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From Scientometric Systems

to Co-Creative Societies:

The Evolution of Leydesdorff’s Approach from the Triple to the Quadruple Helix

  1. Origins: Knowledge Communication and Scientometric Modelling

Loet Leydesdorff’s early work in the 1980s and 1990s focused on the communication structures of science rather than on individual scientists or organisations. Influenced by Niklas Luhmann’s systems theory, he conceived scientific communication as an autopoietic subsystem of society that reproduces itself through publications and citations.
His methodological core was scientometrics: the quantitative analysis of communication flows in publications, citation networks and patent data. By applying information-theoretical measures such as entropy and mutual information, Leydesdorff demonstrated that patterns of co-citation and co-authorship could be interpreted as indicators of self-organisation within scientific knowledge systems.

In this first phase, innovation was understood as the outcome of communication among institutional spheres. Universities generate codified knowledge, industries transform it into technologies and products, and governments regulate and fund the process. The emphasis lay on macro-level network analysis—a systemic view of how knowledge flows rather than how individuals interact.

These works established the methodological foundation for the next conceptual leap: the Triple Helix model.

  1. The Triple Helix: Institutional Co-evolution of University, Industry, and Government

Together with Henry Etzkowitz, Leydesdorff formulated the Triple Helix of University–Industry–Government relations (Etzkowitz & Leydesdorff 1995, 2000). The model proposed that innovation arises from overlapping institutional spheres that both collaborate and compete. Rather than a linear model of science-push or demand-pull, the Triple Helix depicts a recursive dynamic of communication, negotiation and hybridisation between the three helices.

Methodologically, Leydesdorff extended his scientometric tools to this multi-institutional setting. He measured the degree of interaction among universities, firms and governments using co-authorship patterns, patent data and webometric analyses. In doing so, he shifted from describing the internal logic of science to analysing innovation systems as evolving networks of communication.

This framework became widely adopted in regional innovation studies and EU policy discourse. However, as the knowledge economy globalised, questions emerged about legitimacy, cultural context and public understanding of innovation—dimensions that the Triple Helix did not yet address.

  1. Toward a Media-Based Quadruple Helix

Around 2009, in collaboration with Elias G. Carayannis, Leydesdorff contributed to extending the model into what became the Quadruple Helix of innovation.
The central argument of Carayannis & Campbell (2009, 2012) was that knowledge production in the 21st century is not confined to science, industry and government. A fourth helix—the media-based public or civil society—plays a decisive role in shaping innovation by forming perceptions, values and legitimacy.

In this media-based democracy, communication through traditional and digital media connects scientific and political discourses with societal opinion. The public sphere, understood in Habermasian terms, functions as a reflexive mirror that can accelerate or obstruct technological innovation depending on how narratives circulate.

This stage thus reinterprets Leydesdorff’s communication systems at a broader societal scale. Where the Triple Helix analysed citation networks within science, the Quadruple Helix analyses information flows across all societal subsystems. Publications, patents, and news articles become nodes in a wider “knowledge ecology.”

The “media-based” extension was conceptually powerful for macro-level analysis—linking innovation, democracy and culture—but less operational for local contexts. It inspired research on how media framing and public perception affect technology adoption (e.g., in energy transitions or biotechnology).

Yet it treated the public mainly as an audience rather than a co-producer of innovation.

  1. From Media Systems to Civil-Society Co-Creation

After 2015, European researchers (Blok, Wesselink, Popa, Nordberg, and the EU-funded RiConfigure project) sought to make the fourth helix more interactive and participatory. They reframed it from “media-based democracy” to “civil society co-creation.”
In this view, the public is not a passive recipient of innovation discourse but an active partner in experimentation—for example in living labs, citizen science and participatory energy projects.

Methodologically, this shift corresponded to a move from scientometrics to action research and qualitative evaluation. The knowledge of citizens, NGOs and local entrepreneurs was recognised as contextual expertise that complements scientific knowledge. Innovation thus became both a technical and a social learning process.

The object of study changed accordingly: from national innovation systems to regional and community-based ecosystems, such as local energy initiatives or urban living labs.
The metric of success also shifted—from publication output and R&D investment to social impact, inclusion and trust.

Based on their experience with the development of the Brainport Eindhoven region since 1991, Foks, Hofman, and Kokhuis co-authored the book Scenarios for Knowledge Development as a jubilee edition for the Technical Business Administration program at the Eindhoven University of Applied Sciences (HBO Eindhoven). In contrast to scholars such as Leydesdorff—who draw upon Luhmann’s systems theory—the authors grounded their approach in the work of Jürgen Habermas and Talcott Parsons, particularly Parsons’ AGIL schema.

This theoretical framework, presented in a revised form at the Triple Helix Conference in Turin in 2005 by Hofman and Burgmans, extends the classic AGIL model with a participatory and co-evolutionary perspective on innovation ecosystems. While aligning closely with co-evolutionary models of regional development and stakeholder participation, the adjusted AGIL framework offers a richer analytical toolkit. It captures not only the structural-functional aspects of innovation systems but also the communicative and normative dimensions emphasized by Habermas.

The AGIL model—adapted to reflect contemporary innovation dynamics—allows for nuanced scenario building, stakeholder analysis, and strategic foresight. These features are elaborated in the book, positioning the model as a valuable alternative to more linear or mechanistic models of innovation.

In 2021, Hofman and Treur presented a paper with the Self-Modeling Network Modeling Approach based on the AGIL scheme with the regions of Eindhoven and Alkmaar as an example.