Network DEA: efficiency analysis of organizations with complex internal structure

DEA models treat the DMU as a “black box.” Inputs enter and outputs exit, with no consideration of the intervening steps. Consequently, it is di(cult, if not impossible, to provide individual DMU managers with speci;c information regarding the sources of ine(ciency within their DMUs. We show how to use DEA to look inside the DMU, allowing greater insight as to the sources of organizational ine(ciency. 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 an 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. Speci;cally, the Network DEA Model can detect ine(ciencies that the standard DEA Model misses. Perhaps of greatest signi;cance, the Network DEA Model allows individual DMU managers to focus e(ciency-enhancing strategies on the individual stages of the production process. ? 2003 Elsevier Ltd. All rights reserved.