Abstract
Policymakers wishing to enhance innovation processes in small and medium-sized enterprises increasingly channel their interventions through innovation intermediaries. However, limited empirical research exists regarding the activities and performance of intermediaries, with most contributions taking a qualitative approach and focusing on the role of intermediaries as brokers. In this paper, we analyse the extent to which innovation intermediaries, through their engagement in different activities, support the creation of communities of other agents. We use multilayer network analysis techniques to simultaneously represent the many types of interactions promoted by intermediaries. Furthermore, by originally applying the Infomap algorithm to our multilayer network, we assess the contribution of the agents involved in different activities promoted by intermediaries, and we identify the emerging multilayer communities and the intercohesive agents that span across several communities. Our analysis highlights the potential and the critical features of multilayer analysis for policy design and evaluation.
The Authors are members of CAPP-Centro di Analisi delle Politiche Pubbliche, Departiment of Economics, University of Modena and Reggio Emilia, Italy.
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Notes
- 1.
For example, Howells [4] proposed a functional definition of innovation intermediary as ‘[a]n organisation or body that acts [as] an agent or broker in any aspect of the innovation process between two or more parties’.
- 2.
The database is available at the following https://doi.org/10.25431/11380_1182469.
- 3.
This information was collected during two interviews (on April 2011 and June 2013) with policymakers who designed and managed the policy.
- 4.
The first level of description concerns the nodes in which the flow moves, and the second level of description concerns sub-areas of the network, i.e. communities, in which the flow tends to circulate for a long period before exiting. Therefore each detected community maximises the probability of the considered random walk to remain within its boundaries before moving into another community.
- 5.
As reminded by Arenas and De Domenico [22], historically, the term multiplex was coined to indicate the presence of more than one relationship between the same actors of a social network. The terms ‘multiplex’ and ‘multilayer’ are used almost indistinctly as they fundamentally refer to the same concept.
- 6.
Sole-Ribalta and De Domenico [23, p. 76] discuss the problem of overestimation of closeness centrality in an aggregated network, i.e. a network originally formed by several layers that are all aggregated into a single one.
- 7.
- 8.
Directedness, too, may affect the result, although in the case study it did not affect the ranking of agents according to the Infomap flow (results not reported).
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Acknowledgements
This paper has been developed in the research project ‘Poli.in Analysis and modelling of innovation poles in Tuscany’ (www.poliinovazione.unimore.it), co-funded by Tuscany’s Regional Administration and University of Modena and Reggio Emilia, Italy. For their comments to preliminary versions of this paper, we wish to thank the participants in the 1st EAEPE—RA[X] Workshop ‘New Frontiers and Methodological Advances in Cooperation and Network Research’, November 2–3, 2015 in Essen, Germany; the Conference ‘Networks, Complexity and Economic Development’, organised by the Hungarian Academy of Sciences, Research Centre for Economic and Regional Studies MTA KRTK, 30 November to 1 December 2015, Budapest, Hungary; the ARS’17 Conference, held in Naples, Italy, May 15–17, and the EUSN 2017 Conference, held in Mainz, Germany, September 26–29. Simone Righi acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 648693).
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Russo, M., Caloffi, A., Righi, R., Righi, S., Rossi, F. (2020). Multilayer Network Analysis of Innovation Intermediaries’ Activities. In: Ragozini, G., Vitale, M. (eds) Challenges in Social Network Research. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-31463-7_12
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