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| Quadruple Helix Analysis× | Triple Helix Analysis× | |
|---|---|---|
| Field | Science Technology Studies | Science Technology Studies |
| Family | Process / pipeline | Process / pipeline |
| Year of origin≠ | 2009 | 2000 |
| Originator≠ | Elias Carayannis & David Campbell (Quadruple Helix); Loet Leydesdorff (N-tuple formalisation) | Henry Etzkowitz & Loet Leydesdorff |
| Type≠ | Innovation-ecosystem framework | Innovation-systems framework and bibliometric indicator |
| Seminal source≠ | 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 ↗ | Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: from National Systems and 'Mode 2' to a Triple Helix of university–industry–government relations. Research Policy, 29(2), 109-123. DOI ↗ |
| Aliases | Quadruple Helix model, Mode 3 innovation analysis, N-tuple helix analysis | Triple Helix indicator, University-industry-government analysis, Triple Helix synergy analysis |
| Related | 4 | 4 |
| Summary≠ | 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. | Triple Helix analysis is a framework and bibliometric method for studying knowledge-based innovation as the evolving interplay of three institutional spheres—university, industry, and government. Rather than treating these as separate actors that occasionally cooperate, it models innovation as the overlapping, mutually shaping relations among them, and offers an information-theoretic indicator that quantifies how much the three spheres jointly reduce uncertainty in a knowledge economy. |
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