Extending the Bases and Improving the Uses of Data          Envelopment Analysis
{'Code': '04050100', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
{'SignBlockName': 'Shelton White', 'PO_EMAI': None, 'PO_PHON': None}
The overall purpose of this project is to extend previous work on Data          Envelopment Analysis (DEA)--a method for analyzing and evaluating the           relative efficiency and effectiveness of organizational units with              multiple outputs and multiple inputs.  The proposed work builds on              previous theoretical nd methodological work on DEA by the two principal         investigators.  This research will extend this work by addressing               important theoretical, methodological, and applied issues related to            the use of semi-infinite programming, times series analysis,                    envelopment maps, and cone ratio analysis.  In addition, the proposal           includes funds for a workshop aimed at assessing the state of knowledge         in DEA and identifying future directions for basic and applied                  research.                                                                                                                                                       Despite the importance of methods for analyzing and evaluating                  organizational efficiency and effectiveness, conventional methods               provide an inadequate means for representing and measuring the complex          factors that affect efficiency and effectiveness in organizations.              This innovative project will use anew and powerful mathematical                 programming methodology--Data Envelopment Analysis--to address this             issue.  It is expected to the development of methods for analyzing              organizational efficiency and effectiveness.  The project will also             provide important information for both analysts and decision makers             interested in improving organizational efficiency and effectiveness in          the public and private sector.  The principal investigators are highly          experienced researchers who have made numerous important contributions          to the literature on operations research and management science.
[{'FirstName': 'A.', 'LastName': 'Charnes', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'A. Charnes', 'EmailAddress': None, 'NSF_ID': '000213319', 'StartDate': '05/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'William', 'LastName': 'Cooper', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William W Cooper', 'EmailAddress': 'cooperw@mail.utexas.edu', 'NSF_ID': '000213304', 'StartDate': '05/01/1988', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
{'Name': 'University of Texas at Austin', 'CityName': 'AUSTIN', 'ZipCode': '787121139', 'PhoneNumber': '5124716424', 'StreetAddress': '110 INNER CAMPUS DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'V6AFQPN18437', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT AUSTIN', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '132100', 'Text': 'Decision, Risk & Mgmt Sci'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8722504.xml'}