A Decision Analysis of Multi-Attributed Queueing Systems
{'Code': '04050100', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
{'SignBlockName': 'Lisa Martin', 'PO_EMAI': None, 'PO_PHON': None}
The research funded by this proposal extends research under a previous          NSF grant.  The research combines empirical case research with modeling         methods to develop (1) a behavioral multi-attribute understanding of            queues, (2) new performance measures for queueing applications that             incorporate the behavioral attributes, and (3) develop and test a new           class of management science queueing models.  The working laboratories          for the research include a retail branch of the U.S. Postal Service, a          major retail bank and a national department store chain.                                                                                                        The longer range outcome of this research include new directions for            research on queueing theory and a prescriptive methodology for very             significant productivity improvements in congested service systems              that would increase customers' utility of the queueing experience at            costs for less than required to add servers or technology to speed              service.
{'FirstName': 'Richard', 'LastName': 'Larson', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Richard C Larson', 'EmailAddress': 'rclarson@mit.edu', 'NSF_ID': '000189196', 'StartDate': '09/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'E2NYLCDML6V1', 'ORG_LGL_BUS_NAME': 'MASSACHUSETTS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'E2NYLCDML6V1'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '132100', 'Text': 'Decision, Risk & Mgmt Sci'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8709811.xml'}