Università degli studi di Modena e Reggio Emilia

The study develops an original interdisciplinary approach, leveraging complex networks through which it identifies groups of investors and projects in equity crowdfunding, investigates whether clientele effects arise resulting in specific investor-entrepreneur matching, and explores which investor-entrepreneur combinations can lead to the emergence of collective behaviors. Data about campaigns and investors are gathered from Crowdcube to identify investors and company types that populated this leading UK platform during its early years (2011–2016). Results show that the clientele effect exists only between specific investors and project types: serial investors are attracted to innovative companies, whereas high-value and small investors, representing the largest group in the crowd, prefer mature companies in the consumer product industry. Moreover, the study reveals that information exchange in certain matching drives the clientele effect, resulting in collective behavior on specific segments: small investors engage in collective behaviors only when targeting high-tech innovative companies. These findings provide a new view on the clientele effect in equity crowdfunding platforms and the financing of innovative companies.

A growing number of innovation policies rely on publicly-funded innovation intermediaries to provide knowledge-intensive services to firms, particularly small- and medium-sized ones. The performance of innovation intermediaries is often assessed using indicators that need to be closely aligned with policy objectives to be effective. However, this alignment is difficult to achieve and is often overlooked in practice. We analyse the relationship between performance indicators and the behaviour of intermediaries by examining a case study of innovation intermediaries funded with public resources in Tuscany, Italy. The intermediaries implemented actions that allowed them to achieve their performance targets rapidly. However, due to a misalignment between indicators and policy objectives, these actions were not entirely consistent with the latter. After reviewing the literature on this key issue, we build on our findings to suggest how to design performance indicators that can induce intermediaries to more effectively support the achievement of policy objectives.

The database "Innovation Poles in Tuscany 2011-2014" collects data on innovation intermediaries, funded through a regional policy intervention, in the Italian region of Tuscany. It 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. Publications using the present data set are available at www.poliinovazione.unimore.it. The dataset has been already elaborated in - Russo, Margherita, Annalisa Caloffi, Riccardo Righi, Simone Righi, Federica Rossi «Multilayer Network analysis of innovation intermediaries’ activities». In G. Ragozini, M. P. Vitale (eds.), Challenges in Social Network Research, Lecture Notes in Social Networks, © Springer Nature Switzerland AG 2019, https://doi.org/10.1007/978-3-030-31463-7_12 - Russo, Margherita, Annalisa Caloffi, Riccardo Righi, Simone Righi, Federica Rossi. 2016. «Multilayer Network analysis of innovation intermediaries’ activities: methodological issues and an application to a regional policy programme», In Blue Sky Forum: Posters Gallery-Innovation Metrics. Ghent, Belgium. http://www.oecd.org/sti/blue-sky-posters.htm. - Russo, Margherita, Annalisa Caloffi, Federica Rossi, Riccardo Righi. 2018. «Innovation intermediaries and performance-based incentives: a case study of regional innovation poles». Science and Public Policy, 46(1), 2019, 1–12 https://doi.org/10.1093/scipol/scy028. FOLDERS: - folder edges: data on the edgelist in .csv, .dta, .xlsx - folder nodes: data agents in .csv, .dta, .xlsx - folder “graph” : RDS file network in igraph

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.

Innovation intermediaries, i.e. intermediary organisations that support firm-level and collaborative innovation are a varied set of organisations that provide either networking services (e.g. support to R&D partnership formation and to university-industry collaborations) or other knowledge-intensive services (e.g. knowledge and technology mapping, various types of consultancy) or both. Since intermediaries can facilitate knowledge exchange among organisations with different languages, cultures, decision-making horizons, systems of incentives and objectives, they can play an important role in policies aimed at promoting innovation and technology transfer within local, regional and national innovation systems. In particular, as we will argue in this Chapter, the range of activities that intermediaries engage in can potentially address numerous failures in their innovation systems. Our study provides a theoretical framework to address the mismatch between the policies’ objectives to address innovation system failures, on the one hand, and the indicators used to evaluate the intermediaries’ performance, on the other. By suggesting that the measurement of the intermediaries’ performance should be explicitly linked to their success in remedying such failures, this approach can then provide a guide to the design of appropriate indicators. These issues are illustrated through a case study of publicly-funded innovation intermediaries in the Italian region of Tuscany in 2011-2014.

