Evolutionary policy targeting: Towards a conceptual framework for effective policy intervention

This special issue reflects on innovation and industrial policy from the premise that economic growth can be based on the permanent transformation of an economic system via the emergence and/or transformation of multi-agent structures and their inherent competences and knowledge base. The process of emergence or transformation is conceived as being the result of entrepreneurial effort, or entrepreneurs reacting to external stimuli in a way that takes advantage of an evolving knowledge base. The same process, however, can be undermined by both market and institutional failures. Past research has clearly indicated the importance of institutional structures for innovation, but also that structures as they exist may not be ideal: some institutions involved in innovation may provide the wrong incentives, faulty information, or allocate insufficient resources to accomplish their goals or mandates; and they may fail to reduce uncertainty. The paper asks whether and how a targeted, co-evolutionary approach can help overcome a lack of dynamic coordination and other failures that originate in coincidence with the emergence of a complex form of industrial organisation, be it an innovation system, cluster or a new industrial sector. More specifically, it builds upon the extended industry life cycle (EILC) model and the notion of evolutionary targeting to explore the potential benefits (and drawbacks) of targeting biotechnology innovation systems (BISs).