Abstract
Young innovative companies (YICs) are attracting attention in their role of industry regenerators. However, we have little understanding about their relations with universities as sources of information. This chapter explores university-industry interaction involving YIC in the Valencian Community, using YIC founders’ personal attributes and motivations as explanatory variables. The Valencian Community has a relatively high degree of university-industry interaction but surprisingly little technological innovation.
A survey of YICs in the region shows that, in their case, firm size does not affect the probability of contracting with universities and that R&D intensity is not significant if we consider firm founders’ personal characteristics and motivations. YIC founders exploiting market opportunities recognized in previous business activities and necessity entrepreneurs are the least likely to interact with universities. We highlight the role of external advisory services to realise the benefits of universities.
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Notes
- 1.
The YICs analyses were 4 years or younger. As already indicated, EU state aid regulation defines a YIC as a firm established for less than 6 years. The literature on start-ups uses a range of 5 (Cohen et al. 2002) to 1.5 years (Okamuro et al. 2011). Thus, there is no clear cut-off age for a ‘young’ firm.
- 2.
It corresponds to 1 % point above the figure in the previous table because here ‘don’t knows’ are excluded from the total.
- 3.
This classification is based on self-assessment, unlike studies that give precise numbers for R&D intensity. However, many studies using Community Innovation Survey (CIS) data or similar are based on self-assessments. Our results may be more reliable since offering a choice of category can be less prone to inaccuracies than asking for unaccounted numbers. Also, as a robustness check, we used two alternative variables: the budget of granted innovative projects and the budget of granted R&D projects, applied for by firms through competitive tenders. We chose this method because according to the literature (Hyytinen and Toivanen 2005; Takalo and Tanayama 2010), being awarded financial support (subsidy) for innovative activity can be seen as reflecting the high quality of the innovative efforts made by the company. The results (available on request) did not change, in particular, the lack of significance of R&D that we will see afterwards.
- 4.
For the estimations, we tried different breakdowns of the academic and business pull variables; the results did not change. We prefer to present the current aggregates because this results in models with more degrees of freedom. The descriptive and econometric results and the breakdowns are available from the authors on request.
- 5.
Fifteen percent of respondents chose ‘other’ rather than any of the 27 initial categories; they were required to make a qualitative response. This information and the response to another question about the firm’s economic activity allowed us to reclassify this 15 % into the initial categories or to drop unclear cases. One of the authors with many years practical experience at IMPIVA and direct contact with Valencian companies helped in this reclassification exercise.
- 6.
As a robustness check, we carried out another selection strategy: We introduced the independent variables separately into the regressions and retained only those with a significant effect in the joint model. The results were the same as Table 2.8, column 2.
- 7.
In the estimations, only three industry sector dummies are significant (see Table 2.8, column 2): science-based manufactures, ICT services and R&D services. Although further development of this idea is beyond the scope of this study, it is in line with some evidence that the study of university-industry interaction should not be restricted to manufactures but expanded to services (see D’Este and Cameranii 2010).
- 8.
It might be that studies based on more fine-grained information, e.g., variables with more points on a Likert scale, would be more useful. In our case, we included a question in the survey about satisfaction with services provided by universities to be ranked on a five-point Likert scale, ranging from ‘not satisfied’ to ‘very satisfied’. We found that most firms that had interacted with universities were ‘very satisfied’, while most firms with no experience of university contracting expressed an opinion of ‘neither very satisfied or very dissatisfied’. Ordered models predict both outcomes, meaning they perform no better than a simple dichotomous variable.
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Acknowledgements
We are grateful to Jaider Vega-Jurado for his comments. Francisco Mas-Verdú gratefully acknowledges support from the Spanish Ministry of Science and Education (ECO2010-16934) and from the the Universitat Politècnica de Valencia (project PAID 06-10/2392) and the Generalitat Valenciana (GV/2011/049). Joaquín M. Azagra-Caro gratefully acknowledges support from the Spanish National Research Council (project 201010I004).
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Azagra-Caro, J.M., Mas-Verdú, F., Martinez-Gomez, V. (2012). Forget R&D – Pay My Coach: Young Innovative Companies and Their Relations with Universities. In: Audretsch, D., Lehmann, E., Link, A., Starnecker, A. (eds) Technology Transfer in a Global Economy. International Studies in Entrepreneurship, vol 28. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-6102-9_2
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