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The role of information asymmetry in the market for university–industry research collaboration

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Abstract

This study concerns the market for research collaboration between industry and universities. It presents an analysis of the population of all Italian university–industry collaborations that resulted in at least one international scientific publication between 2001 and 2003. Using spatial and bibliometric analysis relating to scientific output of university researchers, the study shows the importance of geographic proximity in companies’ choices of university partner. The analysis also reveals inefficiency in the market: in a large proportion of cases private companies could have chosen more qualified research partners in universities located closer to the place of business.

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Notes

  1. The term “social proximity” is used in the sense given by Boschma (2005): “Social proximity is defined here in terms of embedded relations between agents at the micro-level. Relations between actors are socially embedded when they involve trust based on friendship, kinship and experience”.

  2. After the introduction of academic privilege in 2001, a higher number of patents filed by academics themselves are certainly there, but relevant data are not readily available, which makes their identification really difficult.

  3. For details see Abramo et al. (2008a).

  4. For details see http://www.miur.it/atti/2000/alladm001004_01.

  5. The discipline of Civil engineering and architecture was not included because the SCI™ does not provide full coverage of research output.

  6. Unless otherwise specified, from this point on the term “company” includes the multiple locations of the same legal entity.

  7. The number of university-company pairs is less than the number of university-company collaborations because, in the period considered, some pairs produced more than one collaboration (publication): certain pairs collaborated more than once. The same consideration will apply to the SDS-company level analysis as well.

  8. In reality, each SDS includes multiple and probably non-quantifiable specializations that evolve in a dynamic manner. However, the authors retain that the approximation introduced by considering the SDS as a unique set of competencies, possessed by the participating researchers, permits the understanding of certain aspects of university-industry collaboration.

  9. In this case the company is considered as a whole, not taking account of possible dispersed locations.

  10. Geographic distance is expressed as the straight-line surface distance between partners, measured by means of coordinates of longitude and latitude.

  11. Such distance, which refers to SDS-company pairs is slightly different from that reported in paragraph 5.3, which referred to university-company pairs.

  12. For further information on the calculations and the precautions taken in the use of this indicator see Abramo et al. (2008b).

  13. The authors are aware of the limitations in this use of “impact factor” (Moed and Van Leeuwen 1996; Weingart 2005), but the number of citations to single articles was not available in our data source.

  14. For further information on the calculations and precautions taken in the use of this indicator see Abramo et al. (2008b).

  15. In the presence of more than one company, it is not possible to identify the “decision-maker”.

  16. Where more than one university is involved in a university-industry collaboration grouping, the study conservatively considers the university with the highest position in the ranking for the SDS at stake.

  17. For the analysis of the companies' choice of researchers, the study considers publications co-authored by a single private company (excluding more complex dynamics) and one or more universities. To further increase the reliability of the procedure, the analysis considers only the publications (1,400) by the 2,562 scientists that remained affiliated to the same university and the same SDS throughout the triennium under consideration, out of a total of a potential 2,966 university researchers.

  18. On average, 90% of government funding (which represents 90% of the entire university budget) is required to cover employees’ salaries.

  19. The 183 SDSs that we consider in our analysis is more than the number of Science Citation Index categories (168) in the same disciplines.

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Authors and Affiliations

  1. National Research Council of Italy and Laboratory for Studies of Research and Technology Transfer, Department of Management, School of Engineering, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133, Rome, Italy

    Giovanni Abramo

  2. Laboratory for Studies of Research and Technology Transfer, Department of Management, School of Engineering, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133, Rome, Italy

    Ciriaco Andrea D’Angelo, Flavia Di Costa & Marco Solazzi

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  1. Giovanni Abramo
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  2. Ciriaco Andrea D’Angelo
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  3. Flavia Di Costa
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  4. Marco Solazzi
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Correspondence to Giovanni Abramo.

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Abramo, G., D’Angelo, C.A., Di Costa, F. et al. The role of information asymmetry in the market for university–industry research collaboration. J Technol Transf 36, 84–100 (2011). https://doi.org/10.1007/s10961-009-9131-5

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