The role of science - industry interactions within emerging fields: An analysis of technological performance on the level of regions and firms Cathy Lecocq Dimetic session, Pecs, July 2007

The role of science - industry interactions within emerging fields PhD Framework: The role of science – industry interactions for the technological performance of regions and firms in new emerging fields The role of (national/regional) policies aimed at stimulating the collaboration between academia and industry, and their distinctive impact on inter-organisation collaboration at the level of the firm and the region.

The role of science - industry interactions within emerging fields Using formal R&D collaborations, based on co-publication and co-patenting data => hereby exploring the relevancy of this set of indicators as comprehensive measures for the amount and nature of scientific and technological collaboration on the level of regions and firms. Focusing in a first phase on biotechnology, which can be considered as an emergent and growing field of technological and economical activity over the last decades In a next step, this pilot will be extended towards other technology fields in order to check whether and to what extent the role of science – industry interactions is really distinctive within emerging, knowledge intensive technologies

Collaboration between Academia and Industry and the technological Performance of European Regions: the Case of Biotechnology Catherine Lecocq Bart Van Looy Managerial Economics, Strategy and Innovation Faculty of Economics and Applied Economics K.U.Leuven

Science-Industry interaction and the technological performance of regions System approach of innovation: interaction between multiple actors Innovation Systems  (National) Innovation Systems (Lundvall, 1992; Freeman, 1987; Nelson, 1993)  Regional dynamics (Acs, 2000; Blind and Grupp, 1999; Cooke, 2002; Florida and Cohen, 1999; Keeble and Wilkinson, 2000; Saxenian, 1994)  Triple Helix model (Leydesdorff and Etzkowitz, 1996; 1998) Firms  Suppliers and customers (Shaw, 1994; Von Hippel, 1988)  Potential lead users (Quinn, 1985; Von Hippel et al., 1999)  Universities and public research centres (Gerwin et al., 1992, Santoro, 2000; Tidd et al., 2002, Veugelers and Cassiman, 2005)  Future or existing competitors (Hamel, 1991; Dodgson, 1993) Open Innovation paradigm (Chesbrough, 2003)

Science-Industry interaction and the technological performance of regions Recent research on R&D collaboration of firms differentiates between different types of alliances based on March’s (1991) exploration vs exploitation framework and indicates differentiated relationships with innovative performance (multi-dimensional):  Integrated product development path (Rothaermel and Deeds, 2004; 2006): exploration alliances -> products in development -> exploitation alliances -> new products on the market  Firms engaging more in collaboration with universities and knowledge generating institutes perform better in terms of the development of new technologies and products (Belderbos et al., 2004; Faems et al.,2005)  Firms engaging in exploitative collaborations with other firms perform better in terms of obtaining turnover from improved products (Faems et al., 2005) or show a significant impact on labour productivity growth (Belderbos et al., 2004).

Science-Industry interaction and the technological performance of regions For knowledge creation and diffusion processes involving a substantial amount of tacit knowledge proximity matters (Malmberg and Maskell, 1997; 1999 Jaffe, Trajtenberg, and Henderson, 1993, Anselin, Varga and Acs, 1997)  Universities and research labs contribute to the technological and innovative performance of their regions (Jaffe, 1989; 1993; Mansfield, 1995; Acs et al. 1991; 2002; Anselin et al. 1997; Varga, 2002; Fischer et al. 2003)  But seems more pronounced within certain (broad) technological fields than across all fields (Jaffe, 1989; Acs, et al., 1991; Anselin et al. 2000)  Results in increasing attention for regional innovation dynamics/clusters: unit of analysis within this study

Science-Industry interaction and the technological performance of regions Technologies progress along a Technology Life Cycle (Utterback and Abernathy 1975; Roussel, 1984; Foster 1986; Anderson and Tushman, 1997; Andersen 2001)  Different stages of technology coincide with different characteristics of the technologies with respect to technical and market uncertainty, technical performance, levels of R&D investments, etc. (Roussel, 1984; Foster 1986)  The development path of technologies typically follows an S-shaped growth path (Andersen 2001)

Science-Industry interaction and the technological performance of regions We hypothesize that the nature and impact of university – industry collaborations for regional development vary as technologies and industries progress along the technology/product life cycle. And more specifically : 1) More R&D collaborations between companies and universities/ research centres will lead to better technological performance of regions (within emerging, knowledge intensive, fields) during the first, more explorative, phases of the technology life cycle. 2) More R&D collaboration between companies will lead to better technological performance of the regions during next, more exploitation oriented phases of the technology life cycle.

