• DocumentCode
    2623652
  • Title

    Using fuzzy rule based economic models to measure the performance of state funded agencies

  • Author

    Ammar, Salwa ; Wright, Ronald ; Leathley, Jennifer ; McDonnell, Ian

  • Author_Institution
    Dept. of Bus. Adm., LeMoyne Coll., Syracuse, NY, USA
  • fYear
    1997
  • fDate
    21-24 Sep 1997
  • Firstpage
    418
  • Lastpage
    422
  • Abstract
    US state governments have been seeking analytical methods to show that taxpayer dollars devoted to economic development are utilized effectively. In New York, efforts to quantify the increase in value added as a result of technology development have involved the use of multiple regression to analyze client surveys. In this paper, we describe work with one group of agencies to develop a fuzzy rule-based system. Initial results show that fuzzy models can outperform multiple regression when used on even terms and have the potential to substantially outperform regression models when used to their full advantage
  • Keywords
    economics; fuzzy logic; government data processing; knowledge based systems; statistical analysis; New York, USA; US state governments; added value; client survey analysis; fuzzy rule-based economic models; multiple regression; state-funded agency performance measurement; technology development; Costs; Educational institutions; Fuzzy systems; Government; Information analysis; Keyboards; Knowledge based systems; Marketing and sales; Performance analysis; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American
  • Conference_Location
    Syracuse, NY
  • Print_ISBN
    0-7803-4078-7
  • Type

    conf

  • DOI
    10.1109/NAFIPS.1997.624077
  • Filename
    624077