R&D cluster quality measures and technology maturity

• Published in: Technological forecasting & social change Vol. 70; no. 8; pp. 735 - 758
• Main Authors: Watts, Robert J., Porter, Alan L.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.10.2003
• Subjects: Innovation indicators; R&D cluster quality measures; Technology maturity; Technology maturity; Innovation indicators; R&D cluster quality measures
• ISSN: 0040-1625; 1873-5509
• DOI: 10.1016/S0040-1625(02)00355-4

“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.