Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Quadruple Helix Analysis× | Mapeo de la Ciencia× | |
|---|---|---|
| Campo≠ | Science Technology Studies | Bibliometría |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 2009 | 2000s |
| Autor original≠ | Elias Carayannis & David Campbell (Quadruple Helix); Loet Leydesdorff (N-tuple formalisation) | Katy Börner, Chaomei Chen, and others |
| Tipo≠ | Innovation-ecosystem framework | Method |
| Fuente seminal≠ | Carayannis, E. G., & Campbell, D. F. J. (2009). 'Mode 3' and 'Quadruple Helix': toward a 21st century fractal innovation ecosystem. International Journal of Technology Management, 46(3-4), 201-234. DOI ↗ | Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179–255. DOI ↗ |
| Alias | Quadruple Helix model, Mode 3 innovation analysis, N-tuple helix analysis | knowledge mapping, domain mapping, research landscape visualization |
| Relacionados≠ | 4 | 5 |
| Resumen≠ | Quadruple Helix analysis extends the Triple Helix of university-industry-government relations by adding a fourth helix—the media-based and culture-based public, civil society, and users—as a constitutive actor in innovation. It frames innovation as a 'Mode 3' fractal ecosystem in which knowledge is co-produced across multiple spheres, and it situates this within a broader N-tuple generalisation that can add further helices such as the natural environment in the Quintuple Helix. | Science mapping is a bibliometric visualization method that creates visual representations of research domains, showing the structure, development, and relationships of scientific fields. Using bibliographic data (citations, keywords, authors, journals), science mapping algorithms generate network diagrams where nodes represent documents, concepts, or authors and edges represent relationships (citation, collaboration, semantic similarity). The resulting maps make invisible intellectual structures visible, enabling researchers to understand field topology, identify emerging areas, and navigate disciplinary landscapes. Pioneered by Börner, Chen, and Boyack in the 2000s, science mapping has become a standard tool in research evaluation and strategic planning. |
| ScholarGateConjunto de datos ↗ |
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