Compara mètodes

	Patent–Paper Citation Linkage (NPL)	Triple Helix Indicators (Mutual Information)
Camp	Bibliometria	Bibliometria
Família	Process / pipeline	Process / pipeline
Any d'origen	1997	2003
Autor original	Francis Narin, Kimberly S. Hamilton & Dominic Olivastro	Loet Leydesdorff
Tipus	Citation-linkage pipeline connecting patents to scientific literature	Information-theoretic pipeline for university-industry-government dynamics
Font seminal	Narin, F., Hamilton, K. S., & Olivastro, D. (1997). The increasing linkage between U.S. technology and public science. Research Policy, 26(3), 317-330.	Leydesdorff, L. (2003). The mutual information of university-industry-government relations: An indicator of the Triple Helix dynamics. Scientometrics, 58(2), 445-467.
Àlies	Science Linkage Analysis, Non-Patent Literature Analysis, NPL Citation Analysis, Patent-to-Science Citation Linkage	Triple Helix Mutual Information, University-Industry-Government Synergy Indicator, T(uig) Indicator, Triple Helix Synergy Analysis
Relacionats	3	3
Resum	Patent–paper citation linkage measures how strongly technology draws on science by analyzing the non-patent literature, or NPL, references that appear on patents. When a patent cites a scientific journal article rather than another patent, it leaves a traceable thread connecting an invention to the research it built on. Francis Narin, Kimberly Hamilton, and Dominic Olivastro's landmark 1997 study traced these threads at national scale and found that the citation linkage between U.S. patents and scientific papers was growing rapidly, that the cited science was overwhelmingly public, authored in universities and government laboratories, and that this linkage offered a quantitative measure of the contribution of public science to industrial technology. The resulting science-linkage indicator distinguishes science-intensive technologies from incremental ones and underpins studies of how publicly funded research feeds private innovation.	Triple Helix indicators measure the interaction among universities, industry, and government in a knowledge-based innovation system using information theory. Building on the Triple Helix model of Henry Etzkowitz and Loet Leydesdorff, Leydesdorff proposed in 2003 that the three-way mutual information across these institutional dimensions provides a quantitative indicator of how much the three spheres jointly organize an innovation system. When this three-way mutual information is negative, it signals synergy and self-organization: knowing the values on any two dimensions tells you more about the third than their pairwise relations alone would suggest, a hallmark of an integrated, co-evolving system. Computed over publications, patents, or firm data tagged by geography, sector, and technology, the indicator lets analysts compare regions and nations on the strength of their university-industry-government coupling.