2011/01/13 by Gaston Heimeriks, Loet Leydesdorff, Heimeriks, Gaston +1
Biochemistry, Genetics and Molecular Biology · Business, Management and Accounting · Computer Science · Decision Sciences · Physics and Astronomy · #Adaptation and Self-Organizing Systems (nlin.AO) #Complex Network Analysis Techniques #Digital Libraries (cs.DL) #Evolution and Genetic Dynamics #FOS: Computer and information sciences #FOS: Physical sciences #Innovation and Knowledge Management #University-Industry-Government Innovation Models #cs.DL #nlin.AO #scientometrics and bibliometrics research
paper · pdf · doi:10.48550/arxiv.1101.2591
arxiv created 2011/01/13 · openalex publication_date 2011/01/13 · arxiv updated 2011/01/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Scientometric data is used to investigate empirically the emergence of search regimes in Biotechnology, Genomics, and Nanotechnology. Complex regimes can emerge when three independent sources of variance interact. In our model, researchers can be considered as the nodes that carry the science system. Research is geographically situated with site-specific skills, tacit knowledge and infrastructures. Second, the emergent science level refers to the formal communication of codified knowledge published in journals. Third, the socio-economic dynamics indicate the ways in which knowledge production relates to society. Although Biotechnology, Genomics, and Nanotechnology can all be characterised by rapid growth and divergent dynamics, the regimes differ in terms of self-organization among these three sources of variance. The scope of opportunities for researchers to contribute within the constraints of the existing body of knowledge are different in each field. Furthermore, the relevance of the context of application contributes to the knowledge dynamics to various degrees.