R and D cluster quality measures and technology maturity

Title: R and D cluster quality measures and technology maturity
Format: Journal Article
Publication Date: October 2003
Published In: Technological Forecasting and Social Change
Description: "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. © 2002 Published by Science Inc.
Ivan Allen College Contributors:
Citation: Technological Forecasting and Social Change. 70. Issue 8. 735 - 758. ISSN 0040-1625. DOI 10.1016/S0040-1625(02)00355-4.
Related Departments:
  • School of Public Policy