Are traditional industrial partnerships so strategic for research spin-off development? Some evidence from the Italian case

Abstract

This paper aims to contribute to the literature on research spin-offs (SOs) and strategic alliances. The research SO phenomenon has attracted significant attention in recent years. Yet, research SOs might present a particular situation regarding their economic development. Therefore, the paper focuses on the relevance of traditional industrial partnerships and introduces a new and complementary approach for studying and analysing the role of alliances for this particular kind of firm. The results of a questionnaire investigation of Italian research SOs with and without a traditional industrial partner are investigated and supported by a linear regression model. Due to recent initiatives – a growing interest in the research SO phenomenon – and the increasing number of established research SOs, Italy is a suitable case study for such an investigation. Nonetheless, the results are generalizable beyond the Italian case. The findings demonstrate thought-provoking – and somehow unexpected – results regarding the role of traditional alliances in shaping the geographical and industrial environment as well as the performance, added value, age and production process of the company. This calls for a broader perspective regarding industrial partnerships and research SOs: it reflects new modes of relations for these particular firms in the form of business ecosystems, either they are physical or they are digital.

Keywords::

• research spin-offs
• partnerships
• science parks
• technology transfer
• business ecosystems
• digital business ecosystems

Keywords::

• O3
• L2

Acknowledgements

This work was supported by the scholarship (2007–2009) of the International PhD Programme in “Institutions, Economics & Law (IEL)”, Collegio Carlo Alberto, University of Turin, XXII Cycle; and by the Italian National Research Council (CNR) award under the ‘Promotion of Research 2005’ programme, Project for young researchers (Elisa Salvador, grant number 263/229).

Notes

^1. According to Wright, Vohora, and Lockett (2004, 288), ‘A JVSO is a new venture in which technology is assigned or licensed into a new company that is jointly owned by the university and the industrial partner’.

^2. In particular, ‘We could caution, however, that a potential downside is the need to put mechanisms in place to control the joint venture partner and to select a partner with compatible objectives and expertise’ (Wright et al. 2007, 125; Wright, Vohora, and Lockett 2004, 308).

^3. ‘Italy and France historically are considered the birth places of the university institution’ (Daraio et al. 2011, 154).

^4. For a comparison of key features of cluster, value network and business ecosystem, see Peltoniemi (2005).

^5. This list is updated at June 2008 (year of the empirical investigation through a questionnaire).

^6. The questionnaire was sent by e-mail to SO between January and June 2008 with information about the purpose and details of the survey. An e-mail reminder was sent to firms that did not reply to the first e-mail within a month.

^7. The distribution by Regions of the 155 questionnaires revealed that 58% was from the North, 23% from the Centre and 19% from the South and Islands, while the Italian distribution of the 419 SO showed 54% from the North, 25% from the Centre and 21% from the South and Islands.

^8. Sheehan (2001) finds response rates to oscillate between 21.6% and 36% and Jobber and Saunders (1993) indicate that the rate of response in business-oriented studies is more sensitive than that of consumers to characterise the number of questions, the length of the survey, etc. (cited in Squicciarini 2008, 50).

^9. Aida is a databank that provides company accounts, ratios, activities for 950,000 Italian companies.

^10. Namely s.r.l., in Italian legal terms.

^11. Descriptive statistics, correlation matrix, the linear regression model and tests for multi-collinearity are described in Tables 12–16 (see Appendix).

^12. In addition, it also provided a confirmation of the pertinence of our sample: all firms were actual SO.

^13. We measured the variable ‘flagspinoff’ by using a binary variable which took the value 1 if the firm had an alliance and 0 otherwise.

^14. This variable has been calculated as total assets minus fixed assets.

^15. We decided to measure the firm size in terms of ‘total assets’, because it has not been possible to have enough and reliable data on the number of employees.

^16. We measured the variable ‘time’ starting from 0 if the firm was created in 2007; 1 if it was established in 2006; 2 if it was founded in 2005 and so on.

^17. We measured the variable ‘company’ with a binary variable which took the value 1 if the firm was an srl and 0 otherwise.

^18. We measured the variable ‘location’ by introducing three dummy variables for North, Centre and South and Islands of Italy.

^19. Since 1 January 2008, a new classification of economic activities called Ateco 2007 is in force as the single rule of classification for public administration. This new classification in Italy is published by Istat (National Institute of Statistics), and it is the national version of the European nomenclature NACE Rev. 2, established by the Regulation EC no. 1893/2006 of the European Parliament and the European Council.

^20. We controlled for industry effects by employing five dummy variables for the industrial sectors of ICT, transport, biopharmaceutical, engineering, etc. These variables take a value of 1 if the company is in the sector and 0 otherwise. These sectors were identified starting from the Ateco 2007 classification: we formed groups of firms with the same Ateco code of two digits. In the sector named ‘other’ were included the few firms dealing in general in the consultancy industry and in the commerce and editor industries.

^21. See, among others, Siegel, Westhead, and Wright (2003) for the UK; Rothaermel and Thursby (2005) for the USA; Colombo and Delmastro (2002), Salvador (2011) for Italy; Schwartz (2009) for Germany; Sofouli and Vonortas (2007) for Greece.

^22. For a comprehensive discussion on the distance between the science park and the university campus and the importance of proximity, see Link and Scott (2006), (2007) and Wessner (2009).

^23. On this topic, see among others: Rothaermel and Thursby (2005), Clarysse et al. (2007), Squicciarini (2008), Schwartz (2009), Fini, Grimaldi, and Sobrero (2009) and Clarysse, Wright, and Van de Velde (2011).

^24. See, for example, Mustar (1997), Steffensen, Rogers, and Speakman (1999), Clarysse et al. (2007), Gupte (2007) and D'Este and Perkmann (2011).