Intermediary organisations that support firm-level and collaborative innovation, often called ‘innovation intermediaries’, have gained increasing prominence in knowledge-intensive economies. They provide a range of knowledge-intensive services that include, among others, technology foresight and technology scouting, R&D partnership formation, technical assistance in R&D projects, dissemination and commercialisation of results, and technology transfer. In recent years numerous policy interventions have funded organisations performing at least some innovation intermediary functions, particularly at regional level. Examples are the Regional Competitiveness Poles in France, the Innovation Networks in Denmark, the Strategic Centres for Science, Technology and Innovation in Finland, and the Innovation Poles in Italy. With the growing importance of publicly-funded regional innovation intermediaries, a need has emerged for appropriate instruments to evaluate their performance. Nonetheless, few studies have explored theoretically the key performance dimensions of the activities of innovation intermediaries, with a view to support evaluation processes. This paper analyses what are the main dimensions that should be considered when evaluating the performance of publicly-funded regional innovation intermediaries. Building on a review of the literature on innovation intermediaries and their functions within regional innovation systems, we develop a conceptual framework capturing the key performance dimensions in the activity of publicly-funded regional innovation intermediaries, which could be used as a guide to develop indicators and other metrics for the evaluation of their performance. In particular, we tie these performance dimensions to the set of systems failures that innovation intermediaries are expected to address. These system failures include: information failures, whereby regional organisations are imperfectly informed about the sources of knowledge they can tap into; managerial failures, whereby organisations do not possess the capabilities needed to acquire useful knowledge or technologies, or to usefully implement them into products and services; awareness failures, whereby organisations may be unaware of the knowledge or competences they are lacking; networking failures, whereby organisations lack potentially useful connections; and cognitive failures, which occur when individuals from different institutional backgrounds have too much cognitive distance to adequately learn together. For each of the activities that intermediaries implement in order to address one or more of these system failures, we argue that several performance dimensions should be considered. Besides the direct outputs resulting from the intermediaries’ activities, and the indirect outputs resulting from follow-up activities in which the intermediaries had some involvement, the evaluation should particularly focus on the outcomes achieved. Outcomes can be in the form of improvements in measurable performance in the activities of the intermediaries’ client organisations, or of the intermediaries themselves: for example, how they increased their profitability or turnover or their success in acquiring funds. But outcomes can also take the form of behavioural changes: for example, how these organisations changed their way of innovating, and how the intermediaries improved their own systems and practices to achieve qualitatively better outcomes. We present an implementation of our conceptual framework, with a case study focused on an innovation policy intervention aimed at funding innovation poles (a particular type of innovation intermediary), implemented by the Italian region of Tuscany in 2011-2014.

Starting from the conceptualization of ‘Cluster Index’ (CI), Villani et al. [16, 17] implemented the ‘Dynamic Cluster Index’ (DCI), an algorithm to perform the detection of subsets of agents characterized by patterns of activity that can be considered as integrated over time. DCI methodology makes possible to shift the attention into a new dimension of groups of agents (i.e. communities of agents): the presence of a common function characterizing their actions. In this paper we discuss the implications of the use in the domain of social sciences of this methodology, up to now mainly applied in natural sciences. Developing our considerations thanks to an empirical analysis, we discuss the theoretical implications of its application in such a different field.

The detection of communities of agents that interacted over time through regional innovation policies is analyzed through the application of three methodologies: Clique Percolation Method (CPM) by Palla et al. (2005), Infomap by Rosvall and Bergstrom (2008), and Dynamic Cluster Index analysis (DCI) by Villani et al. (2013). In a economic context of analysis centered on such a complex object as innovation, the three methodologies are applied to investigate different specific aspects of community organizations aimed at developing innovative activities. The investigation of relational structures (through CPM), of shared processes (through Infomap) and of integrated behaviors (through DCI analysis) allowed the identification of communities that reveal, respectively, meaningful characterizations in terms of agents’ participations in specific waves of the policy, of agents’ participations in projects operating in particular technological domains, and in terms of agents’ institutional typologies. The case study regards the policy interventions implemented by region Tuscany (Italy) in 2000-2006 with the aim of supporting innovative network projects among local actors.

