Deeper into innovation forecasting

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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.
Original languageEnglish
Title of host publicationPortland International Conference on Management of Engineering and Technology
Subtitle of host publicationPICMET
PublisherIEEE
Pages2151-2166
Number of pages16
DOIs
Publication statusPublished - 2015

Keywords

  • technological innovation
  • indexes
  • maximum likelihood estimation
  • citation analysis
  • forecasting theory
  • innovation management

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    Cunningham, S. W. (2015). Deeper into innovation forecasting. In Portland International Conference on Management of Engineering and Technology: PICMET (pp. 2151-2166). IEEE. https://doi.org/10.1109/PICMET.2015.7273181