Identifying different types of intermediaries in innovation networks:! the case of PPP in the Tuscany Region

Transcription

1 Identifying different types of intermediaries in innovation networks:! the case of PPP in the Tuscany Region Annalisa Caloffi, University of Padua Federica Rossi, Birkbek College, University of London Margherita Russo, University of Modena and Reggio Emilia PROFILI Project, Padova March 2014

2 Outline Our PPPs Intermediaries Who are they? agents who (should) perform an intermediary function agents who are in an intermediary position What is their role in innovation? Social network analysis tools Brokers & intercohesive agents Results of the empirical analysis Implications for PPPs and next steps

3 Intermediaries: what the inno literature says Who are they? intermediaries, knowledge (or technology, or innovation) brokers, bricoleurs, boundary organizations, superstructure organizations, innovation bridges (e.g. Howells, 2006). Very often identified with KIBS. The functions they perform: facilitate networking (Shohert and Prevezer, 1996; McEvily and Zaheer, 1999); provide services (Shohert and Prevezer, 1996) provide collective goods to their members (Lynn et al., 1996; Russo and Whitford, 2009); support innovation processes by: selecting suppliers (Watkins and Horley, 1986), Screening & adapting available technological solutions (Stankiewicz, 1995) acting as knowledge repositories (Hargadon and Sutton, 1997).

4 Intermediaries: our approach Intermediaries are agents who occupy intermediary positions Intermediaries are a heterogeneous group of agents, having different nature (features) and performing different roles. We investigate 2 different interm. positions: brokers and intercohesive agents By looking at the definitions of brokers & intercohesive, we infer that they may play a different role in innovation exploration or exploitation processes à

5 Brokers Burt (1992): a broker is an agent (a node) that spans a structural hole in a network that is, a node that creates a bridge between two otherwise non-connected parts of that network This agent has the opportunity to broker the flow of information between people, and to control the projects that bring together people from opposite sides of the hole In the empirical applications: routines calculate # pairs connected only via the ego (also normalized measures / total # pairs) à brokerage has various degrees/ intensity, from zero to a cut-point situation!

6 Intercohesive nodes Stark and Vedres (2008): intercohesive nodes are actors who are members of different communities at the same time à a community is a set of nodes that are more intensively connected to each other than to the rest of the network, identifying a particularly cohesive social group In the empirical applications: Palla et al (2007) algorithm, based on the clique percolation methods à identification of network cohesive substructures PURE BROKER INTERCOHESIVE NODE

7 Brokers & intercohesive in innovation processes They can play different intermediary roles in distributed innovation processes involving several organizations, and in particular they can support different forms of learning: Brokers are more often found in networks of organizations operating in a turbulent fast changing technological environment. Brokers connect different pieces of knowledge that were not previously connected à they play a role in creating novelty Intercohesive nodes are more often found in networks of organizations operating in a stable technological environment. Intercohesive nodes connect many agents that are already connected (they are part of the same community) à they play a role in deepening existing knowledge, which is shared by the members of the communities

8 Data Tuscany Region policies supporting R&D networks from 2002 to 2008 ( ): provision of funds for the implementation of innovation projects 5 programs (RPIA ITT, 2004_171E, 2005_171, 2007_171, 2008_171), 141 funded R&D networks participated by 1024 agents Network members: SMEs, large firms; innovation centres, technology parks and similar infrastructures; Universities and research centres; Business associations, Chamber of commerce; Local governments; other public bodies Innovation network = consortium = project 124 intermediaries. They are multiple participants, who lay in-between different innovatiion programs: 27 pure brokers; 97 intercohesive nodes

9 Nature Pure broker (B) Intercohesive Both B and I None Total agents (I) Enterprises Universities & research centres Private research companies Service centres Service providers Associations Chamber of Commerce Local governments Other public bodies Total ,024 Brokers and intercohesive nodes are calculated on the basis of the individual programme. Pure brokers include agents which are broker in at least one of the observed programmes, but not intercohesive agents. The opposite case (intercohesive, but not brokers) is listed in the second column I. The third column reports a list of agents that are broker in at least one of the observed programmes, and intercohesive agents in at least another programme. None refers to agents that never perform any intermediary role.

