• DocumentCode
    1946691
  • Title

    Integration of a Novel Neural Network Algorithm and Kirkpatrick Model and Its Application in R&D Performance Evaluation

  • Author

    Xiong, Fengshan ; Zhang, Yizhen ; Li, Tong ; Liu, Zhibin

  • Author_Institution
    Sch. of Bus. Agric., Univ. of Hebei, Baoding
  • Volume
    1
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    353
  • Lastpage
    356
  • Abstract
    Research and development activities (R&D) as the core competitiveness in the high-tech enterprises play an extremely important role and far-reaching significance. If the high-tech enterprises want to realize the effective management to the R&D activities, and improve their success rate and economic benefits, it is necessary to conduct a scientific evaluation for the R&D performance. To measure the R&D performance of the high-tech enterprises scientifically and accurately, this paper overcomes the shortcoming of tradition linear R&D measuring method, proposes a measuring method which establishes a performance evaluation system combined with Kirkpatrick model and BP neural network. The performance evaluation of 16 enterprises in Hebei Province shows that the results given by this model are reliable, and this method to evaluate the R&D performance is feasible.
  • Keywords
    backpropagation; electronic commerce; neural nets; research and development management; BP neural network; Kirkpatrick model; high-tech enterprises; research and development performance evaluation; Cities and towns; Computer science; Mathematical model; Measurement; Neural networks; Neurons; Power generation economics; Power system modeling; Research and development; Research and development management; R&D; kirkpatrick model; neural network algorithm; performance evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.423
  • Filename
    4721760