Commercializing academic research: a social network approach exploring the role of regions and distance

Andre Spithoven, Jef Vlegels and Walter Ysebaert
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Jef Vlegels: Vrije Universiteit Brussel
Walter Ysebaert: Vrije Universiteit Brussel

The Journal of Technology Transfer, 2021, vol. 46, issue 4, No 13, 1196-1231

Abstract: Abstract Relationships between firms and universities have been centre stage for some time. However, empirical studies on firms contracting research to universities remains limited. The likelihood of engaging in contract research depends on the characteristics of the firm and the university. Because existing literature further suggests that location is a key facilitator for knowledge transfer activities, the paper investigates the role played by regions and geographical distance between firms and universities when engaging in contract research. Hence, the analysis combines characteristics from both organisations and adds relationship-specific features with respect to the distance between them and the region they are located in. It also looks at the role played by cognitive distance. The paper contributes to the understanding of how academic research, commissioned by firms, is influenced by locational features: the ability to engage in contract research and the regional context, the regional embeddedness of research contract partners, and the geographical distance between these partners. It builds on an original dataset with information on contract research at firm. Based on a panel of three consecutive waves of R&D surveys in Belgium conducted in 2006, 2008 and 2010, the linkages of universities with R&D active firms are examined by linking a database on universities with one on firm R&D investments. Using the most recent insights in the social network approach, highlights the variables that impact the likelihood of firms engaging in research contracted to a university. Descriptive measurements are calculated from social network analysis to capture the basic structure of the firm-university network and construct an Exponential Random Graph model to predict firm-university relationships based on network characteristics and node attributes. Four main conclusions are drawn. First, more innovative regions do not show a higher likelihood of firms to engage in contract research with universities. Second, the likelihood for contract research is higher, if firms and universities are located in the same region. Third, geographical distance shows a negative relation to the likelihood of contract research suggesting cluster formation. Fourth, in the case of contract research cognitive distance complements geographic distance.

Keywords: Firm-university relationships; Contract research; Geographical distance; Cognitive distance; Regional embeddedness; Social network analysis; I23; L24; O32; O33; R12 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10961-019-09740-1

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