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The role of universities in the location of innovative start-ups

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Abstract

Start-ups increasingly find the prospect of university–industry collaborations to be a powerful driver of innovation and entrepreneurship activity. Moreover, at the geographical level, they are attracted by teaching and research institutions, either public or private. This paper focuses on the role played by universities. Our hypothesis is that geographical proximity favors the transfer of knowledge and technology from universities to industries and, consequently, represents a positive factor for regional economic development. Results show that university spillovers are positively correlated with the creation of innovative start-ups. Furthermore, the presence of human capital (graduates) exerts a significant influence on the location decisions of start-ups, being a source for competitiveness for firms close to universities. Research quality, especially in the social sciences area, attracts innovative start-ups, while third-mission activities have a weak impact on locational choice.

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Notes

  1. On the role of Italian small-sized firms see Calcagnini and Favaretto (2011).

  2. The Start-Up Regulation Law introduced several exceptions to the general legal principles applicable to enterprises, namely: (a) the reduction of setting-up costs, (b) the possibility of providing work-for-equity instruments to remunerate directors, employees and consultants, and the introduction of significant tax incentives to the subscription of such instruments, and (c) the signature of fixed-term contracts with employees by derogating general labour laws, to lower labour costs. Further, the Start-Up Regulation allows the public offering of quotas of innovative startups incorporated under the form of limited liability companies (otherwise forbidden under Italian law) and tax incentives are specifically introduced for both individuals and legal entities that subscribe such offerings. Finally, it provides exceptions to Italian bankruptcy law: in the event of an insolvency crisis of the innovative start-up, the ordinary pre-insolvency and insolvency procedures are not applicable. Innovative start-ups are only subject to the so-called ‘over-indebtness procedures’ that will provide a fast track to liquidating the firms’ assets and restart other businesses, therefore reducing the damage to reputation that could arise from ordinary insolvency procedures.

  3. Start-ups also generate jobs during recessions. Kane (2010) showed that, between 1997 and 2005, startups created around three million jobs, while other firms lost around one million jobs.

  4. See also Stuart and Sorenson (2003).

  5. eValuation of Research Quality.

  6. The last Italian university reform, L.240/2010, widely known as the Gelmini Act, explicitly sets out three missions: education, research, knowledge/technology transfer.

  7. See Krugman (1991a, b), Fujita and Krugman (1995), Fujita et al. (1999), Berliant and Konishi (2000), Ellison and Glaeser (1997), Kim (1995), Berliant et al. (2002), Henderson (1977, 1988).

  8. In the model of entrepreneurial choice (Knight 1921), and its extensions (Khilstrom and Laffont 1979; Holmes and Schmitz 1990; Alvarez and Barney 2004), the role of location has been neglected, and geography has no effect on expected firm returns.

  9. The procedure has been implemented by Codinglab. The distance dataset is available upon request.

  10. These figures are very close to those shown in Audretsch et al. (2005).

  11. ANVUR evaluated 95 academic institutions, 12 public research bodies under the vigilance of the Italian Ministry of Education, University and Research (MIUR), and 16 “voluntary” organizations (nine research bodies and 17 inter-university consortia). The evaluation process started on November 2011 and lasted 20 months, involving 450 experts divided into 14 groups corresponding to different scientific areas (Group of eValuation Experts, GEV).

  12. ANVUR (2013), Sections 4.1–4.3. We opted to use IRFS2 because it only considers research evaluation, while IRFS1 takes into account the university size together with research quality evaluation. We have other controls for university size.

  13. http://cercauniversita.cineca.it.

  14. The CINECA database also contains information on the location of university branches.

  15. For robustness purposes, we also used the total number of Laurea and Laurea Magistrale graduates. Information on PhDs is unavailable.

  16. For more details see Executive summary of the new Italian legislation on start-ups, available at http://www.sviluppoeconomico.gov.it.

  17. For our analysis we dropped 15 start-ups because they are near to closing, and lost other ten start-ups because of missing information.

  18. This classification is the national version of the European nomenclature, Nace Rev. 2, published in the Official Journal of 30 December 2006 Volume 49 [Regulation (EC) no. 1893/2006 of the European Parliament and of the Council of 20 December 2006].

  19. See European Commission (2013, p. 25, footnote 32).

  20. See European Commission (2013, p. 21, footnote 20), ISTAT (2007, p. 458) and Gotsch et al. (2011, p. 13 Table 1.2).

  21. The sectors are: social assistance, health care, health and social care, education, instruction and training, protection of the environment and the ecosystem, promotion of cultural heritage, social tourism, university and post-graduate education, research and provision of cultural services, training outside school, and operating services of social enterprise services.

  22. http://www.netval.it. See also the MIUR Decree no. 168/2011 for the legal definition of spin-off.

  23. In Italy, an industrial district indicates an agglomeration of small-, medium-sized firms located in a well defined historically determined territory. They are specialized in one or more segments of the productive process and are connected through a complex network of social and economic interrelations.

  24. We define ‘local’ the closest university to the firm, as described in Sect. 3.

  25. Link and Scott (2006) showed that the choice of being close to a university translates in a faster growth than the average. At this stage, our analysis does not consider how distance affects firm performance. The latter will be one of the issues of our future research agenda on knowledge and technology transfers.

  26. See Audretsch et al. (2005).

  27. Concerning this point see Auricchio et al. (2014).

  28. Muscio et al. (2012).

  29. Specifically, we re-estimate the model specifications corresponding to columns (1), (2) and (4) in Table 6.

  30. We performed the following tests (p values in parentheses). Spatial lag Tests: Lagrange multiplier (0.17); robust Lagrange multiplier (0.21). Spatial error tests: Moran’s I (0.24); Lagrange multiplier (0.53); robust Lagrange multiplier (0.84).

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Acknowledgments

This paper benefited from comments and suggestions from participants at the International Conference on Technological Transfer held in Urbino on October 30–31, 2014; from comments and suggestions from participants at the annual workshop of the SIEPI—Italian Association of Industrial Economics and Policy held in Milan on February 5–6, 2015. We are especially grateful to Alessandro Sterlacchini, Giuseppe Travaglini, and Francesco Venturini for useful comments. The usual disclaimers apply.

Conflict of interest

The authors declare to have no potential conflicts of interests that are directly or indirectly related to this research.

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Authors and Affiliations

  1. Department of Economics, Society, and Politics, Università di Urbino Carlo Bo, Via Saffi 42, 61029, Urbino, Italy

    Giorgio Calcagnini, Ilario Favaretto, Germana Giombini, Francesco Perugini & Rosalba Rombaldoni

  2. Mo.Fi.R, Ancona, Italy

    Giorgio Calcagnini & Germana Giombini

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  1. Giorgio Calcagnini
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Correspondence to Germana Giombini.

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Calcagnini, G., Favaretto, I., Giombini, G. et al. The role of universities in the location of innovative start-ups. J Technol Transf 41, 670–693 (2016). https://doi.org/10.1007/s10961-015-9396-9

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