Abstract
Universities have long been involved in knowledge transfer activities and are increasing their efforts to collaborate with industry. However, universities vary enormously in the extent to which they promote, and succeed in commercializing, academic research. In this paper, we focus on the concept of cognitive distance, intended as differences in the sets of basic values, norms and mental models in universities and firms. We assess the impact of cognitive distance on university-industry collaborations. Based on original data from interviews with 197 university departments in Italy, our analysis determines whether cognitive distance is perceived as a barrier to university-industry interactions, and estimates its effects on the frequency of their collaborations. Our results confirm that cognitive, albeit not affecting the probability of departments to collaborate with firms, significantly hinders the frequency of interactions.
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Notes
Following Chiesa and Piccaluga (2000, 339), we use the term ‘research exploitation’ to refer ‘to all the ways in which universities obtain revenues from their scientific research activities’. Research exploitation, in this sense, includes traditional or ‘user-directed commercialization’ activities, such as contract research and collaboration, consultancy and expert advice, together with ‘science-directed commercialization activities’, such as patenting, licensing and spinoff venturing (Gulbrandsen and Slipersæter 2007, 117). Although there is not a clear cut distinction between these categories, it should be remembered that user-directed activities were traditionally carried out by universities, while science-directed commercialization activities are more recent developments. ‘Another important dividing line between the two types of commercialization is that user-directed activities seem to thrive within traditional academic departments, laboratories and units, while science-directed activities may require a broader support structure in the form of TTOs, seed funding and so on’ (Gulbrandsen and Slipersæter 2007, 117).
This holds especially for European universities. In the US, community outreach and development has a long history and was a key driver of the establishment of land-grant universities. However, as Clark (2004, 133) underlines, the US system of higher education presents some specific characteristics (large size, decentralized control, institutional diversity, strong competition between institutions, high level of autonomy), which contribute to making it significantly different from any other system. In most European countries third mission activities, even if not completely new, expanded significantly after the early 1980s. Even in the US, some specific activities, such as patenting, licensing and spinning off new ventures, increased dramatically following the Bayh-Dole Act and related policy measures adopted in the early 1980s (Thursby and Thursby 2003, 2004, 2007).
Again, this holds only if the cognitive distance is not so great as to completely impede the process of communication between the two parts.
The survey was carried out as part of the research project ‘The Governance of Technology Transfer in Italy’, funded by the Italian Ministry of University and Research (MIUR), FIRB project: ‘A Multidimensional Approach to Technology Transfer’.
The list of departments is available at: www.cineca.it. Contact details were available for 1,047 out of 1,116 directors.
Population weights were applied to the econometric analysis. However, the estimations were remarkably similar to those estimated without weights.
The exceptions are the scientific area “Medicine”, which is slightly underrepresented for departments in both large and very large universities (respectively—9.3 and −7.1 %) and “Agriculture and Veterinary” (+4.3). When population weights are applied the estimated results are remarkably similar to those estimated without weights.
We estimated that the share of departments in EPS that received funding from industry in 2007 was 84.28 % (1,013 out of 1,202 departments) whilst the share of departments that collaborated with industry is 85.8 % in our survey.
IPI, a former consulting body within the Ministry for Economic Development, conducted a survey of TTO in Italy (IPI 2005) investigating their activities and how well their services match industry demand for services.
The probit model is based on the same regressors of the negative binomial model with the exception of COLLAB04 and the dummies for scientific areas, which predict success perfectly (all zeros correspond to zeros of the dependent variables). This is because 100 % of departments in some scientific areas (e.g. engineering) collaborate with industry.
For example, this could be the case of departments composed of younger researchers, that despite their high productivity levels (which can have a positive impact on the frequency of collaborations) do not have the necessary connections with industry of their senior counterparts. Therefore, these departments could have fewer opportunities to engage in research contracts and consultancies than departments with older staff.
The focus groups were carried out over the same time period of the questionnaire survey and as part of the same research project on technology transfer processes (cfr endnote n. 4).
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Acknowledgments
This work benefited from valuable comments from Alan Hughes, Georg Licht, Francesco Lissoni, Gianluca Nardone, Markus Perkmann, Antonio Stasi, Giovanna Vallanti and two anonymous referees. The authors would like to acknowledge the financial support of the Italian Ministry of University and Research (FIRB Project 2003—Prot. RBNE033K2R: ‘A multidimensional approach to technology transfer for more efficient organizational models’).
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Muscio, A., Pozzali, A. The effects of cognitive distance in university-industry collaborations: some evidence from Italian universities. J Technol Transf 38, 486–508 (2013). https://doi.org/10.1007/s10961-012-9262-y
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DOI: https://doi.org/10.1007/s10961-012-9262-y