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 difficult, if not impossible, to provide individual DMU managers with specific information regarding the sources of inefficiency within their DMUs. We show ho...
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Veröffentlicht in: | Computers & operations research 2004-08, Vol.31 (9), p.1365-1410 |
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creator | Lewis, Herbert F. Sexton, Thomas R. |
description | DEA models treat the DMU as a “black box.” Inputs enter and outputs exit, 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 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. 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. |
doi_str_mv | 10.1016/S0305-0548(03)00095-9 |
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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.</description><identifier>ISSN: 0305-0548</identifier><identifier>EISSN: 1873-765X</identifier><identifier>EISSN: 0305-0548</identifier><identifier>DOI: 10.1016/S0305-0548(03)00095-9</identifier><identifier>CODEN: CMORAP</identifier><language>eng</language><publisher>New York: Elsevier Ltd</publisher><subject>Computer networks ; Data envelopment analysis ; Efficiency ; Major league baseball ; Networks ; Operations research ; Productivity ; Professional baseball ; Statistical analysis</subject><ispartof>Computers & operations research, 2004-08, Vol.31 (9), p.1365-1410</ispartof><rights>2003 Elsevier Ltd</rights><rights>Copyright Pergamon Press Inc. Aug 2004</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c386t-91603c14764384fe4de3bd843bca008ba15898a037c6de5c0045e1dc863dd2893</citedby><cites>FETCH-LOGICAL-c386t-91603c14764384fe4de3bd843bca008ba15898a037c6de5c0045e1dc863dd2893</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0305054803000959$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Lewis, Herbert F.</creatorcontrib><creatorcontrib>Sexton, Thomas R.</creatorcontrib><title>Network DEA: efficiency analysis of organizations with complex internal structure</title><title>Computers & operations research</title><description>DEA models treat the DMU as a “black box.” Inputs enter and outputs exit, 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 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. 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.</description><subject>Computer networks</subject><subject>Data envelopment analysis</subject><subject>Efficiency</subject><subject>Major league baseball</subject><subject>Networks</subject><subject>Operations research</subject><subject>Productivity</subject><subject>Professional baseball</subject><subject>Statistical analysis</subject><issn>0305-0548</issn><issn>1873-765X</issn><issn>0305-0548</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LAzEQQIMoWKs_QQie9LA6aZLdrBcptX5AUUQFbyHNzmpqu6lJaq2_3n6IV09zefOYeYQcMjhlwPKzR-AgM5BCHQM_AYBSZuUWaTFV8KzI5cs2af0hu2QvxtESgqLDWuThDtPch3d62e-eU6xrZx02dkFNY8aL6CL1NfXh1TTu2yTnm0jnLr1R6yfTMX5R1yQMS5TGFGY2zQLuk53ajCMe_M42eb7qP_VussH99W2vO8gsV3nKSpYDt0wUueBK1Cgq5MNKCT60BkANDZOqVAZ4YfMKpQUQElllVc6rqqNK3iZHG-80-I8ZxqRHfrY6JWpWSiUKUcISkhvIBh9jwFpPg5uYsNAM9CqeXsfTqzIauF7H0yv5xWYPlx98Ogw6rrtg5QLapCvv_jH8AB7MdqY</recordid><startdate>20040801</startdate><enddate>20040801</enddate><creator>Lewis, Herbert F.</creator><creator>Sexton, Thomas R.</creator><general>Elsevier Ltd</general><general>Pergamon Press Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20040801</creationdate><title>Network DEA: efficiency analysis of organizations with complex internal structure</title><author>Lewis, Herbert F. ; Sexton, Thomas R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c386t-91603c14764384fe4de3bd843bca008ba15898a037c6de5c0045e1dc863dd2893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Computer networks</topic><topic>Data envelopment analysis</topic><topic>Efficiency</topic><topic>Major league baseball</topic><topic>Networks</topic><topic>Operations research</topic><topic>Productivity</topic><topic>Professional baseball</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lewis, Herbert F.</creatorcontrib><creatorcontrib>Sexton, Thomas R.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & operations research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lewis, Herbert F.</au><au>Sexton, Thomas R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Network DEA: efficiency analysis of organizations with complex internal structure</atitle><jtitle>Computers & operations research</jtitle><date>2004-08-01</date><risdate>2004</risdate><volume>31</volume><issue>9</issue><spage>1365</spage><epage>1410</epage><pages>1365-1410</pages><issn>0305-0548</issn><eissn>1873-765X</eissn><eissn>0305-0548</eissn><coden>CMORAP</coden><abstract>DEA models treat the DMU as a “black box.” Inputs enter and outputs exit, 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 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. 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.</abstract><cop>New York</cop><pub>Elsevier Ltd</pub><doi>10.1016/S0305-0548(03)00095-9</doi><tpages>46</tpages></addata></record> |
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subjects | Computer networks Data envelopment analysis Efficiency Major league baseball Networks Operations research Productivity Professional baseball Statistical analysis |
title | Network DEA: efficiency analysis of organizations with complex internal structure |
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