Innovation surveys and innovation policy: the European experience

1. Innovation surveys and innovation policy: the European experience Anthony Arundel UNU-MERIT, The Netherlands & University of Tasmania, Australia Bogota, August 2011

2. Why survey? • Case studies insufficient and can be dominated by the ‘loudest voices’ • Surveys give an accurate picture of an entire sector or economy • But, results only as good as the relevance of the questions and the accuracy of the data

3. Public sector innovation CIS-1 (1992) CIS-2 (1996) Business sector innovation MEPIN, NESTA pilot studies on innovation in the public sector CIS-3 (2000) Added service sector 2010 Innobarometer survey, 4,000 responses from public sector agencies CIS-4 (2000) Added organisational innovation OECD/Eurostat project on developing a model questionnaire CIS-2006 All new questions undergo cognitive testing CIS-2008 Addition of one-off modules CIS-2010 New questions

4. How public sector organisations innovate

5. What leads to innovative & effective public services?Regression model results (controlling for size, regional responsibility & country) for Policy drivers Budget decreases Laws or policies Professional organisations User firms, Staff Citizen users Supplier firms Foreign info sources Information sources Involve users Collaboration Staff incentives Evaluations Workgroups Staff training Strategies Note: Excludes management as an information source or as a player in strategies – too important!

6. What have we learnt from business sector innovation surveys? • Firms compete in sectors. • Collaboration and using a variety of knowledge sources increases innovation outcomes, but effect on economic outcomes is ambiguous. • Patents are a minor incentive for innovation. • Half of innovative firms do not perform R&D. • Firms innovate in many different ways. • Very few firms (approx 5%) are ‘pure’ technology adopters.

7. R&D data Patent data Innovation survey data Has what we have learnt about innovation influenced European innovation policy? Most commonly used indicators by the European policy community between 2005 and 2007 Bogota, August 2011

8. 95% of financial support in Europe for ‘innovation’ is for R&D. European policy instruments focus on R&D Bogota, August 2011

9. 2007 Innobarometer survey: 4,395 responses from innovative firms (all EU 27 countries) Bogota, August 2011

10. What the role of innovation surveys should be: • R&D data • Patent data • Innovation survey data

11. Barriers to the policy relevance of Innovation Surveys Bogota, August 2011

12. Lack of policy relevance of academic research based on innovation surveys. … Bogota, August 2011

13. Galia et al, Complementarities between obstacles to innovation: Evidence from France, 2004. Obstacles are complementary (occur together), ‘implies a need to adopt a package of policies in order to help firms’. Example Bogota, August 2011

14. Concerns over data reliability for: • Innovation expenditures and sales from innovative products (innovative sales share) • Effect of different markets on data for innovative sales shares • Comparability of leading indicators by country and sector

15. Example of poor comparability • In 2000, 45% of firms in Portugal innovated compared to 46% of firms in Finland. • On the European Innovation Scoreboard, Finland is usually in first or second place, while Portugal is between 22 and 23 place out of 27 countries.

16. Comparability Bogota, August 2011

17. Bogota, August 2011

18. Indicators often outdated – not timely. Lack of adequate detail and trend data. Innovation survey questions not relevant to policy needs. Other barriers Bogota, August 2011

19. Survey results contradict existing beliefs of policy makers. Bogota, August 2011

20. Only a small number of indicators were in wide use. Main policy use of innovation indicators was for benchmarking. Rarely used to develop specific policies. Occasional use for policy evaluation (collaboration) Result: underuse of innovation survey data Bogota, August 2011

21. Increasing the policy relevance of an innovation survey Bogota, August 2011

22. Improve data reliability Increase survey frequency Reduce time between survey and release of results Bogota, August 2011

23. - Question modules - Results by sector - Additional surveys Provide more detail Bogota, August 2011

24. Involve users in questionnaire development Policy makers Academics Business managers Improve question relevance Bogota, August 2011

25. Establish a strong working relationship with data users Frequent meetings Produce results tailored to user needs Bogota, August 2011

26. Innovative performance of the Aquaculture sector in Tasmania

27. Innovative performance of the marine manufacturing sector

28. Improve awareness European Innovation Scoreboard: 6 of 29 indicators from CIS Bogota, August 2011

29. What still needs to be done to improve the relevance of the CIS Bogota, August 2011

30. Improve data access Insist that academics evaluate the policy significance of their results Improve relevance of academic research Bogota, August 2011

31. Address a lack of interest in results that contradict ‘perceived wisdom’: Careful empirical work to change policy views. Support a ‘science’ of innovation policy Replication of results (increases credibility) More evaluation of policy relevance Develop a ‘science’ of innovation policy Bogota, August 2011

32. Improve relevance of innovation surveys to policies to increase performance • Main policy goal that is also relevant to businesses • Contrast between CIS and survey of public sector innovation: • Shift from asking about barriers to questions on drivers

33. Conclusions • The CIS is expensive • To justify its cost, we need to increase its usefulness to policy, academics and businesses • Long, slow process to improve the relevance of the CIS