Innovation, generative relationships and scaffolding structures: implications of a complexity perspective to innovation for public and private interventions

Abstract

The linear model of innovation has been superseded by a variety of theoretical models that view the innovation process as systemic, complex, multi-level, multi-temporal, involving a plurality of heterogeneous economic agents. Accordingly, the emphasis of the policy discourse has changed over time. The focus has shifted from the direct public funding of basic research as an engine of innovation, to the creation of markets for knowledge goods, to, eventually, the acknowledgement that knowledge transfer very often requires direct interactions among innovating actors. In most cases, policy interventions attempt to facilitate the match between “demand” and “supply” of the knowledge needed to innovate. A complexity perspective calls for a different framing, one focused on the fostering of processes characterized by multiple agency levels, multiple temporal scales, ontological uncertainty and emergent outcomes. This contribution explores what it means to design interventions in support of innovation processes inspired by a complex systems perspective. It does so by analyzing two examples of coordinated interventions: a public policy funding innovating networks (with SMEs, research centers and university), and a private initiative, promoted by a network of medium-sized mechanical engineering firms, that supports innovation by means of technology brokerage. Relying on two unique datasets recording the interactions of the organizations involved in these interventions, social network analysis and qualitative research are combined in order to investigate network dynamics and the roles of specific actors in fostering innovation processes. Then, some general implications for the design of coordinated interventions supporting innovation in a complexity perspective are drawn