"Open Innovation" and "Triple Helix" Models of Innovation: Can Synergy in Innovation Systems Be Measured?

TL;DR

This paper compares 'Open Innovation' and 'Triple Helix' models, proposing a measure of synergy in innovation systems through redundancy, which reflects unrealized options and enhances system innovativeness.

Contribution

It introduces the Triple Helix indicator as a measure of unrealized options and synergy, linking feedback dynamics to innovation system viability.

Findings

Redundancy correlates with increased innovation capacity.

Feedback loops can evolve into feedforward mechanisms for self-organization.

Higher redundancy enhances system synergy and reduces uncertainty.

Abstract

The model of "Open Innovations" (OI) can be compared with the "Triple Helix of University-Industry-Government Relations" (TH) as attempts to find surplus value in bringing industrial innovation closer to public R&D. Whereas the firm is central in the model of OI, the TH adds multi-centeredness: in addition to firms, universities and (e.g., regional) governments can take leading roles in innovation eco-systems. In addition to the (transversal) technology transfer at each moment of time, one can focus on the dynamics in the feedback loops. Under specifiable conditions, feedback loops can be turned into feedforward ones that drive innovation eco-systems towards self-organization and the auto-catalytic generation of new options. The generation of options can be more important than historical realizations ("best practices") for the longer-term viability of knowledge-based innovation systems. A system without sufficient options, for example, is locked-in. The generation of redundancy -- the Triple Helix indicator -- can be used as a measure of unrealized but technologically feasible options given a historical configuration. Different coordination mechanisms (markets, policies, knowledge) provide different perspectives on the same information and thus generate redundancy. Increased redundancy not only stimulates innovation in an eco-system by reducing the prevailing uncertainty; it also enhances the synergy in and innovativeness of an innovation system.