• DocumentCode
    3658272
  • Title

    Deeper into innovation forecasting

  • Author

    Scott W. Cunningham

  • Author_Institution
    Faculty of Technology, Policy and Management, Delft University of Technology, Netherlands
  • fYear
    2015
  • Firstpage
    2151
  • Lastpage
    2166
  • Abstract
    Recent work questions whether publication and patenting time series actually follow the familiar S-shaped growth curve. Evidence suggests that most fields of scientific activity undergo dramatic bursts of growth, growing by two orders of magnitude in a matter of a year. Scientific activity in research fields may be measured by appropriately selected keyword phrases. The dynamics of publication suggest temporary, higher order positive feedback loops. These may involve the intellectual migration of scientists to nearby fields of interest, or it may involve other community-related benefits created by having a suitable group of likeminded researchers at hand. Unfortunately, given standard publication by year counts we cannot be certain what the governing dynamics of the system actually entail. In this paper we supplement standard innovation forecasting measures with additional richer details including numbers of unique authors over time, use of novel vocabulary, and citation patterns. This is used to prove, or disprove, a number of competing hypotheses about the emergence of new scientific fields. Recommendations are provided for using these extended indicator systems for innovation forecasting.
  • Keywords
    "Technological innovation","Maximum likelihood estimation","Indexes"
  • Publisher
    ieee
  • Conference_Titel
    Management of Engineering and Technology (PICMET), 2015 Portland International Conference on
  • Type

    conf

  • DOI
    10.1109/PICMET.2015.7273181
  • Filename
    7273181