A Personalist Approach to Estimating Populations of         Institutions
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
{'SignBlockName': 'Ritchie B. Coryell', 'PO_EMAI': None, 'PO_PHON': None}
More than 10 million U.S. businesses and other institutions                spend over two trillion dollars per year purchasing goods and                   services. Yet many studies have shown that over 70 percent of the               money business and industry spends on new product development is                spent on products that are never commercially successful. Better                quality and more timely research would help this market operate                 more efficiently and allow U.S. suppliers to be more effective in               a global economy.                                                                    The recommended award will support the final (Phase II)                    stage of a project funded under the Small Business Innovation                   Research Program. In Phase II, research will be completed on a                  methodology for industrial market research based upon an approach               to institutional estimation known as "Bayesian," in which heavy                 reliance is placed upon prior judgmental estimates of sources of                error. Accumulated experience in application will provide a                     valuable capital stock of knowledge and expertise that has proven               commercially valuable in other areas of market research. Specific               developments will include institutional data bases along with                   user interfaces and analytic algorithms for performing estimation               studies, and the actual performance of such studies for purposes                of evaluating internal (logical) consistency and external                       validity, including economic valuation.                                              The ultimate aim is to provide a commercial service for the                design, evaluation, and interpretation of institutional                         estimation studies employed in industrial market research. Users                and practitioners of industrial market research would be                        offered both the materials and know-how for applying innovative                 analytic technology in conjunction with complementary survey                    techniques, sampling frames, and data resources. Given that                     quantitative institutional research accounts for billions of                    dollars each year, the potential market for such a service is                   very large.
{'FirstName': 'Rex', 'LastName': 'Brown', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rex V Brown', 'EmailAddress': 'rbrown@osf1.gmu.edu', 'PI_PHON': '7036202443', 'NSF_ID': '000100704', 'StartDate': '08/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Decision Science Consortium Inc', 'CityName': 'Reston', 'ZipCode': '220915434', 'PhoneNumber': '7036200660', 'StreetAddress': '1895 Preston White Dr Suite 300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': None, 'ORG_LGL_BUS_NAME': None, 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '5373', 'Text': 'SBIR Phase II'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8722149.xml'}