1. INSTITUTES OF INNOVATIVE DEVELOPMENT: THEIR ROLE IN REGIONAL CLUSTERS Anna Bykova PhD student, Higher School of Economics Russia 23th September 2011 Milocer, Montenegro

2. Motivation for research General consensus that the most competitive companies generate innovation in cooperation within localized regions (Porter, 2002; Elllison at all, 2010) Small set of observable measures usefully characterize the determinants of innovative capacity Many gaps in theory and empirical results of innovation cluster’s concept (Chesbrough, 2006; Immarino, McCann, 2006; Audretsch, Feldman, 1996Maggioni et al., 2006)

3. Research Design Innovation cluster: Organizations that promote innovation in a sector of the economy (Aydalot, Keeble, 1998) Assumptions: companies are not necessarily linked by technological chains businesses have a high probability of forming part of different types of innovative cluster in the region

4. Research Design (continue) Search for the link between cluster cooperation and firm financial results Testing the Hypothesis: Under other equal conditions, factors of the regional innovation system and of company attitudes have significance for innovation cluster participation Finding out the key factors affecting link between companies’ competitiveness and institutions of innovative development and describe the mechanisms of cooperation

5. Data Base for the Research 401 enterprises of Perm region (Russia) –Russian federal agency of government statistics (Rosstat) and its regional department (Permstat) –“SPARK-INTERFAX” –“FIRA Pro” –Three-digit Standard Industrial Classification codes (SIC) 2005-2007 year 24 In-depth Interviews with cluster participants: –15 Interviews with representatives of enterprises (department heads, CEOs and their deputies) –9 Interviews with representatives of regional and municipal governments and innovation environments (business incubators, universities and research institutes, venture funds)

6. The Sample Structure

7. Criteria for Innovation Clusters Participants Participation in regional business or industrial associations Joint innovation projects (with partners within the Perm region) R&D expenditure positive value

8. Results 15% of firms in the sample are applied with regional innovation clusters participants More than 80% of participants are process industries enterprises, especially chemical and machinery & equipment manufacture firms The mean value of total factor productivity growth rate (27.9%) for cluster participants is upwards of other firms

9. The Investigation of the Relationship between Cluster Participation and Different Factors Dependent variable (Yi) is the dummy for innovation clusters members. It takes value1 if a company is classified as a member of any innovation cluster in the Perm region, 0 if not. X matrix includes the values of independent variables while β is the vector of estimated coefficients

10. Results of Analysis Independent variable Equation 1 βSig. Capital investment 0.2710.000 Company size 0.6430.024 Business incubators 0.3800.507 Employment size -0.4080.387 Venture funds 0.0000.086 Transfer technology centres 0.7470.000 Exports 1.4300.001 Universities or research centres 2.6800.000 Industry membership 0.2450.861 Constant -12.388.000 Prob>χ 2 / Nagelkerke R-square / Observation numbers 0.000 / 0.601/ 397

11. Interview Results Institutes of innovative development have little effect on participation in the collaboration Close interaction of organizations took place in spite of unfavorable institutions Informal contacts, built on the basis of social networks, have made a stronger contribution to successful long-term relationships than formal structures The presence of stable relationships with universities and research institutions, although their potential is not being utilized to the full

12. Conclusion The impact of relationships among companies and institutes on innovative development within the regional spatial concentration of economic activity R&D cooperation and cluster participation with other establishments is substantially associated with innovation and competitiveness Finding out external and internal factors that can influence the probability of participation in innovation clusters This research can serve as an additional advantage substantiation of concentration process

13. Thank you for your attention! Questions & Comments?! Anna Bykova, HSE abykova@hse.ru