Knowledge-Based Systems and the Model of a Triple Helix of University-Industry-Government Relations

Loet Leydesdorff • Science & Dynamics, University of

Amsterdam School of Communications (ASCoR), Kloveniersburgwal 48, 1012 CX Amsterdam, The

Tel.: +31- 20- 525 6598; fax: +31- 20- 525 3681 [email protected]; http://www.leydesdorff.net/

Abstract

The (neo-)evolutionary model of a Triple Helix of University-Industry-Government Relations focuses on the overlay of expectations, communications, and interactions that potentially feed back on the institutional arrangements among the carrying agencies. From this perspective, the evolutionary perspective in can be complemented with the reflexive turn from . The combination provides a richer understanding of how knowledge-based systems of innovation are shaped and reconstructed. The communicative capacities of the carrying agents become crucial to the system’s further development, whereas the institutional arrangements (e.g., national systems) can be expected to remain under reconstruction. The tension of the differentiation no longer needs to be resolved, since the network configurations are reproduced by means of translations among historically changing codes. Some methodological and epistemological implications for studying innovation systems are explicated.

Keywords: innovation, knowledge-based systems, knowledge production, national systems, translation, Triple Helix

Paper presented at the Conference “New Economic Windows: New Paradigms for the New Millennium” Salerno, Italy, September 2001

• I am grateful to Henry Etzkowitz and Terry Shinn for our ongoing discussions about the Triple Helix model. Introduction

Various scholars have proposed categories for the analysis of the ongoing changes in research and innovation systems. Gibbons et al. (1994), for example, distinguished between ‘Mode 1’ and ‘Mode 2’ in the production of scientific knowledge. ‘Mode 1’ research can be considered as disciplinarily organized, while ‘Mode 2’ research is mainly legitimated and organized with reference to contexts of application. Rip & Van der Meulen (1996) used the concept of a ‘post-modern research system’ to describe S&T policy systems. National systems of innovation (Lundvall, 1988; Nelson, 1993) have been particularly studied because of their relevance for government policies (Nelson, 1982; Irvine & Martin, 1984; Freeman, 1987).

Other policy analysts have argued that systems of innovation can no longer be stabilized (like in national systems of innovation), since they remain fundamentally in transition (e.g., Cozzens et al.,1990). Or should one perhaps consider ‘Research, Technology, & Development’ (RTD) systems as in an increasingly steady state (Ziman, 1994)? Sometimes various claims are made within a single text or the contradicting statements are combined in edited volumes.

What generates this lack of consensus about the appropriate unit of analysis in the study of technology and innovation? In my opinion, the various metaphors in the study of knowledge-based systems (Wouters et al., 1999; Cutcliffe, 2000) can be considered as theoretical appreciations of a complex dynamics from different perspectives and with potentially different objectives. The analysts attempt to stabilize a picture by choosing a perspective. Since the systems under study are developing dynamically, the metaphors remain ‘out of focus’ when viewed from one window of appreciation or another. However, the illusion of a stable object enables policy advisors to legitimate S&T policies.

Given the complexity of the dynamics unintended consequ