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R&D cluster quality measures and technology maturity.
- Source :
- Technological Forecasting & Social Change; Oct2003, Vol. 70 Issue 8, p735, 24p
- Publication Year :
- 2003
-
Abstract
- “Innovation indicators” strive to track the maturation of an emerging technology to help forecast its prospective development. One rich source of information is the changing content of discourse of R&D, as the technology progresses. We analyze the content of research paper abstracts obtained by searching large databases on a given topic. We then map the evolution of that topic''s emphasis areas.The present research seeks to validate a process that creates factors (clusters) based on term usage in technical papers. Three composite quality measures—cohesion, entropy, and F measure—are computed. Using these measures, we create standard factor groupings that optimize the composite term sets and facilitate comparisons of the R&D emphasis areas (i.e., clusters) over time.The conceptual foundation for this approach lies in the presumption that domain knowledge expands and becomes more application specific in nature as a technology matures. We hypothesize implications for this knowledge expansion in terms of the three factor measures, then observe these empirically for the case of a particular technology—autonomous navigation. These metrics can provide indicators of technological maturation. [Copyright &y& Elsevier]
- Subjects :
- TECHNOLOGICAL forecasting
TECHNOLOGY
SOCIAL change
RESEARCH
Subjects
Details
- Language :
- English
- ISSN :
- 00401625
- Volume :
- 70
- Issue :
- 8
- Database :
- Supplemental Index
- Journal :
- Technological Forecasting & Social Change
- Publication Type :
- Academic Journal
- Accession number :
- 10504962
- Full Text :
- https://doi.org/10.1016/S0040-1625(02)00355-4