10 Empirical strategy In order to identify the characteristics of the brokers, we estimate a probit model with sample selection (Heckman two-stage probit) Main equation: what is the probability that an agent is a broker / intercohesive node (rather than an intercohesive) given a set of characteristics of the agent (nature), the projects in which it participates (turbulent technological environment rather than stable), and the surroundings in which the agent itself is embedded (homophily indices, measuring if and to what extent the agents are linked to similar others). (124 obs) Selection equation: a number of variables that could have an influence on the fact that the agent becomes an intermediary (number of projects into which it participates, agent s nature, technological features into which the agent participate) + the other features that we have included in the main equation

11 Variable Description Total population N obs=1010 Intermediaries N obs=124 Mean St.Dev Mean St.Dev Intermediary (S) Dependent variable in the selection equation. Dummy variable taking value 1 when the agent is an intermediary (broker or intercohesive) and 0 otherwise. Broker Dependent variable in the main equation. Dummy variable taking value when the agent is a broker and 0 otherwise. The agent is a broker when its normalized brokerage index, as calculated by the software Ucinet, is >0. Intercohesive Not included in the model (is the one s complement of the variable broker) Dummy variable taking value 1 when the agent is an interohesive node and 0 otherwise. The agent is an intercohesive node when it belong to more than one network cohesive subgroup (community) N_proj (S) Total number of projects participated by the agent. The variable is calculated on the total number of policy programmes issued in that promoted the formation of innovation networks (9 programmes, see Caloffi et al, 2012), and not only on the five programmes that admitted multiple participation. Turbo_pct Pct of projects participated by the agent, which focus on technological environments characterized by a fast rate of change Hom_sector Homophily index calculated on agents sector. It is the pct of agents in ego s neighbourhood that have the same sector of ego. Hom_province Homophily index calculated on agents localisation (provincial level). It is the pct of agents in ego s neighbourhood that have the same localisation of ego

12 Descriptives (continue) Enterprises Universities & research centres Private research companies Service centres Service providers Associations Chamber of Commerce Local governments Other public bodies Dummy variable taking value 1 when the agent is an enterprise and 0 otherwise Dummy variable taking value 1 when the agent is a university or research centre and 0 otherwise Dummy variable taking value 1 when the agent is a private research company and 0 otherwise Dummy variable taking value 1 when the agent is a service centre and 0 otherwise Dummy variable taking value 1 when the agent is a service provider and 0 otherwise Dummy variable taking value 1 when the agent is an association and 0 otherwise Dummy variable taking value 1 when the agent is a chamber of commerce and 0 otherwise Dummy variable taking value 1 when the agent is a local government and 0 otherwise Dummy variable taking value 1 when the agent is a public body (other) and 0 otherwise

13 Variables Coef. Std. Err. t P> t [95% Conf.Interval] purebroker Turbo_pct Hom_sector Hom_province Enterprises Universities & research centres Private research (.) companies Service providers Service centres Associations Chamber of Commerce Local governments _cons intermediary n_proj Turbo_pct Hom_sector Hom_province Enterprises Universities & research centres Private research companies Service centres Service providers Associations Chamber of Commerce Local governments _cons /athrho rho

14 Results broker positions are more often occupied by organizations that engage in turbulent contexts, where learning processes are mainly explorative, while intercohesive agents are more often found in stable environments Intermediaries in general seems to be characterized by the presence of a more homogeneous environment than non-intermediaries à this has to be attributed to the presence of intercohesive agents (hom_sector is negative for brokers!) à although there is a high degree of variability, the environment into which brokers operate seems to be more heterogeneous than that of intercohesive As for the agents nature, we do not find a clear and strong correspondence between the fact of being an broker / intercohesive agent and that of being a particular type of agent such as a service provider à it is not possible to strictly rule this category within the call for tenders!

15 Implications for PPPs Projects that we have analyzed are placed at an earlier stage than the PPPs. Here public & private partners have the time to know each other and work together, to identify common problems and opportunities, to learn how to perform together new things à This creates the opportunity to create a good PPP Who should facilitate communication & networking? It is not possible to identify ex ante the type of agent that can play this role. It depends on the type of project / PPP and on the competencies of the people who are in the different organizations

16 Next steps in-depht analisys of the different organizations involved, in order to identify competencies and strategies What is the role that brokers & intercohesive agents play in network formation and dissolution?