Dynamics of Innovation Systems

1. Dynamics of Innovation Systems Simona Negro Marko Hekkert Utrecht University Innovation Studies Group Department of innovation and environmental sciences Copernicus Institute for Sustainable Development and Innovation

2. Introduction • Innovation systems approach is a powerful heuristic framework • Highlights the systemic nature of innovation processes • No innovation in isolation • Very well diffused under policy makers (OECD etc) • It has potential to contribute to ‘system innovations for sustainable development’

3. Theoretical approach • Several authors study IS in relation to the (sub)functions of the IS that they consider important. • These functions relate to what needs to be achieved by (in) the system to create and diffuse innovation

4. System Functions (1/2) • The way a certain system function is fulfilled is determined by many activities of agents and by different institutions • These agents do not act purposely to fulfill a system’s function, but act based on strategies to meet their own (or public) needs. • Free will but also bounded by institutional settings • The way all these activities cumulate determines the functioning of the innovation system • This cumulative outcome can be studied.

5. System Functions (2/2) • Function 1: Entrepreneurial Activities • Function 2. Knowledge Development • Function 3. Knowledge Diffusion through networks • Function 4. Guidance of the Search • Expectations • Legitimation • Vision for future • Function 5. Market Formation • Function 6. Resource Mobilisation • Function 7. Support from Advocacy Coalitions • Lobby activities

6. Interactions

7. Aim • Problem 1: Different lists of functions are used in literature • Problem 2: No detailed mapping method to map function interaction • Goal of our paper: • Testing one set of system functions • Testing whether cycles really take place • Studying which type of interactions often take place / reoccurring patterns

8. Methodology • Method: event history analysis / process method • 10 cases analyzed over time (1980-2004) (all sustainable technological innovation systems) • Combination of qualitative and quantitative data • Reconstruct the evolution in narrative • Make graphs of functional patterns over time

9. Results

10. Trends / Reoccurring patterns • Very preliminary results • Guidance (F4) very important: often starting point of IS dynamics, often also starting point of new virtuous cycle • Guidance often leads to (soft) knowledge development (F2) (via resources formation, F6). Then whole range of different patterns • Entrepreneurial activities (F1) have a pivotal role in IS. Many other functions lead to EA but in turn also many SF are triggered by EA. • Legitimation / lobby / advocacy coalitions (F7) proved to be critical in changing existing legislation / creating alignment – requires well organised entrepreneurs • Market formation (F5) is often final barrier / driver

11. Virtuous and vicious cycles • Strongly growing IS show continuous process of positive interaction between system functions • Sometimes temporary vicious cycles take place, but are quickly terminated / taken over by virtuous cycles • More problematic functioning IS show alternating cycles: virtuous – vicious. • Some developments end due to vicious cycles • Poorly functioning IS show hardly any positive interaction between SF. Also over long time periods several functions are missing

12. Implications • More insights in these patterns may help to improve innovation policy – now instruments often strongly financially dominated • May help to improve entrepreneurial strategies – provides insights in how to include the IS in business / innovation strategy