Abstract
The aim of this work is to give an overview of the use of social network analysis in the study of university industry relations. The structure of networks can be analysed through the lens of Social Network Analysis. This methodological approach is briefly described and its fundamental concepts are presented. The paper reviews the applications of this approach on the study of university industry relations. Different structures in the relations may result in different innovation outcomes, and the use of SNA may be particularly useful to understand differential outcomes. This work is based on a review of available literature on the topics. The paper aims at systematizing the information and knowledge related to the application of SNA on university industry networks, highlighting the main research pathways, the main conclusions and pointing possible future research questions.
TopBackground
UIR is an increasingly important and researched phenomena. Theoretically and structurally, the theme is linked to the study of the innovation process and to the need of understanding it and influencing it. Linear perspectives of the innovation process placed the university at the beginning of a linear sequence of innovation and the firm at the end of it, largely ignoring the interaction between the two types of institutions. New, interactive, dynamic, complex perspectives see the innovation process as a system involving many institutional actors, as a network of relations and as a complicated web of knowledge exchange and utilization. Science and technology are increasingly complex and costly and no single actor commands the necessary resources, relying on multiple sources of information and knowledge exchanges that are crucial for a successful innovation process. In this context, and considering the many types of relations and actors that may be possible in the innovation process, the relationships between academia and industry stand out as particularly relevant, because of the type of institutions that participate and the nature of the information and knowledge that is exchanged. The literature on UIR has raised many issues on the theme, and debates are ongoing, which can be found in some review articles (Baldwin & Green, 1984; D'Este & Patel, 2007; Perkmann et al., 2013). Only some of the issues and debates will be explored here, namely those researched by SNA concepts. They will be referred in more detail in the following section, along with the presentation of the results of the literature review, which is the main focus of this work.
SNA is the study of social structure using a group of quantitative methods. It analyses ties among social entities and looks for key players and group patterns. SNA uses concepts that are related to the structural properties of the network and indicators that are related to relational properties of the network. The most used concepts related to structural properties of the network in UIR studies are the concepts of density, component, and subgroups. The most used social network analysis concepts related to relational properties of the network are the concepts of degree centrality, betweenness centrality and geodesic distance.
Key Terms in this Chapter
Innovation Process: Is a complex social and technical process that transforms ideas and technologies into new or improved products or services.
Open Science: Open science is generally, but not exclusively, performed in university settings and is characterized by the wide non-commercial dissemination of research results and scientific knowledge.
Social Network Analysis: A methodological approach that employs quantitative techniques to analyse social structures.
Degree Centrality: A social network analysis measure that indicates the number of other nodes to which the node is connected.
University-Industry Relations: A set of connections between people in university and people in industry. There are many forms of relations, including informal ones (the flow of graduates to industry, mobility of researchers, public meetings, professional networks) and formal ones (research contracts, licensing, joint labs).
Structural Holes: The connection potential between elements or groups of elements that are not connected.
Density: A social network analysis measure that describes the level of linkages between nodes in a network. The more nodes are connected to each other, the denser the network is.
Proprietary Technology: Is characterized by the appropriation by private entities of specific claims on technology, generally, but not exclusively, through the legal mechanism of patenting.
Strong and Weak Ties: A strong tie represents a person with whom there is a regular interaction, and a weak tie represents a person with whom there are sporadic or punctual contacts.
Betweenness Centrality: A social network analysis measure that indicates how much a node is in the middle of the connections between other nodes.