A growing number of innovation policies provide funding for innovation intermediaries, with the aim to remedy some of the system failures that occur within local, regional and national innovation systems. In order to induce innovation intermediaries to behave in accordance with the policies’ objectives, public funding is often conditioned on their attainment of minimum performance targets measured through indicators, whose design is therefore crucial for the policies’ success. Focusing on the case of a regional policy programme in Italy, the paper shows that policymakers’ choice of performance indicators that were only loosely tied to the policy’s objectives, prompted intermediaries to adopt behaviours that were misaligned with those objectives. The paper then presents a reflection on how to design performance indicators that encourage intermediaries to most appropriately address relevant failures in their innovation systems.

To enhance innovation processes in small and medium-sized enterprises (SMEs), in the last decade innovation policies have increasingly supported the creation and strengthening of intermediaries (Howells, 2006; Lazaric et al, 2008; Kauffeld-Monz and Fritsch, 2013; Russo and Rossi, 2009; Caloffi et al, 2015). So far, however no adequate analytical framework to assess the activity and performance of these intermediaries has been developed. In this paper we address this issue by suggesting a network perspective (a) to analyse the multidimensional activities undertaken by innovation intermediaries and (b) to assess the contribution of the agents involved in different activities promoted by intermediaries. Methodological issues are discussed both in theory and with regard to an empirical application to analyse a regional policy supporting the creation of specialized intermediaries, named “innovation poles”, in the Italian region of Tuscany. The creation of innovation poles has mobilized a large number of agents that were directly involved with different roles in the creation of the regional system of technology transfer. Through the different activities they perform, the various agents create connections between the poles; the poles, in turn, create links between agents, facilitating the exchange of information and creating opportunities for joint actions to boost innovation. This network of networks perspective of analysis asks for the identification of pivotal agents embedded in multidimensional interactions and helps in detecting emerging communities of innovators in the regional innovation system. By adopting the analysis of multilayer networks approach (recently developed by Rosvall & Bergstrom, 2007 and 2008, and De Domenico et al., 2015), we identify the emerging multilayer communities and the intercohesive agents, framing the intermediaries’ impact. The paper concludes discussing the implications of this methodology on policy assessment.

With the growing importance of policies sponsoring innovation intermediaries (Howells, 2006; Lazaric et al, 2008; Kauffeld-Monz and Fritsch, 2013; Russo and Rossi, 2009; Caloffi et al, 2015), a need has emerged for appropriate instruments to analyze their activity. In general, current approaches do not adopt a network perspective to highlight the multidimensional system created through the activities undertaken by the intermediaries. In this paper we present an empirical analysis of a regional policy supporting the creation of specialized intermediaries in the Italian region of Tuscany. In the programming period 2007-2013 (effectively starting from 2010), the regional government of Tuscany funded twelve ‘innovation poles’. They are regional innovation intermediaries (organized to provide a range of services, including brokering and matchmaking) that bring together a number of universities and innovative service providers with potential end-users of these services. Their main goal is to promote linkages between regional actors: universities, public research organizations, KIBS, large businesses and SMEs. We highlight two main domains of interactions that support the entire system of the poles. The first domain is that in which we find the agents promoting the system of poles: this network involves both the organizations directly managing the poles, through the creation of temporary associations, and the organizations who have shareholdings in those managing organizations. The second domain relates to competence networks initiated by the system of the poles not only through the provision of services by the various operators, but also through the skills of employees and consultants, the collaboration agreements with parties outside the poles, and through the facilities of laboratories and incubators. By creating such multilayer networks we focus on interrelations between the poles based on the activities, undertaken jointly, in supporting the member companies. For each of these domains we examine the characteristics of the networks and the centrality index of the agents involved. Moreover, by adopting the analysis of multilayer networks (recently developed by De Domenico et al., 2015), we identify and compare the emerging communities in aggregate networks and in the multilayer networks with regard to the networks promoting the poles and in the competence networks.