Patent Technology class (IPC code) Science-Industry interaction and the technological performance of regions Assignee(s): Name(s) Addresse(s) Inventor(s): Name(s) Adresses(s) DATA: EPO patents -> consistent, field specific and comparable data for a large number of regions and over longer time periods

Science-Industry interaction and the technological performance of regions EPO patents within the domain of Biotechnology (appl years ) Result of a prior effort to map the field of biotechnology (Glänzel et al., 2003)  Assignment of assignee type : University, public research centre, company, hospital, private person Based on the sector assignment methodology developed by the Policy Research Centre for R&D Statistics (Leuven, Belgium, see Van Looy, Du Plessis & Magerman, Eurostat WP, 2006)  Allocation of addresses to regions: nuts 3 level Using the 3-level hierarchical classification of regions established by Eurostat: the Nomenclature of Territorial Units for Statistics (NUTS)  Selection of nuts level: nuts1/2 Nuts1 for smaller European countries, nuts 2 for other countries Criterion: average population on the region level > 1 mio

Science-Industry interaction and the technological performance of regions Overview of selected nuts level, number of regions and average population per country ( EU-15 + Switzerland)

Science-Industry interaction and the technological performance of regions Indicators of technological performance of regions (based on inventor addresses) Collaboration indicators (based on co-assigneeship, allocated to regions based on assignee addresses)

Science-Industry interaction and the technological performance of regions Panel dataset with observations pertaining to 197 regions in EU-15 and Switzerland, over the time period (24 years) Descriptive statistics (per region and year, period )

Science-Industry interaction and the technological performance of regions Clustering of biotech activities in EU-15 and Switzerland ( ) 1/3 of patents is concentrated within 10 regions 17 regions (8,6%) have no biotech patents; 27 (13,7%) regions have no more than 5 patents

Science-Industry interaction and the technological performance of regions Top 10 regions in EU-15 + CH Île de France (FR) Oberbayern (DE) Darmstadt (DE) Denmark (DK) Berkshire, Buckinghamshire and Oxfordshire(UK) East Anglia (UK) Zuid-Holland (NL) Vlaams gewest (BE) Köln (DE) Karlsruhe (DE) GeoDa

Science-Industry interaction and the technological performance of regions Collaboration within biotechnology patents with at least 1 assignee in EU-15 and Switzerland ( ) => (12,3%) with 2 or more assignees 536 KGI – industry collaboration (3,6%) 409 Industry – industry collaboration (2,7%) Correlations

Science-Industry interaction and the technological performance of regions Evolution of patenting in the field of biotechnology Period : steady linear increase of the patent stock Period : exponential growth of the number of patents

Science-Industry interaction and the technological performance of regions MODEL: What is the nature and impact of university – industry collaborations for regional development as technologies and industries progress along the technology/product life cycle? Period : First, explorative phase of the TLC Period : Next, more exploitation orientated phase of the TLC Collaboration in year t-> technological performance of the region in year t+2 Fixed Effect Negative Binomial regression model -> controls for unobserved between region - differences such as BERD and HERD

Science-Industry interaction and the technological performance of regions RESULTS (1): Number of patents per Region (t+2)

Science-Industry interaction and the technological performance of regions RESULTS (2): Number of patents per population per Region (t+2)

Science-Industry interaction and the technological performance of regions CONCLUSIONS: During the first explorative phases of the technology life cycle: – science – industry interaction leads to a better technological performance of the region – collaboration between industrial partners contributes to the technological performance of regions During the more exploitative phases of the technology life cycle: – science – industry interaction leads to a better technological performance of the region, suggesting that even during the later phases of the technology life cycle, exploratory research activities remain present; – but collaboration between industrial partners does not lead to better technological performance of regions: Reduced importance of collaboration between firms during later stages of the life cycle? (<> open innovation system rhetoric)

Science-Industry interaction and the technological performance of regions FURTHER RESEARCH will be focused on the introduction of - the geographical distribution of co-patenting (local, national, international), - characteristics of the regional economical texture (number and size of the firms), - the specific role of scientific capabilities, - and extending indicators signaling collaboration (co-publication) in order to further qualify the relationships identified so far