-enhancing strategies on the individual stages of the production process.

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