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
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